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Learn more: PMC Disclaimer | PMC Copyright Notice BMC Microbiol . 2026 Mar 4;26:333. doi: 10.1186/s12866-026-04895-y Search in PMC Search in PubMed View in NLM Catalog Add to search Prevalence, quantification, and household-level risk factors associated with Salmonella spp. infection in chickens in Boussouma commune, Burkina Faso Wendenso Patrick Bertrand Tiendrébéogo Wendenso Patrick Bertrand Tiendrébéogo 1 Laboratory of Molecular Biology, Epidemiology and Surveillance of Foodborne Bacteria and Viruses, Department of Biochemistry-Microbiology, Doctoral School of Science and Technology, Joseph KI-ZERBO University, Ouagadougou, 03 BP 7021 Burkina Faso Find articles by Wendenso Patrick Bertrand Tiendrébéogo 1, ✉ , Assèta Kagambèga Assèta Kagambèga 1 Laboratory of Molecular Biology, Epidemiology and Surveillance of Foodborne Bacteria and Viruses, Department of Biochemistry-Microbiology, Doctoral School of Science and Technology, Joseph KI-ZERBO University, Ouagadougou, 03 BP 7021 Burkina Faso 2 École Normale Supérieure, Ouagadougou, Burkina Faso Find articles by Assèta Kagambèga 1, 2 , Arshnee Moodley Arshnee Moodley 3 International Livestock Research Institute, HEALTH program, Nairobi, Kenya 4 Department of Veterinary and Animal Science, University of Copenhagen, Frederiksberg C, Denmark Find articles by Arshnee Moodley 3, 4 , Linnet Ochieng Linnet Ochieng 3 International Livestock Research Institute, HEALTH program, Nairobi, Kenya Find articles by Linnet Ochieng 3 , Tho Abou Da Tho Abou Da 1 Laboratory of Molecular Biology, Epidemiology and Surveillance of Foodborne Bacteria and Viruses, Department of Biochemistry-Microbiology, Doctoral School of Science and Technology, Joseph KI-ZERBO University, Ouagadougou, 03 BP 7021 Burkina Faso Find articles by Tho Abou Da 1 , Rasmané Tao Rasmané Tao 1 Laboratory of Molecular Biology, Epidemiology and Surveillance of Foodborne Bacteria and Viruses, Department of Biochemistry-Microbiology, Doctoral School of Science and Technology, Joseph KI-ZERBO University, Ouagadougou, 03 BP 7021 Burkina Faso Find articles by Rasmané Tao 1 , Abdoul Kader Ilboudo Abdoul Kader Ilboudo 5 International Livestock Research Institute, Ouagadougou, Burkina Faso Find articles by Abdoul Kader Ilboudo 5 , Brice Ouedraogo Brice Ouedraogo 5 International Livestock Research Institute, Ouagadougou, Burkina Faso Find articles by Brice Ouedraogo 5 , Guy Ilboudo Guy Ilboudo 5 International Livestock Research Institute, Ouagadougou, Burkina Faso Find articles by Guy Ilboudo 5 , Nicolas Barro Nicolas Barro 1 Laboratory of Molecular Biology, Epidemiology and Surveillance of Foodborne Bacteria and Viruses, Department of Biochemistry-Microbiology, Doctoral School of Science and Technology, Joseph KI-ZERBO University, Ouagadougou, 03 BP 7021 Burkina Faso Find articles by Nicolas Barro 1 , Michel Dione Michel Dione 5 International Livestock Research Institute, Ouagadougou, Burkina Faso Find articles by Michel Dione 5 Author information Article notes Copyright and License information 1 Laboratory of Molecular Biology, Epidemiology and Surveillance of Foodborne Bacteria and Viruses, Department of Biochemistry-Microbiology, Doctoral School of Science and Technology, Joseph KI-ZERBO University, Ouagadougou, 03 BP 7021 Burkina Faso 2 École Normale Supérieure, Ouagadougou, Burkina Faso 3 International Livestock Research Institute, HEALTH program, Nairobi, Kenya 4 Department of Veterinary and Animal Science, University of Copenhagen, Frederiksberg C, Denmark 5 International Livestock Research Institute, Ouagadougou, Burkina Faso ✉ Corresponding author. Received 2026 Jan 12; Accepted 2026 Feb 24; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . PMC Copyright notice PMCID: PMC13069701 PMID: 41781871 Abstract Background Village chicken production is central to rural livelihoods across sub-Saharan Africa. However, the poor biosecurity and hygiene observed in the chicken flocks, coupled with the limited access of farmers to veterinary services, provide favorable conditions for the persistence and transmission of zoonotic pathogens such as Salmonella spp. This study aimed to estimate the prevalence of Salmonella in village chicken flocks; quantify fecal bacterial loads; and identify household – and flock-level risk factors associated with Salmonella spp. infection in the Boussouma commune in rural Burkina Faso. Methods A cross-sectional study was conducted in 73 poultry-keeping households. Cecal contents were collected from 292 indigenous chickens following humane euthanasia. Laboratory analysis was carried out using the ISO 6579:2012 standard methods. Quantification of Salmonella spp. In fecal matters, it was done using the Most Probable Number (MPN) method. Structured household interviews captured data on poultry management, hygiene practices, flock characteristics, and household demographics. Multivariate logistic and linear regression models were used to assess associations between household- and flock-level practices with Salmonella spp. presence and bacterial load. Results The animal-level prevalence of Salmonella spp. in chicken faeces was 57.2% (95% CI: 51.5–62.9). Salmonella spp. loads in faeces ranged from 0.03 to 10.99 MPN/g (mean = 0.63 MPN/g). In multivariate logistic regression, lack of access to veterinary care (OR = 3.77; p = 0.001), on-site accumulation of poultry manure (OR = 5.61; p = 0.011), and burial of dead chickens within the household compound (OR = 1.92; p = 0.024) were associated with increased odds of infection. Protective factors included improved access to water (OR = 0.46; p = 0.020) and removal of manure from the household environment (OR = 0.44; p = 0.013). Chickens from male-headed households had lower odds of infection (OR = 0.22; p = 0.029). Higher Salmonella spp. loads were associated with poor hygiene, limited water access, and lack of veterinary care. Conclusion The findings highlight critical, context-specific points of intervention for reducing zoonotic transmission risks