A global examination of ecological niche modeling to predict emerging infectious diseases: a systematic review - Lawrence, T.J.; Takenaka, B.P.; Garg, A.; Tao, D.; Deem, S.L.; Fèvre, Eric M.; Gluecks, Ilona V.; Sagan, V.; Shacham, E. (Frontiers Media, 2023)
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. We conducted a systematic review (PROSPERO: CRD42021251968) with the research question: What is the state of the science and practice of estimating ecological niches via ENM to predict the emergence and spread of vector-borne and/or zoonotic diseases?