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Journal of Preventive Medicine and Public Health 2005;38(4): 379-385.
Modelling the Impact of Pandemic Influenza.
Byung Chul Chun
1Department of Preventive Medicine, Korea Univerisy Medical College, Korea.
2Department of Epidemiology & Public Health Informatics, Korea University School of Public Health, Korea.
The impact of the next influenza pandemic is difficult to predict. It is dependent on how virulent the virus is, how rapidly it spreads from population to population, and the effectiveness of prevention and response efforts. Despite the uncertainty about the magnitude of the next pandemic, estimates of the health and economic impact remain important to aid public health policy decisions and guide pandemic planning for health and emergency sectors. Planning ahead in preparation for an influenza pandemic, with its potentially very high morbidity and mortality rates, is essential for hospital administrators and public health officials. The estimation of pandemic impact is based on the previous pandemics- we had experienced at least 3 pandemics in 20th century. But the epidemiological characteristics - ie, start season, the impact of 1st wave, pathogenicity and virulence of the viruses and the primary victims of population were quite different from one another. I reviewed methodology for estimation and modelling of pandemic impact and described some nations's results using them in their national preparedness plans. And then I showed the estimates of pandemic influenza impact in Korea with FluSurge and FluAid. And, I described the results of pandemic modelling with parameters of 1918 pandemic for the shake of education and training of the first-line responder health officials to the epidemics. In preparing influenza pandemics, the simulation and modelling are the keys to reduce the uncertainty of the future and to make proper policies to manage and control the pandemics.
Key words: Influenza; Pandemic; Epidemic; Simulation; Epidemic modelling; Korea; Epidemiology
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Overview of Pandemic Influenza.  2005 November;38(4)
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