In search for the hotspots of Disease X: A biogeographic approach to mapping the predictive risk of WHO s Blueprint Priority Diseases

Soushieta Jagadesh; Marine Combe; Mathieu Nacher; Rodolphe Ellie Gozlan

As with all mathematical models, our study has its limitations. The size of the environmental predictor raster layers limited our spatial extent of the models. We chose the quality of the satellite imagery and resolution over a global perspective with poor or outdated data. Our study does not have a temporal component in the form of times series, which would be interesting especially with the climatic covariates. We mitigated this by choosing recent raster data corresponding to the period of the study and linking the spatiotemporal presence and pseudoabsence points to corresponding climatic monthly covariates. Despite these limitations, our study is the first to confirm the validity and effectiveness of using SDMs and other mathematical models to predict and identify the potential hotspots for BPDs. The use of a biogeographic approach in disease modelling offers a wider perspective on the environmental drivers and highlights the importance of climate change in the context of disease emergence. Most of all, our . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.