Asymptomatic testing compared with standard care of the care home staff in shaping care home COVID-19 testing policy: the VIVALDI-CT pragmatic cluster RCT (VIVALDI-CT)

Asymptomatic testing compared with standard care of the care home staff in shaping care home COVID-19 testing policy: the VIVALDI-CT pragmatic cluster RCT (VIVALDI-CT) - NCBI Bookshelf An official website of the United States government Here's how you know The .gov means it's official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site. The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely. 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Asymptomatic testing compared with standard care of the care home staff in shaping care home COVID-19 testing policy: the VIVALDI-CT pragmatic cluster RCT (VIVALDI-CT) Health and Social Care Delivery Research Natalie Adams , Oliver Stirrup , James Blackstone , Maria Krutikov , Jackie Cassell , Dorina Cadar , Catherine Henderson , Martin Knapp , Lara Goscé , Lily O’Brien , Ruth Leiser , Martyn Regan , Iona Cullen-Stephenson , Robert Fenner , Arpana Verma , Adam L Gordon , Susan Hopkins , Andrew Copas , Nick Freemantle , Paul Flowers , and Laura Shallcross . Author Information and Affiliations Authors Natalie Adams , 1,2 ,* Oliver Stirrup , 3 James Blackstone , 4 Maria Krutikov , 1 Jackie Cassell , 2,5 Dorina Cadar , 5,6 Catherine Henderson , 7 Martin Knapp , 7 Lara Goscé , 3,8 Lily O’Brien , 8 Ruth Leiser , 9 Martyn Regan , 2,10,11 Iona Cullen-Stephenson , 4 Robert Fenner , 4 Arpana Verma , 10,11 Adam L Gordon , 12,13 Susan Hopkins , 2 Andrew Copas , 3 Nick Freemantle , 4 Paul Flowers , 9 and Laura Shallcross 1,14 . Affiliations 1 Institute of Health Informatics, UCL, London, UK 2 UK Health Security Agency, London, UK 3 Institute for Global Health, UCL, London, UK 4 Comprehensive Clinical Trials Unit, Institute of Clinical Trials and Methodology, UCL, London, UK 5 Department of Primary Care and Public Health, Brighton and Sussex Medical School, Brighton, UK 6 CEDAR Lab, Centre for Dementia Studies, Department of Clinical Neuroscience, Brighton and Sussex Medical School, Brighton, UK 7 Care Policy and Evaluation Centre, London School of Economics and Political Science, London, UK 8 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK 9 Department of Psychological Sciences and Health, University of Strathclyde, Glasgow, UK 10 Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, The University of Manchester, Manchester, UK 11 Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK 12 Wolfson Institute of Population Health, Queen Mary University of London, London, UK 13 Academic Centre for Healthy Ageing, Barts Health NHS Trust, London, UK 14 NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust, London, UK * Corresponding author ; Email: [email protected] Southampton (UK): National Institute for Health and Care Research ; 2026 Feb 11 . Copyright and Permissions Copyright © 2026 Adams et al. This work was produced by Adams et al . under the terms of a commissioning contract issued by the Secretary of State for Health and Social Care. This is an Open Access publication distributed under the terms of the Creative Commons Attribution CC BY 4.0 licence, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. See: https://creativecommons.org/licenses/by/4.0/ . For attribution the title, original author(s), the publication source – NIHR Journals Library, and the DOI of the publication must be cited. Abstract Background: Regular severe acute respiratory syndrome coronavirus 2 testing of care home staff was introduced to reduce transmission following significant morbidity, mortality and disruption for residents early in the pandemic. However, evidence was lacking on benefits relative to disadvantages. Objectives: The VIVALDI-Clinical Trial aimed to investigate whether regular asymptomatic staff testing for severe acute respiratory syndrome coronavirus 2, alongside funding for sick pay and agency backfill, was feasible and effective in reducing severe coronavirus disease discovered in 2019-related outcomes in residents. Design and methods: VIVALDI-Clinical Trial comprised five interlinking work packages. A cluster randomised controlled trial was conducted from January to August 2023. The ‘Test to Care’ intervention was coproduced with the care sector. Settings and participants: Eighty-one residential/nursing homes in England providing care to adults aged ≥ 65 years. Forty-one homes were randomised to intervention and 40 to control. Interventions: Care homes were randomised 1 : 1 to intervention (twice weekly staff testing, staff sick pay and agency backfill) or control arm (national testing guidance at time of trial). Main outcome measure: Primary outcome was incidence of coronavirus disease discovered in 2019-related hospital admissions in residents. Data sources: Health data from routine national data sets were used alongside aggregate data from participating homes. Health economic and modelling analyses evaluated costs and cost-effectiveness of staff testing. Interviews with care home managers explored post-pandemic policies on staff testing, sickness pay and absence. A process evaluation was conducted to understand intervention roll-out. A mixed-study design investigated the impact of coronavirus disease discovered in 2019 outbreaks on care home residents’ quality of life. Stakeholder engagement was undertaken to enable the sector to coproduce recommendations for policy-makers. Results: The trial stopped early for futility due to site recruitment and primary outcome incidence being lower than expected. There was no significant difference in resident coronavirus disease discovered in 2019-linked hospital admission incidence between intervention and control arms (incidence rate ratio 1.19, 95% confidence interval 0.55 to 2.58; p = 0.66). The process evaluation found that changing epidemiology, policy and social norms around coronavirus disease discovered in 2019 shaped the uptake and maintenance of testing. Interviews with care home managers suggested most homes no longer test staff, even when symptomatic, and do not pay for sickness absence outside of statutory sick pay. Modelling concluded that regular staff testing, when combined with non-pharmaceutical interventions preventing transmission among residents, is an effective strategy to reduce cases and deaths among care home residents that could also lead to significant cost savings. There was lower-than-expected quality of life for 43 residents from 9 care homes without outbreak and 1 home with recent coronavirus disease discovered in 2019 outbreak, with older residents experiencing greater benefits from social care support. Limitations: Intervention acceptability was initially high, but waned because of the changing epidemiological, policy and social context. Conclusions: Contextual changes undermined our ability to evaluate the intervention’s impact. However, trial set-up was achieved in < 3 months, and we present findings on the feasibility and economic implications of routine testing and impact of disease control measures on residents’ quality of life. Costs associated with severe acute respiratory syndrome coronavirus 2 testing including support payments for care home staff and for care homes to fund agency staff backfill were funded by the United Kingdom Health Security Agency. Future work: Our approach provides a model for agile interventional studies in care homes. Research training and capacity building for care home staff are important to ensure that future trials can be delivered efficiently in this setting. Funding: This synopsis presents independent research funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme as award number NIHR154310. Plain language summary Regular COVID-19 testing was necessary to reduce the spread of infection, but it is uncomfortable, expensive and takes time. Care home staff who tested positive could not work, so they lost money. In the VIVALDI Clinical Trial, we aimed to investigate whether it made sense to encourage regular testing in staff who did not have symptoms of COVID-19 to protect residents. We worked with care homes to understand the best way to design our study. Eighty-one care homes in England took part, and half of the homes were randomly assigned to carry out regular (twice-weekly) COVID-19 testing on staff. The remaining care homes followed the existing national testing policy at the time of the trial (testing for people with symptoms and during outbreaks). Care homes taking part in regular testing also received funding to cover staff sickness absences. We looked at the benefits and disadvantages of testing from the perspectives of staff, residents, families, the National Health Service and care homes. We assessed whether regularly testing staff for COVID-19 reduced the number of hospital admissions among residents, if it was value for money and experiences of testing. We found that testing staff regularly when used with other ways to protect residents like isolation did reduce COVID-19 cases and deaths among residents. During our study, the rules about COVID-19 testing in care homes changed, which made it difficult to fully understand the impact of staff testing. The trial was stopped early due to lower-than-anticipated site recruitment and lower-than-expected levels of COVID-19 in the community. Despite this, our project was important to help us understand how we could do research more effectively in care homes in the future, for example by making better use of data and by working in partnership with care providers to design studies. We shared our results with staff, residents and other stakeholders to evaluate how testing could be used in the future and make recommendations for policy. Through this project and our experiences in the COVID-19 pandemic, we have established a new, collaborative way of working with the care sector to deliver research. If this model can be sustained and scaled, it represents a major opportunity to improve care and quality of life for care home residents. Introduction Some parts of this synopsis have been reproduced from Stirrup et al . 1 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) licence, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/ . The text below includes minor additions and formatting changes to the original text. Rationale for research and background Care home residents worldwide experienced among the highest rates of coronavirus disease discovered in 2019 (COVID-19) mortality and morbidity, 2 and in England, they were also subject to stringent and lengthy lockdown measures to reduce transmission of infection. Prolonged use of restrictions (e.g. mask use, visitor restrictions) had a devastating impact on residents’ well-being, and their physical and mental health, for example depriving them of contact with family members in their final weeks of life. 3 The need to consider and ideally quantify the negative impact on residents’ physical and mental health and well-being of public health control measures aiming to protect residents has been widely acknowledged as a priority in seminal publications reflecting on the management of the COVID-19 pandemic. 4 In England and Wales, approximately 280,000 people (3% of > 65-year-olds) live in approximately 11,000 care homes for older adults. 5 Most care home residents are older than 85 years, at least two-thirds live with dementia, and over half die within 12 months of admission to a care home. 6 , 7 Public health control measures were deployed rapidly and simultaneously in care homes early in the COVID-19 pandemic to reduce infection spread, limiting assessment of the impact of individual measures. 8 To our knowledge, there have been no interventional studies of non-pharmaceutical interventions (NPIs) to reduce COVID-19 infection in care homes, but a Cochrane rapid review (published in September 2021) identified 11 observational and 11 modelling studies, all from high-income countries. 9 The review grouped interventions into entry regulations (e.g. reducing visitors), contact regulating and transmission-reducing measures [e.g. personal protective equipment (PPE)], surveillance (symptomatic and asymptomatic testing) and outbreak control measures. Across these domains, the quality of evidence was poor. In addition, there was widespread recognition that some of these measures, for example, preventing visitors from entering care homes, were associated with significant harm. In England, one of the key strategies used throughout the COVID-19 pandemic was testing. Testing was used in three ways to reduce transmission of infection: (1) symptomatic testing, (2) testing during outbreaks to reduce their duration and severity and (3) regular, asymptomatic testing. In England, compliance with regular testing in care homes was likely driven by national policies incentivising testing, including financial support (e.g. Adult Social Care Rapid Testing Fund introduced in January 2021 and the Infection Control Fund introduced in May 2020). 10 , 11 Importantly, relatively few published studies have examined how policies, for example, the withdrawal of financial support, influenced compliance with asymptomatic testing in care homes. There have been no attempts to consolidate the considerable expertise and learning on how to encourage testing in this setting to inform pandemic preparedness. Evidence is also lacking on whether the benefits of regular staff testing for COVID-19 outweighed its disadvantages, and if so, under which scenarios. In 2022, when this trial was conceived, we saw a unique opportunity to evaluate the use of testing/sickness pay as a strategy to reduce transmission of infection and inform the public health response to COVID-19 and other future infections. We speculated that high costs of sick pay and agency backfill were likely to be a major barrier to obtaining grant funding to evaluate this type of intervention outside of a pandemic. In addition, at the time of grant submission (August 2022), there was considerable uncertainty about whether a new and more severe/highly transmissible variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) might emerge in winter 2022, associated with a rapid increase in hospital admissions in residents. In this context, we felt that there was a strong rationale for conducting a randomised controlled trial (RCT) to assess the pros and cons of regularly testing care home staff to protect residents from severe outcomes following infection. A RCT design was chosen over other methods because randomisation overcomes the substantial heterogeneity among care homes with respect to the resident population, care provision and uptake of control measures such as vaccination in staff. We acknowledged that there might be significant challenges associated with undertaking this trial in a rapidly changing policy and epidemiological context. We deliberately designed a series of work package (WP) modules [covering intervention design, the RCT , a process evaluation, quality-of-life (QoL) study, health economics, modelling of outcomes and dissemination] that could operate independently to generate new knowledge to inform policy on testing and sickness pay even if the trial could not be completed as planned. Objectives We aimed to investigate whether continued regular asymptomatic testing of staff was a feasible, effective and cost-effective strategy to reduce the impact of COVID-19 in care homes. Methods for data collection and analysis The VIVALDI-Clinical Trial (VIVALDI-CT) 12 was delivered by a multidisciplinary research team through five WPs ( Table 1 ). TABLE 1 Work package structure and descriptions To develop the ‘Test to Care’ intervention and ensure it was fit for the context in which it would work, we integrated: (1) a behaviour change wheel (BCW) analysis of the results from a systematic review of barriers and facilitators to staff testing for SARS-CoV-2 from 14 international studies; (2) findings from a series of 8 stakeholder events with UK care home staff and policy-makers ( N = ~70) to iteratively operationalise emerging intervention content; and (3) the findings of a thematic analysis of barriers and facilitators to biweekly asymptomatic SARS-CoV-2 testing from four focus groups ( N = 15). We then specified our intervention, the context it would work, the problems it was solved, the mechanisms it employed and the way it would change our outcomes via programme theory and a high-level overview logic model. 12 The clinical trial ( Figure 1 ) was a multicentre, open-label, cluster randomised controlled, phase III/IV superiority trial conducted in 81 residential and/or nursing homes in England providing care to adults aged > 65 years. All regular and agency staff were eligible for enrolment, with opt-out option available. Care homes were randomised to intervention arm (twice-weekly asymptomatic staff testing for SARS-CoV-2) or control arm (national testing guidance in place at the time of the trial). Staff in the intervention arm who tested positive for SARS-CoV-2 self-isolated and received sick pay. Care providers were reimbursed for costs associated with employing temporary staff to backfill absences arising directly from the trial. FIGURE 1 Flow diagram of study site enrolment and intervention implementation. SD, standard deviation. Reproduced from Stirrup et al . This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) licence, (more...) The primary outcome of interest was the incidence of COVID-19-related hospital admissions in residents. This was selected because of the importance of preventing severe outcomes following infection, recognising that by the time the trial started most residents had been vaccinated against SARS-CoV-2 ; so the majority of infections resulted in mild to moderate illness. Secondary outcomes included COVID-19-related mortality, all-cause hospital admissions and mortality, and SARS-CoV-2 infections in residents. We used three methods to collect data on resident outcomes: To minimise the burden on care home staff, data on resident hospital admissions and mortality and SARS-CoV-2 testing records for both residents and staff were obtained from routinely collected healthcare information held within the UK COVID-19 Datastore, based on the data pipeline for the previous VIVALDI observational study, 13 with linkage of residents to participating homes provided by Care Quality Commission Identification (CQC-ID) codes stored as part of SARS-CoV-2 test records. Weekly aggregate data on current numbers of staff and residents at each care home and total number of COVID-19-related hospital admissions were collected from care providers and combined with the routine health data for analysis. We also asked care providers to upload individual-level records of COVID-19-related hospital admissions among residents to the COVID-19 datastore through a secure process to provide a timelier data-feed for primary outcome events, as a time lag existed at the time of study operation of several months for the diagnostic coding of routine data on hospital admissions. We planned to recruit 280 homes randomised 1 : 1 to intervention and control arms to provide 84% power to detect a reduction in primary outcome due to the intervention from 3.0% to 1.9% (relative risk 0.63) over the trial period. Early cessation of the trial led us to adapt the originally planned in-trial economic evaluation to explore, qualitatively, the economic aspects of the intervention in more detail, to inform policy on the design of future strategies using financial incentives to reduce the spread of respiratory infections in care homes. We investigated the evidence for care home providers’ policy and practice on asymptomatic COVID-19 testing, respiratory infections and related sickness absence, sick pay and shift backfill in the late pandemic period (2023) and on UK health protection services’ processes of care home respiratory illness outbreak management. We calculated costs of the elements of the trial intervention, drawing on the trial data collections, to contribute to modelling cost-effectiveness. We also calculated indicative costs of Health Protection Teams’ (HPTs) inputs to responding to care home respiratory illness outbreaks. We developed a compartmental model to simulate the transmission of SARS-CoV-2 in England, stratifying the population into three distinct groups: general population, care home staff and care home residents. The model employed a susceptible–exposed–infectious–recovered framework and was coded using R (v4.3.3, The R Foundation for Statistical Computing, Vienna, Austria). We considered a baseline scenario and different intervention