---
title: "Cultural and behavioural drivers of zoonotic disease risk in Cameroon’s wild meat value chain"
id: "plos-one-13-cultural-and-behavioural-drivers-of-zoonotic-disease-risk-along-the-wild-meat"
canonical_url: "https://medichelpline.com/clinical-feed/plos-one-13-cultural-and-behavioural-drivers-of-zoonotic-disease-risk-along-the-wild-meat"
content_type: "clinical_feed_article"
specialty: "Infectious Disease"
source_name: "PLOS ONE (Medicine)"
source_url: "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355275"
published_at: "2026-08-05T14:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Cultural and behavioural drivers of zoonotic disease risk in Cameroon’s wild meat value chain
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/plos-one-13-cultural-and-behavioural-drivers-of-zoonotic-disease-risk-along-the-wild-meat
- **Specialty:** [Infectious Disease](https://medichelpline.com/clinical-feed/infectious-disease.md)
- **Primary Source:** PLOS ONE (Medicine)
- **Source URL:** [Original Journal Publication](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355275)
- **Published At:** 2026-08-05T14:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- The study conducted 2,374 structured interviews across 44 rural villages in Cameroon and surveyed 64 wild meat vendors in four regional markets to examine behaviours and perceptions linked to **zoonotic disease** risk along the **wild meat** value chain. - Hunting participation differed by ethnicity: a higher proportion of Indigenous **Baka** reported hunting than Bantu respondents, and Baka hunters more often targeted **bats**, a high-risk taxonomic group. - Gender, age, and ethnicity influenced contact patterns: women and older people were generally less likely to hunt or handle visibly abnormal animals; however, **Baka women** frequently hunted (notably by setting snares) while **Bantu women** rarely hunted. - Women across groups were more likely than men to take home carcasses found dead and to hunt small mammals (e.g., rodents), altering exposure pathways to wildlife pathogens. - Hygiene during handling and processing was very low: under 1% of household respondents reported any use of protective equipment and only 6% reported cleaning butchering surfaces with soap. - Consumption or sale of meat from animals with visible disease signs (abnormal organs, discolouration, unusual odours) was commonly admitted; injuries during butchering were also frequently reported. - Only 14.7% of households expressed concern about disease; this concern was associated with modest behavioural changes—about a 5 percentage point increase in **handwashing** and a 16 percentage point increase in avoiding contact with dead animals. - Ethnic and gender differences shaped both perceptions and behaviours, indicating that interventions must be culturally tailored and sensitive to livelihood and food-security needs. - The authors emphasise designing public health strategies that reduce zoonotic risk while safeguarding livelihoods, respecting cultural roles of wild meat, and avoiding indiscriminate bans that could harm food sovereignty. - Data from the study are available on Dataverse; the research was supported by GIZ and the authors reported no competing interests.
## Clinical Analysis & Structured Key Points
Cultural and behavioural drivers of zoonotic disease risk along the wild meat value chain in rural Cameroon | PLOS One Browse Subject Areas ? Click through the PLOS taxonomy to find articles in your field. For more information about PLOS Subject Areas, click here . Article Authors Metrics Comments Media Coverage Peer Review Reader Comments Figures Figures Abstract Wild meat remains a critical source of food security and income in tropical regions, yet it poses significant public health risks due to the potential for zoonotic disease transmission. To better understand these risks, we conducted 2,374 structured interviews with hunters and food preparers across 44 rural villages in Cameroon and surveyed 64 wild meat vendors in four regional markets. This study explores prevailing wild meat handling practices and perceptions of disease risk, providing essential insights for designing targeted interventions to safeguard human health and livelihoods. Hunting patterns varied by ethnicity: a higher percentage of Indigenous Baka reported hunting than Bantu, and Baka hunters were more likely to target bats, a high-risk taxonomic group. Gender, age, and ethnicity also shape behaviours. Women and older individuals were generally less likely to hunt or handle animals exhibiting clinical abnormalities. However, notable differences were observed between ethnic groups. Among the Indigenous Baka, women frequently participated in hunting, particularly by setting snares, whereas Bantu women seldom did so. Across both groups, women were more likely than men to take home carcasses found dead and to hunt small mammals such as rodents. These distinctions highlight how gendered and cultural norms influence patterns of wildlife contact and exposure to zoonotic risk. Hygiene standards during the handling and processing of wild meat were generally very low. Fewer than 1% of household respondents reported using any protective equipment, and only 6% cleaned butchering surfaces with soap. A substantial number admitted to consuming or selling meat from animals that appeared visibly diseased, exhibiting signs such as abnormal organs, discolouration, or unusual odours. Injuries sustained during butchering were also commonly reported, further compounding health risks. Concern about disease was relatively low, reported by only 14.7% of households. However, it was associated with a modest increase in the likelihood of handwashing (by 5 percentage points) and