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Climate change increases cross-species viral transmission risk.

Colin J CarlsonGregory F AlberyCory MerowChristopher H TrisosCasey M ZipfelEvan A EskewKevin J OlivalNoam RossShweta Bansal
Published in: Nature (2022)
At least 10,000 virus species have the ability to infect humans but, at present, the vast majority are circulating silently in wild mammals 1,2 . However, changes in climate and land use will lead to opportunities for viral sharing among previously geographically isolated species of wildlife 3,4 . 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.
Keyphrases
  • climate change
  • sars cov
  • genetic diversity
  • human health
  • social media
  • health information
  • small molecule
  • healthcare
  • gene expression
  • dna methylation
  • public health
  • high throughput
  • quantum dots
  • network analysis