Spillover risk estimate based on the combination of a high-risk pathogen pool and human population density

Golchin, Maryam, Hoskins, Andrew J., Di Marco, Moreno, Horwood, Paul F., Paini, Dean, and Hickson, Roslyn I. (2022) Spillover risk estimate based on the combination of a high-risk pathogen pool and human population density. In: [Presented at the Global Health Security Conference 2022]. From: Global Health Security Conference 2022, 28 June - 1 July 2022, Singapore.

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Abstract

Introduction: Infectious disease emergence from spillover events is of global concern and has the potential to cause significant harm to society. More than 70% of the +400 infectious diseases that emerged in the past five decades have a zoonotic origin, including all recent pandemics.

Context and Aim: Emerging infectious diseases can have devastating consequences to society, the economy, and human life at the global level. We are developing a simple estimate for use in early warning systems and comparing this to existing methods and risks of known drivers such as biodiversity and humans.

Method: We calculate a pathogen pool map by combining the spatial distributions of mammals and bird groups and the potential pathogens found within them, based on known historic human infections. We then estimate the risk of spillover by combining the generated pathogen map with the human population density map.

Findings: We developed the spatial distribution of potential zoonotic pathogens existing within natural systems across the globe. Then, we compare our pathogen pool map to know drivers, including biodiversity maps and key factors, such as human population density maps.

Innovative contribution to policy, practice and/or research: Our One Health approach could form the basis of an early warning system for decision-makers at all levels: from local land managers to international biosecurity.

Item ID: 76982
Item Type: Conference Item (Poster)
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Date Deposited: 13 Dec 2022 23:56
FoR Codes: 49 MATHEMATICAL SCIENCES > 4901 Applied mathematics > 490199 Applied mathematics not elsewhere classified @ 100%
SEO Codes: 20 HEALTH > 2004 Public health (excl. specific population health) > 200404 Disease distribution and transmission (incl. surveillance and response) @ 100%
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