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Learn more: PMC Disclaimer | PMC Copyright Notice Lancet Reg Health West Pac . 2026 Mar 30;69:101848. doi: 10.1016/j.lanwpc.2026.101848 Search in PMC Search in PubMed View in NLM Catalog Add to search China’s nationwide antimicrobial resistance surveillance networks: a systematic analysis from One Health perspective Weibin Li Weibin Li a Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, China Find articles by Weibin Li a , Lianping Yang Lianping Yang b School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China Find articles by Lianping Yang b , Fenqi Du Fenqi Du a Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, China Find articles by Fenqi Du a , Xiaodong Guan Xiaodong Guan a Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, China c International Research Center for Medicinal Administration (IRCMA), Peking University, Beijing, 100191, China Find articles by Xiaodong Guan a, c, ∗ , Haishaerjiang Wushouer Haishaerjiang Wushouer a Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, China c International Research Center for Medicinal Administration (IRCMA), Peking University, Beijing, 100191, China Find articles by Haishaerjiang Wushouer a, c, ∗∗ Author information Article notes Copyright and License information a Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, China b School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China c International Research Center for Medicinal Administration (IRCMA), Peking University, Beijing, 100191, China ∗ Corresponding author. Peking University Health Science Center, 38 Xueyuan Road, Haidian District, Beijing, 100191, China. [email protected] ∗∗ Corresponding author. Peking University Health Science Center, 38 Xueyuan Road, Haidian District, Beijing, 100191, China. [email protected] Received 2026 Jan 24; Revised 2026 Mar 19; Accepted 2026 Mar 19; Collection date 2026 Apr. © 2026 The Author(s) This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). PMC Copyright notice PMCID: PMC13068644 PMID: 41971758 Summary Antimicrobial resistance (AMR) poses a growing threat to human, animal, and environmental health, necessitating integrated surveillance systems to effectively address this challenge. Globally, many countries have committed to expanding AMR monitoring under their national action plans, yet the development and alignment of surveillance systems across different sectors remain insufficiently documented, likewise in China with rapid economic transformation and severe health challenges. Using the EPI-Net One Health reporting guideline, we reviewed 13 nationwide AMR surveillance networks in China. The findings demonstrate notable progress in sector-specific surveillance, particularly within human and animal sector. However, gaps persist in environmental monitoring, cross-sector integration, methodological standardization, and data sharing, which constrain the generation of high-quality, comprehensive AMR data. These findings highlight the urgent need for increased investment in advanced technologies like whole-genome sequencing (WGS), alongside broader stakeholder engagement and clearer consensus on data governance and data-sharing mechanisms to strengthen AMR surveillance from One Health perspective. Keywords: Antimicrobial resistance, Surveillance network, One Health, China Introduction Antimicrobial resistance (AMR) is a major global public health threat. In 2021 alone, antimicrobial-resistant bacterial infections were directly responsible for an estimated 1.14 million deaths worldwide, and this figure is projected to reach 1.91 million by 2050. 1 AMR has been widely recognized as a phenomenon driven by multifactorial determinants operating across human, animal, and environmental systems, rather than from clinical antibiotic misuse alone. For example, China's decisive ban on colistin use in food-producing animals led not only to a reduction in colistin residues in agricultural settings, but also to a substantial decline in colistin resistance among Escherichia coli isolates from both animals and humans. 2 Together, such evidences emphasise the urgent need for integrated surveillance systems capable of capturing the emergence and transmission. 3 Despite increasing recognition of the importance of AMR surveillance, surveillance systems remain markedly underdeveloped in many low- and middle-income countries (LMICs). Fragmentation across governance and management sectors, inconsistent surveillance standards, and the absence of interoperable data infrastructures frequently hinder cross-sectoral information exchange. As a result, surveillance efforts are frequently duplicated with incomplete coverage, and the capacity to generate timely, actionable insights is limited. 