Integrating systems thinking for analyzing and designing national early warning surveillance for animal health: a perspective from Tanzania

Animal health surveillance has demonstrated its value in global health security. The effectiveness of a surveillance system in reducing health threats and their impact depends on complex interactions between processes, enablers and context. However, most national animal health surveillance systems, including those in Tanzania, still face complex, interconnected challenges that undermine their efficiency. This paper is presented as a conceptual perspective that synthesizes insights from previously published studies on the use of integrative approaches for analyzing, designing, and evaluating animal health surveillance systems. The studies focused on evaluating the system, identifying data sources, mapping stakeholders for collaboration, and developing a prototype of an integrated animal health surveillance system. The paper offers a structured socio-technical framework drawing on experience from Tanzania, a resource-limited setting. It highlights the complex interplay between technical and social factors that shape the implementation of animal health surveillance. Strengthening surveillance systems required the adoption of technologies that facilitate integration and interoperability of multiple data sources for continuous improvement on system attributes, decision outcomes and ultimately health outcomes. It is also critical to consider social aspects, such as investment in human and financial resources, and foster collaboration between public and private stakeholders to improve data flow from various sources. Most importantly, there should be capacity building in using data for decision-making to enhance a timely response to health threats. This paper provides additional guidance to countries in assessing their current surveillance setups and developing more efficient early warning systems.