The future of zoonotic risk prediction

Abstract

In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from known zoonoses to identify which animal pathogens could someday pose a threat to global health. We synthesize the findings of an interdisciplinary workshop on zoonotic risk technologies to answer the following questions. What are the prerequisites, in terms of open data, equity and interdisciplinary collaboration, to the development and application of those tools? What effect could the technology have on global health? Who would control that technology, who would have access to it and who would benefit from it? Would it improve pandemic prevention? Could it create new challenges? This article is part of the theme issue ‘Infectious disease macroecology: parasite diversity and dynamics across the globe’.

Present and future distribution of bat hosts of sarbecoviruses: implications for conservation and public health

“…Global climate change and human encroachment into natural habitats is simultaneously driving the biodiversity extinction crisis and increasing disease emergence risk [2]. Climate and land cover change will alter the range distribution of species [3], an important, poorly defined predictor of zoonotic (animal to human) disease risk [4,5], and the direction and magnitude of range shifts are not estimated for many species, leaving the impacts on their viral interactions uncertain [6,7].…”

Biosecurity in an age of open science

“…Code could be used directly or adapted to achieve nefarious goals [ 37 , 38 ]. Machine learning–guided engineering of antibiotic resistance genes exemplifies this: A model for engineering Escherichia coli β-lactamase has been described and shared openly [ 39 ].…”

Emergence of epidemic diseases: zoonoses and other origins

“…There are 17 stable roosts of mixed Pteropus species in Sydney, although individual bats migrate long distances and visit other roosts in the bush 54 , permitting exchange of potential pathogens. Thus, although it behooves us to scan the far horizon for pandemic preparedness using a panoply of modern approaches 66 , the next “exotic” epidemic might well arise in an orchard or the belfry of a church or temple.…”