Spatial examination of social and environmental drivers of Middle East respiratory syndrome coronavirus (MERS-CoV) across Kenya.

Climate and agricultural land-use change has increased the likelihood of infectious disease emergence and transmissions, but these drivers are often examined separately as combined effects are ignored. Further, seldom are the influence of climate and agricultural land use on emerging infectious diseases examined in a spatially explicit way at regional scales. Our objective in this study was to spatially examine the climate, agriculture, and socio-demographic factors related to agro-pastoralism, and especially the combined effects of these variables that can influence the prevalence of Middle East respiratory syndrome coronavirus (MERS-CoV) in dromedary camels across northern Kenya.

A global examination of ecological niche modeling to predict emerging infectious diseases: a systematic review.

Introduction: As emerging infectious diseases (EIDs) increase, examining the underlying social and environmental conditions that drive EIDs is urgently needed. Ecological niche modeling (ENM) is increasingly employed to predict disease emergence based on the spatial distribution of biotic conditions and interactions, abiotic conditions, and the mobility or dispersal of vector-host species, as well as social factors that modify the host species' spatial distribution. Still, ENM applied to EIDs is relatively new with varying algorithms and data types.