scenarios, with testing rates and the implementation of an additional NPI differing between them. Testing and hospitalisation costs were associated to each modelling scenario, and we estimated the cost-effectiveness of each by calculating incremental costs per case averted. A subsequent process evaluation using qualitative data ( n = 22) from six diverse care homes (two large care home chains, two small care home chains and two single care homes) was conducted to understand intervention roll-out and identify areas for optimisation to inform potential intervention scale-up in the future. We used a retrospective design and deductive thematic analysis on data collected from diverse care home staff through focus groups. Key elements of the intervention’s programme theory guided both data collection and initial analysis. Analysis initially grouped data concerning (1) important aspects of the context, (2) the problem(s) the intervention was intended to solve, (3) the delivery of the primary intervention elements (e.g. fidelity and acceptability), (4) purported and novel mechanisms, and (5) intended and unintended outcomes. Subsequent analysis gauged relative support for, and relative importance of, these programme theory elements. From the outset, stakeholder engagement was undertaken alongside all empirical work to enable the sector to plan for results and their implications and to coproduce, with the care sector, recommendations on the use of testing for policy-makers. Results summary Within a rapid time frame (~ 6 months), insights from the literature, stakeholder engagement and qualitative research were cumulatively synthesised to develop a scalable, low-intensity intervention, ‘Test to Care’ ( Figures 2 and 3 ). Details of the intervention development process, including a full narrative programme theory showing how the intervention was intended to work in situ, are available elsewhere (Preprint). The intervention promoted biweekly staff self-testing for asymptomatic SARS-CoV-2 via lateral flow devices (LFDs). ‘Test to Care’ was built on the sectors’ prior experiences of testing and initially used persuasive communications to kickstart the intervention (harnessing the care home setting and touching on professional identity). We had hypothesised that the financial incentives (both for staff testing positive and for care providers and temporary staff to backfill) would then maintain testing over time (via modelling the personal and organisational benefits of testing). However, this was contingent on the continued circulation of COVID-19 in the community. FIGURE 2 The preliminary logic model reflecting the intervention’s initial programme theory. COVID, coronavirus disease. FIGURE 3 An example of part of a poster used to promote the start of ‘Test to Care’. COVID, coronavirus disease. The RCT was conducted from January to August 2023. Eighty-five care homes were recruited, with 43 randomised to intervention and 42 to control. Two intervention-arm and two control-arm homes dropped out of the study before any outcome data collection. Therefore, 41 care homes randomised to intervention and 40 randomised to control were included in the analysis. The trial was stopped early following the recommendation of the oversight committees as it was not adequately powered for the primary outcome due to lower-than-anticipated site recruitment and lower-than-expected incidence of COVID-19 in the community. The median number of residents per home was 40 [interquartile range (IQR), 33–55] in the control and 39 (IQR, 29–57) in the intervention arm. Aggregate data were collected from Providers for 1356/1396 (97.1%) site-study-weeks, with information on resident numbers for missing weeks filled in by interpolation. There was one control arm site for which we were unable to establish linkage to routinely collected data based on the home’s CQC-ID; this site was excluded from the analysis of all affected outcomes. The mean proportion of staff per home with a recorded SARS-CoV-2 test result each week was 1.3% (median: 0%, IQR: 0–1%) in the control arm and 14.4% (median: 13%, IQR: 3–21%) in the intervention arm. There was a reduction in logged staff testing beyond the end of March 2023 in the intervention arm and near-total cessation in the control arm ( Figure 4 ). This corresponds to a change in the national testing guidelines at the start of April 2023, with an end to routine symptomatic and outbreak testing of staff for SARS-CoV-2 . The mean proportion of staff reported by intervention sites to be opting out of testing per home per week was 16.3% (median: 5%, IQR 0–20%). FIGURE 4 Line graph of the percentage of staff at each participating home with at least one SARS-CoV-2 test recorded in the national testing data set within each week of the study. Reproduced from Stirrup et al . This is an Open Access article distributed in accordance (more...) There was no significant difference in the primary outcome of resident COVID-19-linked hospital admission incidence between intervention and control arms [22.7/1000 person-years vs. 15.0/1000 person-years, incidence rate ratio (IRR) 1.19, 95% confidence interval (CI) 0.55 to 2.58; p = 0.66; incidence rate difference 4.0, 95% CI −14.3 to 22.2]. A total of 22 primary outcome events were observed using routine health data, but only one of these was directly uploaded to the COVID-19 Datastore as an individual trial event, and Providers reported a total of eight COVID-19-linked admissions in their weekly aggregate data. There was no significant difference between intervention and control arms in the incidence rates among residents of COVID-19-linked mortality (IRR 0.64, 95% CI 0.15 to 2.70; p = 0.54), all-cause mortality (IRR 1.13, 0.84 to 1.52; p = 0.43), the composite event of coronavirus disease (COVID)-linked hospital admission or mortality (0.95, 0.43 to 2.08, p = 0.89) or in the incidence of SARS-CoV-2 infections (2.65, 0.77 to 9.19, 0.12). However, there was a statistically significant reduction in the rate of all-cause hospital admission in the intervention arm relative to control (IRR 0.74, 95% CI 0.56–0.98, p = 0.03) (this was also observed on unadjusted analyses). As expected, the prevalence of SARS-CoV-2 among staff who tested in the intervention arm was lower than that in the control arm [8.1% vs. 26.9%, adjusted odds ratio (aOR) 0.25, p < 0.01]. There was no difference between intervention and control arms in the proportion of staff on sick leave each week (6.4% vs. 6.2%, aOR 0.99, p = 0.90) or in the proportion of shifts filled by agency staff (6.4% vs. 5.1%, aOR 1.25, p = 0.73). The trial data and findings, as well as our challenges with both recruitment and the primary outcome, are illuminated by insights from the qualitative process evaluation (e.g. the analysis of care home-staff perspectives such as front-line staff, care home managers, receptionists, nurses and senior administrators). Figure 5 shows how some elements of the context remained important in shaping intervention roll-out [such as changing social norms about testing and labile levels of COVID). Other elements of the context diminished in importance (e.g. exhausted sick pay). Major aspects of the problem the intervention was designed to address were no longer important (e.g. the financial burden of testing positive). In this way, although the intervention was delivered as expected, the very low levels of COVID-19 reduced its relevance (i.e. individual receipt of sick pay for COVID-19) and it did not gain traction through visible receipt of sick pay. Further, some important mechanisms did not work as anticipated, for example, cascading norms and professional identity flipped from being supportive of testing and adherence to COVID restrictions at the start of the trial, to rejecting them (as a result of wider social norms such as ‘getting back to normal’ and the changes to care home staff being a priority group for vaccination). Thus, between the development and latter stages of implementing ‘Test to Care’, key aspects of the context changed dramatically (e.g. lowered COVID-19 incidence and withdrawal of symptomatic testing for care home staff, except for those who were clinically vulnerable), as well as social norms: FIGURE 5 Updated logic model reflecting what happened during the trial. People were tired of testing and, when everybody else in the country went back to normal and decided that COVID-19 wasn’t a thing, our teams were still wearing masks. They were still wearing heavy PPE during heatwaves, and they were still being heavily scrutinised over symptoms and still being tested very heavily when everybody else was away to a disco. Large care home chain staff member These profound contextual changes meant the problems the intervention had initially intended to solve had considerably diminished in the meantime (e.g. needing sick pay for asymptomatic COVID-19, the low risk that infection in residents would culminate in severe outcomes). The incidence of COVID-19 cases was low and, as such, the intervention failed to gain traction and momentum. But we haven’t got a case at the moment; across the whole organisation, we’ve got no outbreak. So, our dashboard says today. Care home chain director As per Figure 4 , initial high levels of intervention acceptability (reflected in the uptake of testing in intervention homes) waned, although there was evidence to support ongoing fidelity of intervention components (the distribution of communication materials and the local administration of tests and managing test results). Unsurprisingly, over time, many of the intervention’s main mechanisms ceased to work as anticipated (e.g. professional identity reinforcing testing) as new contextual mechanisms superseded the interventions (e.g. professional identity became associated with resistance to COVID-19 restrictions as the sector felt abandoned). As such, the intended intervention outcomes were not delivered as anticipated. The residents have just had their next booster, but obviously, now that’s not open to the staff, and that’s the first time that that’s happened – that care staff haven’t been – been included in – in who can have the vaccine. So, I think there’s kind of a, ‘Well, why should we bother doing anything now for anybody else when we’re not getting anything back? We’re not getting any protection in the form of the vaccine anymore, so why should we test anyway, because it’s – you know, it’s like it [COVID-19] doesn’t exist anymore, so let’s just carry on’. Single care home chain staff member The VIVALDI Adult Social Care Outcomes Toolkit (ASCOT) and Ethnography Study 14 assessed the impact of COVID-19 and respiratory outbreaks on the QoL and psychological well-being of care home residents. Using a cross-sectional design, we conducted in-person interviews with 46 residents across 10 care homes in Southeast England between April and July 2024, employing ASCOT and additional measures of mental and functional capabilities. Ethnographic observations in three care homes complemented quantitative data obtained from 10 care homes, offering insights into residents’ lived experiences. During the study period, we only had one report of a COVID-19 outbreak and completed three interviews in that care home; therefore, we were not in the position to meaningfully compare the QoL in care home residents impacted by COVID-19 outbreaks with the QoL of residents from care homes without outbreaks. Therefore, this study employed an observational study design in 43 residents from 9 care homes without any outbreaks and 3 residents from 1 care home with a COVID-19 outbreak. An analysis of the eight domains captured by the ASCOT social care-related quality of life (SCRQoL) highlighted that 46% of participants had adequate access to food and drink, while 44% reported sufficient social contact. The SCRQoL score averaged 0.75, indicating minimal variation between perceived and expected QoL . Figure 6 illustrates the distribution of top responses across eight ASCOT QoL domains among care home residents. The domains with the most positive responses include personal safety (74%), accommodation cleanliness and comfort (63%), and personal cleanliness and comfort (61%) in most care homes observed that did not experience an outbreak during the study period. Areas with lower satisfaction include control over daily life and dignity, each of them with 39% of residents expressing the top level of satisfaction. FIGURE 6 Quality of life in care home residents across ASCOT domains in the VIVALDI ASCOT and Ethnography Study. This figure presents the percentage of care home residents reporting the highest level of satisfaction across eight ASCOT QoL domains. In the analysis of the eight domains of QoL (ASCOT), the Friedman test indicated a statistically significant difference between the domains (Friedman = 137.87, p < 0.001), suggesting variability in how residents rated different aspects of their QoL . Subsequent pairwise comparisons using Wilcoxon signed-rank tests revealed significant differences between the control domain and cleanliness ( z = −3.641, p = 0.0003), food ( z = −2.197, p = 0.0280), safety ( z = −3.754, p = 0.0002) and comfort ( z = −2.929, p = 0.0034) domains. No significant differences were found between the control domain and the social ( z = −0.969, p = 0.3327), occupation ( z = −0.195, p = 0.8453) and dignity ( z = 0.344, p = 0.7308) domains. Social care-related quality of life Gain was calculated by comparing observed SCRQoL against expected SCRQoL scores based on individual characteristics of residents from participating care homes. Findings revealed that most residents, regardless of gender, had a negative SCRQoL Gain, indicating lower-than-expected QoL independent of outbreaks, number of care home staff, number of residents and care home characteristics. Regression analyses identified age as a significant predictor of SCRQoL Gain ( β = 0.03, p = 0.029), suggesting older residents experienced greater benefits from social care support. The moderation analysis showed that the interaction between age and care home type (nursing) was significant ( β = −0.01, p = 0.003), indicating that the effect of age on SCRQoL differs based on the type of care home. Specifically, in nursing homes, older age was associated with a more pronounced negative impact on SCRQoL compared to other care home types. Additionally, the interaction between age and staffing levels was significant ( β = 0.001, p = 0.007), suggesting that higher staffing levels moderate the relationship between age and SCRQoL, such that the negative effect of age is mitigated in care homes with higher staffing ratios. In contrast, no significant moderation effect was found for other variables like care home size or outbreak status. Overall, our findings underscore the need for decisions on outbreak control and other health protection to address both SCRQoL and psychological well-being. A thematic analysis of 33 semistructured interviews with care home residents from the VIVALDI ASCOT and Ethnography Study was also conducted to understand their perceptions and responses to COVID-19 restrictions in general and the impact of the COVID-19 pandemic. Our analyses revealed that isolation affected residents’ social interactions, autonomy and engagement in meaningful activities. Residents expressed varied responses to isolation, with many reporting increased feelings of loneliness. Preferences for private versus communal spaces were influenced by the need for control and social connection. Adaptive strategies, such as engaging in solitary hobbies and using technology, emerged as coping mechanisms, although influenced by access and environmental limitations. Furthermore, an important issue emerging was how restrictions were explained and communicated to residents in care homes. During the COVID-19 pandemic, informing the public about restrictions and governmental guidelines was of paramount importance when trying to get infection rates under control. Most residents recalled being informed about the COVID-19 outbreaks or infection prevention measures by members of staff in the care home, followed by being informed by television. Most residents described being informed directly but lacking additional meaningful explanations: They come and say, ‘I’m shutting the door for 10 days, They just said we’ve got a slight outbreak, and we’re doing our best for you. We were just left with that, All they said was you’re isolated. Get us all together, tell them all in one go. Although some residents stated they understood the reasons for infection prevention measures, with one resident stating, ‘Yes (I understood the infection prevention measures), just do as you were told’, this statement may still suggest a lack of understanding as to why specific measures were taken but instead demonstrates an understanding for simply following instructions given by members of staff. Other residents felt as though they lacked understanding: ‘No (I did not understand the infection prevention measures), I just left it to the staff here, and they kindly did what was necessary’. Furthermore, both statements suggest that there is a strong sense of trust from residents towards the staff, which perhaps reflects why many residents would prefer to be informed of future outbreaks, like COVID-19, by members of staff. One resident noted that they would prefer staff to inform them of future outbreaks since if ‘they don’t understand, they can just ask questions’, something which television, leaflets, or films could not enable. Our findings underscore the complex interplay between physical and psychological-well-being, as well as the importance of communication for promoting a safe environment in the care home and maintaining optimal QoL for vulnerable residents, advocating for interventions that address a more holistic approach to QoL in older age. To inform the economic research and modelling, we conducted rapid reviews of (1) UK evidence on care home providers’ policy and practice on asymptomatic testing for COVID-19, sickness absence and unfilled shifts (since 2023), (2) international evidence on incidence of respiratory infections, care home sick pay and/or shift backfill policies (since 2023), and (3) UK public health costs of managing care home outbreaks of respiratory infections (see Appendix 1 ). We found almost no evidence on any of these questions. A single peer-reviewed study was located for rapid review 1, which partially addressed this question but did not describe care home policy relating to sickness absence or unfilled shifts. We did not find evidence on UK public health team costs of managing care home outbreaks of respiratory infections. We also sought to understand post-pandemic care home providers’ policies and practices on care home testing for COVID-19, sickness absence due to respiratory infections and consequent shift backfill in English care homes, and to explore costs to providers of outbreaks of respiratory infections. We interviewed 11 senior managers from 10 privately owned care homes or care home groups across England providing services to older people. The sample was diverse in terms of region, size of provider and Care Quality Commission rating. Interview transcripts were analysed using the framework approach and findings tabulated. At the time of the interviews, none of the care homes conducted asymptomatic COVID-19 testing. A minority required that staff with respiratory infection symptoms continued to test for COVID-19. Care homes’ COVID-19 testing and sickness pay policies were in line with current public health guidance on COVID testing and statutory sick pay regulations. Pay and conditions have been linked to presenteeism in the social care sector and may contribute to the risks of staff transmission to residents at times when respiratory infections are highly prevalent. Although regular staff testing combined with self-isolation for those who test positive may be effective in reducing transmission of infection, such policies require careful design, given the important financial implications for care workers, care home providers and for the wider public health and care sector. We also investigated the direct costs of costs of public health responses to outbreaks of COVID-19 and respiratory infections. Two focus groups were held in July 2024 with staff from United Kingdom Health Security Agency (UKHSA) HPTs from two regions of England (two staff members in one region and four in the other), exploring how HPTs are notified of outbreaks of COVID-19 or respiratory infections and the time and resources needed to respond to outbreaks. Financial information was sought from UKHSA