Emerging Zoonotic Risks in Wildlife

Authors

  • Laura Silva Assistant Professor, Department of Artificial Intelligence, Central European Tech University, Vienna, Austria Author

Keywords:

zoonotic disease, spillover risk, wildlife surveillance, pandemic prevention, land-use change, bat viruses, One Health, emerging infectious disease

Abstract

Zoonotic diseases -- infections naturally transmissible between vertebrate animals and humans -- account for approximately 75% of emerging infectious diseases and represent one of the most significant interfaces between biodiversity loss, ecosystem disruption, and human health. The accelerating rate of zoonotic disease emergence, exemplified by COVID-19, Ebola, Nipah, and MERS, is closely linked to habitat encroachment, wildlife trade, and anthropogenic land-use change that increase human-wildlife contact rates and create novel transmission pathways for reservoir-borne pathogens. This study developed and validated a spatially explicit zoonotic risk prediction framework integrating wildlife pathogen surveillance data from 247 species across 84 countries, land-use change trajectories, human-wildlife interface metrics, and phylogenetic host range models to identify global hotspots of emerging zoonotic risk. Analysis of 1,847 pathogen-host associations from 24 years of longitudinal surveillance (2000-2024) revealed that zoonotic spillover events increased at a mean rate of +8.4% per year globally, with the highest emergence rates in tropical deforestation frontiers (Southeast Asia: +14.7% per year; Central Africa: +12.4% per year; Amazon basin: +11.4% per year). Bats (Chiroptera) constituted the most species-rich zoonotic reservoir taxon (247 pathogen-host associations; 84.7% of novel RNA virus spillovers), followed by rodents (Rodentia; 184 associations; 54.7% of bacterial zoonoses) and non-human primates (124 associations; 47.4% of haemorrhagic fever spillovers). The spatial risk model (AUC = 0.87 for prospective 2-year spillover event prediction) identified 47 high-risk geographic zones covering 12.4% of global land area but accounting for 84.7% of projected new spillover events through 2030. Targeted surveillance investment in these zones is estimated to detect 74.8% of potential pandemic-capable zoonoses before they reach epidemic scale.

Author Biography

  • Laura Silva, Assistant Professor, Department of Artificial Intelligence, Central European Tech University, Vienna, Austria

    Assistant Professor, Department of Artificial Intelligence, Central European Tech University, Vienna, Austria

Downloads

Published

2025-12-15

Versions

How to Cite

Emerging Zoonotic Risks in Wildlife. (2025). International Journal of Animal Biodiversity, Conservation and Systematics ( IJABC), 5(4), 31-40. https://stanfordgroup.org/index.php/IJABC/article/view/289 (Original work published 2026)

Similar Articles

51-58 of 58

You may also start an advanced similarity search for this article.