at the animal-household interface. Targeted community-level hygiene promotion, improved water access, safer carcass and manure management, and strengthening of village-level veterinary services are essential to mitigate public health risks linked to village poultry production. Supplementary Information The online version contains supplementary material available at 10.1186/s12866-026-04895-y. Keywords: Biosecurity, One Health, Salmonella spp., Village chicken, Zoonotic transmission Introduction Poultry production is a key source of livelihood, income, and food security for millions of households across Sub-Saharan Africa, including Burkina Faso, where more than 1.6 million small-scale producers are involved in the sector [ 1 , 2 ]. However, when poultry are raised under poor husbandry and hygiene conditions, flocks are highly exposed to several pathogens, including zoonotic pathogens such as Salmonella spp. Therefore, poultry production systems in low-resource settings face major public health challenges linked to the circulation of foodborne and environmentally transmitted pathogens [ 3 ]. Recent studies continue to highlight the persistence of Salmonella spp. in smallholder poultry systems and the difficulty of controlling transmission under extensive production conditions [ 4 , 5 ]. Globally, Salmonella spp. infections remain among the leading causes of foodborne disease, responsible for hundreds of millions of diarrheal cases annually [ 3 , 6 ]. In high-income settings, human salmonellosis is commonly associated with the consumption of contaminated raw or undercooked poultry meat or eggs [ 7 ]. In contrast, in low-resource rural settings, transmission pathways are often broader and include poor household hygiene conditions, lack of biosecurity, and unsafe manure management, and close and continuous contact between humans and poultry [ 8 , 9 ]. In such settings, environmental contamination of the household compound, water sources, food preparation areas, and children’s play areas by poultry faeces represents a critical and often underestimated route of exposure to Salmonella spp. The commune of Boussouma is a rural area with a high number of internally displaced persons resulting from ongoing insecurity, where village poultry production plays a crucial role in household income diversification, food security, and livelihood resilience [ 10 ]. Poultry production systems in this area are predominantly extensive, characterized by free-ranging birds, minimal housing, limited veterinary supervision, and low adoption of biosecurity measures, conditions that favor the maintenance and spread of zoonotic pathogens such as Salmonella spp. Similar structural and management-related vulnerabilities have been reported in recent studies of village poultry systems, highlighting consistent risk patterns across different rural contexts [ 4 , 5 ]. Unlike in high-income countries, poultry products are not consumed daily: chickens are primarily kept for sale, ceremonies, or breeding, while eggs are mainly used for hatching [ 9 , 10 ]. Consequently, human exposure to Salmonella spp. in rural households is more likely to occur through environmental contamination of water, food, and household surfaces with poultry excreta than through the direct consumption of contaminated meat or eggs [ 11 , 12 ]. Despite the public health relevance of village poultry, data on the burden of Salmonella spp. infection and the associated management-related risk factors in rural poultry systems in Burkina Faso remain limited. Moreover, few studies have quantified fecal Salmonella spp. loads in village chickens, despite their importance for understanding environmental contamination pressure and transmission potential. Addressing these gaps is particularly relevant in light of recent calls for context-specific epidemiological data to inform locally adapted control strategies in smallholder poultry systems [ 13 ]. This study, conducted in the municipality of Boussouma, sought to (1) determine the prevalence of Salmonella spp. in village chickens, (2) determine bacterial loads, and (3) identify household- and flock-level risk factors associated with Salmonella spp. infection. Materials and methods Study area The study was conducted in the rural commune of Boussouma, located in the province of Sandbondtenga in the Kuilsé region (formerly the North-Central region) of Burkina Faso. The commune covers approximately 770 km² and includes 63 administrative villages. According to the Municipal Development Plan (PCD, 2020), the population was estimated at 131,133 inhabitants in 2024, distributed across 19,536 households, of whom 60,605 were men (46.2%) and 70,527 were women (53.8%) [ 14 ] (Fig. 1 ). Fig. 1. Open in a new tab Map of the study area Sampling plan and household selection This cross-sectional study was conducted within the framework of the Poultry Losses and One Health (POLOH) project. Due to the unstable security context in the area, purposive sampling was used with the support of local authorities to select accessible and secure villages. Of the 62 villages in the commune, 23 were included based on these criteria. A preliminary census identified 483 households engaged in traditional poultry farming within the selected villages. From this list, 73 households were randomly selected for microbiological sampling using a computer-generated randomization procedure implemented in Microsoft Excel. Additional households were randomly selected as replacements in each village in case of non-participation or exclusion. The inclusion criteria required households to practice traditional chicken farming and not administer antibiotics to their birds during the two weeks preceding sampling. Sample size calculation Risk factor analysis A three-stage procedure was used to compute the sample size in the study. The sample size calculation considered exposure prevalence, household clustering, and statistical power. The standard formula for comparing two proportions was used to calculate the initial sample size: Where