4 , 5 Strengthening coordination and establishing a comprehensive landscape of AMR surveillance resources are therefore essential to improving efficiency and supporting integrated, evidence-informed policy responses. 6 In line with the World Health Organization (WHO)'s call for a One Health response to AMR, China has been among the earlier adopters of national strategies to address AMR by implementing two National Action Plans and developed multiple surveillance programmes spanning human, animal, food, and environmental domains. 7 , 8 However, these efforts have largely developed in parallel, and an integrated overview is lacking, limiting the ability to assess coverage, identify gaps, and coordinate resources across sectors. To address this gap, this study systematically maps and analyses China's nationwide surveillance networks. We focus on initiatives with broad geographic representativeness across the Eastern, Central, and Western regions of China, as well as those supported by established administrative mandates for national-scale monitoring. Through this approach, we aim to provide a comprehensive overview of China's nationwide AMR surveillance framework from a One Health perspective. Methods Search strategy and selection criteria We conducted a systematic scoping review following the methodological framework proposed by Arksey and O'Malley, and aligned it with the EPI-Net One Health reporting guideline for antimicrobial consumption and resistance surveillance data. 9 , 10 The EPI-Net guideline provides a comprehensive expert consensus on the structuring and full-scale reporting of AMR, antimicrobial consumption (AMC), and antimicrobial residues (AR) data across the human, animal, and environmental sectors. In this study, we utilized this guideline as a standardized framework to categorize and evaluate the surveillance activities identified. Specifically, it guided data extraction on dissemination frequency, reporting structure, and the selection of core metrics used for AMC/AR and AMR data. In this review, an antimicrobial surveillance activity was defined as any initiative that systematically collects, analyses, and reports data on AMR, AMC/AR in at least one of the three One Health sectors: human health, animal health, or the environment. The search strategy combined the following terms: (antibiotic∗ OR antimicrobial∗ OR antifungal∗ OR resistan∗ OR residual) AND (hospital∗ OR clinic∗ OR communit∗ OR animal∗ OR livestock∗ OR poultry∗ OR pet OR pets OR soil OR water OR wastewater OR river∗ OR lake∗) AND (monitor∗ OR surveillance∗ OR survey∗ OR report∗ OR review) AND (China). We systematically screened the literature available in PubMed, Embase and CNKI, as well as documents published on the official websites of relevant government agencies, including the National Health Commission, the Ministry of Agriculture and Rural Affairs, the National Medical Products Administration, the Ministry of Ecology and Environment, the National Healthcare Security Administration, the Ministry of Education, the Ministry of Finance, the National Development and Reform Commission, and the Ministry of Science and Technology. The search period covered all records from database inception to September 8, 2025, with no language restrictions applied. During the initial screening, we observed that studies in the environmental sector were predominantly point-prevalence investigations, with few ongoing surveillance programmes. To ensure comparability across sectors, we included national-scale sampling initiatives and reviews reporting aggregated resistance or residue patterns additionally. To ensure comprehensive coverage of publicly available monitoring activities, supplementary searches were conducted using two major Chinese search platforms (Baidu and WeChat). Studies were included if they described official government programmes or academic research that explicitly outlined a monitoring plan or reported surveillance results. Studies were excluded if they: 1) focused on pathogens outside the scope of conventional AMR, such as Mycobacterium tuberculosis , viruses, or parasites; 2) reported only subnational findings that neither claimed nationwide coverage nor provided representative data across China's diverse regions (i.e., lacking concurrent data from the Eastern, Central, and Western regions). To distinguish systematic surveillance from one-off cross-sectional surveys, an initiative was defined as a “surveillance activity” only if it demonstrated continuity through a consistent project title or leading institution with repeated data collection over at least two years. When multiple documents referred to the same surveillance network, duplicates were removed based on network name and leading institution ( Fig. 1 ). Eligibility assessment was conducted independently by two reviewers (WL and LY), with discrepancies resolved through adjudication by two additional reviewers (XG and HW). Fig. 1. Open in a new tab PRISMA Flow Diagram for Networks and surveys selection . Data extraction and analysis The data extraction framework was developed based on the methodological framework developed by Lucie Collineau and Clémence Bourély. 