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

is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.27.20044156 doi: medRxiv preprint regions (5, 6) . Bushmeat consumption and animal trading, arising from the growing demand of animal protein, causes significant changes at the human-animal reservoir interface (7). Among the BPDs, studies demonstrate that the SARS and EVD outbreaks were directly linked to the consumption of infected bushmeat (8, 9) . LF, MVD and EVD flourish in West and central Africa where the consumption of bushmeat is four times greater than the Amazon, which is richer in biodiversity (10) . Moreover, EIDs are also triggered by anthropogenic pressures on land use for agricultural expansion and livestock farming to meet the demand of a growing human population. The fruit-bat migration driven by the deforestation through forest fires in the islands of Sumatra lead to the emergence of Nipah disease in farmers and abattoir workers in Malaysia (11, 12) . Once sufficient infection cycles between human-animal without the sustainable transmission among humans termed as viral chatter is established, the emergence of human-tohuman transmission is inevitable (7). Mathematical modeling and prediction provides quick assessment for control and potential preventive efforts when time for epidemiological studies is scarce (13) . Modeling of infection dynamics analyses diseases outbreaks in animal population and estimates the rate of transmission as well as the potential chance of spillover. Yet, the increasing trends of EIDs risks surpass our capacity in the surveillance and detection of spillovers and outbreaks. Thus, the current public health response to EIDs is to "get ahead of the curve" and the growing resolution of satellite imagery has shifted the paradigm towards identifying potential environmental drivers such as deforestation, land fragmentation, biodiversity loss and climate change rather than the surveillance of the EIDs themselves.