Data can be used for real-time estimation of influenza infection rates

A new study shows that serological data, coupled with clinical surveillance data, can provide a real-time estimation of the infection rate and severity of an emerging influenza pandemic.

Dr. Joseph Wu and his colleagues from the University of Hong Kong recently published a study on their predictive model in the medical journal PLoS Medicine, according to

"[Serological surveillance] strategies would be useful not only for situational awareness of influenza pandemics but also for pandemics caused by other pathogens, for example a future SARS-like event,” Wu said, reports. “Serologic surveillance should be considered in updated plans for influenza pandemic preparedness and response and for other pandemics."

The project received major funding from the government of Hong Kong’s Research Fund for the Control of Infectious Disease, Food and Health Bureau, the Hong Kong University Grants Committee, the Harvard Center for Communicable Disease Dynamics, the U.S. National Institutes of Health Models of Infectious Disease Agent Study Program and the U.S. National Institutes of Allergy and Infectious Diseases.

MedImmune, Inc., a major manufacturer of influenza vaccines, also aided in the study’s completion, but the funding bodies reportedly had no role in study’s design, data collection and analysis, or the preparation of the report and the decision to publish it.

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