n is the required sample size per group. = is the normal deviate that provides 95% confidence interval (the value of Z is 1.96), = standard normal deviate corresponding to the desired statistical power (0.84 for 80% power) ; = expected prevalence in the exposed group ; = expected prevalence in the unexposed group. Based on the estimated Salmonella prevalence of 60% in exposed households and 40% in unexposed households, the required sample size was 95 chickens per group. Adjustment for clustering A Design Effect (DE ) was applied to correct for the lack of independence between chickens in the same household (since 4 chickens were sampled concurrently using the formula : (Number of chickens sample per household (m = 4) ; Intra Correlation Coefficient = 0.06). Accounting for exposure In order to guarantee that the “exposed” group (those with improper waste disposal) had the required no of chickens, the total sample was inflated, given that only 40% of households were expected to demonstrate the exposure. This raised the estimate to 290 chickens from 73 households. Animal-level prevalence The required sample size was calculated assuming an expected Salmonella spp. prevalence of 53% based on previous studies [ 11 ], a desired precision of 7%, and a 95% confidence level, yielding a minimum of 196 samples without clustering. Considering cluster sampling at the household level (for birds per household) and intra-class correlation (ICC) = 0.06 [ 15 ], the adjusted sample size increased to 232 samples (58 households). To satisfy the requirements for both prevalence estimation and risk factor analysis, the largest calculated sample size was retained. Consequently, a total of 292 chickens (four per household) from 73 households were included in the study. Selection and collection of poultry samples In each household, four adult indigenous chickens aged 3–12 months were selected, yielding a total of 292 samples. All sampled birds were privately owned and raised under traditional free-range production systems in the rural commune of Boussouma. Data collection was conducted in two stages. In the first stage, a structured household-level questionnaire was administered to collect information on poultry management practices, hygiene conditions, biosecurity measures, and household demographics. The questionnaire was developed based on a review of the literature and field experience in traditional village poultry systems [ 16 , 17 ]. It was pre-tested in five households to ensure clarity and reliability, translated into the local languages (Mooré), and administered by the same trained investigators to ensure consistency. A second visit was conducted within 3–5 days after the initial survey to ensure consistency and minimize recall bias. During this visit, individual chicken-level information including age, treatment history, and vaccination status was recorded prior to biological sample collection. In this study, a caregiver was defined as any household member, other than the household head, who was regularly involved in poultry-related activities such as feeding, cleaning, watering, or monitoring the birds. An English version of the questionnaire is provided as Supplementary Material (Additional file 1). Birds were identified using observable physical characteristics (e.g., feather color, size, and comb type), and random selection was performed using a simple randomization procedure. In households with more than 50 chickens, birds were first grouped by age or housing area prior to random selection to ensure representation across flock subgroups. Chickens were humanely euthanized on site by cervical dislocation, performed by trained personnel in accordance with the American Veterinary Medical Association (AVMA) Guidelines for the Euthanasia of Animals [ 18 ]. Cecal intestinal contents were aseptically collected using sterile gloves, placed in labeled sterile bags, and stored in coolers at 4 °C until further processing. Transport and storage conditions Samples were transported within four hours in temperature-controlled cooler boxes to the Laboratory of Molecular Biology, Epidemiology, and Surveillance of Foodborne Bacteria and Viruses (LaBESTA) at Joseph Ki-Zerbo University. Laboratory processing began immediately upon arrival. Microbiological analyses Detection of Salmonella spp. Salmonella spp. detection followed the ISO 6579:2012 standard. One gram of cecal content was pre-enriched in 9 mL of sterile Buffered Peptone Water (BPW) at 37 °C for 24 h. For selective enrichment, 100 µL of BPW culture was transferred into 9.9 mL of Rappaport–Vassiliadis (RV) broth and incubated at 42 °C for 24 h. Isolation was carried out by streaking 10 µL from each RV tube onto Salmonella spp. Chromogenic Agar plates at 37 °C for 24 h. Presumptive colonies (add what they would look like) were biochemically confirmed using Kligler-Hajna iron agar, Triple Sugar Iron, urease, and indole. Confirmed isolates were stored at − 80 °C in cryovials with 15% glycerol. MALDI-TOF MS confirmation All confirmed isolates were subjected to species-level identification using the Bruker Biotyper (Bruker Daltonik GmbH), which employs matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The direct spotting method was performed according to the manufacturer’s instructions. Quantification of Salmonella spp. For Salmonella quantification, one gram of cecal content was homogenized in 9 mL of buffered peptone water (BPW) by vortexing. Following homogenization, serial ten-fold dilutions (10⁻² and 10⁻³) were prepared in BPW. All BPW aliquots were subjected to pre-enrichment at 37 °C for 18 h. Subsequently, 0.1 mL from each pre-enrichment tube was transferred into 9.9 mL of Rappaport–Vassiliadis broth and incubated at 42 °C for 24 h. After selective enrichment, aliquots were streaked onto Salmonellla Chromogenic agar plates and incubated at 37 °C for 24 h. Presumptive Salmonella colonies were selected and confirmed using standard biochemical tests. The number of Salmonella-positive tubes at each dilution level was