Reframing pandemic preparedness: an intelligence-led solidarity model for multi-layered emergencies.

Authors

Alpha Umaru Bai-Sesay, Daniel Lavalie, Mohamed S Bah, Patrick Maada Bundu, Aloubi Walter Emaka, Chizaram Anselm Onyeaghala

Published in

Tropical diseases, travel medicine and vaccines. Volume 12. Issue 1. Jul 31, 2026. Epub Jul 31, 2026.

Abstract

The convergence of infectious disease outbreaks, climate shocks, and conflict is exposing fundamental limitations in existing global health preparedness systems, which remain largely fragmented and disease-specific. Epidemics increasingly occur within multi-layered emergencies, where overlapping risks interact to overwhelm fragile health systems and complicate response efforts. This perspective examines structural gaps in current preparedness approaches, including siloed financing, limited integration of multi-sectoral intelligence, and constrained institutional autonomy. Drawing on a structured policy analysis of publicly available literature and institutional experiences, particularly from the Africa Centres for Disease Control and Prevention (Africa CDC), the analysis highlights how integrated epidemic intelligence and regional coordination can support more anticipatory and context-responsive preparedness. Africa CDC's evolving architecture illustrates the potential of combining surveillance data across health, environmental, and mobility domains to inform earlier and more targeted interventions. Building on these insights, this perspective proposes an intelligence-led solidarity model that integrates equitable resource allocation, interoperable regional intelligence, and predictable financing as interdependent components of resilient preparedness systems. Such an approach repositions preparedness as a shared global public good, emphasizing alignment between data, resources, and governance structures. In the context of increasingly complex and concurrent crises, an intelligence-led solidarity framework offers a pathway to strengthen global health security by enabling more coordinated, adaptive, and forward-looking responses.

PMID:
42547882
Bibliographic data and abstract were imported from PubMed on 04 Aug 2026.

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