Thread by @McNeill_Tweets

THREAD: I want to tell you a little background of our new series, which dates back to the summer of 2020 when COVID was raging around the world. My colleague Deb Nelson and I started talking about the next one and how to stop it. reuters.com/investigates/s…

Deb had been studying the science of zoonotic spillover, the term scientists use to describe when a human is infected by a virus circulating among wildlife. Scientists were increasingly linking these spillovers to habitat disruption — tree loss, agricultural intensification, etc

I wondered if we could use data to figure out what areas of the world are most at risk.

We were particularly interested in bats, these amazing flying mammals so important to ecosystems but also a leading reservoir of coronaviruses, Nipah, Hendra, Marburg, Ebola and others.

So @allisonmartell and I were able to map 95 bat virus during the last two decades and pair them with dozens of environmental variables for each year — 8 billion in all, mostly derived from satellites.

We used a machine learning algorithm called random forest to first learn about the conditions around those known spillovers and make predictions about where else in the world similar conditions might exist.

We made these predictions for nearly the entire land surface of the earth. We divided the world into millions of sectors, each about 25 square km, and each received a risk score for 2002 through 2020.

We used those predictions to identify areas most at risk. We dubbed those “jump zones.” From there, we assembled an amazing team of Reuters journalists who visited jump zones in Brazil, Liberia, Ghana, India, Laos and China. We connected the forces on the ground behind the data.

Billions of people — an estimated 1 in 5 of every human — live in jump zones. The conclusion: Our relentless thirst for resources is putting humanity at risk on every continent except Antarctica.