Climate change increases cross-species viral transmission risk.

Colin J Carlson1,2 Gregory F Albery3,4 Cory Merow5 Christopher H Trisos6 Casey M Zipfel7 Evan A Eskew8,9 Kevin J Olival8 Noam Ross8 Shweta Bansal7
Affiliations 9 institutions
  1. Department of Biology, Georgetown University, Washington, DC, USA. [email protected].
  2. Center for Global Health Science & Security, Georgetown University, Washington, DC, USA. [email protected].
  3. Department of Biology, Georgetown University, Washington, DC, USA. [email protected].
  4. EcoHealth Alliance, New York, NY, USA. [email protected].
  5. Eversource Energy Center, University of Connecticut, Storrs, CT, USA.
  6. African Climate and Development Initiative, University of Cape Town, Cape Town, South Africa.
  7. Department of Biology, Georgetown University, Washington, DC, USA.
  8. EcoHealth Alliance, New York, NY, USA.
  9. Department of Biology, Pacific Lutheran University, Tacoma, WA, USA.

Abstract

At least 10,000 virus species have the ability to infect humans but, at present, the vast majority are circulating silently in wild mammals1,2. However, changes in climate and land use will lead to opportunities for viral sharing among previously geographically isolated species of wildlife3,4. In some cases, this will facilitate zoonotic spillover-a mechanistic link between global environmental change and disease emergence. Here we simulate potential hotspots of future viral sharing, using a phylogeographical model of the mammal-virus network, and projections of geographical range shifts for 3,139 mammal species under climate-change and land-use scenarios for the year 2070. We predict that species will aggregate in new combinations at high elevations, in biodiversity hotspots, and in areas of high human population density in Asia and Africa, causing the cross-species transmission of their associated viruses an estimated 4,000 times. Owing to their unique dispersal ability, bats account for the majority of novel viral sharing and are likely to share viruses along evolutionary pathways that will facilitate future emergence in humans. Notably, we find that this ecological transition may already be underway, and holding warming under 2 °C within the twenty-first century will not reduce future viral sharing. Our findings highlight an urgent need to pair viral surveillance and discovery efforts with biodiversity surveys tracking the range shifts of species, especially in tropical regions that contain the most zoonoses and are experiencing rapid warming.

Supporting text Virus Host Location
Climate Change 5 Mammals 92 Viral Zoonoses 65 Viruses 49 Animal Migration 21 Animals 1948 Biodiversity 10 Chiroptera 371 Environmental Monitoring 5 Humans 1440 Phylogeography 30 Risk Assessment 13 Tropical Climate 2

Evidence records

2 total
Zoonotic Surveillance
2 records · 1 evidence types
Evidence type
2 records
OVE5906
Key finding

Modeling projected that mammal species will aggregate in new geographic combinations, leading to an estimated 4,000 cross-species transmissions of their associated viruses under future climate and land-use scenarios.

Virus
Host
Location
Supporting text

We predict that species will aggregate in new combinations at high elevations, in biodiversity hotspots, and in areas of high human population density in Asia and Africa, causing the cross-species transmission of their associated viruses an estimated 4,000 times.

Method
phylogeographical modeling | range-shift projection
Geographic raw
Asia and Africa
OVE5907
Key finding

Climate and land-use changes are projected to create opportunities for viral sharing among wild mammals, facilitating zoonotic spillover to humans and linking environmental change to disease emergence.

Virus
Host
Location
Not specified
Supporting text

At least 10,000 virus species have the ability to infect humans but, at present, the vast majority are circulating silently in wild mammals. In some cases, this will facilitate zoonotic spillover-a mechanistic link between global environmental change and disease emergence.

Method
phylogeographical model | mammal-virus network simulation