6 For surveillance activities with clearly documented information, we extracted network name, official website link, year of establishment, initiating and participating institutions, surveillance methodology, and monitored items (antimicrobials and bacterial species). For review articles or cross-sectional surveys, we extracted information on monitored items only. All extracted data were collated and summarized using Microsoft Excel 2021. To assess the coverage of surveillance activities, we first characterized the provincial distribution of surveillance networks in the human and animal sectors, including the number of participating hospitals, sampling volumes, target animal species, and isolated pathogens. This information were primarily sourced from the China Antimicrobial Resistance Surveillance System (CARSS), 11 , 12 China Fungal Diseases Surveillance System (CFDSS), 13 and Center for Antibacterial Surveillance (CAS), 14 , 15 and the 2023 National Monitoring Program for Antimicrobial Resistance in Animal-Derived Bacteria. 16 These indicators were examined in relation to the total number of hospitals and levels of agricultural output (meat production) in each province, using data from the Chinese Statistical Yearbook, to provide contextualized measures of surveillance coverage. Antimicrobials monitored in the human and animal sectors, as well as those investigated in environmental studies, were subsequently classified according to the 2024 WHO List of Medically Important Antimicrobials. 17 , 18 In the human sector, data were primarily derived from CAS reports, while in the animal sector, data were sourced from the Annual Report on the Use of Veterinary Antibiotics in China, 19 the National Monitoring Plan for Veterinary Drug Residues in Livestock, Poultry, and Their Products, 20 and the National Monitoring Plan for Veterinary Drug Residues in Aquaculture Products. 21 In the environmental sector, antimicrobials monitored were identified based on representative studies from relevant fields. 22 , 23 , 24 , 25 To evaluate cross-sectoral consistency in antimicrobial monitoring, we calculated the number of antimicrobials consistently included across sectors within each classification category. Finally, we compared the microorganisms targeted in human and animal surveillance and the corresponding antimicrobial susceptibility testing (AST) panels. Information was obtained from CARSS, the Monitoring Plan for Antimicrobial Resistance in Animal-Derived Bacteria, and the China Antimicrobial Resistance Surveillance Network for Pets (CARPet). 26 Bacterial species names were standardized using the taxonomy of the China Center for Type Culture Collection (CCTCC), and priority levels were assigned according to the 2024 WHO Bacterial Priority Pathogens List. 27 Results Overview of surveillance networks and cross-sectional surveys in China Prior to the release of the National Action Plan on AMR in 2016, China had already established nine national surveillance networks for AMR, AMC/AR in the human health and food-producing animal sectors. These programmes were initiated by government agencies, universities, or hospitals. In total, seven surveillance programmes focused on AMR in humans, 11 , 12 , 13 , 28 , 29 , 30 , 31 , 32 , 33 while only two monitored AMR in animal-derived bacteria. 16 , 26 Additionally, two programmes monitored AR in animal-derived food products, 20 , 21 and one programme each targeted AMC in humans and animals, 14 , 15 , 19 respectively. The earliest AMR surveillance programme in the human sector was the China Antimicrobial Surveillance Network (CHINET). 