a more substantial increase in the possibility of avoiding contact with dead animals (by 16 percentage points). Ethnic and gender differences influenced both concerns about disease risk and behaviours. These findings highlight the importance of designing public health strategies grounded in local sociocultural realities, aimed at reducing zoonotic risk while safeguarding livelihoods and respecting the economic and cultural roles that wild meat plays within communities. Citation: Fa JE, Tata C, Coad L, Friant S, Kamogne Tagne CT, Mbane J, et al. (2026) Cultural and behavioural drivers of zoonotic disease risk along the wild meat value chain in rural Cameroon. PLoS One 21(8): e0355275. https://doi.org/10.1371/journal.pone.0355275 Editor: Pierre Roques, CEA, FRANCE Received: July 14, 2025; Accepted: July 10, 2026; Published: August 5, 2026 Copyright: © 2026 Fa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: The data underlying the results presented in the study are available from Dataverse: https://data.cifor.org/dataset.xhtml?persistentId=doi:10.17528/CIFOR/DATA.00328 . Funding: German Agency for International Cooperation GmbH, Deutsche fur Internationale Zusammenarbeit (GIZ), Agreement number: 81279235; Project processing number:20.2256.4-002.00. The funders had no role in the study design, data collection and analysis, the decision to publish, or the preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. Introduction Wild meat plays a vital role in the livelihoods, food security, and cultural practices of many rural communities across tropical and subtropical regions worldwide [ 1 – 3 ]. In Central Africa, wild animals provide an important source of protein and income, particularly in remote forest regions where alternative livelihood opportunities and domestic livestock production are limited. At the same time, the harvesting, handling, and consumption of wild animals create opportunities for zoonotic pathogen transmission from wildlife to humans [ 4 ]. Research on zoonotic disease risks in wildlife systems has often focused on ecological drivers such as biodiversity loss and land-use change. However, cultural practices, livelihood strategies, and behavioural norms strongly influence how people interact with wildlife and therefore shape patterns of pathogen exposure. Understanding these social and behavioural dimensions is essential for designing disease prevention strategies that are both culturally appropriate and locally feasible. Several zoonotic diseases of wildlife origin have been documented in Cameroon, underscoring the country’s vulnerability to pathogen emergence. Fruit bats are natural reservoirs for filoviruses such as Ebola and Marburg [ 5 , 6 ], while non-human primates carry simian retroviruses closely related to HIV and other pathogens capable of cross-species transmission [ 7 , 8 ]. Small mammals, including rodents and civets, are also implicated in bacterial infections such as leptospirosis, salmonellosis, and plague [ 9 – 11 ]. Human exposure to these pathogens frequently occurs during hunting, butchering, transport, and food preparation, when contact with animal blood, bodily fluids, or contaminated surfaces provides opportunities for transmission. These repeated and close interactions along wild meat value chains make rural Cameroon an important setting for investigating zoonotic disease dynamics and the human behaviours that shape them. Zoonotic spillover events have repeatedly demonstrated their capacity to escalate into major global health and economic crises. The 2003 SARS outbreak, the West and Central African Ebola epidemics, and the COVID-19 pandemic illustrate how emerging pathogens can spread rapidly across continents, causing widespread mortality and severe economic disruption [ 12 – 15 ]. In response, some policymakers have proposed banning or severely restricting wildlife trade to prevent future pandemics [ 16 – 18 ]. However, conservationists, social scientists, and public health experts have warned that indiscriminate bans could exacerbate poverty, undermine food sovereignty, and alienate communities whose cooperation is essential for disease prevention [ 19 – 23 ]. A more balanced approach requires a deeper understanding of the social, cultural, and behavioural dimensions of zoonotic risk. Disease transmission is not only a biological process but also a social one, shaped by people’s perceptions, beliefs, and everyday practices. Studies across Africa show that many individuals are unaware of the zoonotic potential of wild meat or perceive little risk in its consumption [ 24 – 26 ]. In Nigeria and Ghana, wild animals are sometimes viewed as “purer” than domestic livestock and therefore safer to eat [ 27 , 28 ], while in the Democratic Republic of the Congo vendors and consumers often distinguish between “clean” and “unclean” animals according to cultural norms rather than biomedical criteria [ 29 ]. In Cameroon, symptoms such as diarrhoea, fever, or stomach pain are frequently normalised or attributed to spiritual or environmental causes rather than foodborne infection [ 30 ]. These interpretations influence how people evaluate health threats and whether they adopt preventive practices. When wild meat is essential for nutrition or income, individuals may rationally downplay potential disease risks in favour of immediate livelihood needs. Understanding how local actors perceive and respond to zoonotic risk is therefore critical for designing effective and context-sensitive disease prevention strategies. Despite growing recognition of the importance of behavioural drivers of spillover risk, relatively few studies have examined how everyday practices along wild meat value chains influence the transmission of potential