Ground-truth data collection - We strategically undertake one-off longitudinal ground truth data collection using drone technology and low-cost weather sensors, to improve classification algorithms and downscaling of coarser-resolution environmental datasets (e.g., satellite images, climate reanalysis and forecasts). 

Climate data post-processing - We develop methodologies for bias-correction, downscaling and forecast quality assessment of seasonal climate predictions for input in health impact models. 

Policy-relevant tools - We harmonise the post-processed data with socio-economic and health data in an automated workflow packaged for users in bespoke hotspot-specific toolkits. These sustainable tools will facilitate generation of actionable knowledge to inform local risk mapping and build robust early warning and response systems to build resilience in low-resource settings.

User engagement and coproduction -  We organise co-production activities with stakeholders in each study site, involving interviews and workshops at different stages of the project to strengthen the community of practice, ensure the digital architecture design is transferable between countries and organisations and provide training and mentorship opportunities.

Extreme climatic events, environmental degradation and socio-economic inequalities exacerbate the risk of infectious disease epidemics. Over the last decades, the incidence in the Latin America & the Caribbean region of vector-borne diseases, such as dengue or chagas, has considerably increased, while new arboviruses have emerged, including chikungunya and Zika. We currently lack the evidence-base to understand and predict the impacts of extreme events, such as drought or floods, and landscape changes on disease risk, leaving communities in climate change hotspots vulnerable to increasing health threats. There is therefore an urgent need to invest in the development of digital infrastructure and tools to facilitate the information needed to support decision making by public health practitioners.