Extreme climatic events, environmental degradation and socio-economic inequalities exacerbate the risk of infectious disease epidemics. However, there are significant challenges in obtaining science-based evidence to understand and predict the impacts of extreme events and landscape changes on disease risk, leaving communities in climate change hotspots, vulnerable to increasing health threats. This is partly due to a lack of longitudinal and localised data, describing fine-scale environmental changes in remote and under-resourced areas, a lack of investment and capacity building in data science and software tools, and a lack of trained research software engineers and data scientists. The HARMONIZE project convenes a transdisciplinary community of practitioners, community-based organisations, local governments, software  engineers and data scientists to address these challenges. 

The main goal of the project is to develop cost-effective and reproducible digital tools for decision-makers in climate change hotspots in Latin America & the Caribbean, including cities, small islands, highlands, and the Amazon rainforest. HARMONIZE will collate existing multi-source climate, environmental, socio-economic and health data, and collect new longitudinal ground-truth data using drone technology and low-cost weather sensors, to calibrate and downscale coarser-resolution Earth Observation, climate reanalysis and forecast datasets in areas most relevant for disease transmission. The HARMONIZE digital toolkits will allow local researchers and users, including national disease control programs, to link, interrogate and use multi-scale spatiotemporal data, to understand the links between environmental change and infectious disease risk in their local context, and to build robust early warning and response systems in low-resource settings.

At the core of HARMONIZE is the digital infrastructure, which collects and post-processes different data streams to create harmonised datasets across different spatiotemporal scales and communities of practice. Existing datasets, including global Earth observations from satellite images and gridded climate reanalysis, and forecast data, will be combined with new data collected from drones and weather sensors during the project, to improve classification, bias-correction and downscaling of existing products. This will be merged with socio-economic, demographic and health system data (i.e., census, micro survey, and health service data) and disease surveillance data (e.g., case reports for dengue, chikungunya, Zika, malaria, leptospirosis, Chagas, etc.) collected via online platforms and provided by public health practitioners. From this core digital infrastructure, digital toolkits will be designed for key decision-makers operating across a range of hotspot, including cities, the Amazon rainforest, highland areas, and small islands. This new knowledge and technology will have lasting benefits for the wider community of practice and generate new evidence to design strategies to protect local communities from the adverse health impacts of a changing climate.