contacts provided by focus group participants, so that costs could be attached to the inputs described by participants. Focus groups discussed responses to scenarios describing low-risk and high-risk outbreaks. Indicative costs were calculated from the inputs by attaching unit costs obtained from UKHSA or public sources. We identified that low-risk outbreaks require minimal input from HPTs. Notifications are logged initially by administrative officers who either conduct a basic risk assessment or administer an automatic assessment form and send standard pre-written infection control advice. These cases are reviewed by health protection practitioners, infection control advice is provided to the care home, and the case is usually closed after that. There was considerable variation in the estimated costs of a low-risk outbreak, but none of these exceeded £50 per outbreak (2023–4 prices). In contrast, based on the outbreak scenario presented to the groups, it appears that high-risk outbreaks required significant inputs from the HPTs. Processes following the initial notification were similar to those of a low-risk outbreak but would then lead to a more intensive review by a health protection practitioner. Once the presence of infection was established, and as more information revealed complexities that increased risk, the health protection response was to conduct more in-depth risk assessments and assemble an Incident Management Team (IMT) to mount a response, which would involve both health protection staff and external partners – local authority or Integrated Care Board (ICB) Infection Prevention and Control (IPC) teams, local authority public health teams, other local authority teams involved in quality assurance, general practitioners (GPs), pharmacists and care home staff. Actions after the IMT focused on swabbing, laboratory testing and prescription of medications (antivirals). The costs associated with a high-risk outbreak could vary from £585 to about three times as much (£1805), depending on the costing method and region/group. The focus groups’ discussions of IMT were of particular interest, demonstrating that there could be a wide range of responses to the stylised version of a high-risk outbreak presented to the groups. The number of meetings could vary considerably, as could the personnel and agencies involved in those meetings. The personnel involved in organising practicalities such as swabbing, testing and co-ordination of prescriptions via GPs and pharmacists’ tasks varied between the groups including Business Support teams and health protection practitioners. One of our original aims was to model the impact of the intervention under different epidemiological scenarios to inform policy. However, early cessation of the trial meant the modelling team did not have access to estimates of intervention effectiveness as originally planned. Following funder approval, the modelling team therefore revised the aims and design of their study (see Appendix 2 ) to focus on a scenario analysis set during a hypothetical peak of the COVID-19 pandemic, calibrating the model to observed COVID-19 prevalence rates in the general population (UK Health Security Agency 15 ) and care home residents 13 using recorded numbers of staff tests and COVID-19 cases among staff and residents derived from the VIVALDI study, 16 in participating care homes between January 2021 and March 2022, with effectiveness of treatment and testing being informed by literature. During this time, ~74% of staff had at least one test recorded in any given month, and we compared this baseline with testing scenarios of all staff members being tested monthly, bimonthly, weekly, biweekly and daily testing. We found evidence that only testing staff (without the use of additional NPI measures preventing transmission among residents, such as resident isolation) had minimal impact on reducing infections and deaths in residents. By contrast, combining NPIs with staff testing significantly reduces resident cases and deaths. These analyses also assumed that staff members who tested positive self-isolated until they were no longer infectious. Modelling projections for 12 months showed that daily staff testing, without additional NPIs, reduced resident cases by 3.8% [95% uncertainty interval (UI) 3.1% to 4.5%] compared to baseline (less than one test per staff member per month) and reduced resident deaths by 3.5% (95% UI 2.3% to 4.4%) compared to the baseline. Biweekly staff testing, combined with resident isolation, reduced resident cases by 27% (95% UI 23% to 30%) and resident deaths by 25% (95% UI 14.2% to 30.7%) compared to the baseline. Daily staff testing, combined with a NPI , reduced resident cases by 53.6% (95% UI 49.5% to 57.7%) and resident deaths by 49.9% (95% UI 26.3% to 59.1%) compared to the baseline. Non-pharmaceutical interventions, when paired with baseline, monthly, or bimonthly testing, resulted in a small number of cases and deaths averted (5.7–14.1% cases and 5.2–14% deaths). This approach was, however, associated with substantial cost savings compared to baseline testing without additional NPI measures. We calculated the total cost of each intervention as the sum of intervention costs (costs of tests, sick pay and staff backfill collected during the trial) and hospitalisation costs (with and without critical care, from the National Institute for Health and Care Excellence). When compared to baseline, monthly and bimonthly testing strategies saved from £677,804 to £3,408,775 during the 12-month analysis. These costs are saved due to a reduction in resident hospitalisations. The analysis however does not take the cost of the hypothetical NPI into account. Meanwhile, weekly, biweekly and daily testing resulted in a higher reduction of cases (14.7–57.7%) and deaths (9.8–59.7%), but little (weekly and biweekly) to no (daily) costs saved £−5,352,720 to £2,660,018 due to the high cost of testing. All interventions involving staff testing, without NPI , led to increased costs compared to the baseline testing (£−574,658 to £−22,428,306.4). This is because the reduction of resident hospitalisations was insufficient to balance the expense of the testing interventions. Research papers that are being synthesised in the synopsis ‘Test to Care’: an integrative approach to co-produce an intervention to maintain biweekly asymptomatic SARS-CoV-2 testing amongst UK care home staff using the behaviour change wheel – submitted to the British Journal of Health Psychology . VIVALDI-CT shaping care home COVID-19 testing policy: a pragmatic cluster randomised controlled trial of asymptomatic testing compared to standard care in care home staff – published in PLOS ONE . Understanding the implementation of ‘Test to care’ within UK care homes: a qualitative process evaluation using programme theory – submitted to the British Journal of Health Psychology . VIVALDI ASCOT and Ethnography Study: protocol for a mixed-methods longitudinal study to evaluate the impact of COVID-19 and other respiratory infection outbreaks on care home residents’ quality of life and psychosocial well-being – published BMJ Open 2024; 14 :e088685. https://doi.org/10.1136/bmjopen-2024-088685 The impact of COVID-19 outbreaks on social care related quality of life of older care home residents in England: findings from the VIVALDI ASCOT and Ethnography Study – submitted to Lancet Healthy Longevity . Lonely together: the impact of COVID-19 restrictions on social connection, autonomy, and well-being in care homes residents in England – submitted to Lancet Healthy Longevity . Exploring post-pandemic policies on staff testing, sickness pay and absence related to COVID and respiratory infections in English care homes – under review with BMC Health Services Research . Rapid reviews of policy and practice on respiratory infection care homes outbreaks: COVID-19 testing, sick pay and public health outbreak management – short report under review with the Journal of Public Health . Staff testing in care homes for older people: policy implications for future pandemics – submitted to BMJ Global Health . Effects and cost-effectiveness of staff testing in care homes for older people: policy implications for early stages of future pandemic responses – awaiting final decision from PLOS Global Public Health . Copyright © 2026 Adams et al . This work was produced by Adams et al . under the terms of a commissioning contract issued by the Secretary of State for Health and Social Care. This is an Open Access publication distributed under the terms of the Creative Commons Attribution CC BY 4.0 licence, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. See: https://creativecommons.org/licenses/by/4.0/ . For attribution the title, original author(s), the publication source – NIHR Journals Library, and the DOI of the publication must be cited. Some parts of this synopsis have been reproduced from Stirrup et al . This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) licence, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/ . The text below includes minor additions and formatting changes to the original text. Discussion/interpretation Principal findings, achievements and take-home messages An evidence-based and theoretically informed intervention, ‘ Test to Care ’, was successfully developed with input from the care sector and patient and public involvement and engagement (PPIE) within a compressed time frame. We specified the contexts in which it would work, its key components and their mechanisms (e.g. sick pay and agency backfill supported by light touch communications and peer support) and the ways it would change our primary outcome measures. The learning from this work (i.e. the process of its development and its careful theorisation) is directly relevant for the future rapid deployment of public health measures in the care sector in the event of new and emerging infections, pandemics, or other threats (e.g. heat), particularly where it is critical to co-design interventions from an emerging evidence base at pace. The subsequent cluster RCT was successfully initiated within 3 months of funding being granted. Data on resident health outcomes were successfully collated from routine data sources through the COVID-19 data set and combined with aggregate data collected directly from participating care providers. Still, it was challenging to collect individual-level data on residents directly from care providers, highlighting the challenges associated with studies that rely on prospective data collection by care home staff. Site recruitment and staff motivation to continue asymptomatic testing for SARS-CoV-2 were both impacted by changes to SARS-CoV-2 epidemiology, national testing policy and broader social changes resisting COVID-19-related restrictions. This led to early cessation of the trial, with fewer care homes recruited than planned, waning testing levels within intervention homes (see Figure 4 ) and a lower incidence rate of the primary outcome than expected in the control arm. Unsurprisingly, therefore, there was no significant difference in the primary outcome of the trial. In relation to transferable lessons learnt from the COVID-19 pandemic to future pandemics, the profound changes to the context in which this intervention was trialled may occur again depending on factors such as pathogen biology, its population reach and the stages of the pandemic in which intervention research is conducted. The complexity of these varied contextual factors suggests there is a need for more conceptual clarity around the changing contexts of pandemics. Interventions developed and used at the start of a pandemic may not work as anticipated towards the latter stages of a pandemic. For those developing intervention content, it may be worth considering this flux in relation to modifiable active intervention content (e.g. elements and mechanisms) contingent on changing contexts. Although our study was conducted at pace and processes such as intervention development were expediated, our analysis highlighted a temporal lag between the problems that existed at intervention development and at intervention implementation. Future research may focus on anticipating the changing nature of the problems that pandemic interventions may usefully address, and systematically building-in contingency intervention content. There is a need for intervention development approaches to be distinct and different in pandemics compared to developing interventions around non-communicable disease (e.g. diabetes or sedentary behaviour) in which the contexts (and the associated problems the intervention is addressing) are likely to be far more static. There was a nominally statistically significant reduction in all-cause hospital admissions between control and intervention homes. However, this should be interpreted with caution because weekly tests were logged by only 14% of staff in intervention homes, implying a level of testing too low to cause an appreciable impact. Low uptake of testing was likely due to a combination of COVID-19 fatigue and the fact that the salience of the behavioural intervention, which primarily relied on financial incentives (sickness pay) to encourage staff to maintain testing, was reduced by a lack of visible peers reaping the benefits of asymptomatic testing (i.e. sick pay) and low rates of COVID-19 in the community. Our process evaluation also highlights that rates of testing were highly affected by changes to national policy, as declines in testing rates coincided with the UKHSA ’s recommendation in April 2023 to cease symptomatic testing in all staff, except those who were clinically vulnerable ( Figure 7 ) and not to offer booster vaccinations to staff. FIGURE 7 Stepped graph showing the number of active care homes taking part in the trial over time, along with the daily number of COVID-19-linked hospital admissions in England. Note: Stepped graph showing the number of active care homes taking part in the trial (more...) The dual approach of integrating quantitative ASCOT measures with qualitative ethnographic observations underscores the importance of capturing both measurable outcomes and residents’ lived experiences, providing a richer context and allowing for a nuanced understanding of how daily routines, social interactions and care environments influence residents’ QoL , insights that cannot be fully captured through standardised tools alone. Ethnographic data highlighted how factors such as restricted mobility, reduced social interaction and adjustments to infection control practices can negatively impact both the physical and psychological well-being of care home residents. Our study also addressed a significant gap in the literature, which has traditionally prioritised clinical outcomes over non-clinical ones in infection control policy, leaving QoL and social and psychological well-being insufficiently explored in the care home resident population. The rapid systematic review, undertaken to inform the economic analyses, highlighted the lack of published evidence from the post-pandemic period (since 2023) on UK care home providers’ policy and practice regarding conducting asymptomatic testing for COVID-19, sickness absence and/or unfilled shifts. It also demonstrated the lack of evidence on costs of UK health protection and infection control teams’ contributions to managing outbreaks of respiratory infections in care homes. Contribution to existing knowledge We conducted high-quality research during an unfolding pandemic in a sector that was in crisis. By necessity, the trial had to take place in a rapidly evolving policy and epidemiological context. Still, we assessed that this risk was outweighed by the opportunity to capture insights that could almost certainly only be gained during a pandemic (given the high costs of sick pay and the low likelihood that such an intervention would be funded in future). The grant review process was expedited (application submitted in August 2022, funding outcome October 2022), and we were able to expedite approvals from the Health Research Authority (HRA) Research Ethics Committee (REC) and Confidentiality Advisory Group (CAG) to enable recruitment to start in January 2023. These timelines are exceptionally fast for a clinical trial, but particularly for a study based in social care. This agility and ability to respond rapidly are likely to be vital for future pandemics. However, we still encountered significant contractual delays, which delayed study setup with some providers, largely due to the complexity of arrangements of funding sickness payments and agency staff backfill, recognising that each provider does this differently. Funding for sickness pay and agency staff was provided by UKHSA . However, the mechanism for providers to evidence these payments was complex, which introduced a significant additional workload for providers, University College London (UCL) and UKHSA . Utilising the expertise of the UCL Comprehensive Clinical Trials Unit (CCTU) enabled the trial to be set up robustly and efficiently. Although we identified that the rigour of a CCTU-led approach may not always be necessary or appropriate for the social care sector, the extensive and varied experience in trial conduct methods meant that the approach could be tailored and revised to make it easier for care providers who were relatively new to research and ensure a pragmatic approach to the research. We were also purposefully pragmatic about building on sector expertise and involved the sector in every way possible from the start and operationalising the trial at pace but safely, expediating processes wherever possible. Despite the vulnerability of the care home population, with the exception of interventions to improve hand hygiene, 17 – 19 there have been few trials of NPIs to reduce transmission of COVID-19 or other respiratory infections in this setting. 9 More broadly, while the need for more research in care homes is widely recognised, there are many barriers to research delivery, particularly for clinical trials. 20 VIVALDI-CT aimed to address a specific research question, but we were also motivated by the opportunity to build on the existing care home network, data and testing infrastructure established during the pandemic and the VIVALDI study 16 and investigate how this might be used to support efficient future trials. Developing the research capabilities of individual care home staff was central to this work, with staff completing short-format good clinical practice courses and gaining experience in real-world and clinical trial research. This grounding provided a platform for the use of systematic intervention development within an unfolding pandemic, which we believe to be the only example of such work. This work is an important example of the synergies of transdisciplinary working, enabling our findings to contribute to existing knowledge beyond the clinical trial. Strengths, limitations and reflections Strengths of VIVALDI-CT were its dynamic and open approach, interconnectedness with the sector, and the existing expertise within wider VIVALDI collaborations. The ability to build on goodwill and strong partnerships forged through this previous work meant that there was a collective approach, leveraging links to government and the wider public health system to generate evidence to rapidly inform policy decisions. There was a strong desire to adapt and build on this evidence and not to return to ‘business as usual’ post pandemic. Working in partnership enabled creative and pragmatic solutions to problems encountered and has contributed to the sustainability of research within the sector. The funder, ethics and CAG processes were responsive and agile, which enabled the rapid development of the trial, and this success should be celebrated and modelled for future pandemics. The use of programme theory and pre-specification of what the intervention was and how it would work enabled us to understand what was happening (i.e. that the context changed rather than this being a poor intervention) and allowed us to separate what did and did not work, and the reasons for this. The qualitative approach also delivered a nuanced understanding of changes occurring over time and a sense of growing frustration with testing. The main limitation of the trial is that its timing (e.g. the latter stages of a pandemic and not including a winter season) limited participation and ultimately led to its early cessation, and results should be interpreted with these limitations in mind. Early cessation meant that we were unable to address our original research question as it was underpowered for primary and secondary outcomes. The total of 22 primary outcome events observed corresponds to a 6-month cumulative incidence across trial arms of 0.93%, substantially lower than the control arm cumulative incidence of 3.0% that was assumed for the sample size calculations (or the assumed average of 2.45% across the two trial arms). As such, the trial would have been underpowered even if the target number of care homes had been recruited. There is also some uncertainty regarding the level of staff testing achieved in the intervention homes, as the average staff opt-out level reported by homes was ~15%, but our testing data show an average proportion of staff testing per week of only ~15%. This might be explained by a combination of staff not testing while not formally opting out or staff testing but not logging their results into the digital portal. It is unclear how we might have collected accurate information on this, without having access to an embedded research workforce to support prospective data collection. The national incidence of SARS-CoV-2 infections was dropping at the time of the trial, and severe outcomes, even among care home residents, were relatively rare due to high vaccination and booster coverage and prior infections. 