Hidden Challenges in Evaluating Spillover Risk of Zoonotic Viruses using Machine Learning Models

Abstract excerpt

Machine learning models have been deployed to assess the zoonotic spillover risk of viruses by identifying their human infectivity potential. However, the scarcity of comprehensive datasets poses a major challenge, limiting the predictable range of viruses. Our study addressed this limitation through two key strategies: constructing expansive datasets across 26 viral families and developing new models leveraging l...

Topics

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• Animal Disease Management and Epidemiology
• Animal Virus Infections Studies
• COVID-19 epidemiological studies
• Plant Virus Research Studies
• Rabies epidemiology and control
• Viral gastroenteritis research and epidemiology
• Viral Infections and Vectors
• Zoonotic diseases and public health

Identifiers and source

Literature Corpus work

9339bf84-1b19-576f-bf84-8db8ae93d276

DOI

10.1101/2024.04.25.591033