Co-creation of a multi-pathogen predictive dashboard to improve health system responsiveness to climate-sensitive diseases in rural Madagascar

Few empirical models of infectious diseases have been operationalized into decision-support tools on the ground. Even fewer have been evaluated for their ability to improve health system readiness.

Madagascar is particularly vulnerable to climate-sensitive infectious diseases due to low investment in its health system and the population's widespread poverty and high exposure to rising temperatures and extreme precipitation events. We will create an infectious disease forecasting tool to inform an adaptive health system strengthening intervention on how to respond to local disease burdens in a rural health district of Madagascar. This will include empirical models, a multi-pathogen predictive dashboard, and an associated R package that will be integrated into an existing health information system.

The dashboard will include predicted and historical indicators for three major climate-sensitive infectious diseases prioritized by local health actors: malaria, diarrheal disease, and acute respiratory infections. The complete set of tools will be co-created using methods based in participatory modelling to ensure their applicability, usability, and sustainability. In addition, we will measure the impact of integrating this tool on health outcomes and health system readiness.