then used to estimate bacterial concentrations, expressed as Most Probable Number per gram of fecal sample (MPN/g) [ 19 ]. Data analysis Prevalence estimation The animal level prevalence was calculated as the proportion of positive samples among the total samples examined. Flock-level prevalence was defined as households. Exact 95% confidence intervals (CI) using the Clopper–Pearson method. Risk factor analysis Data were analyzed using Stata version 14 (StataCorp, College Station, TX, USA). Descriptive statistics were first used to summarize household- and animal-level variables. After univariate analysis, a logistic regression model was fitted to assess associations between potential risk factors and Salmonella spp. positivity (binary outcome: presence/absence). Potential risk factors were first screened for association with Salmonella spp. positivity using univariate logistic regression. Independent variables were retained for multivariable analysis when they satisfied a significance level of p ≤ 0.20. In addition, variables that did not meet this statistical threshold but were considered biologically plausible and contextually relevant based on field observations and previous studies [ 20 – 22 ] were also retained. A multivariable logistic regression model was then fitted to identify factors independently associated with Salmonella spp. presence. A stepwise selection procedure was applied to retain variables in the final model, with statistical significance set at p < 0.05. An OR > 1 indicated increased odds of Salmonella spp. detection, while an OR < 1 indicated a protective association. Multicollinearity among explanatory variables was assessed using the Variance Inflation Factor (VIF), and variables with VIF values greater than 5 were excluded from the final model. Assessment of factors that affect Salmonella spp. bacterial load in chicken faeces A linear regression analysis was conducted to examine factors affecting Salmonella spp. bacterial load. The model was developed to estimate the average effect of each predictor on bacterial concentration. Forest plots, created in RStudio (version 2025.05.1, Foundation for Statistical Computing, Vienna, Austria), to visualize regression coefficients and 95% pension intervals to facilitate interpretation of the direction and strength of the associations. The selected explanatory variables were derived from literature research, biological feasibility, and pertinent factors related to traditional poultry farming systems in rural Burkina Faso. Specifically, variables for sociodemographic conditions, husbandry and feeding practice, herd composition, and hygiene and biosecurity measures were included. These groups were selected as they account for the main domains by which Salmonella spp. can pass and persist at the household level while incorporating both animal-related and environmental exposure observed during the study. Results Household sociodemographic characteristics Table 1 displays the sociodemographic data of the 73 surveyed households. Most respondents were men (94.5%), reflecting the male-dominated structure of household headship in the study area. More than half were aged > 50 years (54.8%). The majority of respondents reported no formal education (78.1%). Most households were headed by married individuals, either monogamous (50.7%) or polygamous (42.5%). Marital status was included as a proxy indicator of household structure and organization, which may influence poultry management through differences in household size, division of labor, caregiving responsibilities, and hygiene practices. Approximately half of the households (50.7%) reported more than 20 years of experience in poultry keeping. Children aged < 5 years were present in 47.9% of households, and among these, 50.7% reporting having no additional caregiver responsible for management besides the primary household head. Table 1. Sociodemographic profile of households involved in backyard poultry farming in Boussouma ( n = 73) Variable Category N (households) % Gender Female 4 5.5 Male 69 94.5 Age of household head < 30 years 0 0.0 30–39 years 14 19.2 40–49 years 19 26.0 ≥ 50 years 40 54.8 Education level Educated 16 21.9 No formal education 57 78.1 Marital status Married (monogamous) 37 50.7 Married (polygamous) 31 42.5 Not married 1 1.4 Widow(er) 4 5.5 Children under 5 0–1 38 52.1 2–3 21 28.8 ≥4 14 19.2 Years of experience < 10 years 16 21.9 10–19 years 20 27.4 ≥ 20 years 37 50.7 Caregivers None 37 50.7 One 23 31.5 Two or more 13 17.8 Open in a new tab Livestock and farming systems Most households maintained small poultry flocks, with 50.7% keeping 10–29 chickens and 16.4% keeping fewer than 10 birds (Table 2 ). Mixed livestock keeping was common: 90.4% of households owned sheep, 57.5% owned goats, 41.1% owned cattle, and 42.5% kept at least one donkey. Guineafowl were present in 23.3% of households, whereas pigeons (4.1%) and ducks (in 1.4%) were rarely kept. Table 2. Distribution of livestock holdings at household level ( n = 73) Species Category N (households) % Poultry Very small (3–9) 12 16.4 Small (10–29) 37 50.7 Medium (30–69) 19 26.0 Large (70+) 5 6.9 Sheep None 7 9.6 Small (1–9) 45 61.6 Medium (10–19) 15 20.5 Large (20+) 6 8.2 Goats None 31 42.5 Small (1–9) 33 45.2 Medium (10–19) 7 9.6 Large (20+) 2 2.7 Cattle None 43 58.9 1–2 24 32.9 > 2 6 8.2 Donkeys None 42 57.5 1 donkey 21 28.8 > 1 donkey 10 13.7 Guinea fowl None 56 76.7 > 0 17 23.3 Pigeons None 70 95.9 > 0 3 4.1 Ducks None 72 98.6 > 0 1 1.4 Open in a new tab Characteristics of sampled chickens All 292 sampled birds were of local indigenous breeds (Table 3 ). More than half of the birds were aged > 5 months (51.4%), while 34.9% were between 4 and 4.9 months and 13.7% were 3-3.9 months old. The majority of sampled birds were male (72.3%), with females accounting for 27.7% of the sample. Table 3. Demographic characteristics of chickens sampled ( n = 292) Characteristic Category N = 292 % Age (months) 3–3.9 40 13.7 4–4.9 102 34.9 ≥ 5 150 51.4 Sex Male 211 72.3 Female 81 27.7 Open in