28 Established in 2004 as a multicentre collaborative network led by Huashan Hospital, Fudan University, CHINET initially consolidated data from eight founding member hospitals. The voluntary network has since expanded to 80 member institutions across 31 provinces, providing longitudinal data that reflect broader national trends in antimicrobial resistance. In the animal sector, the earliest national effort dates back to 2008, with the launch of the Monitoring Plan for Antimicrobial Resistance in Animal-Derived Bacteria, led by the Ministry of Agriculture and Rural Affairs 16 ( Table S1 ). Following the release of the 2016 National Action Plan, four new initiatives emerged. These include CFDSS, 13 initiated by the National Health Commission to monitor fungal pathogens and antifungal resistance; the launch of AMC monitoring for veterinary drugs; the establishment of CARPet; 26 and the expansion of AR monitoring in aquaculture products 21 ( Table S1 ). To date, China has not established a formal surveillance system for AMR or AR in the environmental sector. Four comprehensive review initiatives have partially addressed this gap by documenting AR in aquatic environments, pharmaceutical wastewater, solid waste, and agricultural soils. 22 , 23 , 24 , 25 Beyond the environmental sector, an additional 20 national surveys and initiatives have addressed critical gaps within existing human and animal health frameworks. 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 These activities encompass monitoring for non-prescription antimicrobial dispensing, Neisseria gonorrhoeae , and atypical pathogens such as Mycoplasma pneumoniae and Helicobacter pylori , as well as AMR in companion animals ( Table 1 ). Table 1. One Health surveillance networks and surveys in China. Sector Surveillance Surveys Antimicrobial resistance Antimicrobial use/Residue Human health • China Antimicrobial Resistance Surveillance System (CARSS) 11 , 12 • China Antimicrobial Surveillance Network (CHINET) 28 • Chinese Infectious Disease Surveillance of Pediatrics (ISPED) program 29 • Bacterial Resistant Investigation Collaborative System (BRICS) 30 • China Antimicrobial Resistance Surveillance Trial (CARST) Program 31 , 32 • China Hospital Invasive Fungal Surveillance NET (CHIF-NET) 33 • China Fungal Diseases Surveillance System (CFDSS) 13 • Center for Antibacterial Surveillance (CAS) 14 , 15 • Non-prescription antibiotic dispensing 34 , 35 • Antimicrobial resistance of community-acquired respiratory tract infection pathogen 36 , 37 , 38 , 39 , 40 • Antimicrobial resistance of Helicobacter pylori 41 • China Gonococcal Antimicrobial Susceptibility Programme (China-GASP) 42 , 43 , 44 Animal health and food safety • Monitoring Plan For Antimicrobial Resistance in Animal-Derived Bacteria 16 • China Antimicrobial Resistance Surveillance Network for Pets (CARPet) 26 • Annual Report on the Use of Veterinary Antibiotics in China 19 • National Monitoring Plan for Veterinary Drug Residues in Livestock, Poultry and Their Products 20 • National Monitoring Plan for Veterinary Drug Residues in Aquaculture Products 21 • Antibiotic resistance of pet-derived bacteria 45 , 46 , 47 • Antibiotic residue for food-producing animals 48 • Antibiotic residues in animal-derived foods 49 , 50 , 51 • Antibiotic usage and residues in aquaculture 52 , 53 Environment None None • Antimicrobial residues in the aquatic environments 22 • Antimicrobial resistance and residues in wastewater and solid waste 23 • Antimicrobial residues in agricultural soils 24 , 25 Open in a new tab Geographical coverage of surveillance networks As of 2023, national human AMR surveillance networks in China have expanded to cover all 31 provinces in mainland China. Among the 38,355 hospitals nationwide, 7691 hospitals (20.0%) participated in CAS, and 6595 hospitals (17.2%) were enrolled in CARSS, whereas CFDSS covered only 804 hospitals (2.1%). Although the exact number of unique hospitals across all systems is not publicly available due to potential overlap, the number of hospitals participating in each surveillance network was positively correlated with the total number of hospitals in each province ( Fig. 2 A). Fig. 2. Open in a new tab Geographic coverage of antimicrobial surveillance systems in China . A) Provincial distribution of hospitals participating in national human health surveillance networks in 2023. Provinces are shaded according to the total number of hospitals, with overlaid clustered bar charts indicating the number of hospitals enrolled in each surveillance system. B) Provincial distribution of bacterial isolates collected. Provinces are shaded according to total meat production, while overlaid pie charts represent the composition of bacterial species sampled in each province. The size of each pie chart is proportional to the total number of isolates. The dashed line delineates the provinces covered by the central testing laboratory. In the animal health sector, approximately 8700 bacterial isolates were collected in 2023 from 30 provinces across mainland China. Sample volumes were broadly aligned with provincial meat production levels, demonstrating a general positive association. Surveillance activities focused primarily on livestock-associated pathogens, including E. coli , Enterococcus spp., Salmonella spp., Staphylococcus aureus , Clostridium perfringens , Campylobacter spp., and Actinobacillus pleuropneumoniae. In addition, targeted sampling of pet-derived E. coli and Enterococcus spp. was conducted in four urban centres—Beijing, Shanghai, Guangdong, and Sichuan—yielding 240 isolates from companion animals ( Fig. 2 B). Antimicrobials covered in surveillance networks As of 2023, surveillance networks recorded 183 antimicrobials in the human sector and 66 in the animal sector, with 25 antimicrobials shared between the two sectors. According to 2024 WHO List of Medically Important Antimicrobials, 16 of these shared agents were classified as Highly Important Antimicrobials (HIA). Two antimicrobials, ciprofloxacin and colistin, were categorized as Highest Priority Critically Important Antimicrobials (HPCIA). However, only ciprofloxacin residues have been routinely monitored across food production and environmental settings. By contrast, colistin residues have not been reported in terrestrial environments, aquatic products, lakes, wastewater, or agricultural soils. In addition, six HIAs that were monitored both in the human and animal sectors, including ampicillin, benzylpenicillin, cloxacillin, oxacillin, nafcillin, and cefalexin, have not been investigated in the food production or environmental sectors ( Fig. 3 ). Fig. 3. Open in a new tab Antimicrobials surveyed across human, animal, and environmental sectors in China . Antibiotics are categorized according to the 2024 WHO List of Medically Important Antimicrobials. Non-gray blocks indicate the classes of antimicrobials monitored within each sector, with darker shades representing a broader range of antimicrobials surveyed. “…” denotes that only representative antibiotic classes are shown; the complete list is provided in Table S2 . Bacterial species covered in surveillance networks As of 2023, surveillance systems monitored a total of 21 genera and 27 species of pathogens across both human and animal sectors. However, alignment at the species level remains limited: only E. coli and S. aureus were consistently monitored as species in both sectors. For most pathogens, surveillance was conducted at the genus level rather than the species level, resulting in limited comparability between human and animal surveillance systems. This lack of species-level alignment is particularly evident in companion animal surveillance. Pathogens such as Klebsiella (including Klebsiella pneumoniae ), Enterobacter (including Enterobacter cloacae ), Enterococcus (including Enterococcus faecalis ), Streptococcus (including Streptococcus pneumoniae and Streptococcus pyogenes ), Acinetobacter (including Acinetobacter baumannii ), and Pseudomonas (including Pseudomonas aeruginosa ) are not consistently monitored at the species level in the human sector. Similarly, surveillance of Enterococcus species in food-producing animals is not aligned with the species-level monitoring of Enterococcus faecium and E. faecalis in humans. In terms of AST, surveillance in the human sector currently covers all pathogens classified within the WHO Critical Group, including carbapenem-resistant Enterobacterales and carbapenem-resistant A. baumannii . In the animal sector, companion animal surveillance covers five pathogens listed in WHO Bacterial Priority Pathogens List, compared with only two pathogens covered in food-producing animal surveillance ( Fig. 4 ). Fig. 4. Open in a new tab Bacterial species and resistance phenotypes monitored across human, companion animal, and food-producing animal sectors in China . The dots represent resistant bacteria and resistance phenotypes included in surveillance networks. Blue dots indicate inclusion in the China Antimicrobial Resistance Surveillance System (CARSS), green dots represent the Monitoring Plan for Antimicrobial Resistance in Animal-Derived Bacteria, and red dots correspond to the China Antimicrobial Resistance Surveillance Network for Pets (CARPet). Different shapes represent resistance phenotypes classified by the 2024 WHO Bacterial Priority Pathogens List: diamonds for the Critical group, squares for the High group, and triangles for the Medium group. Discussion This study provides the first systematic, cross-sectoral mapping of national surveillance activities for AMR, AMC/AR in China from a One Health perspective. Although previous studies have attempted to describe China's surveillance landscape across various sectors, they primarily relied on general literature reviews or broad policy analyses without detailing the specific operational frameworks of active surveillance programmes. 