A Theoretical Framework for Community-Driven Livestock Disease Control in Fragile and Conflict-Affected States: Evidence from North East Nigeria

This dissertation develops an original theoretical framework for community-driven livestock disease control in fragile and conflict-affected states (FCAS), using North East Nigeria as the primary empirical context. Conventional livestock disease control frameworks assume functioning state institutions, accessible veterinary infrastructure, and stable community governance, none of which reliably exist in conflict-affected North East Nigeria, where protracted insecurity has destroyed formal veterinary systems across large areas of Borno, Yobe, and Adamawa States. The dissertation employs a mixed-methods theory-building design across four phases: systematic literature review of disease control in FCAS globally; longitudinal qualitative research involving 90 key informant interviews with pastoralist leaders, community-based animal health workers, NGO programme managers, and state veterinary officials over two years; quantitative survey of 400 livestock-keeping households assessing disease burden, service access, and community governance capacity; and co-design workshops with stakeholder communities producing the draft theoretical framework. The dissertation proposes the Community-Led Livestock Health Resilience Model (CLHRM) as an original theoretical contribution, specifying seven design principles for effective community-driven livestock health systems in FCAS contexts. The CLHRM identifies community trust networks, adaptive supply chain design, and conflict-sensitive extension communication as the three foundational pillars of resilient disease control in fragile contexts. Empirical validation demonstrates 38 percent higher vaccination coverage and 29 percent lower livestock mortality in communities implementing CLHRM-aligned programmes compared to standard approach communities. Keywords: community-driven disease control, fragile states, livestock health, North East Nigeria, CLHRM.