Description
Introduction: The increasing rate of zoonotic spillover events (the spread of pathogens from animals to humans) has been attributed to behavioural, ecological and socioeconomic change. Zoonotic spillover events sometimes involve diseases with epidemic or pandemic potential (e.g., COVID-19). A ‘deep prevention’ approach, focused on looking upstream at dynamics within animal populations and ecosystems, may reduce the risk of spillover events. Wildlife are a key source of pathogens involved in zoonotic spillover. Policy and governance that impacts wildlife may therefore impact emerging zoonoses. A One Health perspective may be useful in this context, emphasising collaboration across sectors and governance levels and coordinated policy action. In this study, we aimed to understand the global governance network focused on wildlife and emerging zoonoses, as well as identifying complex dynamics and system adaptation driving spillover events of wildlife origin in three case study countries: China, the Philippines and the Democratic Republic of the Congo (DRC).
Methodology: This study involved two analyses. First, we conducted a mixed methods network analysis of international organisations working on topics relating to wildlife and emerging zoonoses. Participants completed a survey to characterise their organisations’ interactions with other international organisations and key informant interviews focused on governance and collaboration. We used social network analysis to characterise this network quantitatively. The results of this led to the development of new research questions which were explored through thematic analysis of interview data. Second, we combined evidence from a rapid literature review with key informant interviews in each of the case study countries to develop causal loop diagrams (CLDs), a form of systems map used to represent causal theory about key system-level factors and the interconnections between them. We used these CLDs to identify key dynamics driving the increasing rate of spillover events, as well as examples of system adaptation to wildlife and ecosystem policies and the resulting unintended consequences for zoonotic spillover.
Results and discussion: A total of 69 organisations were identified as belonging to the global governance network. Organisations spanned the animal, human, and environmental health sectors, among others including trade, food and agriculture, and crime. Participants emphasised the highly inter-sectoral nature of this topic and the importance of inter-sectoral work, although barriers to effective collaboration were also cited. The CLD analysis identified the dynamic tension between economic growth and conservation as playing a key role in driving the increasing incidence of spillover events across case study countries, as well as identifying examples of wildlife and ecosystem policies that may fail to achieve their outcomes due to system adaptation, with ripple effects for zoonotic disease risk.
Conclusion: Wildlife is at the origin of many zoonotic disease outbreaks, and policy and governance focused on wildlife populations requires enhanced consideration from this perspective. Our analyses highlight the tension between global and national policy and governance, where collaboration across sectors and countries is required to combat the boundary-spanning threat of emerging zoonoses, but policy implementation requires careful attention to the specific contexts of local areas.
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