Governance of the wildlife trade and the prevention of emerging zoonoses

A mixed methods network analysis of transnational organisations, silos, and power dynamics

Bibliographic Data

ID19534689
AuthorsChloe C Astbury (0000-0003-2955-7833, York University), Anastassia Demeshko (0000-0002-0671-3103, York University), Eduardo Gallo-Cajiao (0000-0002-8607-2675, University of Washington), Ryan McLeod (York University), Mary Wiktorowicz (0000-0001-7539-2043, York University), Cécile Aenishaenslin (0000-0002-8594-4945, Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal), Katherine Cullerton (0000-0001-9517-6380, The University of Queensland), Kirsten Lee (0000-0002-9166-5547, York University), Kirsten M Lee, Arne Ruckert (0000-0001-5689-0629, University of Ottawa), A M Viens (0000-0002-2379-4523, York University), Peter Tsasis (0000-0002-8611-7378, York University), Tarra L Penney (0000-0002-4889-9102, York University, corresponding author)
Year2024
Volume20
Issue1
Pages49-49
Publication date2024-06-20
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueGlobalization and Health (JOURNAL)
Journal identifiersISSN: 1744-8603 • E-ISSN: 1744-8603
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1186/s12992-024-01055-7
PMID38902738
OpenAlexW4399861637
LanguageEN
Citations received2
References cited42

INTRODUCTION: The wildlife trade is an important arena for intervention in the prevention of emerging zoonoses, and leading organisations have advocated for more collaborative, multi-sectoral approaches to governance in this area. The aim of this study is to characterise the structure and function of the network of transnational organisations that interact around the governance of wildlife trade for the prevention of emerging zoonoses, and to assess these network characteristics in terms of how they might support or undermine progress on these issues. METHODS: This study used a mixed methods social network analysis of transnational organisations. Data were collected between May 2021 and September 2022. Participants were representatives of transnational organisations involved in the governance of wildlife trade and the prevention of emerging zoonoses. An initial seed sample of participants was purposively recruited through professional networks, and snowball sampling was used to identify additional participants. Quantitative data were collected through an online network survey. Measures of centrality (degree, closeness, and betweenness) were calculated and the network's largest clique was identified and characterised. To understand the extent to which organisations were connected across sectors, homophily by sector was assessed using exponential random graph modelling. Qualitative data were collected through semi-structured interviews. The findings from the quantitative analysis informed the focus of the qualitative analysis. Qualitative data were explored using thematic analysis. RESULTS: Thirty-seven participants completed the network survey and 17 key informants participated in semi-structured interviews. A total of 69 organisations were identified as belonging to this network. Organisations spanned the animal, human, and environmental health sectors, among others including trade, food and agriculture, and crime. Organisation types included inter-governmental organisations, non-governmental organisations, treaty secretariats, research institutions, and network organisations. Participants emphasised the highly inter-sectoral nature of this topic and the importance of inter-sectoral work, and connections were present across existing sectors. However, there were many barriers to effective interaction, particularly conflicting goals and agendas. Power dynamics also shaped relationships between actors, with the human health sector seen as better resourced and more influential, despite having historically lower engagement than the environmental and animal health sectors around the wildlife trade and its role in emerging zoonoses. CONCLUSION: The network of transnational organisations focused on the governance of wildlife trade and the prevention of emerging zoonoses is highly multi-sectoral, but despite progress catalysed by the COVID-19 pandemic, barriers still exist for inter-sectoral interaction and coordination. A One Health approach to governance at this level, which has gained traction throughout the COVID-19 pandemic, was shared as a promising mechanism to support a balancing of roles and agendas in this space. However, this must involve agreement around equity, priorities, and clear goal setting to support effective action

Betweenness centrality · Business · Centrality · Corporate governance · Exponential random graph models · Focus group · Political science · Public relations · Qualitative property · Qualitative research · Random graph · Snowball sampling · Social capital · Social media · Social network analysis · Social science · Sociology · Thematic analysis · Brucella: diagnosis, epidemiology, treatment · Data-Driven Disease Surveillance · Medicine · Zoonotic diseases and public health · Marketing