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To Stop Ebola, Scientists Are Trying to Predict Its Next Target

As Congo’s deadly outbreak rages, two new tools show promise for the future

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Who-Profits-From-the-Health-Datasets-of-Patients To Stop Ebola, Scientists Are Trying to Predict Its Next Target
More than 2,000 people have died in the Democratic Republic of Congo since an Ebola outbreak was declared last August, the second largest such outbreak ever recorded. The number of such outbreaks has ballooned since the disease was discovered in 1976. One reason it’s been so difficult to control is that Ebola is hard to track.

Karin Huster, a nurse who worked with Doctors Without Borders on the front lines of the record-breaking Ebola outbreak of 2014–2016, says that medical professionals often lack the tools to know whether an outbreak is happening and contain it when it is. “We knew some of the signs, [but] we didn’t have the tools,” she tells OneZero.

But two new tools for identifying outbreaks could soon prevent those situations from taking place.

A team led by David Redding, PhD, and Kate Jones, PhD, professors at the Centre for Biodiversity and Environment Research at University College London, created a computer model that predicts where Ebola outbreaks will most likely occur in the future, together with their magnitude and causes. Their model, described in a paper this month in Nature Communications, successfully predicted the 2014–2016 outbreak and the current one, Redding tells OneZero. Its predictive power can help public health professionals prepare for outbreaks before they occur.

“You identify new hot spots that you didn’t have on your radar before.”

Researchers still track the spread of Ebola through contact tracing, a labor-intensive process that involves in-person interviews with patients and the people they came in contact with. Computer models can help, but they are limited if they rely on public data on Ebola outbreaks, which Redding and his co-authors say isn’t enough for accurate pattern recognition because it spans only 40 years. Instead, the new model takes into account environmental and socioeconomic factors like climate change, population growth, and changing health care practices. By 2070, the model predicts, there’ll be a 1.75-to-3.2-fold increase in the rate of Ebola outbreaks in Africa.

The model also predicts climate change will lead to a “subtle” increase in the risk that it will spread to humans, Redding says. Because Ebola is a zoonotic disease — one that begins in animals and is passed on to humans — and climate change could broaden the geographic area in which some animals survive (mostly fruit bats and, to a lesser extent, apes and duikers), the risk of infection could rise.

Redding says, though, that population growth and poverty remain the biggest factors in future Ebola outbreaks. The new model allows for more holistic predictions, which may identify at-risk areas that haven’t been considered before. The model predicts Ebola outbreaks in the eastern, southern, and western parts of Africa, where they haven’t occurred in the past.

While the model can predict where Ebola might strike next, another new tool can help contain the disease when it has already struck. Earlier this month, the U.S. Food and Drug Administration gave market approval to the OraQuick Ebola Rapid Antigen Test, a powerful diagnostic tool. Instead of taking days to produce a test result from potentially infected individuals, this new test can diagnose Ebola in 30 minutes. Importantly, it can be used on living and dead bodies, allowing people like Huster to quickly determine when an outbreak has already begun and whether families can safely bury their dead without first decontaminating the bodies.

“This tool is super useful,” says Huster, who used a trial version of the tool in Sierra Leone in 2014. Because it’s simple to use, doesn’t require specialist training, and isn’t reliant on electricity, it can be used in remote areas by medical workers who need urgent results.

“You identify new hot spots that you didn’t have on your radar before,” Huster says. “So you can intervene much faster than if you had to take the blood, bring it to a lab that might be far — a day, or two, or three — away, and by that time, the virus has already gone from one person to another.”

“But Ebola is not the only thing we’re going to have more of and going to have to deal with.”

The new diagnostic tool comes with its own drawbacks: It isn’t as accurate as a polymerase chain reaction (PCR) test, considered the “gold standard” for Ebola diagnosis. Hunter fears that false negative readings from the rapid test could result in infected individuals being sent back into the community instead of quarantined.

Huster and Redding both say that the recently developed Ebola vaccine has been key in containing the current outbreak in the DRC. But to prevent future outbreaks, we need disease-specific tools like computer models and rapid tests, Redding says. And as climate change raises the risk of outbreaks of other zoonotic viruses like West Nile — something the new model can also predict — even the slightest head start on diagnosis and prevention will be extremely valuable.

“I don’t think this is unique to Ebola,” Huster says. “It might be a good tool for us to use, because Ebola is so scary for most people that it might make them move on the climate crisis because they don’t want to have Ebola in their countries. But Ebola is not the only thing we’re going to have more of and going to have to deal with.”


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