A risk-based framework for live bird shops (LBSs) in Gujarat, India: Identifying pathogen entry and exposure risk profiles

Live bird shops (LBSs) and markets (LBMs) are frequent venues for chicken trading in Asia. Public-health research commonly explores LBMs across Southeast Asia, emphasizing their relevance in infectious disease epidemiology. However, LBSs' role in pathogen transmission remains understudied, particularly in India, where broiler and indigenous chickens (deshi) are common. This study, conducted in Gujarat, India, described LBSs practices and assessed their potential for pathogen entry and exposure to chickens and humans. Standardized questionnaires and field observations were collected at 86 LBSs across eight major tribal and non-tribal cities, from December 2020 to March 2021. A risk-assessment framework identified three pathogen risk-pathways: LBS pathogen entry, chicken exposure and human exposure. Multivariate analyses assessed LBSs' risk profiles for each risk-pathway, distinguishing between chicken types where applicable. The findings revealed three LBS clusters categorized as lower- or higher-risk for each risk-pathway and respective chicken type sold. LBSs' region was a strong determinant of cluster composition. Higher-risk LBSs were typically located in non-tribal cities and received chicken supplies from farther away and more suppliers compared to other LBSs. The relatively uniform distribution of clusters per city, noticeable in tribal regions, suggests an opportunity for targeted interventions to mitigate pathogen transmission. Higher-risk clusters for chicken exposure were linked to free-roaming rearing conditions for broiler LBSs and a high proportion of surplus for deshi LBSs. Human exposure risks were driven by inadequate individual-protective-equipment use, poor hygiene standards and failure to separate slaughtering from sales areas. Mixing of unsold poultry with newly supplied birds and keeping live birds overnight were observed across all clusters, potentially facilitating spread and persistence of poultry pathogens. This study identified LBS risk-clusters with distinct management and geographical characteristics, highlighting the need for tailored disease control strategies. The presented risk-based framework offers a valuable tool for targeted interventions in similar poultry trade settings.

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Publication Details

Journal
Preventive Veterinary Medicine
Published
2025-08-15
DOI
https://doi.org/10.1016/j.prevetmed.2025.106661
Citations
1
Primary Topic
COVID-19 Pandemic Impacts
Type
article
Field-Weighted Citation Impact
3.13

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article

A risk-based framework for live bird shops (LBSs) in Gujarat, India: Identifying pathogen entry and exposure risk profiles

Ketankumar Panchal, Dirk Udo Pfeiffer, Akash Golaviya, Prakash Koringa et al.
1 citations
Preventive Veterinary Medicine
COVID-19 Pandemic Impacts
3.13
article

A risk-based framework for live bird shops (LBSs) in Gujarat, India: Identifying pathogen entry and exposure risk profiles

Ketankumar Panchal, Dirk Udo Pfeiffer, Akash Golaviya, Prakash Koringa, Lorraine Chapot, Fiona M. Tomley, Anne Conan, Damer P. Blake, H.I. Paleja, Guillaume Fournié, S. Sequeira
article en
1 citations

Abstract

Live bird shops (LBSs) and markets (LBMs) are frequent venues for chicken trading in Asia. Public-health research commonly explores LBMs across Southeast Asia, emphasizing their relevance in infectious disease epidemiology. However, LBSs' role in pathogen transmission remains understudied, particularly in India, where broiler and indigenous chickens (deshi) are common. This study, conducted in Gujarat, India, described LBSs practices and assessed their potential for pathogen entry and exposure to chickens and humans. Standardized questionnaires and field observations were collected at 86 LBSs across eight major tribal and non-tribal cities, from December 2020 to March 2021. A risk-assessment framework identified three pathogen risk-pathways: LBS pathogen entry, chicken exposure and human exposure. Multivariate analyses assessed LBSs' risk profiles for each risk-pathway, distinguishing between chicken types where applicable. The findings revealed three LBS clusters categorized as lower- or higher-risk for each risk-pathway and respective chicken type sold. LBSs' region was a strong determinant of cluster composition. Higher-risk LBSs were typically located in non-tribal cities and received chicken supplies from farther away and more suppliers compared to other LBSs. The relatively uniform distribution of clusters per city, noticeable in tribal regions, suggests an opportunity for targeted interventions to mitigate pathogen transmission. Higher-risk clusters for chicken exposure were linked to free-roaming rearing conditions for broiler LBSs and a high proportion of surplus for deshi LBSs. Human exposure risks were driven by inadequate individual-protective-equipment use, poor hygiene standards and failure to separate slaughtering from sales areas. Mixing of unsold poultry with newly supplied birds and keeping live birds overnight were observed across all clusters, potentially facilitating spread and persistence of poultry pathogens. This study identified LBS risk-clusters with distinct management and geographical characteristics, highlighting the need for tailored disease control strategies. The presented risk-based framework offers a valuable tool for targeted interventions in similar poultry trade settings.

Preventive Veterinary MedicineVol. 244
Université Claude Bernard Lyon 1 (FR), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (FR), Royal Veterinary College (GB), University of Lisbon (PT), City University of Hong Kong (HK), Indian Veterinary Research Institute (IN), Université de Montpellier (FR), Kamdhenu University (IN), Charotar University of Science and Technology (IN), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Animal, Santé, Territoires, Risques et Ecosystèmes (FR), Hong Kong Jockey Club (HK), VetAgro Sup (FR)
Government of the United Kingdom, UK Research and Innovation
No poverty
Openalex Percentile: Top 7%
COVID-19 Pandemic Impacts
3.13
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