54 , 55 Meanwhile, global assessments of surveillance systems frequently tended to overlook Chinese initiatives, which remain underrepresented in major academic databases. 56 , 57 Our review addresses these gaps by integrating diverse data sources to capture a more complete account of both formal and informal monitoring activities. Our findings indicate that China has established operational surveillance systems in both the human and animal sectors, with extensive geographic coverage and regular reporting of internationally prioritized antimicrobial classes and bacterial pathogens. However, formal surveillance system in the environmental sector remains absent, and cross-sectoral integration is still limited. Surveillance coverage is a critical determinant of the validity and interpretability of AMR data. The Global antibiotic resistance surveillance report 2025 emphasises that, 58 in countries with limited surveillance infrastructure, resistance data are often derived from a small number of tertiary hospitals, where patients typically present with more severe infections, with multiple previous treatment failures, or infections caused by treatment-resistant pathogens. Such sampling bias can lead to overestimation of resistance prevalence and limits the generalizability of findings to the broader population, thereby reducing the value of AMR surveillance data for national decision-making and for informing global empirical treatment guidance. Although China's human health sector AMR surveillance now spans all provinces nationwide, most data are generated through passive surveillance in secondary and tertiary hospitals. This model is likely to over-represent isolates from hospitalised populations and may include a substantial proportion of hospital-acquired colonising organisms. The prevalence of these clinical-setting signals can mask the detection of emerging resistance signals originating from the community, thereby weakening the timeliness and sensitivity of community-level surveillance. 59 The absence of complementary active surveillance further limits coverage of community populations and atypical pathogens. 60 Moreover, beyond reporting AMR prevalence, China's national AMR surveillance networks rarely collect key contextual variables, such as patient demographics, clinical characteristics, and health outcomes. The absence of these data constrains the linkage between AMR monitoring and AMC surveillance, thereby undermining the interpretability and policy relevance of AMR data. 59 In the animal sector, China initiated nationwide active surveillance programmes early on and conducts annual monitoring. However, surveillance outputs are not routinely released in the public domain by regulatory authorities, partly owing to concerns about commercial sensitivity. Limited transparency in turn restricts cross-sectoral data sharing and hampers integration across One Health domains. With respect to surveillance indicators, animal-sector monitoring often prioritises information to guide disease management and treatment decisions, rather than systematically tracking resistance to antimicrobials that are directly relevant to both veterinary and human medicine. Although there is some overlap existing between the pathogens and antimicrobial agents monitored in animals and those prioritized in human health, misalignment in surveillance targets hinders meaningful interpretation in relation to human AMR risks. Recent efforts, such as the establishment of the CARPet surveillance network has sought to narrow this gap by strengthening AMR monitoring in companion animals. 26 Where routine surveillance remains incomplete, systematic synthesis of point-prevalence surveys may provide a pragmatic complementary approach. For example, one large-scale synthesis combining 901 surveys, estimate resistance patterns in animals and food products across LMICs between 2000 and 2018. 48 , 61 While such approaches can partially compensate for the gaps in routine surveillance, they also highlight the need for more strategic allocation of monitoring resources and stronger standardization of survey methodologies. The absence of a formal AMR surveillance network in the environmental sector is not unique to China. Even in high-income countries, the integration of environmental monitoring into national AMR surveillance frameworks remains at an early stage and is often considered as complementary rather than central to surveillance activities. 