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

ABSTRACT

Anthropization of natural habitats including climate change along with overpopulation and global travel have been contributing to emerging infectious diseases outbreaks. The recent COVID-19 outbreak in Wuhan, highlights such threats to human health, social stability and global trade and economy. We used species distribution modelling and environmental data from satellite imagery to model Blueprint Priority Diseases occurrences. We constructed classical regression and Support Vector Machine models based on environmental predictor variables such as landscape, tree cover loss, climatic covariates. Models were evaluated and a weighed mean was used to map the predictive risk of disease emergence. We mapped the predictive risk for filovirus, Nipah, Rift Valley Fever and coronavirus diseases. Elevation, tree cover loss and climatic covariates were found to significant factors influencing disease emergence. We also showed the relevance of disease biogeography and in the identification potential hotspots for Disease X in regions in Uganda and China. Article Summary LineIn our study with the use of a biogeographic approach, we were able to identify Wuhan as a potential hotspot of disease emergence in the absence of COVID-19 data and we confirm that distribution of disease emergence in humans is spatially dependent on environmental factors.