pathogens in Central Africa. In this study, conducted in rural Cameroon, we investigate how individuals involved in the wild meat value chain—including hunters, vendors, and food preparers—perceive disease transmission risks and how these perceptions influence behaviours related to wildlife handling and consumption. We also examine how risk perceptions and practices vary across gender, ethnicity (Bantu and Indigenous Baka), and age groups. By analysing these cultural and behavioural dimensions, this study aims to provide evidence to inform risk communication strategies and community-based interventions designed to reduce zoonotic disease risks, while recognising the socio-economic importance of wild meat systems. Methods Study area Our research was conducted in two locations—Study Area 1 (SA1) and Study Area 2 (SA2)—SA1 is situated within the South Region of Cameroon, while SA2 is in the East Region ( Fig 1 ). Download: PNG larger image TIFF original image Fig 1. Study area. The sites of the first study area, SA1, are villages around the towns of Mintom (South Dja), Bengbis (West Dja) and Lomié (East Dja). The second study area, SA2, comprises villages between Boumba Bek National Park and Yokadouma. The regional markets Lomié, Djoum, Sangmelima, and Yokadouma were also surveyed. The small, bottom map shows the spatial context of Cameroon and the study area, which is shown in detail in the top map (RC: Republic of Congo, DRC: Democratic Republic of Congo, EG: Equatorial Guinea). The figure was assembled from openly licensed vector datasets. Populated-place and protected-area information derived from OpenStreetMap data is available under the Open Database License (ODbL 1.0), with attribution to © OpenStreetMap contributors. Country and administrative boundaries were obtained from the World Bank Official Boundaries dataset, which is licensed under CC BY 4.0. The locations classified as market, SA1 and SA2 towns were generated from the authors’ study data. Full source and licence information for each external spatial dataset has now been included in the Fig 1 caption. https://doi.org/10.1371/journal.pone.0355275.g001 Study Area 1 (SA1) includes 33 villages around the Dja Biosphere Reserve (DBR), a UNESCO World Heritage Site established in 1950. Spanning approximately 5,260 km 2 , the DBR is one of Central Africa’s largest and best-preserved tropical rainforest reserves (UNESCO, 2021). It is bordered on three sides by the Dja River, which acts as a natural boundary and helps preserve the area’s ecological integrity. The region is home to a mixture of Baka Pygmies and various Bantu ethnic groups, including the Boulou, Fang, Zaman, Badjoué, and Nzimé, many of whom rely heavily on hunting for subsistence and income generation [ 31 ]. While subsistence hunting is permitted within the reserve’s buffer zones, commercial hunting and agricultural expansion are strictly prohibited [ 32 ]. Human population density in SA1 was estimated at 1.5 people per km 2 in 2001 [ 33 ] but has increased in recent years due to natural population growth and infrastructure development, such as dam construction and agroforestry plantations. SA1 was further divided into three sampling clusters to capture geographical and socio-cultural variation: South Dja (11 villages located south of the reserve near Mintom), West Dja (12 villages situated west of the reserve, close to Bengbis) and East Dja (11 villages found east of the reserve, near Lomié). Study Area 2 (SA2) comprises 10 villages near Boumba Bek National Park in Cameroon’s East Region. This area lies between the Boumba River and the town of Yokadouma. Officially designated in 2005, Boumba Bek National Park covers approximately 2,382 km 2 and is recognised for its high biodiversity, including significant populations of forest elephants and other threatened species [ 34 ]. The human population in SA2 consists primarily of Baka Pygmies and the Konabembe, a Bantu-speaking community. The Konabembe are traditionally agriculturalists, while the Baka—historically nomadic hunter-gatherers—have undergone a gradual socio-economic transition [ 35 ]. Many Baka now farm or work as agricultural labourers in Bantu households, often in exchange for food, goods, or limited monetary compensation. Both regions are ecologically diverse, dominated by dense tropical rainforests that form part of the Congo Basin, one of the world’s most extensive and biologically rich forest systems [ 36 , 37 ]. These forests provide critical habitat for a wide array of plant and animal species, some of which are globally threatened or endemic. SA1 and SA2 represent complementary ecological and socio-cultural contexts, allowing us to assess patterns across varied settings. This enhances the generalizability of our findings and reduces the risk of location-specific bias. Research design We carried out a structured quantitative study to examine wild meat practices and perceptions of disease risk. Data collection concentrated on three key groups: rural hunters, household food preparers, and wild meat vendors operating in the markets of Lomié, Djoum, Sangmelima, and Yokadouma ( Fig 1 ). Pre-study engagement Before data collection, we conducted a scoping visit to both study areas to initiate dialogue with key stakeholders and build trust within the communities. Consultations were held with administrative authorities at the regional, divisional, and sub-divisional levels, including Governors, Divisional Officers, and Sub-Divisional Officers, as well as with forestry and wildlife officials, conservation organisations, local councils, and village chiefs. These meetings introduced the study, clarified its objectives, and helped secure community support for the research. Research permits were obtained