Mathematical Modeling of the Novel Influenza A (H1N1) Virus and Evaluation of the Epidemic Response Strategies in the Republic of Korea.

Mina Suh; Jeehyun Lee; Hye Jin Chi; Young Keun Kim; Dae Yong Kang; Nam Wook Hur; Kyung Hwa Ha; Dong Han Lee; Chang Soo Kim

doi:10.3961/jpmph.2010.43.2.109

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Original Article Mathematical Modeling of the Novel Influenza A (H1N1) Virus and Evaluation of the Epidemic Response Strategies in the Republic of Korea.: Mina Suh, Jeehyun Lee, Hye Jin Chi, Young Keun Kim, Dae Yong Kang, Nam Wook Hur, Kyung Hwa Ha, Dong Han Lee, Chang Soo Kim; Journal of Preventive Medicine and Public Health 2010;43(2):109-116
DOI: https://doi.org/10.3961/jpmph.2010.43.2.109

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¹Department of Preventive Medicine, Yonsei University College of Medicine, Korea. preman@yuhs.ac
²Department of Computational Science and Engineering, Yonsei University, Korea.
³Department of Internal Medicine, Yonsei University Wonju College of Medicine, Korea.
⁴Clinical Trials Center, Yonsei University Health System, Korea.
⁵Department of Public Health, Graduate School of Yonsei University, Korea.
⁶Division of Public Health Crisis Response, Korea Centers for Disease Control and Prevention, Korea.

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Abstract

OBJECTIVES
The pandemic of novel influenza A (H1N1) virus has required decision-makers to act in the face of the substantial uncertainties. In this study, we evaluated the potential impact of the pandemic response strategies in the Republic of Korea using a mathematical model. METHODS: We developed a deterministic model of a pandemic (H1N1) 2009 in a structured population using the demographic data from the Korean population and the epidemiological feature of the pandemic (H1N1) 2009. To estimate the parameter values for the deterministic model, we used the available data from the previous studies on pandemic influenza. The pandemic response strategies of the Republic of Korea for novel influenza A (H1N1) virus such as school closure, mass vaccination (70% of population in 30 days), and a policy for anti-viral drug (treatment or prophylaxis) were applied to the deterministic model. RESULTS: The effect of two-week school closure on the attack rate was low regardless of the timing of the intervention. The earlier vaccination showed the effect of greater delays in reaching the peak of outbreaks. When it was no vaccination, vaccination at initiation of outbreak, vaccination 90 days after the initiation of outbreak and vaccination at the epidemic peak point, the total number of clinical cases for 400 days were 20.8 million, 4.4 million, 4.7 million and 12.6 million, respectively. The pandemic response strategies of the Republic of Korea delayed the peak of outbreaks (about 40 days) and decreased the number of cumulative clinical cases (8 million). CONCLUSIONS: Rapid vaccination was the most important factor to control the spread of pandemic influenza, and the response strategies of the Republic of Korea were shown to delay the spread of pandemic influenza in this deterministic model.

Keywords: Influenza Mathematical model Pandemic Influenza vaccines Public policy

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