6 , 62 , 63 In contrast to the relatively well-defined human and animal AMR monitoring, environmental surveillance is frequently embedded within other sectors. For example, urban environments are often assessed through clinical surveillance, while agricultural settings are monitored through veterinary systems. Consequently, environmental surveillance activities are highly heterogeneous and lack a coherent, unified framework. This fragmentation leaves several fundamental questions unresolved, such as which pathogens or resistance determinants to prioritize, which populations or ecological compartments are the primary targets of protection, and which interventions are most effective. Addressing these gaps requires clear surveillance objectives to guide policy and technical implementation. 59 , 64 , 65 Although no country has yet established a comprehensive and integrated national environmental AMR surveillance network, several international initiatives offer valuable reference points for future development. For instance, the WHO Integrated Surveillance on ESBL-producing E. coli (the “Tricycle” project) provides a standardized protocol for monitoring resistance indicators across human, animal, and environmental sectors, specifically targeting wastewater and surface water. 66 In Europe, a pilot study on AMR surveillance in surface water was launched to establish a unified framework for sampling and reporting. This effort is further supported by the recently revised Urban Wastewater Treatment Directive, which mandates AMR monitoring in large European settlements. 67 Similarly, the United States Environmental Protection Agency (EPA) leads the National Antimicrobial Resistance Monitoring System (NARMS) Environmental Working Group, which has implemented a large-scale project across 2000 sites to assess the spatial variability of AMR in national surface waters. 65 These emerging international practices provide critical policy and technical guidance for China as it begins to designate antimicrobials as emerging pollutants and strengthen environmental monitoring and regulation under the Ministry of Ecology and Environment. Encouragingly, China has begun to recognize environmental AMR as a priority through scientific research and policy engagement. Under the Ministry of Ecology and Environment, several government bodies, including the Ministries of Industry, Agriculture, and Commerce, have designated antimicrobials as emerging pollutants for enhanced monitoring and control. 54 , 68 , 69 Although the establishment of cross-sectoral surveillance systems has been identified by the Quadripartite organizations as one of the five priority research areas, 70 there is still no globally accepted normative model to guide implementation. One comparative analysis reviewed 14 relatively mature AMR surveillance systems worldwide and categorized them into four broad typologies. 6 The first involves independent oversight within each sector; the second is characterised by high levels of information integration and operational coordination; the third incorporates contributions from multiple sectors but remains under the human health sector's oversight; and the fourth is led by food safety authorities, with close collaboration with the animal health sector. China's AMR surveillance system most closely resembles the first typology, in which data collection, analysis and interpretation are conducted independently within each sector, with limited cross-sector comparison or joint assessment. As a result, the current configuration does not yet function as a fully integrated AMR surveillance system. Increased investment in surveillance capacity and the adoption of advanced diagnostic technologies may partially alleviate the fragmentation of AMR monitoring systems. Whole-genome sequencing (WGS) has emerged as a promising tool for integrated AMR surveillance within a One Health framework. By bridging AMR genes to specific bacterial lineages, it enables a more precise tracking of how resistant determinants spread across different sectors. This genomic resolution is particularly valuable for identifying emerging threats and evaluating the impact of interventions such as vaccination programmes or stewardship measures. 71 , 72 According to WHO guidance, WGS serves as a powerful complement to phenotypic methods by providing the highest resolution for pathogen subtyping and early warnings of resistance emergence. 73 However, across the networks reviewed here, wider implementation and centralized coordination of WGS data remains limited by constraints in cost, uneven sequencing capacity, and the lack of standardized reporting and data-sharing systems. Establishing a coordinated genomic surveillance infrastructure will therefore be essential for translating these high-resolution data into actionable strategies and strengthen integrated One Health surveillance. 