from the Ministry of Scientific Research and Innovation (MINRESI), and authorization to conduct research in protected areas was obtained from the Ministry of Forestry and Wildlife (MINFOF) prior to fieldwork. These permits ensured that all research activities complied with national regulations and ethical standards governing scientific research in Cameroon. Stakeholder feedback also informed the identification of villages with notable hunting activity in the vicinity of the Dja Biosphere Reserve and Boumba Bek National Park. In addition, our longstanding and intensive collaboration with Baka and Bantu hunters in the Djoum area has played a key role in fostering mutual trust and facilitating community engagement with local communities and local and national administrative authorities [ 20 , 36 , 37 – 39 ]. Village selection Villages were stratified into three demographic categories based on their ethnic composition: predominantly Bantu, mainly Baka, and mixed-population settlements. This stratification enabled the study to compare practices and perceptions across cultural groups and generate insights that are more broadly representative of the region. Eligible villages had at least 100 households. Within each village, households were randomly selected to participate in structured surveys. Data collection methods We collected data on hunting practices, wild meat handling behaviours, and perceptions of disease risk using structured questionnaires administered to selected households and wild meat vendors (see Supplementary Materials). Interviews with hunters also gathered information on the primary methods used to capture wildlife, including snaring, firearm hunting, opportunistic capture, and trapping techniques. Although hunting methods were not the focus of the present analysis, they were documented because they influence the nature and frequency of human–wildlife contact and therefore may affect hunters’ potential exposure to zoonotic pathogens. The study focused on key actors involved in the wild meat value chain. For the purposes of this study, hunters were defined as household members actively engaged in hunting activities, whether occasionally or professionally. Food preparers , typically women, were primarily responsible for preparing meals in the household and, therefore, frequently handled raw wild meat. Vendors were individuals selling wild meat in local markets, usually as part of informal or small-scale commercial networks. In addition, wildlife products are sometimes moved through intermediaries , defined as individuals who purchase wild meat from hunters in villages and transport or redistribute it to urban or peri-urban markets, thereby linking hunters to market vendors. Sample sizes Using population data from the 2005 census (BUCREP, 2005) and consultations with local authorities, we estimated an average of 1,100 households in SA1 (Lomie, Bengbis, and Mintom). In SA2, the population of the selected villages was estimated at 1,549 households according to the 2012 census. For sample size estimation, we applied the following formula [ 40 ]: (1) where: X = 1.96 (Z-value for 95% confidence) N = 1100 (population size) P = 0.5 (assumed distribution of variables of interest) d = 0.05 (margin of error) The minimum required sample size was 285 households per site in SA1 and 308 households per site in SA2. Data collection and analysis Participant selection and survey administration. We interviewed a total of 2,374 individuals, classified as either hunters or household food preparers. To complement these data, we also conducted structured interviews with all wild meat vendors operating in the four principal regional markets—Lomié, Djoum, Sangmelima, and Yokadouma—ensuring comprehensive representation of key actors along the wild meat value chain. In total, 64 vendors were surveyed. Data collection procedures. The household and vendor survey questionnaires ( S1 and S2 Tables ) were specifically developed for this study and administered between 14 October and 4 November 2022. Data were collected using KoboCollect ( www.kobotoolbox.org ), a mobile platform compatible with tablets and smartphones that enables real-time data entry and synchronisation. A team of five Cameroonian enumerators, fluent in French and the local languages relevant to each study site, conducted the interviews at each study site. Before data collection, enumerators received training from the project team and participated in a pretest phase that informed revisions to enhance the clarity and reliability of the questionnaires. Statistical analysis Following data collection, survey responses were exported from the Kobo Collect platform and transferred to Microsoft Excel for data cleaning and organisation. The processed dataset was then imported into Stata 17 [ 41 ] and R [ 42 ] for comprehensive statistical analysis, including descriptive (Table 2) and inferential methods. We began with descriptive analyses to explore key demographic and behavioural patterns across respondent groups. We then used regression models to examine how individual characteristics, such as sex and ethnicity, independently influenced the likelihood of hunting. Dummy variables representing each study site were included to control for location-specific effects not captured by other covariates. Hunting model. We used a logistic regression model to examine predictors of hunting behaviour. The dependent variable was whether the respondent engaged in hunting, and the explanatory variables included demographic characteristics (e.g., age group, sex, ethnicity) and site-specific fixed effects. This allowed us to assess which individual attributes were significantly associated with
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