21 The findings at this stage of the pandemic may not have matched those that would have been obtained at earlier points in time. The reduced incidence and impact of SARS-CoV-2 over the trial period were also associated with a reduced level of resident testing, with regular asymptomatic testing in residents having already ceased on 31 March 2022 and outbreak testing stopping at the end of April 2023. This was a concern because the trial’s data pipeline relied on SARS-CoV-2 testing records for the identification of residents of participating homes and subsequent linkage to their health outcome data. Linkage of residents to care homes was carried forward for 12 months from their most recent test, and so we may have included some outcome events for residents who had already left a participating care home or missed events for residents newly admitted to a care home without any SARS-CoV-2 tests recorded. Aggregate and individual-level data collection of COVID-19 linked resident hospital admissions from care providers was included in the study protocol to provide robustness against this issue for the trial’s primary outcome. Still, after reviewing the available data sources, we concluded that the linked routine health data were the most reliable despite the concerns regarding linkage. There were severe challenges to recruitment as participants were mostly senior staff, with very few front-line staff involved. This reflected the growing COVID-19 fatigue that also shaped intervention uptake. This also resulted in a small and biased sample, with a tendency for participants to report that everything was fine and that everyone had been testing. Although the intervention was tailored to a context, this context changed. If we had felt that the intervention should have continued regardless given our equipoise, we would have boosted the intervention with new components and mechanisms (e.g. auditing, reminders and so on). This would have turned the intervention from low intensity to medium intensity and its demands would have been novel and required far more resource (staff, staff remuneration, training and so on) which would have also influenced the cost-effectiveness. Managing the ethical approval processes for the clinical trial at pace as well as intervention development and process evaluation was challenging but achievable. There were also internal contingencies, with interconnecting WPs being reliant on the trial. The significant contractual delays and challenges with recruitment and engagement due to sector fatigue significantly impacted most of the WP and resulted in delayed interviews with care home managers and public health officials, shortening the available time for data collection. As the funded time had run out, we had to stop data collection and so did not quite meet the target sample size for interviews with care home managers. Our aspiration was to approach infection prevention and control staff in local authorities to participate in the public health focus groups, but as this would have required further permissions from individual councils, we decided that this was not feasible within project time frames. We relied on qualitative data only for the intervention development, collected exclusively via online recruitment given the COVID-19 restrictions that were in place at the time which may have restricted our findings. It was also a challenge to ensure the timing was correct for a context-sensitive tailored intervention given the unfolding nature of this pandemic. This study did not explore different interventions aimed at reducing transmission among residents, such as different forms of resident isolation, use of face masks, room ventilation, and so on, which could be explored in future work. In the modelling, we considered a best-case scenario where LFD tests have 100% sensitivity and did not account for variations in test accuracy. Modelling did not account for visits from relatives or professionals such as physiotherapists or GPs, which may impact transmission, and we assumed that contact patterns between staff and residents did not change throughout the simulation. Patient and public involvement and engagement was challenging throughout, and resident voices were difficult to include. This is reflected on in greater detail in the PPIE section. For the VIVALDI ASCOT and Ethnography Study, only those with the ‘Mental Capacity’ to agree to study participation were recruited because we were unable to secure sponsorship for a study that recruited residents without capacity, even when using standard approaches to consent in this population such as nominated and/or personal consultees. Therefore, the findings might not be fully generalisable to the entire care home population where many residents have dementia and other severe cognitive impairments. Nonetheless, this could also speak to the impact of age-related cognitive decline on recall, especially relating to subjects potentially clouded by their memories during times of COVID-19. Furthermore, results may have been biased as questions required to recall past events and feelings during the time of being faced by the pandemic, yet subject cognitive dysfunction restricted our ability for a thorough investigation. To reduce the impact of cognitive or language deficits, data were effectively sieved at times, leading to a lack of depth in some analyses. The cross-sectional design could also limit its generalisability. Additionally, data collection outside of peak outbreak periods may introduce recall bias and reduce the applicability of these findings during active outbreak situations. The current study had a reduced sample, and this might have impacted the statistical power of our analysis. Future research could expand upon our findings through longitudinal studies that monitor SCRQoL changes over time, particularly during and following outbreak periods, to better capture the lasting impacts of pandemic restrictions and other infection control measures on resident-well-being. Engagement with partners and stakeholders We dedicated a whole WP to stakeholder and partner engagement, and this proved invaluable for the project. These engagement activities were a key platform to disseminate findings, check key project decisions, get informed decisions on trial cessation, and to source different kinds of expertise. The project was able to build on the legacy of the preceding VIVALDI project, which meant multiple relationships and network access were already established and could be drawn upon easily. Further engagement was straightforward given the nature of the unprecedented crisis that the intervention was situated within at the start and the national policy focus. We also had significant involvement from UKHSA , with one coinvestigator (Prof Cassell) having a dual role. Given the policy focus of the government at the time, coupled with the uncertainties of potential new variants escaping growing immunity, engaging key stakeholders was relatively easy, particularly in the early days of the intervention roll-out. However, in smaller future epidemics/pandemics, which may lack the capacity, momentum and sustained interest of a global pandemic, engagement might not be so easy. We had anticipated holding events to share the end results, enabling wider UK engagement but have not managed this given the necessary early cessation of the trial. Although there was representation from other UK nations in the team via the steering committee, it was challenging to engage with nations other than England. Moreover, as pandemic recovery became more of a focus, engagement overall reduced. From the outset we actively involved care home chains and had one care home chain coinvestigator, although her involvement ceased when she changed roles and left her organisation (not an uncommon scenario in social care). Our engagement of large care home chains in decisions and planning was successful overall and should be repeated in future epidemics/pandemics that particularly affect the sector but, although it delivers access at scale and rapidly, our study was not able to recruit smaller and local authority homes due to the pace of the trial setup. Care provider organisational alignment with the intervention focus enabled good engagement, although there were considerable start-up costs. These costs would not likely be recurrent but understanding these and differences across organisations/providers is a future priority. Similarly, there were challenges in ensuring homes were ready to participate in the trial and, while this may be partly explained by the fact that it was their first experience with research, it does highlight the need for recognising the timeline lags associated with trial-ready transformations in other locations and different kinds of homes. Meetings were held with Chief Executives and Senior Leadership Teams of major care providers, the trial co-principal investigator (LS) and the UKHSA Chief Medical Adviser to encourage participation in the VIVALDI-CT . These meetings led to the decision to include payments to care providers for agency backfill as part of the intervention. Individual training and institutional capacity-strengthening activities Individual and institutional capacity strengthening was central to this project, as described in earlier sections and the subsequent section on Patient and public involvement and engagement , ensuring care homes and staff were research-ready to participate in VIVALDI-CT . It is also integral to our planned work following on from this project, which is outlined in greater detail in Impact and learning . Patient and public involvement and engagement Patient and public involvement and engagement was used extensively to inform the development of this programme by highlighting the barriers to testing and the need to capture its adverse impacts on staff, residents and providers. The importance of developing a strong plan for implementation and recognising the financial implications of long-term use of testing and sickness payments informed our emphasis on implementation in WP5. Despite extensive efforts to establish a formal PPIE group, we found that the only way we were able to engage with relatives and/or public representatives to get input into the project was through one-to-one meetings with our PPIE lead (RL). This made it very challenging to get sustained input from individuals who could represent residents’ voices and to create a coherent group and associated collective identity and goals (and change typical power dynamics). A key lesson is that it is critical to establish a strong PPIE group before embarking on a project with the care sector, such as VIVALDI-CT . Unfortunately, this was not possible for this project due to the compressed timescales for the project setup and this is likely to be a problem for future epidemics/pandemics. However, we now have a well-established PPIE group called the ‘Adult Social Care Engagement Collective’ (ASCEC), which consists of 30–40 people who represent residents, relatives, care home staff and the views of the care sector. We have achieved this by partnering with a Community Interest Company called ‘The Outstanding Society’, which promotes quality in social care and is led by previous directors of care homes/care home managers. Via their extensive networks, we have been able to ensure sustained input into all our research projects without overburdening specific individuals. ASCEC is part of the VIVALDI Social Care project, which is funded by UKHSA and National Institute for Health and Care Research (NIHR) through Professor Shallcross’s NIHR Research Professorship. All our future research studies in adult social care will be designed with, delivered with and overseen by the ASCEC , subject to continued funding for this group. The VIVALDI ASCOT and Ethnography Study design and materials were revised in consultation with a group of four patient and public involvement (PPI) advisors in Sussex co-ordinated by Sussex Partnership Foundation NHS Trust. The PPI group was consulted on: (1) the suitability of the written materials to recruit residents (e.g. invitation letter, participant information sheet); (2) procedures for administering the resident’s subjective well-being and cognitive measures; and (3) the choice of measures included in the resident interview. The PPI advisors also reviewed the wording of participant-facing documents. This consultation allowed us to make several changes that were beneficial for the study. Dissemination activity was established as a formal WP to ensure stakeholders were aware and involved in the work as it progressed, and they were ready to implement findings as they emerged. They were also tasked with exploring the generalisability of our findings to different kinds of care homes. We took an inclusive approach, working with varied stakeholders, including the National Care Forum, care home industry representatives, care home staff, NHS and primary care perspectives, policy-makers and public health teams at the national [Department for Health and Social Care (DHSC), UKHSA] and regional/local level (e.g. HPTs, local authorities, Directors of Public Health). Our stakeholder engagement also had a particular focus on representing residents’ voices, either directly or via their family, friends, and carers and through the involvement of organisations such as Healthwatch, the Residents and Relatives Association and our own dedicated PPI group. Our original goal was to hold a series of four ‘world café style’ 22 meetings with stakeholders with additional responsive activities as required to address issues arising during the project. The first took place online due to the COVID-19 context at the time, and the second took place via multiple smaller meetings where we gauged support for the early trial cessation. Trial cessation and PPIE activities were discussed and revised once it became clear that the trial would have to stop early and that we would not have clear results to share with stakeholders, given the partial nature of what the study has delivered with specific impacts on WP2, 3b, 4a and 4b. We therefore sought advice from the ASCEC on how to disseminate findings to the care sector and get feedback. It was agreed that the best approach would be to combine the third and fourth meetings into a session at The Care Show, which is held annually at the National Exhibition Centre in Birmingham (9–10 October 2024). This event is a trade fair rather than a research meeting and is well attended by the care sector, providing an ideal opportunity to engage with a range of stakeholders (care providers, care home managers, care home and nursing staff of varying seniority, the Care Quality Commission, commissioners, researchers and relatives). We had a series of discussions about the study and particular findings from each WP , including the transferability of the projects’ insights to other UK nations, to the types of care homes that did not take part in the trial, and to other future pandemics or outbreaks of infectious disease outbreaks, as well as the study’s various limitations. Throughout the 4-hour event, attendees were highly engaged and adamant about their long-term commitment to future trial research and the sector’s desire to maintain momentum with varied lessons learnt from the COVID-19 pandemic as well as from taking part in the study (e.g. data management, research governance) and shaping future research agendas. Equality, diversity and inclusion Care home residents represent a substantial proportion of society, with nearly 280,000 people aged > 65 years recorded as living in a care home in England and Wales in the 2021 National Census. 5 Most care home residents are aged > 85 years, 5 at least two-thirds live with dementia, and over half die within 12 months of admission to a care home. 6 Groups of care homes were recruited through contact with the senior management teams of larger providers in England, although a small number of independent homes were also recruited. We worked through our existing networks and collaborated with NIHR ENRICH to identify possible sites. All care homes for older adults were eligible to take part, but we initially prioritised providers with > 10 care homes in an attempt to achieve our original recruitment target. This restriction was removed when it became clear it was challenging to recruit homes to take part in the study. All care home staff were eligible to participate in the testing intervention, including temporary staff with no restrictions (e.g. including catering, administrative and maintenance staff), but not professionals visiting the care home, such as GPs and health visitors. All residents of participating care homes were eligible for evaluation of trial outcomes. The 85 care homes recruited into this study were geographically spread across England, with 26 in the South, 6 in London, 32 in the Midlands and 20 in the North of the country. The care homes included a mixture of nursing (25.7%), residential (39.3%) and dementia (35.2%) beds, meaning that residents were included with varying levels of care need. The staff ethnicity of recruited homes was varied, reflecting diversity across the country, with 39% of staff reported to be of ethnic minority background where known. To ensure that our trial was representative of the care sector, including being representative of residents as well as the homes themselves, the Trial Steering Committee (TSC) included one member of the public with experience of care homes as well as two care providers. Overall, it remains challenging to recruit a ‘representative’ set of residents and care homes, partly because we lack reliable, detailed information on the diversity and health inequalities that exists across the sector. For WP 3B specifically, there were limitations regarding the timing of data collection outside the pandemic period and the inclusion criteria, which only permitted inclusion of residents with the mental capacity to consent in compliance with our ethical approval requirements. Given that 60–70% of care home residents have cognitive impairments or dementia, the provisions of our ethical compliance, as approved by the HRA Social Care REC , might conflict with the newly developed NIHR initiative on Enabling Research in Care Homes aiming to be inclusive of the population with cognitive impairment and dementia. Finally, our study team comprised a broad range of disciplines and individuals at varying career stages with varying sociodemographic characteristics including age, sex and ethnicity. The study team comprised individuals from a range of universities in London, the Midlands, Scotland, and the North West and South East of England. Impact and learning What difference has been made already? Timely intervention development is particularly useful in the context of infectious diseases and pandemics. We demonstrated that it is feasible to use robust, comprehensive methods to develop a complex intervention in the context of a pandemic. Our use and combination of multiple complementary current frameworks and guidance (e.g. the Index study, the BCW approach) to develop the intervention were unique to this study. We drew upon each framework proportionately and combined the strengths of each approach. A further strength was the use of programme theory and accompanying logic model to provide both a granular and