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Influenza research: Can dynamic mapping reveal clues about seasonality?

MEDFORD/SOMERVILLE, Mass. - Influenza outbreaks in the United States typically begin with the arrival of cold weather and then spread in seasonal waves across geographic zones. But the question of why epidemics can vary from one season to the next has baffled scientists.

In a paper titled "Deviations in Influenza Seasonality: Odd Coincidence or Obscure Consequence," Elena Naumova, Ph.D., professor of civil and environmental engineering at Tufts School of Engineering, and collaborators from the U.S. and India suggest that the search for answers has been thwarted, in part, by the lack of standardized research methods.

This paper builds on Naumova's previous work in which she suggests a role for dynamic mapping in epidemiological research. Here, the team concludes that newly emerging technologies like dynamic mapping can be used in concert with traditional approaches, which Naumova describes as "fraught with problems." The paper was published in advance of print in Clinical Microbiology and Infection.

Naumova points out several of these problems. Data collection methods are not uniform. Researchers use ambiguous terminology and definitions. Research results are not presented in a uniform manner. "This produces volumes of information or noise that is prone to substantial measurement error and uncertainty that potentially obscures the causes behind seasonality rather than illuminating them," she says.

Another way influenza research falls short is that it doesn't take into account the behavior of the disease as it changes across time and geography. Using dynamic mapping as a tool, Naumova, the paper's senior author, and her team analyzed hospitalization records for adults age 65 and over from across the United States during individual flu seasons in 1991, 1997, 1999, and 2003.

The data, provided by the Centers for Medicare and Medicaid Services, were superimposed onto national maps showing average weekly temp

Contact: Alex Reid
Tufts University

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