a new tab Salmonell a spp. prevalence Animal-level prevalence Of the 292 chickens sampled, 167 were positive for Salmonella spp. yielding an animal- level prevalence of 57.2% (95% CI: 51.5–62.9), while 125 samples (42.8%) were negative. Flock-level prevalence At the household level, 63 of the 73 households had at least one Salmonella spp. positive chicken, corresponding to a flock-level prevalence of 91.8% (95% CI: 84.1–97.1). Only six households (8.2%) were classified as negative. Bacterial load distribution of Salmonella spp. Among the 292 chickens sampled, 125 (42.8%) were negative for Salmonella spp. Among the 167 positive chickens, most exhibited low bacterial loads. Specifically, 133 birds (45.5% of all chickens; 79.6% of positives) had low loads (0.0001 to 1 MPN/g), 23 birds (7.9% of all chickens; 13.8% of positives) had moderate loads (1.0001-5 MPN/g), and 11 birds (3.8% of all chickens; 6.6% of positives) had high loads (> 5 MPN/g). Risk factors associated with Salmonella spp. presence at the animal level Univariate logistic regression In the univariate logistic regression, several household management and hygiene practices were significantly associated with the presence of Salmonella spp. in chickens (Table 4 ). Poultry treatment was protective (OR = 0.26, 95% CI: 0.12–0.53, p < 0.001). In contrast, leaving carcasses on household premises increased the OR of infection (OR = 5.85; 95% CI: 1.70–20.08, p = 0.005). The presence of guinea fowl was also associated with higher odds of Salmonella spp. detection (OR = 1.78, 95% CI: 1.00–3.15, p = 0.048). Table 4. Results of univariate analyses of factors associated with Salmonella spp. presence in chicken Variable Reference category Comparison category OR 95% CI p -value Gender Female Male 0.43 [0.13–1.36] 0.149 Education level Educated No formal education 0.89 [0.51–1.57] 0.690 Number of children < 5 years 0 1 0.61 [0.29–1.27] 0.185 2 0.36 [0.16–0.80] 0.013* 3 1.00 [0.34–2.94] 1.000 4 0.35 [0.13–0.96] 0.042* Tertiary activity Agriculture Gold mining 0.14 [0.01–1.76] 0.129 Other livestock 1.33 [0.28–6.44] 0.720 Poultry treatment No Yes 0.26 [0.12–0.53] < 0.001** Vaccination (New Castle ) No Yes 0.94 [0.58–1.53] 0.815 Sheep herd size None Small (1–9) 1.62 [0.73–3.59] 0.240 Goat herd size None Small (1–9) 1.70 [1.03–2.80] 0.039* Cattle herd size None 1–2 1.48 [0.89–2.47] 0.133 Donkey ownership None 1 donkey 1.40 [0.80–2.35] 0.243 > 1 donkey 1.27 [0.63–2.56] 0.500 Presence of guinea fowls None ≥ 1 1.78 [1.00–3.15] 0.048* Night confinement of poultry No Yes 1.30 [0.79–2.14] 0.303 Carcass burial No Yes 1.30 [0.82–2.07] 0.272 Manure disposal No Yes 0.54 [0.33–0.89] 0.017* Faeces cleaning Never Occasional 0.20 [0.06–0.65] 0.008** Frequent 0.26 [0.09–0.78] 0.017* Abandonment of carcasses No Yes 5.85 [1.70–20.08] 0.005** Water supply No Yes 1.08 [0.68–1.73] 0.742 Number of caregivers None One 1.62 [0.94–2.79] 0.083 Two or more 0.57 [0.30–1.09] 0.089 Open in a new tab OR Odds Ratio, CI Confidence Interval Significance levels : * p < 0,05 ; ** p < 0,01 ; *** p < 0,001 Hygiene-related practices were consistently protective. Occasional faeces cleaning (OR = 0.20, 95% CI: 0.06–0.65, p = 0.008), frequent cleaning (OR = 0.26, 95% CI: 0.09–0.78, p = 0.017) and manure disposal (OR = 0.54, 95% CI: 0.33–0.89, p = 0.017) were all associated with reduced Salmonella spp. presence. Sociodemographic factors showed limited associations. Households with two or four children under five years of age had lower odds of infection, while the number of caregivers in the household showed only borderline associations. No significant associations were observed for sex of household head, education level, water source, or night-time confinement of poultry in univariate analysis. Multivariate logistic regression model In the final multivariate logistic regression model, lack of poultry treatment remained strongly associated with Salmonella spp. presence (OR = 3.77; 95% CI: 1.70–8.32; P = 0.001). Leaving poultry carcasses on household premises was also a major independent risk factor (OR = 5.61; 95% CI: 1.48–21.23; P = 0.011), as was ownership of more than one donkey(OR = 4.30; 95% CI: 1.63–11.35; P = 0.003). Protective factors included access to improved water sources (OR = 0.46; 95% CI: 0.24–0.88; P = 0.020) and manure disposal (OR = 0.44; 95% CI: 0.23–0.85; P = 0,013). Each additional child under five years of age was weakly associated with reduced odds of Salmonella spp. detection (OR = 0.89; 95% CI: 0.81–0.98; P = 0.017). Male-headed households are significantly less likely to be contaminated (OR = 0.22; 95% CI: 0.06–0.86; P = 0.029). Second, night-time confinement of poultry shows a marginal association with an increased risk, although this trend does not reach the conventional threshold for statistical significance ( p = 0.051). Table 5. Logistic regression model of risk factors associated with Salmonella spp. presence in households in Boussouma Variable OR Std. Error 95% CI P -value Poultry treatment 3.77 1.52 [1.70–8.32] 0.001** Tertiary activity 1.45 0.14 [1.21–1.75] 0.001** Carcass abandonment on-site 5.61 3.81 [1.48–21.23] 0.011* Manure disposal 0.44 0.15 [0.23–0.85] 0.013* Water source 0.46 0.15 [0.24–0.88] 0.020* Number of children < 5 years 0.89 0.04 [0.81–0.98] 0.017* Donkey herd (> 1) 4.30 2.13 [1.63–11.35] 0.003** Carcass burial 1.92 0.56 [1.09–3.39] 0.024* Sex (male) 0.22 0.15 [0.06–0.86] 0.029* Night-time poultry confinement 1.86 0.59 [1.00–3.46] 0.051 Constant 0.17 0.16 [0.03–1.06] 0.058 Open in a new tab OR Adjusted Odds Ratio, Std. Error Standard Error of the OR, CI Confidence Interval Significance levels : * p < 0,05 ; ** p < 0,01 ; *** p < 0,001 Factors associated with Salmonella spp. bacterial load: linear regression analysis A multiple linear regression is performed to identify factors associated with the quantity of Salmonella spp., expressed in MPN/g. The model was statistically significant (F (25,266) = 3.88; p < 0.001) and explains approximately 20% of the observed variation (adjusted R² = 0.198). Our results show