Ebola Infections Fewer Than Predicted by Disease Models

A few months ago the U.S. Centers for Disease Control and Prevention predicted that up to 1.4 million people in Liberia and Sierra Leone could become infected with Ebola by mid-January. In a recent address to the Senate, CDC director Tom Frieden said that worst-case scenario would not pan out.

That is partly because health care workers in the Ebola hot zone are engaged in a battle to contain the epidemic. It is also because of assumptions about human and viral behavior that are built into the mathematical models used to predict the spread of infectious diseases. Assumptions are inherent in these models. “You take islands of data from different places and build bridges of assumptions that link up all these islands,” says Martin Meltzer, senior health economist at the CDC. Meltzer’s model, which predicted the 1.4 million infections in Liberia and Sierra Leone, worked on the assumption that things would not improve. “Our forecasts are based on the idea that nothing will change,” he says.

But things have changed. About 3,000 U.S. military personnel have been deployed to West Africa since September. They’ve helped build Ebola treatment units and laboratories and train local staff. Alongside them, health care workers from international aid agencies such as Doctors Without Borders and Partners in Health are working with local doctors, nurses and epidemiologists to identify and treat Ebola patients.

Meltzer says those interventions were not built into the model because predicting their impact is difficult. “It’s easy for me to say that suddenly 100 [Ebola treatment units] have been built,” he says. “In the model that’s just two lines of code. But the reality of building those units and seeing that they work, that’s much harder.”

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http://www.scientificamerican.com/article/ebola-infections-fewer-than-predicted-by-disease-models/