high-level account of the intervention, how it should work, the context and specific expected outcomes. This led us to generate a complex intervention with clear, discernible interacting parts which have been theorised. We also benefitted from the ability to tap into a flexible workforce, including public health registrars, to support literature reviews and so on. Our inclusion of multiple stakeholders and PPIE in the development of the intervention allowed for varied perspectives from diverse experts to be a central part of the intervention development process. This close collaboration with policy-makers ensured that we designed a pragmatic intervention that could be implemented and scaled. Our findings speak to the importance of enabling local approaches to intervention delivery and data collection and management. Given heterogeneity of homes, one size may not fit all and the fact that many systems and processes were already developed and available (e.g. rooms to test in, systems to log to test results) and were bespoke to local set-up and team dynamics (familial or transactional), there were likely benefits to enabling local problem solving to some implementation problems. VIVALDI-Clinical Trial represents an innovative and pragmatic approach to producing evidence on the impact of COVID-19 and other respiratory outbreaks on the QoL and psychological well-being of residents in care homes. This key evidence gap was highlighted by the Chief Medical Officer in his technical report on the COVID-19 pandemic. By using existing measures of social-care-related QoL , functional capability and psychosocial well-being, we employed a standardised approach to assessing the impact of outbreaks and public health policies on residents’ QoL and psychological well-being. This is important because policy-making has previously focused on clinical and public health priorities, and QoL in care homes has not been prioritised. To our knowledge, this is the first application of ASCOT to assess the impact of outbreaks on care home residents’ QoL . This study highlighted the major challenges to delivering this type of research in care homes, and we were unable to gain support from the research sponsor to capture data on residents who lacked the capacity to consent by working with nominated or personal consultees. Concerns about informed consent remain a major barrier to delivering impactful, inclusive research in care homes. The research has illuminated the profound psychological and social effects of pandemic restrictions, with residents frequently experiencing isolation, reduced autonomy and limited opportunities for social interaction. By capturing these experiences, the study underscores the critical need for care strategies that balance infection control measures with social engagement and emotional support and has emphasised the importance of tailored care strategies that balance infection control with social engagement and emotional support. Together, these studies underscore the importance of developing adaptable care models that include assistive tools and training for healthcare professionals, enabling them to better communicate infection control guidelines to vulnerable populations. Findings from this collaboration also suggest the importance of community engagement and health behaviour models in ensuring health guidelines are both effective and inclusive. By translating these insights into policy and practice, we aim to create more resilient and resident-centred care frameworks that enhance the QoL for individuals in care homes, particularly in times of crisis. This is the first modelling analysis of testing strategies in care homes to include a health economic component and consider the cost-effectiveness of the interventions. This study has demonstrated the importance of combining regular staff testing with additional NPIs aimed at reducing transmission among residents to improve resident outcomes, especially at the beginning of an epidemic when vaccination and treatment are not yet available. We have shown how the implementation of resident isolation and regular staff testing can also be economically advantageous, whereas interventions focused solely on staff testing lead to increased costs. These findings provide a strong evidence base for policy-makers, who may be required to decide how to optimise the use of staff testing and other NPIs in the event of a future pandemic. What longer-term impact might there be? VIVALDI-Clinical Trial enabled us to progress the development of a pragmatic and scalable approach for interventional care home research to inform policy and practice. We found it feasible to use routinely collected data on testing, hospital admissions and mortality to evaluate primary and secondary outcomes, providing reliable data with reduced data collection workload relative to a traditional trial. This research model has major potential to enable the delivery of efficient observational and intervention studies in care homes and would be equally applicable to studies of non-communicable diseases (e.g. dementia) and prevention (e.g. falls), which would also benefit from an established research network and access to routine data on health outcomes. This study highlights some of the challenges associated with undertaking a trial in a dynamic policy and epidemiological context. When the trial was conceived, asymptomatic testing for staff was still recommended nationally in the UK. There were concerns that there would be a resurgence in SARS-CoV-2 incidence and morbidity in the coming winter season (2022–3) or that a new viral variant would once again change the dynamics of the epidemic (as had the Omicron variant in late 2021). By the time we started the trial, such concerns were receding, and only symptomatic staff were eligible for testing. The policy was further revised on 3 April 2023 to restrict symptomatic testing to only the minority of staff eligible for COVID-19 therapeutics, coinciding with a marked decline in asymptomatic testing in intervention homes. In retrospect, it may have been preferable to have undertaken this trial 6–12 months earlier when the incidence of COVID-19 within care homes was higher, 21 asymptomatic testing was still recommended as national policy, and the request to care providers would have been to opt out of rather than re-instate asymptomatic testing, which may have been more palatable to care home staff. Still, it would have raised ethical and practical challenges by contravening the public health guidance that was in place at the time of the trial and potentially leaving care homes exposed to claims of negligence, for example in the event of an outbreak. This highlights the need for sleeping protocols that enable operational issues such as insurance and indemnity to be resolved before rather than during a public health crisis, so that studies can be rapidly established to address critical gaps in research evidence. The longer-term impact of this work may be significant in transforming care home policies and practices, particularly in enhancing the resilience of these settings during public health emergencies. By documenting the adverse effects of social isolation, limited autonomy and restricted social interaction on residents, the study offers evidence for embedding more flexible, resident-centred care approaches that protect mental health and emotional well-being alongside physical safety. This research could lead to sustained changes in care home design and staffing, promoting environments that better support residents’ social needs through accessible outdoor areas and dedicated activity spaces. Additionally, it may influence workforce planning by reinforcing the value of consistent staffing and specialised roles for social and emotional support, ensuring continuity of care. Policy-makers might also be encouraged to adopt clearer and more tailored communication protocols for future health crises, particularly for older adults with cognitive and sensory needs. Overall, the study’s findings may contribute to a shift in the sector from a primarily clinical focus to a more holistic, QoL-oriented approach in care homes. Lessons learnt for future research Much of our ability to be flexible and solutions-focused came from effective relationships between academia, policy, and the care sector, and our track-record and commitment to using ‘data for action’. These are critical enablers that gave us credibility with the sector and need to be maintained if we want to increase research in social care. There is a huge opportunity for industry partnership, for example, to support vaccine trials and the evaluation of diagnostics and digital technologies, including artificial intelligence. The rapid setup of the trial was dependent on the pre-existing data pipelines and testing infrastructure, and it would not have been possible to deliver the trial at such a pace without following directly from the original VIVALDI study. 16 Without further funding to sustain these partnerships and investment to harness the potential of electronic care records as a research enabler given the target for 80% of care homes to be digitised by March 2024, 23 the opportunity to build on this infrastructure and momentum, transform how we deliver research in social care and to be genuinely prepared for the next pandemic will be lost. Our use of a variety of conceptual tools for intervention development, alongside involvement of the care sector and people that would be affected by the intervention, was a significant strength of this work and should be reproduced in future pandemics. Expanded and formal involvement in the intervention material development would also have improved the work, for example supporting social media streams. Having the network and connections in place before they are needed is crucial to being able to conduct this type of research quickly. In the future, it would be good to work both online and offline with care homes to enhance relationship building and recruitment to interviews. Given the uncertainties about future pandemics and the transmission routes of infectious agents, site visits may not always be possible. However, dedicated time to relationship building within homes is likely to yield higher engagement with projects. Ideally, these relationships need to be built at multiple organisational levels (senior leadership teams, care home managers, front-line staff) because each of these groups encounters different barriers to research participation and delivery. Developing this kind of penetration within care provider organisations will be challenging, but it is essential if we want to enable the delivery of complex studies in social care. To make the comparison with the NHS, research-active hospitals (such as those hosting Biomedical Research Centres) aim to embed research throughout their organisations, with active support and engagement from board level through to front-line staff, and research training/awareness embedded for medical staff and nurses as part of their curriculum. This is in addition to dedicated funding for research delivery in secondary care via the NIHR Clinical Research Network [now Research Delivery Network (RDN)]. Our work offers a robust foundation for future research into the impacts of respiratory outbreaks on care home residents, especially by incorporating a framework that combines assessments of both quantitative and qualitative methods of collecting psychological well-being and QoL data. Often, the key barrier is getting such studies set up; it would be ideal to collect data over a longer time period in a set of homes to observe SCRQoL changes over time and in response to acute events (e.g. outbreaks, hospital admissions) to enable an understanding of the enduring effects of infection control measures on well-being. It is critical to include residents with cognitive impairments in these studies to enhance the generalisability of these findings and ensure that our research is inclusive. In the long term, we need mechanisms to regularly capture assessments of QoL in residents alongside health outcomes, to enable a holistic assessment of the impact of interventions on residents’ physical and mental health and well-being. Our findings can inform policies and practices in care homes, advocating for a more flexible, resident-centred approach during public health crises. VIVALDI-CT provides key insights for future research in care homes, emphasising the need for a holistic approach to assessing residents’ QoL that encompasses physical, social and emotional dimensions, especially during crises. It demonstrates the importance of resident-centred care practices tailored to individual needs and preferences, which enable greater autonomy and meaningful social interactions. The study highlights the positive impact of consistent staff-resident relationships, suggesting future research should focus on how specific staffing models and rapport-building affect QoL in care home settings. Effective, direct communication also emerged as a priority, with residents valuing clear updates from staff over other sources, indicating a need for tailored messaging strategies for those with cognitive or sensory impairments. The role of both indoor and outdoor environments in supporting well-being is another valuable lesson, suggesting that future research should investigate how the design and accessibility of care home spaces contribute to resident satisfaction, particularly in providing opportunities for outdoor and communal activities. The study underlines the importance of adaptable care models that balance infection control with resident well-being, proposing that future studies explore how flexible, resident-centred approaches can be swiftly implemented to mitigate the effects of isolation and disruption during health emergencies. These findings collectively point towards a more nuanced and resilient framework for research and practice, focused on supporting mental health, autonomy and QoL even amidst challenging circumstances. From our interview with care home managers, we noted variations in policies and practice around where staff were supposed to test. To inform potential use of testing in future pandemics, it would be useful to assess the effects of requirements to test at work or at home on care home workers’ experiences. From focus groups with health protection staff, we found some variability in HPT in responding to high-risk outbreaks, possibly related to local practices, participants’ interpretation of scenarios presented or job roles, but also in the range of external partners required for a full response. Outbreak response involves a combination of local authority, or ICB Infection Prevention and Control teams, local authority public health teams, other local authority teams involved in quality assurance, GPs, pharmacists and care home staff. More research is warranted on how significant outbreaks are managed across a region or local authority area, and whether there is any scope to ascertain best practices and rationalise the numbers of teams and agencies involved. To quantify the wider costs of complex outbreaks would require a more extensive study, deploying observational or survey methods. Further, there is a need for progress on the recommendations of the Independent Review on Research Bureaucracy 24 in order to ensure efficient and effective research, particularly in relation to application processes, assurance and in-grant management. Real-world impact For the first time, we demonstrated that it is feasible to make use of routine national healthcare data to evaluate the impact of a trial intervention within the setting of residential care homes in the UK. Care providers were willing and able to provide the research team with weekly aggregate data regarding their homes for use in the analyses, but the uncertainty of care home staff regarding data governance approvals and technical processes meant that it was not possible to collect individual-level data on hospital admissions among care home residents via secure upload to a national data platform. There is a strong argument for delivering cluster rather than individually randomised trials in care homes, provided this makes sense in the context of the intervention. Many interventions are well-suited to being delivered at care home level because they aim to change behaviours or have herd effects (e.g. vaccine trials). In addition, care home-level interventions can often be evaluated using care home-level (aggregate) data, which may reduce the requirement for individual-level consent for data collection. This overcomes a key barrier to research delivery because many residents lack the capacity to consent. It also reduces the risk that those who lack capacity are automatically excluded from research studies. However, cluster randomised trials typically require a greater number of both participants and study sites than individually randomised trials, so a scalable and reliable approach for data collection is a necessity for any future trials of home-level policy interventions in this setting. Our QoL finding aligns with the Lancet Commission’s call for a transformation in long-term care, advocating for person-centred, rights-based approaches to improve the QoL in communal living settings. The real-world impact of this work lies in its potential to reshape care home practices and policies to better support the well-being of residents, particularly during crises. By providing evidence on how social isolation, reduced autonomy and limited interaction affect residents’ mental and emotional health, the study highlights the need for a more resident-centred approach in care homes that prioritises not only physical safety but also social and emotional needs. The revised WP 4a capitalised on the unique opportunity in this study to gain insights into the costs associated with paying staff to isolate when unwell – a strategy widely used in the pandemic but not traditionally used in the social care sector to limit the spread of infection. The work generated valuable evidence on testing, sick pay and shift management in English care homes to inform future public health policy on the prevention/management of infection in care homes. Work evaluating the costs of outbreak investigations also addressed an important gap in the literature, providing planners with estimates of expenditure on UKHSA HPTs likely to be required in typical outbreak situations. Related and future work Following on from the success of the original VIVALDI study, as well as building on the capacity and learning arising from VIVALDI-CT , the VIVALDI Social Care Study is a collaborative research project which is co-led by the Outstanding Society, Care England and UCL . The project is funded by UKHSA and NIHR via Professor Shallcross’s NIHR Research Professorship. We are working together with the care sector to undertake a 12- to 18-month pilot study to mitigate the impact of all priority infections and outbreaks in care homes, by using routinely collected data to generate accurate information on the burden of common infections among care home residents. Outputs, presented via dashboards to policy-makers and providers, will inform policy and practice and are being developed in partnership with UKHSA. We will also create an anonymised research database that can serve as a valuable resource for observational studies and, hopefully, interventional research in the future, subject to further funding. A key finding from VIVALDI-CT is that effective delivery of clinical trials in care homes requires embedded staff who are at least ‘research-aware’ if not research-trained. While organisations such as NIHR ENRICH have established training programmes to support research in care homes, the lack of trained staff within the care home is a major barrier to research delivery, particularly when trying to evaluate complex interventions. Through the VIVALDI Social care project, we have made tentative steps towards research training, working in partnership with the Outstanding Society. In the last few months, we have visited care homes to provide in-person and online training to care home staff about the project, use of data and to ensure that staff are sufficiently knowledgeable to be able to explain the study to residents and people visiting the care home. We have also coproduced a short explainer video. 