Via ProPublica: How We Used Machine Learning to Look Where Ebola May Strike. Excerpt:
ProPublica spent months teaching a computer to analyze past Ebola outbreaks linked to deforestation. What we found reveals a weakness in the way that governments and public health experts are preparing for future pandemics.
The bright spots on the map struck us like a lightning bolt.
We had spent months teaching a computer about the Ebola virus –– feeding it information about the landscapes and populations in places where the disease had previously emerged, showing it how to analyze those outbreaks for patterns, and then instructing it to flag other areas that looked similarly perilous.
Some of the highlighted spots were predictable; the virus had repeatedly ravaged one of those countries.
But we didn’t expect our model to light up Nigeria, the most populous country in Africa. The West African nation and international travel hub has never seeded an Ebola outbreak, but just a year ago, it served as the springboard for another virus to travel into Europe and the Americas and spread across the globe. However that virus, mpox, originally known as monkeypox, is rarely fatal.
What if it had been Ebola, which kills about half of the people it infects?
We asked Nigerian public health officials whether they were concerned.
“Ebola is not part of our top concerns any more,” said Oyeladun Okunromade, the director of surveillance and epidemiology at the Nigeria Centre for Disease Control.
In the aftermath of the 2014 West African Ebola epidemic, the worst on record, Nigerian officials were on high alert. But last year, they took the virus off the list of the top infectious diseases the country needed to prepare for, downgrading Ebola in relation to threats like mpox, which Nigeria was actively fighting.
The disjoint between how our model sees Nigeria’s risk and how the nation’s health officials view it reveals a weakness in the way that governments and public health experts are preparing for future pandemics. The methods many countries use to rank threats focus mainly on factors that occur after an outbreak has already begun, such as the potential economic impact of an epidemic. Or they rely on past cases, looking at where a pathogen has previously struck.
Neither approach considers the root causes.
We’ve spent more than a year digging into the question of what causes outbreaks and what the world can do to prevent them. And we’ve learned that while science has advanced so we’re starting to understand the complex factors that trigger an outbreak, the world is not doing nearly enough to try to head off the next big one.
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