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Detecting Epidemics using statistics

National Institute of General Medical Sciences, one of the National Institutes of Health has awarded the $3 million, five-year award of national Models of Infectious Disease Agent Study (MIDAS) grants to // the Harvard Medical School and Harvard Pilgrim Health Care-led research team.

The goal of this project is to develop powerful mathematical and statistical modeling techniques. These techniques would be used later to quickly detect and monitor infectious disease outbreaks.

It is a joint venture by the Harvard Medical School and Harvard Pilgrim Health Care, Brigham and Women's Hospital, Massachusetts Department of Public Health, Harvard Vanguard Medical Associates, Harvard School of Public Health, Kaiser Permanente Northern California Division of Research, and the Argentine National Institute of Infectious Diseases.

Richard Platt, professor and chair of the Department of Ambulatory Care and Prevention of Harvard Medical School and Harvard Pilgrim Health Care says that this technology is developed to recognize unusual patterns of illness at the earliest possible time.

Martin Kulldorff, an associate professor and biostatistician said that it would allow us to combine the electronic device to monitor infectious disease outbreaks such as pandemic influenza and also to detect the risk of a particular population.

Richard Platt and his research group plan to integrate these details of large studies into computer models and then test these models in a very complex health care scenario. This will help in the early detection of an outbreak.

This project will combine mathematical and statistical models with computerized medical information for disease outbreak detection and surveillance. This will be very useful to identify hospital-based outbreaks of antimicrobial-resistant infections.

The team will make use of the available data from two health plans, Harvard Pilgrim Health Care in Massa chusetts and Kaiser Permanente Northern California, Brigham and Women's Hospital, Massachusetts registry of methicillin-resistant Staphylococcus aureus, and from a national antibiotic resistance monitoring consortium (55 hospitals in Argentina).

Brigham and Women's Hospital's (BWH) Microbiology Laboratory investigators Thomas F. O'Brien along with his colleagues have developed WHONET, a microbiology information system for monitoring antimicrobial resistance. It is from here that all the data are collected.

Kaiser Permanente Northern California Division of Research's John Hsu along with Boston-based MIDAS researchers will test complex detection algorithms thereby looking for outbreaks of resistant pathogens that may be regional or national in scope.

The researchers have three areas to concentrate such as model specification, which gives the number of people using the health care services. Model building, which includes models that have the ability to detect and generate signals in case of an outbreak. Model evaluation, which combines the historical data with actual disease outbreaks thereby, helps us to understand the disease pattern.


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