Global hotspots and correlates of emerging zoonotic diseases

TLDR

Zoonoses originating from wildlife pose a major threat to global health, security, and economic growth, yet the mechanisms driving their emergence remain poorly understood. The study updates a global database of emerging infectious disease events, introduces a novel reporting‑effort metric, and seeks to analyze their demographic, environmental, and biological correlates. Boosted regression tree models were employed to fit the data and assess the relationships between these correlates and disease emergence. We found that zoonotic EID risk is higher in forested tropical regions experiencing land‑use change and high mammal species richness, and produced a global hotspot map and partial dependence plots to aid surveillance and experimental design.

Abstract

Abstract Zoonoses originating from wildlife represent a significant threat to global health, security and economic growth, and combatting their emergence is a public health priority. However, our understanding of the mechanisms underlying their emergence remains rudimentary. Here we update a global database of emerging infectious disease (EID) events, create a novel measure of reporting effort, and fit boosted regression tree models to analyze the demographic, environmental and biological correlates of their occurrence. After accounting for reporting effort, we show that zoonotic EID risk is elevated in forested tropical regions experiencing land-use changes and where wildlife biodiversity (mammal species richness) is high. We present a new global hotspot map of spatial variation in our zoonotic EID risk index, and partial dependence plots illustrating relationships between events and predictors. Our results may help to improve surveillance and long-term EID monitoring programs, and design field experiments to test underlying mechanisms of zoonotic disease emergence.