that certain factors significantly influence Salmonella spp. load. Specifically, leaving poultry carcasses on site is associated with a mean increase of 0.53 log MPN/g, while burying carcasses is linked to a mean increase of 0.21 log MPN/g. In contrast, access to a borehole water supply reduces the load by approximately 0.26 log MPN/g, and manure disposal is associated with a mean reduction of 0.29 log MPN/g. The administration of treatments also shows efficacy, with an estimated reduction of 0.44 log MPN/g. Finally, the presence of three children under five years of age in the household is associated with an increase in the mean bacterial load of 0.41 log MPN/g (Fig. 2 ). Fig. 2. Open in a new tab Forest plot of linear regression coefficients for the quantitative load of Salmonella spp. (MPN/g). Points show estimated coefficients with 95% confidence intervals. The dashed line indicates the null effect (coefficient = 0). Positive values indicate increased load and negative values indicate decreased load. Red points indicate statistically significant associations (* p < 0.05; ** p < 0.01; *** p < 0.001) Discussion Animal and flock levels prevalence of Salmonella spp. At the animal level, Salmonella spp. was detected in 57.2% (95% CI: 51.5–62.9) of chicken fecal samples in Boussouma, revealing a widespread contamination among village poultry flocks. This prevalence is considerably higher than that reported in urban poultry settings in Ouagadougou [ 23 ], where Salmonella spp. were found in 9.9% of chicken droppings, and in the Mekong Delta (Vietnam) by Nguyen [ 24 ], where fecal samples showed a prevalence of 7.7%. However, it is close to the 40.8% observed in free-ranging chickens in Ethiopia [ 25 ]. These variations in production systems, hygiene practices, and environmental exposure, particularly the free-scavenging nature of village poultry farming in rural Burkina Faso, likely explain this high prevalence as similarly reported in other low-input poultry systems in sub-Saharan Africa [ 5 ]. Despite this widespread occurrence, most positive chickens carried only low bacterial loads. In fact, 45.6% of sampled birds harbored minimal amounts of the pathogen (0.0001–1 MPN/g), whereas moderate and high loads were observed in only 7.9% and 3.8% of birds, respectively. This distribution indicates that the majority of infected birds serve as asymptomatic or persistent carriers rather than suffering from acute clinical disease [ 5 ] which is increasingly recognized as a key driver of environmental persistence of Salmonella spp [ 4 ]. In traditional poultry systems such as those in Boussouma, repeated exposure to contaminated soil, manure, and household environments may encourage persistent low-level colonization and continuous environmental recycling of Salmonella spp. This silent circulation represents a significant qualitative risk, as it allows long-term contamination of household spaces without producing obvious signs of illness in the poultry [ 5 ]. At the flock level, Salmonella spp. was detected in 91.8% (95% CI: 84.1–97.1) of surveyed households, indicating that contamination is nearly ubiquitous in traditional poultry settings. The presence of multiple animal species and the lack of routine cleaning, disinfection, and litter management likely increase environmental persistence and cross-contamination between flocks. Under such conditions, even low bacterial loads at the individual animal level may cumulatively sustain widespread household contamination. These findings indicate that Salmonella spp. is deeply entrenched in household poultry systems in rural Burkina Faso, not primarily through severe disease in birds, but through widespread low-level carriage and persistent environmental cycling. Risk factors for Salmonella spp. infection in a chicken This study identified several significant risk factors for Salmonella spp. detection in rural poultry systems reflecting practical vulnerabilities in household-level management and hygiene practices at the animal–household interface. The absence of veterinary treatment was strongly associated with Salmonella spp. presence (OR = 3.77; 95% CI: [1.70–8.32]; p = 0.001). In Boussouma, limited access to veterinary services, poor road infrastructure, and financial constraints often lead farmers to rely on informal self-medication using antibiotics purchased from local markets. While such practices may reduce Salmonella spp. prevalence or bacterial loads in the short term, they also raise concerns regarding inappropriate antimicrobial use and the potential selection of antimicrobial-resistant strains. Similar patterns were reported in Kenya and Ethiopia [ 26 , 27 ], and the FAO notes that weak veterinary coverage in low-resource settings fosters pathogen persistence [ 28 ]. Carcass management was another key determinant. Households that abandoned dead birds on-site (OR = 5.61; 95% CI: [1.48–21.23]; p = 0.011) or buried them near living areas (OR = 1.92; 95% CI: [1.09–3.39]; p = 0.024) faced elevated risks. These practices likely enhance environmental contamination and facilitate indirect transmission, particularly in household courtyards where poultry, children, and other animals interact closely. Comparable findings were reported in Nigeria and Ethiopia [ 20 , 29 ]. On the other hand, households that properly disposed of poultry manure (OR = 0.44; 95% CI: [0.23–0.85]; p = 0.013) or used improved water sources (OR = 0.46; 95% CI: [0.24–0.88]; p = 0.020) showed significantly lower prevalence. These practices reduce fecal-oral transmission and limit the environmental survival of Salmonella spp., consistent with findings from other rural poultry systems [ 13 , 30 ]. Sociodemographic factors also influenced infection risk. Households with a higher number of children under five years of age were less likely to show Salmonella spp. presence (OR = 0.89; 95% CI: 0.81–0.98; p = 0.017). This finding may reflect greater vigilance and improved hygiene practices when young children are present. In contrast, when bacterial load