Ebola is one of the deadliest epidemics in the world in terms of fatality rates. Now, a new computer model could help predict where future outbreaks of the virus might strike next. Researchers from University College London conducted a study and published their findings in the Nature Communications journal.
The model tracks how changes in society and the environment could affect the spread of the deadly virus. Specifically, factors such as climate change and increased poverty could increase the likelihood of an Ebola outbreak.
As with any natural disaster or deadly pandemic, being able to predict when and where an Ebola outbreak might happen next could save tens of thousands of lives.
Researchers first detected the Ebola virus in 1976 in the Democratic Republic of the Congo (DRC). Over 40 years, periodic outbreaks have occurred in countries across Africa.
The West African epidemic of 2014 was the largest Ebola outbreak in history. According to the CDC, 28,610 cases of the Zaire Ebola virus were documented in Guinea, Liberia, and Sierra Leone. Of these cases, 11,308 people died. Those fatalities equate to 39 percent of all reported illnesses.
In 2018, the Zaire strain reappeared in the Democratic Republic of the Congo and Uganda. Out of 54 cases in the DRC, 33 people (61 percent) died. That outbreak is still ongoing.
Over time, Ebola fatality rates have been as high as 90 percent. The virus kills, on average, about half of all the people who contract it. Making matters worse is the fact that there is no approved cure despite some promising advancements being on the horizon. Given these frightening statistics, discovering a way to forecast future outbreaks is critical.
“The future is inherently uncertain. But policymakers and decision-makers want to understand the range of future possibilities,” Kristie Ebi, a professor of global health at the University of Washington, said in an interview with The Verge. “You need information about what could happen so that you can be better prepared.”
How Does Ebola Spread?
Researchers conclude that contact with infected animals, like a fruit bat or a primate, can transmit the Ebola virus to people. After this “spillover,” the virus spreads in human populations through direct contact with the blood and bodily fluids of an infected person.
Lead author of the Nature Communications study, David Redding, told The Verge that, eventually, the computer model could help officials determine where to vaccinate people before an outbreak hits an area. It could also help local governments implement border protocols to stop sick travelers from spreading the virus.
Redding also emphasized that it’s essential to consider how socioeconomic, environmental changes, and changes in animal behavior affect the spread of the disease.
Impacts of Climate Change and Poverty Levels
The computer model predicts that the likelihood of a widespread Ebola outbreak could increase by as much as 60 percent in 2070 if global warming and poverty levels continue on their current paths.
The effects of climate change could cause people and animals to migrate and force them to adapt to new environmental conditions. As such, people and bats may live closer together.
Another global warming study suggests that, as the world becomes warmer, people might take food risks and eat wild animals. In turn, these people could unknowingly eat animals infected with Ebola. Furthermore, doctors and scientists worry that zoonotic disease outbreaks might be harder to predict as climate change disrupts ecosystems.
For instance, warmer temperatures have already caused disease-bearing ticks and mosquitos to move around. Unfortunately, they have transmitted diseases like Lyme, Dengue, Zika, and most recently, the deadly EEE virus to humans.
“Contact opportunity and frequency are crucial drivers in infectious disease spread,” Konstans Wells, an ecologist at Swansea University, told The Verge.
In making 2070 Ebola projections, the research team that developed the computer model explored different ways that communities work to decrease economic inequalities, slow population growth, and cut harmful greenhouse gas emissions. Results showed that without working to resolve these issues, chances of Ebola outbreaks increase.
The complex model matches “Previously-observed outbreak patterns with high accuracy and suggests further outbreaks could occur across most of West and Central Africa.”
It’s worth noting that the model also identified Nigeria as a target area. However, an Ebola outbreak has never occurred there. Researchers feel that healthcare systems in that area could handle the risk better. A healthcare infrastructure’s ability to treat any deadly virus is vital to containing it.
The new predictive model might help arm officials and humanitarian organizations who are fighting on the front lines of a future epidemic with life-saving knowledge.
As technology continues to evolve, this model offers hope that researchers can better fight all sorts of infectious diseases. Giving communities a warning about a deadly outbreak before it strikes is undoubtedly a step in the right direction.