25 However, this training is very basic and a sustained, more sophisticated programme of research training and capacity building for care home staff will be required if we truly want to deliver trials in care homes, and work towards a culture of care sector-led research. To this end, we are also working with the NIHR RDN to scope out options for providing research training and capacity building to care home staff so they can support the sustained delivery of research into care homes. We are developing a paper for the RDN Board which sets out different ways in which research training and capacity building could be delivered (e.g. outreach training into care homes vs. developing research skills in an embedded workforce). If successful, the intention is that the programme would become part of NIHR RDN infrastructure and support delivery of all care home trials that are adopted into the NIHR portfolio. Over the next 2–5 years, our goal is that capacity building through the VIVALDI studies (VIVALDI, VIVALDI-CT , Vivaldi Social Care) will support the delivery of the following activities: A world-leading care home research programme (e.g. public health and clinical trials, biology of ageing, evaluation of diagnostics, AI and digital technologies). Improved surveillance of infection and antimicrobial resistance (AMR) in residents (incorporating sentinel sampling and genomics over time). Quality improvement (by identifying variation in care quality and outcomes in partnership with care providers, NHS England and ICBs). Career development and new career pathways for social care staff, by providing training in research and opportunities to work with researchers and universities. Dissemination Significant emphasis was placed on dissemination of the work of VIVALDI-CT , details of which have been described in full in Patient and public involvement and engagement . Implications for decision-makers Implications for practice or local service delivery One of the key challenges identified in VIVALDI-CT was sustaining testing in staff when levels of SARS-CoV-2 fell, highlighting the need for interventions such as this to be constantly titrated to the level of threat. Ideal timing for a trial in a pandemic setting is difficult, particularly for cluster-level NPIs, even with rapid trial start-up. The moment of equipoise for this intervention passed quickly, but it was not possible to predict this confidently in advance. It is therefore crucial to be able to identify when to switch interventions on and off, requiring high-quality, real-time data and surveillance on disease trends and their impact. We also need ‘research-ready infrastructure’ and potential sleeping protocols in this setting so studies can be deployed quickly in response to public health emergencies. This study has demonstrated the importance of combining regular staff testing with additional NPIs aimed at reducing transmission among residents to improve resident outcomes, especially at the beginning of an epidemic when vaccination and treatment are not yet available. We have also shown that implementing resident isolation and regular staff testing can be economically advantageous, whereas interventions focused solely on staff testing led to increased costs. These findings illustrate the need to target interventions to specific populations and underscore their relevance for future pandemics, where establishing the optimal frequency of staff testing and other NPIs will be necessary. Close collaboration is required between academia, care providers, resident and relative groups, and public health organisations to provide this type of evidence, particularly on policy timescales. Implications for decision-makers in the context of the evidence In epidemics and pandemics, time criticality is central, and we are often working in an evidence vacuum. Any insights can be more useful than none, although there were examples throughout of a lack of evidence about many decisions that had been made, and the shelf life of some of the evidence that was published. Key to the success of VIVALDI-CT was our ability to work closely with policy-makers from UKHSA , to problem-solve when trying to set the study up quickly, but also to ensure that our research was addressing and informing pertinent research questions. It is essential that academics and policy-makers can move fluidly between sectors to communicate policy needs and research findings. Ideally, we need opportunities for researchers and policy-makers to come together outside of public health emergencies to share ideas, learn to communicate effectively and gain an understanding of each other’s priorities and constraints. Post pandemic it is once again impossible to generate evidence on the timescales that are necessary for public health policy-making in relation to care homes. The VIVALDI infrastructure and testing programme were key research enablers (set up in 3 months) but no longer exist beyond the pandemic. Over time, the VIVALDI Social Care project outlined above aims to address this evidence gap, but this is contingent on sustained funding and the ability to work across organisations ( UKHSA , NHS England, DHSC and so on). For future pandemics/outbreaks, it is also crucial to consider the broader impacts of infectious diseases in care homes, which affect residents and family members’ mental health and well-being, as well as the economic impact on care providers of closing care homes and restricting new admissions. This demands a much more holistic approach to assessing impact, which we have begun to explore within VIVALDI-CT , and plan to explore further in Professor Shallcross’s NIHR Research Professorship. The Developing Resources and Minimum Data Set for Care Homes’ Adoption (DACHA) Study 26 aims to establish a minimum data set to support research, service development and uptake of innovation in care homes and includes measures of QoL collected using tools such as ASCOT . However, there is a significant workload to capture this information from every resident, which makes it a major challenge to monitor QoL in all residents. If this issue can be overcome, the idea is that these measures will be available in electronic care plans and recorded regularly (e.g. after key life events or every 6 months). In this scenario, it would in theory be possible to include this information as an outcome measure in the VIVALDI Social Care project. Clear actions needed arising from evidence There is a clear need to resource the development of plans to integrate the social care sector with research and vice versa. It is important to recognise care providers as a key partner in care home research and improve our understanding of what they need in order to participate in and shape future studies. A barrier to the delivery of care home trials is the lack of ‘on the ground’ care home staff who are trained to support research delivery. This can only be addressed by NIHR investment in a programme of research training and capacity building for embedded care home staff. This should be in addition to current initiatives such as those led by ENRICH, which provide research training and support to care homes, but arguably have limited opportunity to foster a culture of social care research and act as a ‘trusted source’ for residents, care home staff and relatives because they are external to care homes rather than embedded. The greater impact of research delivered in partnership, such as this, which involved a collaboration between UKHSA , UCL and the social care sector, should also be acknowledged, but this also presents challenges, particularly when delivering research outside of ‘normal’ grant funding mechanisms. Organisations such as UKHSA and DHSC can commission research and move rapidly (e.g. UKHSA funded testing and sick pay in this trial), but they usually operate on short-term funding (e.g. 1 year) making it difficult to plan. On the other hand, the standard grant funding model can take a long time to set up, creating unhelpful delays in a public health crisis. Agile models that enable academic-led partnerships with UKHSA and other organisations are fundamental to delivering impactful research with and for the social care sector. A good example of how this can work are the NIHR Health Protection Research Units (HPRUs), which are a collaboration between universities and UKHSA . One approach to address this gap in longer-term collaborations in social care research would be to establish a HPRU for vulnerable populations and inclusion health. This would also support efforts to create a wider pool of researchers working in social care and increase partnership work between researchers and care provider organisations. Pandemic preparedness in the care sector is another crucial action to be taken, and this needs to be adequately resourced. Harnessing existing mechanisms such as the Care Quality Commission and local public health teams to audit and incentivise pandemic/epidemic preparedness plans, recognising that adult social care is a key setting at the frontline, could be one mechanism to improve preparedness. How rapidly is the ‘knowledge base’ in this area developing? The COVID-19 pandemic highlighted the need for better evidence and methods to identify and mitigate the risks of infections to care home residents and staff, and, as such, the knowledge base in this area is developing rapidly. The VIVALDI Social Care Project, 25 building on the successes of the earlier VIVALDI projects, aims to provide detailed data on the burden and outcomes of infection in a subset of approximately 1500 care homes (equating to around 10% of all homes in England). This will transform our ability to monitor infections in care homes, and information gained from this work will inform public health policy and quality improvement activities. Data began flowing in January 2025. Similarly, projects such as the NIHR-funded DACHA Study 26 are exploring the potential use of routinely collected data to inform a minimum care home data set for use in surveillance and research. Research recommendations Three priority areas for future research have been highlighted by this work which have been cocreated with the care sector following the workshop held at the Care Show 2024. 1. Develop, pilot and evaluate different models of research training and capacity building for care home staff to enable research delivery and work towards a culture of social care-led research. There is an urgent need to develop, pilot, evaluate and implement a programme of research training and capacity building for care home staff to enable efficient, sustainable delivery of care home trials. This will require sustained investment in research capacity within the care sector. This clinical trial has highlighted the potential benefits of using routinely collected data to assess outcomes in care home studies, recognising that there is no embedded, funded workforce to support study delivery in this setting, unlike the NHS. Greater opportunities are also required for electronic health record-enabled observational and interventional studies in care homes to enable research at pace and scale. Further research is also needed to understand the differential potential to enhance research training and capacity issues across the sector as a whole – for example how research readiness is patterned by geography, regional poverty and the sociodemographic status diversity of care home staff. 2. Establish a care home network underpinned by routinely collected health/social care data to enable research delivery/digital trials and support rapid evidence generation as part of pandemic preparedness. Rapid roll-out of digital care records is an opportunity to create new research models that do not rely on prospective data collection, reducing the workload for care home staff. Research networks and pipelines need to be in place and maintained to be ready for future pandemics, specifically in this sector, alongside sleeping protocols which address critical operational barriers to research delivery (e.g. sick pay, agency staff backfill and so on). Limited surveillance and research infrastructure were in place prior to Wave 1 of the COVID-19 pandemic, meaning that there was a lack of available data for researchers or policy-makers at the point at which SARS-CoV-2 had the greatest impact on care homes. These networks and data pipelines could also form the basis for sustained research within care homes on endemic infectious diseases and other health outcomes for residents, and potentially a platform for scalable cluster randomised trials of healthcare interventions. We have demonstrated that the use of opt-out consent and analysis of routine health data are feasible for the delivery of interventional research in this setting. However, the data pipeline used in VIVALDI-CT was dependent on SARS-CoV-2 testing of care home residents to identify the relevant health records of residents of participating homes. We are currently working on the next iteration of this data pipeline in which residents of participating homes can be more reliably identified through daily data outputs of NHS numbers from the electronic records systems of care providers into secure NHS England environments, where they will be pseudonymised before linkage to routine health and mortality data sets. Once the basic data pipeline of patient identifiers has been established for participating homes, it may then be possible to collect some further data directly from the record systems of care providers: for example, QoL measures as explored in the DACHA Study. 26 At present, studies that evaluate QoL in care home residents are extremely resource intensive, but sustained investment in research in this sector alongside ongoing engagement with care providers, residents and relatives could make large-scale studies of resident QoL feasible. Research into non-residential adult social care has also been limited in the UK by a lack of research capacity or infrastructure. The data pipeline under development could also potentially be replicated for recipients of non-residential care for older adults, another important subset of the older population. 3. Holistic, mixed-methods approaches to developing the evidence base in care homes regarding IPC , AMR and healthcare utilisation, drawing on experiences from VIVALDI-CT . Many areas of care sector policy, particularly around infection control, have poor evidence bases and would benefit from more interventional studies. It is crucial to develop novel, holistic approaches to assess the impact of infections, outbreaks and the measures that are used to control them on residents’ physical and mental health and well-being to inform the future use of public health strategies to prevent the spread of infection and pandemics. This needs to include robust approaches for quantifying QoL of residents and staff to improve the quality of care and workplace conditions, as well as to contribute to the estimation of quality-adjusted life-years. New approaches are needed to prevent, control and reduce the transmission of infection and AMR in care homes, considering the increased risks of imported infections, for example, tuberculosis with changing patterns of migration and demographics of care home staff. This should also be extended to include strategies to mitigate the impact of climate change on the physical and mental health and well-being of residents. Our planned research network and data pipeline will also allow monitoring and analysis of the healthcare usage and pathways of care home residents, for example evaluating the frequency and characteristics of hospital admissions at end of life. This is an important topic both from the perspective of optimising QoL for care home residents and their relatives and for reducing the burden on the healthcare system created by hospital admissions that could have been avoided. Conclusions We set up and delivered a clinical trial at pace in a dynamic policy and epidemiological environment. We used robust, mixed methods to rapidly develop our intervention ‘Test to Care’, providing a model for rapid intervention development in future public health emergencies. However, we were unable to deliver the trial as planned because the management and staff motivation for maintaining asymptomatic staff testing was unsustainable beyond March 2023, as the country moved into the next phase of living with SARS-CoV-2 . Although our trial stopped early, our transdisciplinary approach enabled us to generate valuable evidence to inform the use of testing in future pandemics. We also gained insights about what needs to be in place to enable efficient delivery of future trials. These include the importance of ongoing engagement between academia, the care sector and public health bodies to improve research capacity in this sector and the creation of high-quality evidence to inform policy. This work highlights the differences in approach that are required when conducting research within the social care sector in light of the heterogeneity that exists across care homes. Embedded, dedicated research staff and new ways of working are essential if research in the care sector is to be successful, particularly at pace and scale. We are now building on this learning, and insights from care home research in the COVID-19 pandemic to create the Vivaldi Social Care project, which aims to lay the foundation for efficient delivery of future clinical trials in care homes. If this model can be sustained and scaled, it represents a major opportunity to deliver research which improves care and QoL for care home residents. Additional information CRediT contribution statement Natalie Adams ( https://orcid.org/0000-0002-6131-480X ) : Conceptualisation, Investigation, Methodology, Writing – original draft, Writing – reviewing and editing. Oliver Stirrup ( https://orcid.org/0000-0002-8705-3281 ) : Conceptualisation, Data curation, Formal analysis, Investigation, Validation, Visualisation, Writing – original draft, Writing – reviewing and editing. James Blackstone ( https://orcid.org/0000-0003-4335-5269 ) : Conceptualisation, Investigation, Methodology, Writing – original draft, Writing – reviewing and editing. Maria Krutikov ( https://orcid.org/0000-0002-3982-642X ) : Conceptualisation, Investigation, Methodology, Writing – original draft, Writing – reviewing and editing. Jackie Cassell ( https://orcid.org/0000-0003-0777-0385 ) : Conceptualisation, Data curation, Formal analysis, Investigation, Validation, Visualisation, Writing – original draft, Writing – reviewing and editing. Dorina Cadar ( https://orcid.org/0000-0003-1398-5841 ) : Conceptualisation, Data curation, Formal analysis, Investigation, Validation, Visualisation, Writing – original draft, Writing – reviewing and editing. Catherine Henderson ( https://orcid.org/0000-0003-4340-4702 ) : Conceptualisation, Data curation, Formal analysis, Investigation, Validation, Visualisation, Writing – original draft, Writing – reviewing and editing. Martin Knapp ( https://orcid.org/0000-0003-1427-0215 ) : Conceptualisation, Data curation, Formal analysis, Investigation, Validation, Visualisation, Writing – original draft, Writing – reviewing and editing. Lara Goscé ( https://orcid.org/0000-0003-2392-6271 ) : Conceptualisation, Data curation, Formal analysis, Investigation, Validation, Visualisation, Writing – original draft, Writing – reviewing and editing. Lily O’Brien ( https://orcid.org/0009-0009-8676-5023 ) : Conceptualisation, Data curation, Formal analysis, Investigation, Validation, Visualisation, Writing – original draft, Writing – reviewing and editing. Ruth Leiser ( https://orcid.org/0000-0002-6493-2793 ) : Formal analysis, Investigation, Writing – original draft, Writing – reviewing and editing. Martyn Regan ( https://orcid.org/0000-0003-2962-9913 ) : Supervision, Validation. Iona Cullen-Stephenson ( https://orcid.org/0009-0001-3503-6375 ) : Project administration, Resources. Robert Fenner ( https://orcid.org/0000-0002-5819-9601 ) : Project administration, Resources, Data curation. Arpana Verma ( https://orcid.org/0000-0002-7950-2649 ) : Supervision, Validation. Adam L Gordon ( https://orcid.org/0000-0003-1676-9853 ) : Supervision, Validation. Susan Hopkins ( https://orcid.org/0000-0001-5179-5702 ) : Supervision, Validation. Andrew Copas ( https://orcid.org/0000-0001-8968-5963 ) : Conceptualisation, Data curation, Formal analysis, Investigation, Validation, Visualisation, Writing – original draft, Writing – reviewing and editing. Nick Freemantle ( https://orcid.org/0000-0001-5807-5740 ) : Supervision, Validation. Paul Flowers ( https://orcid.org/0000-0001-6239-5616 ) : Conceptualisation, Funding acquisition, Investigation, Methodology, Supervision, Writing – original draft, Writing – reviewing and editing. Laura Shallcross ( https://orcid.org/0000-0003-1713-2555 ) : Conceptualisation, Funding