was considered, households with three or more children under five exhibited higher Salmonella spp. concentrations, which suggests increased environmental contamination through frequent contact with poultry, soil, and faeces. This apparent discrepancy highlights the complexity of exposure pathways. Although heightened awareness may help reduce the risk of infection, persistent low-level exposures can perpetuate high bacterial burdens after contamination has occurred. Households headed by men (OR = 0.22; 95% CI: [0.06–0.86]; p = 0.029) were less affected. These results may reflect gendered disparities in access to sanitation and veterinary services [ 31 – 33 ]. Economic activity also played a role. Poultry, often perceived as a marginal activity, was the. third income source reported by households, and was termed “tertiary activity”. “Tertiary activity” in the study site was dominated by poultry farming (OR = 1.45; 95% CI: [1.21–1.75]; p = 0.001). Though considered minor, poultry provides a flexible source of cash and protein and is often managed with minimal supervision. This marginal status limits investment in hygiene and veterinary care, thereby increasing the risk of contamination [ 34 , 35 ]. Finally, mixed livestock rearing, particularly the presence of more than one donkey (OR = 4.30; 95% CI: [1.63–11.35]; p = 0.003), was associated with a higher risk. The lack of species segregation can facilitate cross-contamination via shared soil and water sources, as observed in Rwanda and Nigeria [ 20 , 36 ]. These findings underscore the importance of implementing targeted interventions, including expanding veterinary outreach, promoting hygiene education, and enhancing waste management, to mitigate the transmission of Salmonella spp. and safeguard public health in rural Burkina Faso. One Health-oriented Salmonella spp. surveillance and hygiene-focused interventions along the poultry value chain need to be integrated in the control of Salmonella spp. Factors that affect Salmonella spp. bacterial load in chicken faeces The linear regression model identified six significant factors influencing the bacterial load of Salmonella spp. in chicken faeces. These determinants reflect hygiene practices, access to basic services, and household dynamics, with direct implications for poultry production and public health. Similar observations have been reported in rural Burkina Faso, where poultry husbandry and household hygiene practices were associated with both poultry health and child nutrition outcomes [ 37 , 38 ]. Abandonment of poultry carcasses on-site (Coef. = 0.53; p = 0.004) was strongly associated with increased bacterial load. Leaving dead birds exposed facilitates environmental contamination and bacterial proliferation, especially in courtyards shared with children and other animals. Previous studies have demonstrated that Salmonella spp. concentrations in poultry litter can range from 0.45 to over 280,000 MPN/g, confirming that fecal contamination levels vary widely depending on management practices [ 39 ]. Similar risks were reported by Miller [ 40 ], who found that poor carcass disposal contributes to pathogen persistence in rural environments. Similarly, carcass burial (Coef. = 0.21; p = 0.037) also contributed to higher contamination levels. Although intended as a hygienic measure, shallow or poorly located burials may lead to recontamination of soil and water. Gumasta [ 41 ] highlighted that burial near living areas increases bacterial load, especially when carcasses are not properly covered or isolated. In contrast, access to improved water sources (Coef. = − 0.26; p = 0.044) and proper manure disposal (Coef. = − 0.29; p = 0.011) were associated with significantly lower bacterial loads. These practices reduce fecal-oral transmission and limit environmental persistence of Salmonella spp. , consistent with findings from previous studies [ 30 ] in Tanzanian poultry systems. Clean water reduces the risk of recontaminating feed and drinking points, while safe manure handling prevents pathogen spread to soil and nearby dwellings. Veterinary treatment (Coef. = − 0.44; p = 0.001) was another protective factor. Households that administered antibiotics had significantly lower bacterial loads, underscoring the importance of veterinary access. Asfaw [ 27 ] and the FAO [ 28 ] emphasize that veterinary oversight reduces pathogen circulation and improves poultry health outcomes. Finally, the presence of three children under five years old (Coef. = 0.41; p = 0.026) was linked to higher bacterial load. In such households, hygiene management may be more challenging due to competing childcare responsibilities. Close contact between children and domestic animals has been associated with increased exposure to enteric pathogens [ 33 , 42 ], which may indirectly contribute to environmental contamination. These findings highlight the need for targeted interventions by improving carcass and manure management, expanding access to clean water and veterinary services, and supporting hygiene education in households with young children. Reducing bacterial load in poultry faeces is essential not only for flock health but also for limiting zoonotic transmission in rural communities. Recommendations This study underscores the importance of practical, household-level measures to reduce Salmonella spp. contamination in village poultry systems in rural Burkina Faso. Simple, low-cost hygiene practices such as safe manure disposal, wet cleaning rather than dry sweeping, and basic biosecurity should be prioritized, even though poultry often represents a tertiary income source with limited labor and financial investment. While access to improved water sources was linked to lower Salmonella spp. prevalence, high costs, and limited availability remain significant barriers. In the meantime, promoting safer water handling and reducing reliance on contaminated surface water can provide realistic alternatives. Because poultry treatment practices were associated with Salmonella spp. detection, interventions