John Drake, assistant professor in the UGA Institute of Ecology, has created a mathematical model that takes into account how factors such as the speed at which information is gathered about a disease and how quickly that information is disseminated to the public affect the final size of an outbreak.
The model, published in the journal PloS (Public Library of Science) One finds that in the 2003 SARS outbreak in Singapore, doubling the rate at which infected people removed themselves from the larger population by quarantining themselves or seeking treatment would have cut the total number of infected people from 238 to 116. If infected individuals had removed themselves at half the actual rate, the number of cases would have ballooned to nearly 800.
“Infectious diseases are like weeds,” Drake said. “They grow multiplicatively – two infected people, four infected, eight and so forth. So that means you have exponential returns in your ability to control the outbreak the earlier you catch it.”
Drake said that with modifications to account for differences in factors such as transmission rate, the model can be applied to other emerging infectious diseases such as avian influenza.
He said that part of what makes the model so useful is its simplicity. Rather than relying on a complicated computer model that takes into account tens or even hundreds of variables, Drake’s model has the potential to estimate outbreak size based on four variables: the transmission rate, infectious period, the removal rate and the rate at which the public health response begins to produce diminishing returns.
Drake points out that during the Singapore outbreak, there was little evidence that the public health response began to produce diminishing returns. He said this finding suggests that although an aggressive public health response is costly, a sluggish one is far worse.
“An outbreak is very sensitive to how hard you hit it at the very beginning,” Drake said. “The important thing is to gain ground as quickly as possible.”
Sam Fahmy | EurekAlert!
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