acquisition, Investigation, Methodology, Supervision, Writing – original draft, Writing – reviewing and editing. Patient data statement This work uses data provided by patients and collected by the NHS as part of their care and support. Using patient data is vital to improve health and care for everyone. There is huge potential to make better use of information from people’s patient records, to understand more about disease, develop new treatments, monitor safety and plan NHS and care services. Patient data should be kept safe and secure, to protect everyone’s privacy, and it is important that there are safeguards to make sure that they are stored and used responsibly. Everyone should be able to find out about how patient data are used. #datasaveslives You can find out more about the background to this citation here: https://understandingpatientdata.org.uk/data-citation . Data-sharing statement Individual-level source data from the trial cannot be openly shared, as consent was not obtained from study participants. However, weekly aggregate data on primary and secondary outcomes at the level of each care home are provided as a supporting information file accompanying the main trial impact paper. Additional information can be obtained from the corresponding author. Ethics statement The study was approved by the London – Bromley Research Ethics Committee (reference number 22/LO/0846) and the Health Research Authority (HRA) (22/CAG/0165) on 8 December 2022. The VIVALDI ASCOT and Ethnography Study (WP3b) was sponsored by University of Sussex and received ethical approval from the HRA Social Care REC ( REC number 24/IEC08/0001) for both elements of this study (interviews and ethnographic observations). Prior to data collection, informed consent was sought from care home managers and residents. We only interviewed residents with mental capacity to consent. Every resident received a £20 voucher as a token of appreciation for their contribution to the study. Information governance statement All organisations involved in this study are committed to handling all personal information in line with the UK Data Protection Act (2018) and the UK General Data Protection Regulation (UK GDPR) 2016/679. Under the Data Protection legislation, the Department of Health and Social Care (DHSC) and University College London are the joint data controllers for the study. UKHSA is an executive agency of DHSC and acts on behalf of DHSC in carrying out its obligation as joint data controller in relation to VIVALDI-CT . The study obtained Section 251 approval from the HRA CAG (22/CAG/0165) to permit use of data on clinical outcomes (tests, hospital admissions, deaths) in residents and data on uptake of testing in staff without consent. However, staff and residents had the option to opt out of taking part. The legal basis for use of data in the study was: UK GDPR Article 6(1)(e) ‘processing is necessary for the performance of a task carried out in the public interest’ UK GDPR Article 9(2)(h) ‘processing is necessary for the provision of health or social care or treatment or the management of health or social care systems and services’ UK GDPR Article 9(2)(j) ‘processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes’ You can find out more about how we handle personal data, including how to exercise your individual rights and the contact details for our Data Protection Officer here ( www.ucl.ac.uk/health-informatics/research/vivaldi/vivaldi-study-2020-2023/vivaldi-privacy-notice ). The following information materials were approved by CAG to explain how we used data in this study to residents and relatives, as well as staff: www.ucl.ac.uk/health-informatics/sites/health_informatics/files/20221129_vivaldi-ct_data_info_poster_residents_v5.pdf www.ucl.ac.uk/health-informatics/sites/health_informatics/files/20221129_vivaldi-ct_data_info_poster_staff_v5.pdf Disclosure of interests Full disclosure of interests: Completed ICMJE forms for all authors, including all related interests, are available in the toolkit on the NIHR Journals Library report publication page at https://doi.org/10.3310/GJLS1610 . Primary conflicts of interest: James Blackstone, Oliver Stirrup, Nick Freemantle, Andrew Copas, Adam Gordon, Catherine Henderson and Laura Shallcross received payments from NIHR trial grants in support of their professional work on academic projects. Professor Laura Shallcross is funded by the NIHR under a Research Professorship (grant number 302435 to Professor Laura Shallcross) and by the NIHR University College London Hospitals Biomedical Research Centre. Laura Shallcross is Deputy Chair of the Advisory Committee on Antimicrobial Resistance, Prescribing and Health care Acquired Infections. Laura Shallcross also reports grants from the Department of Health and Social Care during the conduct of the study. All other authors declare no competing interests. Nick Freemantle’s work in the UCL CCTU was supported in part by NIHR from 1 September 2015 to 31 August 2025. Department of Health and Social Care disclaimer This publication presents independent research commissioned by the National Institute for Health and Care Research (NIHR). The views and opinions expressed by the interviewees in this publication are those of the interviewees and do not necessarily reflect those of the authors, those of the NHS, the NIHR, MRC, NIHR Coordinating Centre, the Health and Social Care Delivery programme or the Department of Health and Social Care. This synopsis was published based on current knowledge at the time and date of publication. NIHR is committed to being inclusive and will continually monitor best practice and guidance in relation to terminology and language to ensure that we remain relevant to our stakeholders. Publications Adams N, Stirrup O, Blackstone J, Krutikov M, Cassell JA, Cadar D, et al . Shaping care home COVID-19 testing policy: a protocol for a pragmatic cluster randomised controlled trial of asymptomatic testing compared with standard care in care home staff (VIVALDI-CT). BMJ Open 2023; 13 :e076210. https://doi.org/10.1136/bmjopen-2023-076210 Flowers P, Leiser R, Adams N, Kruitikov M, Nacer H, Shallcross L. Improving COVID-19 Testing in Care Home Staff: A Behaviour Change Wheel Analysis of Published Literature . 37th Annual Conference of the European Health Psychology Society, Bremen, Germany, 4–8 September 2023. Bertini L, Schmidt-Renfree N, Blackstone J, Stirrup O, Adams N, Cullen-Stephenson I, et al . VIVALDI ASCOT and Ethnography Study: protocol for a mixed-methods longitudinal study to evaluate the impact of COVID-19 and other respiratory infection outbreaks on care home residents’ quality of life and psychosocial well-being. BMJ Open 2024; 14 :e088685. https://doi.org/10.1136/bmjopen-2024-088685 Flowers P, Leiser R, Krutikov M, Adams N, Nacer H, McLeod J, et al. Improving COVID-19 Testing in Care Home Staff: A Behaviour Change Wheel Analysis of Published Literature . International Long-Term Care Policy Network Conference, Bilbao, 14 September 2024. O'Brien L, Stirrup O, Blackstone J, Cullen-Stephenson I, Fenner R, Adams N, et al. Modelling the Epidemiological Impact of Testing on Transmission of COVID-19 Infection under Different Transmission Scenarios . International Long-Term Care Policy Network Conference, Bilbao, 14 September 2024. Shallcross L, Flowers P, Fry Z, Slator M, Henderson C, Gosce L, et al. Shaping Care Home COVID-19 Testing Policy (VIVALDI-CT). Working with the Care Sector to Maximise the Impact and Usefulness of Our Research Findings . The Care Show, Birmingham, 10 October 2024. Stirrup O, Blackstone J, Cullen-Stephenson I, Fenner R, Adams N, Krutikov M, et al. Shaping Care Home COVID-19 Testing Policy: A Pragmatic Cluster Randomised Controlled Trial of Asymptomatic Testing Compared to Standard Care in Care Home Staff . International Long-Term Care Policy Network Conference, Bilbao, 14 September 2024. Stirrup O, Blackstone J, Cullen-Stephenson I, Fenner R, Adams N, Leiser R, et al . VIVALDI-CT shaping care home COVID-19 testing policy: a pragmatic cluster randomised controlled trial of asymptomatic testing compared to standard care in care home staff. PLOS ONE 2025; 20 :e0324908. https://doi.org/10.1371/journal.pone.0324908 Trial registration The VIVALDI-CT was registered with the International Standard Randomised Controlled Trial Number website (ISRCTN 13296529) on 5 December 2022. ClinicalTrials.gov registration: NCT05639205 . Funding This synopsis presents independent research funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme as award number NIHR154310. Box This synopsis provided an overview of the research award Shaping care home COVID- testing policy: A pragmatic cluster randomised controlled trial of asymptomatic testing compared to standard care in care home staff (VIVALDI-CT) . For other articles from (more...) About this synopsis The contractual start date for this research was in November 2022. This article began editorial review in December 2024 and was accepted for publication in July 2025. The authors have been wholly responsible for all data collection, analysis and interpretation, and for writing up their work. The Health and Social Care Delivery Research editors and publisher have tried to ensure the accuracy of the authors’ article and would like to thank the reviewers for their constructive comments on the draft document. However, they do not accept liability for damages or losses arising from material published in this article. Copyright Copyright © 2026 Adams et al . This work was produced by Adams et al . under the terms of a commissioning contract issued by the Secretary of State for Health and Social Care. This is an Open Access publication distributed under the terms of the Creative Commons Attribution CC BY 4.0 licence, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. See: https://creativecommons.org/licenses/by/4.0/ . For attribution the title, original author(s), the publication source – NIHR Journals Library, and the DOI of the publication must be cited. Copyright and credit statement Every effort has been made to obtain the necessary permissions for reproduction, to credit original sources appropriately and to respect copyright requirements. However, despite our diligence, we acknowledge the possibility of unintentional omissions or errors and we welcome notifications of any concerns regarding copyright or permissions. List of abbreviations AMR antimicrobial resistance ASCEC Adult Social Care Engagement Collective ASCOT Adult Social Care Outcomes Toolkit BCW Behaviour Change Wheel CAG Confidentiality Advisory Group CCTU Comprehensive Clinical Trials Unit COVID coronavirus disease COVID-19 coronavirus disease discovered in 2019 CQC ID Care Quality Commission Identification DACHA Developing Resources and Minimum Data Set for Care Homes’ Adoption DHSC Department for Health and Social Care GP general practitioner HPRU Health Protection Research Unit HPT Health Protection Team HRA Health Research Authority ICB Integrated Care Board IMT Incident Management Team IPC Infection Prevention and Control LFD lateral flow device NIHR National Institute for Health and Care Research NPI non-pharmaceutical intervention PPE personal protective equipment PPI patient and public involvement PPIE patient and public involvement and engagement QoL quality of life RCT randomised controlled trial RDN Research Delivery Network REC Research Ethics Committee SARS-CoV-2 severe acute respiratory syndrome coronavirus 2 SCRQoL social care-related quality of life TSC Trial Steering Committee UCL University College London UKHSA UK Health Security Agency VIVALDI-CT VIVALDI Clinical Trial WP work package References 1. 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DACHA: Developing Research Resources and Minimum Data Set for Care Homes’ Adoption and Use. 2024. URL: https://dachastudy ​.com/ (accessed 31 October 2024). [ PubMed : 41665272 ] Appendix 1. Literature search Every effort has been made to find and credit the original source/author(s) of the search strategies and to obtain permission from their copyright holders to reproduce this material; any further information related to the rightsholder if notified will be incorporated in any revisions or updates to this report/article . Rapid reviews of policy and practice on respiratory infection care homes outbreaks: COVID-19 testing, sick-pay and public health outbreak management. Three bibliographic databases were searched for the first and second rapid reviews (MEDLINE via Ovid, CINAHL via EBSCO host , and Web of Science via Clarivate), and two were searched for the third rapid review (MEDLINE via Ovid, CINAHL via EBSCO host ), on 24 November 2023. Google searches were undertaken between December 2023 and January 2024. The full electronic search strategy is included below. View in own window # Search term (Search for MEDLINE via Ovid) 1 SARS-CoV-2/ or COVID-19/ 2 (corona* adj1 (virus* or viral*)).ti,ab,kw,kf. 3 (covid* or coronavirus* or 2019nCoV* or 19nCoV* or “2019 novel*” or Ncov* or “n-cov” or “ SARS-CoV-2 *” or “SARSCoV-2*” or SARSCoV2* or “SARS-CoV2*” or “severe acute respiratory syndrome*” or pandemic* or longcovid* or postcovid* or postcoronavirus* or postsars*).ti,ab,kw,kf. 4 or/1-3 5 ((intermediate or “long term” or longterm or institution* or day or extended or respite) adj3 care).ti,ab,kw,kf 6 Residential Facilities/ or exp Nursing Homes/ or Respite Care/ or Long-Term Care/ or Housing for the Elderly/ or Geriatric Nursing/ or Adult Day Care Centres/ or Assisted Living Facilities/ or Homes for the Aged/ 7 ((“old age” or “old* people*” or “old* person*” or “old* adult*” or aged or geriatric* or retirement or nursing or care or resident* or long-term or longterm or senior* or aging or ageing or elder*) adj3 (home? or institution* or facility or facilities or hous* or center* or centre* or unit or units or establishment*)).ti,ab,kw,kf. 8 or/5-7 9 COVID-19 Testing/ 10 ((asymptomatic or covid* or coronavirus* or “ SARS-CoV-2 ” or “SARSCoV-2*” or SARSCoV2* or “SARS-Cov2*” or PCR or rapid or “lateral flow”) adj3 (test* or swab* or kit* or assay* or measure* or immunoassay* or detect* or screen* or diagnos*)).ti,ab,kw,kf. 11 Sick Leave/ or Occupational Health/ 12 ((sick* or ill* or unwell or authori#ed or excused or permitted or unpaid or medical*) adj3 (leave or absence* or “time off” or day*)).ti,ab,kw,kf. 13 (((employee* or staff or work* or shift*) adj3 (shortage* or gap* or missing or absence*)) or “short-staffed”).ti,ab,kw,kf. 14 or/9-13 15 4 and 8 and 14 16 limit 15 to yr=“2023 -Current” 17 exp Animals/ not Humans/ 18 16 not 17 # Search term (Search for CINAHL via EBSCOhost) 1 (MH “ SARS-CoV-2 ”) or (MH “COVID-19+”) 2 TI (corona* N1 (virus* or viral*)) or AB (corona* N1 (virus* or viral*)) 3 TI (covid* or coronavirus* or 2019nCoV* or 19nCoV* or “2019 novel*” or Ncov* or “n-cov” or “ SARS-CoV-2 *” or “SARSCoV-2*” or SARSCoV2* or “SARS-CoV2*” or “severe acute respiratory syndrome*” or pandemic* or longcovid* or postcovid* or postcoronavirus* or postsars*) or AB (covid* or coronavirus* or 2019nCoV* or 19nCoV* or “2019 novel*” or Ncov* or “n-cov” or “ SARS-CoV-2 *” or “SARSCoV-2*” or SARSCoV2* or “SARS-CoV2*” or “severe acute respiratory syndrome*” or pandemic* or longcovid* or postcovid* or postcoronavirus* or postsars*) 4 S1 or S2 or S3 5 TI ((intermediate or “long term” or longterm or institution* or day or extended or respite) N2 care) or AB ((intermediate or “long term” or longterm or institution* or day) N2 care or extended or respite) 6 (MH “Residential Facilities”) or (MH “Nursing Homes”) or (MH “Respite Care”) or (MH “Long-Term Care”) or (MH “Housing for Older Persons”) or (MH “Gerontologic Nursing”) 7 TI ((“old age” or “old* people*” or “old* person*” or “old* adult*” or aged or geriatric* or retirement or nursing or care or resident* or long-term or longterm or senior* or aging or ageing or elder*) N2 (home# or institution* or facility or facilities or hous* or center* or centre* or unit or units or establishment*)) or AB ((“old age” or “old* people*” or “old* person*” or “old* adult*” or aged or geriatric* or retirement or nursing or care or resident* or long-term or longterm or senior* or aging or ageing or elder*) N2 (home# or institution* or facility or facilities or hous* or center* or centre* or unit or units or establishment*)) 8 S5 or S6 or S7 9 (MH “COVID-19 Testing”) 10 TI ((asymptomatic or covid* or coronavirus* or “ SARS-CoV-2 ” or “SARSCoV-2*” or SARSCoV2* or “SARS-Cov2*” or PCR or rapid or “lateral flow”) N2 (test* or swab* or kit* or assay* or measure* or immunoassay* or detect* or screen* or diagnos*)) or AB ((asymptomatic or covid* or coronavirus* or “ SARS-CoV-2 ” or “SARSCoV-2*” or SARSCoV2* or “SARS-Cov2*” or PCR or rapid or “lateral flow”) N2 (test* or swab* or kit* or assay* or measure* or immunoassay* or detect* or screen* or diagnos*)) 11 (MH “Sick Leave”) or (MH “Family and Medical Leave”) or (MH “Occupational Health”) 12 TI ((sick* or ill* or unwell or authori?ed or excused or permitted or unpaid or medical*) N2 (leave or absence* or “time off” or day*)) or AB ((sick* or ill* or unwell or authori?ed or excused or permitted or unpaid or medical*) N2 (leave or absence* or “time off” or day*)) 13 TI (((employee* or staff or work* or shift*) N2 (shortage* or gap* or missing or absence*)) or “short-staffed”) or AB (((employee* or staff or work* or shift*) N2 (shortage* or gap* or missing or absence*)) or “short-staffed”) 14 S9 or S10 or S11 or S12 or S13 15 S4 and S8 and S14 16 (MH “Animals+” or “Animal Studies” or TI “animal model*”) not MH “Human” 17 S15 not S16 18 Limiters – Published Date: 20230101-20240101 # Search term (Search for Web of Science via Clarivate) 1 TS = (corona* NEAR/1 (virus* or viral*)) or (covid* or coronavirus* or 2019nCoV* or 19nCoV* or “2019 novel*” or Ncov* or “n-cov” or “ SARS-CoV-2 *” or “SARSCoV-2*” or SARSCoV2* or “SARS-CoV2*” or “severe acute respiratory syndrome*” or pandemic* or longcovid* or postcovid* or postcoronavirus* or postsars*) 2 TS = ((intermediate or “long term” or longterm or institution* or day or extended or respite) NEAR/2 care) 3 TS = ((“old age” or “old* people*” or “old* person*” or “old* adult*” or aged or geriatric* or retirement or nursing or care or resident* or long-term or longterm or senior* or aging or ageing or elder*) NEAR/2 (home? or institution* or facility or facilities or hous* or center* or centre* or unit or units or establishment*)) 4 #2 or #3 5 TS = ((asymptomatic or covid* or coronavirus* or “ SARS-CoV-2 ” or “SARSCoV-2*” or SARSCoV2* or “SARS-Cov2*” or PCR or rapid or “lateral flow”) NEAR/2 (test* or swab* or kit* or assay* or measure* or immunoassay* or detect* or screen* or diagnos*)) 6 TS = ((sick* or ill* or unwell or authorised or authorized or excused or permitted or unpaid or medical*) NEAR/2 (leave or absence* or “time off” or day*)). 7 TS = (((employee* or staff or work* or shift*) NEAR/2 (shortage* or gap* or missing or absence*)) or “short-staffed”). 