Several University of Georgia researchers teamed up to create a statistical method that may allow public health and infectious disease forecasters to better predict disease reemergence, especially for preventable childhood infections such as measles and pertussis.
Several University of Georgia researchers teamed up to create a statistical method that may allow public health and infectious disease forecasters to better predict disease reemergence, especially for preventable childhood infections such as measles and pertussis.
As described in the journal PLOS Computational Biology, their five-year project resulted in a model that shows how subtle changes in the stream of reported cases of a disease may be predictive of both an approaching epidemic and of the final success of a disease eradication campaign.
“We hope that in the near future, we will be available to monitor and track warning signals for emerging diseases identified by this model,” said John Drake, Distinguished Research Professor of Ecology and director for the Center for the Ecology of Infectious Diseases who researches the dynamics of biological epidemics. His current projects include studies of Ebola virus in West Africa and Middle East respiratory syndrome-related coronavirus in the horn of Africa.
In recent years, the reemergence of measles, mumps, polio, whooping cough and other vaccine-preventable diseases has sparked a refocus on emergency preparedness.
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Image: John Drake in the Ecology Auditorium at UGA (Credit: UGA)
