The HARMONIZE toolkit comprises different R and Python libraries tailored for health, climate, environmental, and socioeconomic data acquisition, harmonisation, and visualization. Each data type is managed by a dedicated tool: data4health in the case of health data, clim4health for climate data, socio4health for socioeconomic data, land4health for land use and land cover data, and drone4health for processing drone images. The tools handle everything from data acquisition and formatting to pre- and post-processing, creating harmonised datasets at the desired spatiotemporal resolution. All processes are integrated into (semi-)automated workflows. This will enable local users to link, interrogate and extract multi-scale spatiotemporal data, to understand the links between environmental change and infectious disease risk in their local context, and build robust early warning and response systems in low-resource settings.