This is some pretty outstanding sleuthing. Very good science — and a keen insight on epidemiology patterns — particularly in the developing (but not yet post-industrial) world. Do go read it all. And then do think about what the CDC and/or the EPA might offer as potential mitigation strategies.
Here is the article in full, from ProPublica’s fine work:
…Around the same time Olivero’s team developed the deforestation model, a different group of researchers, led by Christina Faust at the University of Glasgow, Scotland, created an epidemiological model that calculates an area’s spillover risk by using information about its deforestation over time. This model, unlike the deforestation model, doesn’t only consider changes to forests in aggregate, but it also takes into account how the patterns of tree loss might impact risk.
It is an adaptation of a classic epidemiological model that tracks how populations of susceptible, infected and recovered individuals change over time as a virus spreads. Crucially, it incorporates information about the degree and type of deforestation that’s occurring in an area over time….
The researchers found that the highest risk of spillover occurs at intermediate levels of forest loss. That’s because there’s just enough disturbed forest left for adaptable species like bats to survive.
At the same time, the total amount of edge around those deforested patches — the places where people are most likely to come in contact with wildlife — is at its peak. When the scale tips beyond that intermediate level of habitat loss, there isn’t as much forest to support the wildlife, resulting in less total edge where humans and animals can collide….
This is. . . intuitively very sensible — but not at all obvious, least not until ProPublica took the time and care to sort it all out.
Onward — when you know better — you do better.
नमस्ते