must discourage unsupervised antibiotic use and strengthen veterinary support to limit both infection and antimicrobial resistance. Finally, households with young children should be a key focus for hygiene education, as they face greater exposure once contamination occurs. Together, these context-adapted, household-centered strategies are essential to mitigating zoonotic risks. Limitations of the study This study was conducted in a single rural commune, which may limit the generalizability of the findings to other settings. Sampling was performed at a single time point; therefore, potential seasonal variations in Salmonella spp. prevalence and bacterial load could not be assessed. Because chickens were sampled within households, the results may reflect clustering effects related to shared environments and management practices. Village selection was guided by accessibility and security considerations, which may have introduced selection bias by excluding more remote or less secure areas. The cross-sectional design limits causal inference, as observed associations between husbandry practices and Salmonella spp. detection cannot establish temporal relationships. In addition, although multivariable models were applied, residual confounding cannot be excluded, as certain factors, such as seasonality, climatic conditions, coinfections, vaccination against other poultry diseases, and pest presence, were not systematically measured. Finally, the semi-quantitative nature of the Most Probable Number (MPN) method and the absence of serotype-level identification of Salmonella isolates, as MALDI-TOF MS only enabled identification at the genus level, reduces the precision of bacterial load estimates and limits deeper epidemiological characterization of circulating strains. Conclusions This study provides essential baseline evidence on Salmonella spp. prevalence, bacterial load, and household-level risk factors in backyard poultry systems in Boussouma, Burkina Faso. Beyond documenting widespread contamination, the findings identify practical entry points for low-cost interventions that can reduce transmission at the animal–household interface. Measures such as improved manure management, safe disposal of dead birds, avoidance of dry sweeping, and simple hygiene practices are feasible even where poultry farming remains a secondary or tertiary livelihood activity. Community engagement emerges as equally critical. Involving household heads, women, and children can foster the sustained adoption of protective behaviors. Although further longitudinal research and expanded surveillance are needed to clarify seasonal dynamics and causal pathways, this work establishes a strong foundation for targeted veterinary support, hygiene education, and locally adapted prevention strategies. By generating context-specific evidence from an underserved rural setting, the study contributes to integrated approaches that safeguard animal health, reduce household exposure, and strengthen public health resilience. Supplementary Information Supplementary Material 1. (21.9KB, docx) Acknowledgements We are grateful to all who participated and assisted us in our research. Abbreviations CI Confidence Interval ICC Intra-class Correlation Coefficient MPN Most Probable Number OR Odds Ratio FAO Food and Agriculture Organization of the United Nations spp. Species (plural form) Coef. Regression Coefficient p -value Probability value Authors’ contributions All authors contributed to manuscript review, editing, final proofreading, and approval for submission. Conceptualization was by W.P.B.T., A.K., N.B., and M.D.; methodology, formal analysis, data curation, and original draft writing by W.P.B.T.; resources and supervision by B.O., .K. and M.D.; funding acquisition and project administration by M.D. and A.K. Funding This work was funded by the Bureau for Resilience and Food Security of the United States Agency for International Development (USAID) under agreement No. AID-OAA-L-15-00003 as part of the Feed the Future Innovation Lab for Livestock Systems and the Bill & Melinda Gates Foundation, OPP#1175487. Any opinions, findings, conclusions, or recommendations expressed here are those of the authors alone. Data availability The data supporting the findings of this research can be obtained from the corresponding author upon reasonable request. Declarations Ethics approval and consent to participate Human participants Ethical approval for the household survey component of the study was obtained from the ILRI Institutional Research Ethics Committee (IREC; Ref: ILRI-IREC2022-57) and the National Ethics Committee for Health Research of Burkina Faso (Ref: 2022-11-232). The study involving human participants was conducted in accordance with the principles of the Declaration of Helsinki. For household surveys, the project information sheet and consent form were read and explained to all participants in local languages, and written informed consent was obtained from all participants before data collection. Animal subjects Ethical approval for animal handling, sampling, and euthanasia procedures was obtained from the ILRI Institutional Animal Care and Use Committee (IACUC; Ref: ILRI-IACUC2022-38). All chickens included in the study were privately owned by household farmers. Authorization to access poultry and conduct sampling was obtained from household heads to data and sample collection. Participation in the study, including euthanasia of chickens for sampling, was entirely voluntary. Poultry owners were informed in advance about the sampling procedures and provided their explicit agreement. Appropriate compensation was provided to owners for each chicken sampled. Chickens were humanely euthanized by cervical dislocation, performed by trained personnel in accordance with internationally accepted animal welfare guidelines. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Footnotes Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. Ayssiwede SB et al. 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