8 #5 or #6 or #7 9 #1 and #4 and #8 10 #9 and (PY=2023) # Search term (Search for MEDLINE via Ovid) 1 SARS-CoV-2/ or COVID-19/ 2 (corona* adj1 (virus* or viral*)).ti,ab,kw,kf. 3 (covid* or coronavirus* or 2019nCoV* or 19nCoV* or “2019 novel*” or Ncov* or “n-cov” or “ SARS-CoV-2 *” or “SARSCoV-2*” or SARSCoV2* or “SARS-CoV2*” or “severe acute respiratory syndrome*” or pandemic* or longcovid* or postcovid* or postcoronavirus* or postsars*).ti,ab,kw,kf. 4 exp Respiratory Tract Infections/ or exp Influenza, Human/ or Respiratory Syncytial Virus, Human/ 5 (flu or influenza* or pneumonia* or rsv or (respiratory adj1 (virus* or viral* or infectio*))).ti,ab,kw,kf 6 or/1-5 7 ((intermediate or “long term” or longterm or institution* or day or extended or respite) adj3 care).ti,ab,kw,kf 8 Residential Facilities/ or exp Nursing Homes/ or Respite Care/ or Long-Term Care/ or Housing for the Elderly/ or Geriatric Nursing/ or Adult Day Care Centres/ or Assisted Living Facilities/ or Homes for the Aged/ 9 ((“old age” or “old* people*” or “old* person*” or “old* adult*” or aged or geriatric* or retirement or nursing or care or resident* or long-term or longterm or senior* or aging or ageing or elder*) adj3 (home? or institution* or facility or facilities or hous* or center* or centre* or unit or units or establishment*)).ti,ab,kw,kf. 10 or/7-9 11 Sick Leave/ or Occupational Health/ 12 ((sick* or ill* or unwell or authori#ed or excused or permitted or unpaid or medical*) adj3 (leave or absence* or “time off” or day*)).ti,ab,kw,kf. 13 ((sick* or ill* or absence*) adj3 (pay* or benefit* or money or compensat* or insur* or allow*)).ti,ab,kw,kf. 14 (((employee* or staff or work* or shift*) adj3 (shortage* or gap* or missing or absence*)) or “short-staffed”).ti,ab,kw,kf. 15 (backfill* or overtime or agenc* or promotion* or cover* or “on-call” or “under* shift*” or locum*).ti,ab,kw,kf. 16 or/11-15 17 6 and 10 and 16 18 limit 17 to yr=“2023 -Current” 19 exp Animals/ not Humans/ 20 18 not 19 # Search term (Search for CINAHL via EBSCOhost) 1 (MH “ SARS-CoV-2 ”) or (MH “COVID-19+”) 2 TI (corona* N1 (virus* or viral*)) or AB (corona* N1 (virus* or viral*)) 3 TI (covid* or coronavirus* or 2019nCoV* or 19nCoV* or “2019 novel*” or Ncov* or “n-cov” or “ SARS-CoV-2 *” or “SARSCoV-2*” or SARSCoV2* or “SARS-CoV2*” or “severe acute respiratory syndrome*” or pandemic* or longcovid* or postcovid* or postcoronavirus* or postsars*) or AB (covid* or coronavirus* or 2019nCoV* or 19nCoV* or “2019 novel*” or Ncov* or “n-cov” or “ SARS-CoV-2 *” or “SARSCoV-2*” or SARSCoV2* or “SARS-CoV2*” or “severe acute respiratory syndrome*” or pandemic* or longcovid* or postcovid* or postcoronavirus* or postsars*) 4 (MH “Influenza”) or (MH “Pneumonia”) or (MH “Respiratory Tract Infections) or (MH “Respiratory Syncytial Viruses”) or (MH “Respiratory Syncytial Virus Infections”) 5 TI (flu or influenza* or pneumonia* or rsv or (respiratory N1 (virus* or viral* or infectio*))) or AB (flu or influenza* or pneumonia* or rsv or (respiratory N1 (virus* or viral* or infectio*))) 6 S1 or S2 or S3 or S4 or S5 7 TI ((intermediate or “long term” or longterm or institution* or day or extended or respite) N2 care) or AB ((intermediate or “long term” or longterm or institution* or day or extended or respite) N2 care) 8 (MH “Residential Facilities”) or (MH “Nursing Homes”) or (MH “Respite Care”) or (MH “Long-Term Care”) or (MH “Housing for Older Persons”) or (MH “Gerontologic Nursing”) 9 TI ((“old age” or “old* people*” or “old* person*” or “old* adult*” or aged or geriatric* or retirement or nursing or care or resident* or long-term or longterm or senior* or aging or ageing or elder*) N2 (home# or institution* or facility or facilities or hous* or center* or centre* or unit or units or establishment*)) or AB ((“old age” or “old* people*” or “old* person*” or “old* adult*” or aged or geriatric* or retirement or nursing or care or resident* or long-term or longterm or senior* or aging or ageing or elder*) N2 (home# or institution* or facility or facilities or hous* or center* or centre* or unit or units or establishment*)) 10 S7 or S8 or S9 11 (MH “Sick Leave”) or (MH “Family and Medical Leave”) or (MH “Occupational Health”) 12 TI ((sick* or ill* or unwell or authori?ed or excused or permitted or unpaid or medical*) N2 (leave or absence* or “time off” or day*)) or AB ((sick* or ill* or unwell or authori?ed or excused or permitted or unpaid or medical*) N2 (leave or absence* or “time off” or day*)) 13 TI ((sick* or ill* or absence*) N2 (pay* or benefit* or money or compensat* or insur* or allow*)) or AB ((sick* or ill* or absence*) N2 (pay* or benefit* or money or compensat* or insur* or allow*)) 14 TI (((employee* or staff or work* or shift*) N2 (shortage* or gap* or missing or absence*)) or “short-staffed”) or AB (((employee* or staff or work* or shift*) N2 (shortage* or gap* or missing or absence*)) or “short-staffed”) 15 TI (backfill* or overtime or agenc* or promotion* or cover* or “on-call” or “under* shift*” or locum*) or AB (backfill* or overtime or agenc* or promotion* or cover* or “on-call” or “under* shift*” or locum*) 16 S11 or S12 or S13 or S14 or S15 17 S6 and S10 and S16 18 (MH “Animals+” or “Animal Studies” or TI “animal model*”) not MH “Human” 19 S17 not S18 20 Limiters – Published Date: 20230101-20240101 # Search term (Search for Web of Science via Clarivate) 1 TS = (corona* NEAR/1 (virus* or viral*)) or (covid* or coronavirus* or 2019nCoV* or 19nCoV* or “2019 novel*” or Ncov* or “n-cov” or “ SARS-CoV-2 *” or “SARSCoV-2*” or SARSCoV2* or “SARS-CoV2*” or “severe acute respiratory syndrome*” or pandemic* or longcovid* or postcovid* or postcoronavirus* or postsars*) 2 TS = (flu or influenza* or pneumonia* or rsv or (respiratory NEAR/1 (virus* or viral* or infectio*))) 3 #1 or #2 4 TS = ((intermediate or “long term” or longterm or institution* or day or extended or respite) NEAR/2 care) 5 TS = ((“old age” or “old* people*” or “old* person*” or “old* adult*” or aged or geriatric* or retirement or nursing or care or resident* or long-term or longterm or senior* or aging or ageing or elder*) NEAR/2 (home? or institution* or facility or facilities or hous* or center* or centre* or unit or units or establishment*)) 6 #4 or #5 7 TS = ((sick* or ill* or unwell or authorised or authorized or excused or permitted or unpaid or medical*) NEAR/2 (leave or absence* or “time off” or day*)). 8 TS = ((sick* or ill* or absence*) NEAR/2 (pay* or benefit* or money or compensat* or insur* or allow*)). 9 TS = (((employee* or staff or work* or shift*) NEAR/2 (shortage* or gap* or missing or absence*)) or “short-staffed”). 10 TS = (backfill* or overtime or agenc* or promotion* or cover* or “on-call” or “under* shift*” or locum*) 11 #7 or #8 or #9 or #10 12 #3 and #6 and #11 13 #12 and (PY=2023) # Search term (Search for MEDLINE via Ovid) 1 SARS-CoV-2/ or COVID-19/ 2 (corona* adj1 (virus* or viral*)).ti,ab,kw,kf. 3 (covid* or coronavirus* or 2019nCoV* or 19nCoV* or “2019 novel*” or Ncov* or “n-cov” or “ SARS-CoV-2 *” or “SARSCoV-2*” or SARSCoV2* or “SARS-CoV2*” or “severe acute respiratory syndrome*” or pandemic* or longcovid* or postcovid* or postcoronavirus* or postsars*).ti,ab,kw,kf. 4 exp Respiratory Tract Infections/ or exp Influenza, Human/or Respiratory Syncytial Virus, Human/ 5 (flu or influenza* or pneumonia* or rsv or (respiratory adj1 (virus* or viral* or infectio*))).ti,ab,kw,kf 6 or/1-5 7 ((intermediate or “long term” or longterm or institution* or day or extended or respite) adj3 care).ti,ab,kw,kf 8 Residential Facilities/ or exp Nursing Homes/ or Respite Care/ or Long-Term Care/ or Housing for the Elderly/ or Geriatric Nursing/ or Adult Day Care Centres/ or Assisted Living Facilities/ or Homes for the Aged/ 9 ((“old age” or “old* people*” or “old* person*” or “old* adult*” or aged or geriatric* or retirement or nursing or care or resident* or long-term or longterm or senior* or aging or ageing or elder*) adj3 (home? or institution* or facility or facilities or hous* or center* or centre* or unit or units or establishment*)).ti,ab,kw,kf. 10 or/7-9 11 COVID-19 Testing/ 12 ((symptomatic or asymptomatic or covid* or coronavirus* or “ SARS-CoV-2 ” or “SARSCoV-2*” or SARSCoV2* or “SARS-Cov2*” or PCR or rapid or “lateral flow”) adj3 (test* or swab* or kit* or assay* or measure* or immunoassay* or detect* or screen* or diagnos*)).ti,ab,kw,kf. 13 Sick Leave/ or Occupational Health/ 14 ((sick* or ill* or unwell or authori#ed or excused or permitted or unpaid or medical*) adj3 (leave or absence* or “time off” or day*)).ti,ab,kw,kf. 15 (((employee* or staff or work* or shift*) adj3 (shortage* or gap* or missing or absence*)) or “short-staffed”).ti,ab,kw,kf. 16 Disease Outbreaks/ 17 ((outbreak* or inciden* or case* or infection* or ‘public health’) adj3 response).ti,ab,kw,kf 18 or/11-17 19 Economics/ or exp “Costs and Cost Analysis”/ or Economics, Nursing/ or Economics, Medical/ or Economics, Pharmaceutical/ or exp Economics, Hospital/ or Economics, Dental/ or exp “Fees and Charges”/ or exp Budgets/ or exp Models, Economic/ or Markov Chains/ or exp Decision Theory/ or Monte Carlo Method/ 20 (budget*).ti,ab,kf. 21 (economic* or cost or costs or costly or costing or price or prices or pricing or pharmacoeconomic* or pharmaco-economic* or expenditure or expenditures or expense or expenses or financial or finance or finances or financed).ti,kf. 22 (economic* or cost or costs or costly or costing or price or prices or pricing or pharmacoeconomic* or pharmaco-economic* or expenditure or expenditures or expense or expenses or financial or finance or finances or financed).ab./freq=2 23 (cost* adj2 (effective* or utilit* or benefit* or minimi* or analy* or outcome or outcomes)).ab,kf. 24 (value adj2 (money or monetary)).ti,ab,kf. 25 economic model*.ab,kf. 26 markov.ti,ab,kf. 27 monte carlo.ti,ab,kf. 28 (decision* adj2 (tree* or analy* or model*)).ti,ab,kf. 29 or/19-28 30 6 and 10 and 18 and 29 31 exp Animals/ not Humans/ 32 30 not 31 # Search term (Search for CINAHL via EBSCOhost) 1 (MH “ SARS-CoV-2 ”) or (MH “COVID-19+”) 2 TI (corona* N1 (virus* or viral*)) or AB (corona* N1 (virus* or viral*)) 3 TI (covid* or coronavirus* or 2019nCoV* or 19nCoV* or “2019 novel*” or Ncov* or “n-cov” or “ SARS-CoV-2 *” or “SARSCoV-2*” or SARSCoV2* or “SARS-CoV2*” or “severe acute respiratory syndrome*” or pandemic* or longcovid* or postcovid* or postcoronavirus* or postsars*) or AB (covid* or coronavirus* or 2019nCoV* or 19nCoV* or “2019 novel*” or Ncov* or “n-cov” or “ SARS-CoV-2 *” or “SARSCoV-2*” or SARSCoV2* or “SARS-CoV2*” or “severe acute respiratory syndrome*” or pandemic* or longcovid* or postcovid* or postcoronavirus* or postsars*) 4 (MH “Influenza”) or (MH “Pneumonia”) or (MH “Respiratory Tract Infections) or (MH “Respiratory Syncytial Viruses”) or (MH “Respiratory Syncytial Virus Infections”) 5 TI (flu or influenza* or pneumonia* or rsv or (respiratory N1 (virus* or viral* or infectio*))) or AB (flu or influenza* or pneumonia* or rsv or (respiratory N1 (virus* or viral* or infectio*))) 6 S1 or S2 or S3 or S4 or S5 7 TI ((intermediate or “long term” or longterm or institution* or day or extended or respite) N2 care) or AB ((intermediate or “long term” or longterm or institution* or day) N2 care or extended or respite) 8 (MH “Residential Facilities”) or (MH “Nursing Homes”) or (MH “Respite Care”) or (MH “Long-Term Care”) or (MH “Housing for Older Persons”) or (MH “Gerontologic Nursing”) 9 TI ((“old age” or “old* people*” or “old* person*” or “old* adult*” or aged or geriatric* or retirement or nursing or care or resident* or long-term or longterm or senior* or aging or ageing or elder*) N2 (home# or institution* or facility or facilities or hous* or center* or centre* or unit or units or establishment*)) or AB ((“old age” or “old* people*” or “old* person*” or “old* adult*” or aged or geriatric* or retirement or nursing or care or resident* or long-term or longterm or senior* or aging or ageing or elder*) N2 (home# or institution* or facility or facilities or hous* or center* or centre* or unit or units or establishment*)) 10 S7 or S8 or S9 11 (MH “COVID-19 Testing”) 12 TI ((asymptomatic or covid* or coronavirus* or “ SARS-CoV-2 ” or “SARSCoV-2*” or SARSCoV2* or “SARS-Cov2*” or PCR or rapid or “lateral flow”) N2 (test* or swab* or kit* or assay* or measure* or immunoassay* or detect* or screen* or diagnos*)) or AB ((asymptomatic or covid* or coronavirus* or “ SARS-CoV-2 ” or “SARSCoV-2*” or SARSCoV2* or “SARS-Cov2*” or PCR or rapid or “lateral flow”) N2 (test* or swab* or kit* or assay* or measure* or immunoassay* or detect* or screen* or diagnos*)) 13 (MH “Sick Leave”) or (MH “Family and Medical Leave”) or (MH “Occupational Health”) 14 TI ((sick* or ill* or unwell or authori?ed or excused or permitted or unpaid or medical*) N2 (leave or absence* or “time off” or day*)) or AB ((sick* or ill* or unwell or authori?ed or excused or permitted or unpaid or medical*) N2 (leave or absence* or “time off” or day*)) 15 TI (((employee* or staff or work* or shift*) N2 (shortage* or gap* or missing or absence*)) or “short-staffed”) or AB (((employee* or staff or work* or shift*) N2 (shortage* or gap* or missing or absence*)) or “short-staffed”) 16 (MH “Disease Outbreaks”) 17 TI ((outbreak* or inciden* or case* or infection* or “public health”) N2 (response)) or AB ((outbreak* or inciden* or case* or infection* or “public health”) N2 (response)) 18 S11 or S12 or S13 or S14 or S15 or S16 or S17 19 MH “Economics” OR MH “Costs and Cost Analysis+” OR MH “Economic Aspects of Illness” OR MH “Resource Allocation+” OR MH “Economic Value of Life” OR MH “Economics, Pharmaceutical” OR MH “Economics, Dental” OR MH “Fees and Charges+” OR MH “Budgets” OR MH “Decision Trees” OR TI budget* OR TI (economic* OR cost OR costs OR costly OR costing OR price OR prices OR pricing OR pharmacoeconomic* OR “pharmaco-economic*” OR expenditure OR expenditures OR expense OR expenses OR financial OR finance OR finances OR financed) OR TI (cost* N2 (effective* OR utilit* OR benefit* OR minimi* OR analy* OR outcome OR outcomes)) OR TI (value N2 (money OR monetary)) OR TI (markov OR monte carlo) OR TI (decision* N2 (tree* OR analy* OR model*)) OR AB budget* OR AB (economic* OR cost OR costs OR costly OR costing OR price OR prices OR pricing OR pharmacoeconomic* OR “pharmaco-economic*” OR expenditure OR expenditures OR expense OR expenses OR financial OR finance OR finances OR financed) OR AB (cost* N2 (effective* OR utilit* OR benefit* OR minimi* OR analy* OR outcome OR outcomes)) OR AB (value N2 (money OR monetary)) OR AB (markov OR monte carlo) OR AB (decision* N2 (tree* OR analy* OR model*)) 20 S6 and S10 and S18 and S19 21 (MH “Animals+” or “Animal Studies” or TI “animal model*”) not MH “Human” 22 S20 not S21 Appendix 2. Protocol amendments View in own window Protocol version Protocol date Summary of changes V1.0 21 October 2022 Initial version V2.0 28 November 2022 Revisions following REC/ CAG , update to algorithm to asymptomatic staff members testing positive on LFD , addition of support payments to care homes for agency staff backfill to cover staff absence V3.0 4 January 2023 Revisions to: address typographical and grammatical errors. update the title to bring in line with that submitted in the funding application. add to the Secondary Outcomes to reflect those submitted in the revised stage 2 application to NIHR . remove references regarding recruiting residents as part of WP3A as this will no longer take place and there is no ethical approval in place for it. update to the 5.3 Trial Pathway table to amend when SAEs should be reported. clarify the sample size reasoning. clarify the interim analyses section regarding trial duration. amend errors in referencing. update to Appendix A. add to the members of the TSC . remove reference to only recruiting providers with at least 50 care homes. V4.0 5 June 2023 S1.1 Background and Rationale updated to include UKHSA change to national care home testing strategy from April-23. S.4.3.1 Usual Care section updated to reflect possibility that symptomatic testing could be withdrawn as national testing policy. S.5.1.4 clarifies that ethical permissions for WP3B of the project will be applied for separately under new IRAS ID and will be sponsored by University of Sussex. S.8.3.2 Interim Analyses section has been updated to provide the Independent Data Monitoring Committee (IDMC) with power to stop the trial for futility under certain scenarios. S.8.2.3 Blinding updated to clarify that the statisticians will be blinded until the final stages of analyses for the interim report. S.9.2.2.2. Costs of Healthcare Resource Use has been updated to include research into HPT outbreak costs. V5.0 14 January 2024 Roles and responsibilities section – minor updates to affiliations and roles. S1.1 Introduction/Background section updated to cover epidemiological and trial events since initial approvals. S1.2 aligns objectives summary with updates made in later sections of the protocol. S5.1.3 economic outcomes updated. S5.1.4 exploratory analyses updated to include other respiratory infections, beside solely COVID-19. S5.2 data sources updated to add qualitative interviews with head office staff, care home managers, and from focus groups and correspondence with health protection and infection control teams. S7.3.2 confidentiality updated to reflect addition of online and in-person interviews for economic outcomes, detailing the data collection and storage approaches to be used. S7.4 notes that economic interviews will be video-recorded if online, and audio-recorded if in-person. Where focus groups are undertaken, these will be video-recorded. S7.7 updated to also describe the data storage of transcribed interviews for economic outcomes. S9 (Economic evaluations) has been comprehensively revised following the conclusion of the RCT (WP2). Cost-effectiveness is no longer being evaluated, with the objectives instead assessing: the costs implications of providers’ policies and practice on testing, as well as COVID-19 and other respiratory infection-related sick pay, and shift management; and also, to assess the costs of public health responses to outbreaks of COVID-19 and other respiratory infections. The rationale and methodology are also substantially revised for this. S9.2.1 Outcomes is also revised in light of the conclusion of the RCT . S9.2.1.1 Resource use now focuses on collection of qualitative and quantitative data on asymptomatic testing and management of outbreaks. S9.2.2 Cost data have been revised to focus on primarily NHS and Personal Social Services perspectives, but also exploring costs of elements of the intervention and of outbreaks from the care home provider perspective. S9.2.2.1 costs of the trial intervention, will now calculate direct costs of testing, providing staff sick pay and backfilling shifts over the trial period. The revised cost calculation methodology is also provided. S9.2.2.2 healthcare resource use is updated to focus on HPT and IPC input for the management of COVID-19 and other respiratory infection outbreaks. A revised data collection strategy is provided. S9.2.4.1 updates the primary analysis to determining first, the costs of the testing intervention; second, care home providers policies on asymptomatic testing for COVID-19, sickness absence and unfilled shifts related to COVID-19 and other respiratory infection outbreaks; third, public health costs of COVID-19 and other respiratory infections; and fourth, costs of outbreaks will be summarised. S9.2.4.2 (missing data handling) and S9.2.4.4 (secondary analyses) are both now removed. S9.3 Modelling analysis, comprehensively updated to reflect the new approach of modelling the epidemiological impact of the testing intervention vs. standard care in terms of infections and deaths averted under different transmission scenarios, along with the methods and deliverables supporting this. About the Series Health and Social Care Delivery Research ISSN (Electronic): 2755-0079 Article history The contractual start date for this research was in November 2022. This article began editorial review in December 2024 and was accepted for publication in July 2025. The authors have been wholly responsible for all data collection, analysis and interpretation, and for writing up their work. The Health and Social Care Delivery Research editors and publisher have tried to ensure the accuracy of the authors’ article and would like to thank the reviewers for their constructive comments on the draft document. However, they do not accept liability for damages or losses arising from material published in this article. Last reviewed: December 2024; Accepted: July 2025. Copyright © 2026 Adams et al . This work was produced by Adams et al . under the terms of a commissioning contract issued by the Secretary of State for Health and Social Care. This is an Open Access publication distributed under the terms of the Creative Commons Attribution CC BY 4.0 licence, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. See: https://creativecommons.org/licenses/by/4.0/ . For attribution the title, original author(s), the publication source – NIHR Journals Library, and the DOI of the publication must be cited. Bookshelf ID: NBK621011 DOI: 10.3310/GJLS1610 Share Views PubReader Print View Cite this Page Adams N, Stirrup O, Blackstone J, et al. Asymptomatic testing compared with standard care of the care home staff in shaping care home COVID-19 testing policy: the VIVALDI-CT pragmatic cluster RCT (VIVALDI-CT) [Internet]. Southampton (UK): National Institute for Health and Care Research; 2026 Feb 11. doi: 10.3310/GJLS1610 PDF version of this title (1.6M) In this Page Introduction Discussion/interpretation Patient and public involvement and engagement Equality, diversity and inclusion Impact and learning Implications for decision-makers Research recommendations Conclusions Additional information List of abbreviations References Literature search Protocol amendments Other titles in this collection Health and Social Care Delivery Research Related information NLM Catalog Related NLM Catalog Entries PMC PubMed Central citations PubMed Links to PubMed Recent Activity Clear Turn Off Turn On Asymptomatic testing compared with standard care of the care home staff in shapi... 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