73 , 74 , 75 However, technological advances alone are unlikely to deliver sustained integration. More substantial progress will depend on broader stakeholder engagement and the implementation of effective data-sharing policies. To establish a comprehensive and sustainable AMR surveillance network, participation from a wide range of stakeholders is required, including those involved in infection prevention, antimicrobial stewardship, the pharmaceutical sector, food safety authorities, and environmental groups. Such engagement is essential not only to mobilize resources, but also to ensure that surveillance findings can be translated into coordinated action. 76 In parallel, inclusive consultation across these stakeholders is essential to build a shared data consensus, including agreement on the scope of data collection, standardized reporting metrics, analytical approaches, and mechanisms for data sharing across domains, thereby supporting more integrated One Health analyses. 10 This study has several limitations. First, our analysis focused on nationwide surveillance programmes identified through publicly available sources. Subnational systems and internal government reports were not included. Furthermore, detailed information regarding certain monitoring networks may not have been captured if the relevant documentation was inaccessible due to government website migrations or its status as internal security files. Thus, some pilot initiatives or region-specific efforts may not have been captured. Second, several national systems lacked publicly available documentation with sufficient methodological detail for in-depth analysis. Our evaluation was limited to programmes with transparent and accessible information, which may have led to the exclusion of some initiatives. Conclusion This study provides the first systematic synthesis of AMR, antibiotic use, and antibiotic residue surveillance activities in China across human, animal, and environmental sectors. Our findings indicate that China has made significant progress in developing sector-specific surveillance, particularly in human and animal health, and has laid important foundations for more comprehensive surveillance efforts. However, persistent gaps in environmental monitoring, cross-sectoral integration, standardization, and data sharing continue to constrain the effectiveness of AMR risk assessment under a One Health framework. Looking ahead, strengthening intersectoral coordination and harmonising surveillance standards and indicators should be prioritised. The development of an integrated One Health system with shared objectives across sectors will be crucial. Such efforts are critical to improving evidence-informed policymaking and enhancing China's capacity to address the interconnected and evolving challenges posed by AMR. Contributors WL, XG, and HW conceptualized the study. WL undertook data curation, software, and visualization. WL and HW performed formal analysis. HW acquired the funding. WL, XG, and HW conducted the investigation. WL, LY, and HW developed the methodology. WL, XG, and HW managed project administration. WL and HW provided resources. XG and HW provided supervision. WL, LY, XG, and HW performed validation. WL and HW drafted the original manuscript. WL, LY, FD, XG, and HW critically revised the manuscript for important intellectual content. All authors interpreted the data and approved the final version for publication. WL, XG and HW had full access to all the data in the study and held final responsibility for the decision to submit for publication. Editor note The Lancet Group takes a neutral position with respect to territorial claims in published maps and institutional affiliations. Declaration of interests All authors declare no competing interests. Acknowledgements This study was supported by the National Natural Science Foundation of China (72374009). The funders of the study had no role in the study design, data collection, data analysis, data interpretation, or writing of the paper. Footnotes Translation: For the Chinese translation of the abstract see the Supplementary Materials section . Appendix A Supplementary data related to this article can be found at https://doi.org/10.1016/j.lanwpc.2026.101848 . Contributor Information Xiaodong Guan, Email: [email protected]. Haishaerjiang Wushouer, Email: [email protected]. Appendix A. Supplementary data Supplementary Tables mmc1.pdf (199KB, pdf) Translated abstract mmc2.docx (14.5KB, docx) References 1. Global burden of bacterial antimicrobial resistance 1990-2021: a systematic analysis with forecasts to 2050. Lancet. 2024;404(10459):1199–1226. doi: 10.1016/S0140-6736(24)01867-1. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 2. Wang Y., Xu C., Zhang R., et al. 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