Doing Mathematics with Aftermath of Pandemic Influenza 2009

Article information

Osong Public Health Res Perspect. 2015;6(1):1-2
Publication date (electronic) : 2015 February 27
doi :
Osong Public Health and Research Perspectives, Korea Centers for Disease Control and Prevention, Cheongju, Korea
College of Medicine, Eulji University, Daejeon, Korea
Osong Public Health and Research Perspectives, Korea Centers for Disease Control and Prevention, Cheongju, Korea
Corresponding author.
Corresponding author.

The influenza A/H1N1 pandemic in 2009–2010 brought a hug impact to both scientists and public health authorities in public health sector in Korea. The Korean scientists traced the pathogenesis and chronological localization of influenza A/H1N1 [1], and also checked antiviral resistance in Korea [2]. Surveillance data on influenza-like illness (ILI) utilized to model to estimate the influenza patents in Korea [3]. Mathematical modelers evaluated the parameters of the existing preparedness plan in Korea [4]. Many pharmaceutical and non-pharmaceutical measures are implemented during an epidemic to delay the peak and reduce the casualties [5]. Some study has demonstrated the effectiveness of non-pharmaceutical measures under certain situation [6], but the timely intervention with pharmaceutical measures with vaccines and antiviral treatment is known to effectively contain or mitigate the impact of an outbreak [7–9]. Public health experts have paid remarkable attention on the preventive strategies implemented for recurrent or future epidemics. Recently, many more realistic, tailored mathematical transmission models have been evolved to answer specific public health questions on an epidemic and tested for the empirical validity [8,9].

In the current issue of Osong Public Health and Research Perspective, the authors investigated how the onset time and the levels of control measures were associated with the effectiveness of intensive vaccination and antiviral treatment [10]. In this study, results from models with full control measures and models with partial control measures were compared, highlighting the significant differences in model outcomes. The intensive vaccination was the single most critical factor to prevent the severe outbreak. The authors estimated the half vaccination resulted in the total infected proportion six times larger or more. This study has shown a unique approach to evaluate the effectiveness of mass vaccination in Korea. This evaluation would provide a valuable insight for public health officials and scientists to prepare for the next possible pandemic in Korea.


1. Kwon D., Shin K., Shin J.Y.. Pathogenesis and chronologic localization of the human influenza A (H1N1) virus in cotton rats. Osong Public Health Res Perspect 2(1)2011 Jun;:15–22. 24159445.
2. Choi W.Y., Yang I., Kim S.. The emergence of oseltamivir-resistant seasonal influenza A (H1N1) virus in Korea during the 2008–2009 season. Osong Public Health Res Perspect 2(3)2011 Dec;:178–185. 24159470.
3. Lee J.S., Park S.H., Moon J.W.. Modeling for estimating influenza patients from ILI surveillance data in Korea. Osong Public Health Res Perspect 2(2)2011 Sep;:89–93. 24159457.
4. Chu C., Lee J., Choi D.H.. Sensitivity analysis of the parameters of Korea's pandemic influenza preparedness plan. Osong Public Health Res. Perspect 2(3)2011 Dec;:210–215. 24159475.
5. Lee V.J., Lye D.C., Wilder-Smith A.. Combination strategies for pandemic influenza response–a systematic review of mathematical modeling studies. BMC Med 72009 Dec;:76. 20003249.
6. Miller M.A., Viboud C., Somonsen L.. The Signature Features of Influenza Pandemics – Implications for Policy. N Engl J Med 360(25)2009 Jun;:2595–2598. 19423872.
7. Towers S., Feng Z.. Pandemic H1N1 influenza: predicting the course of pandemic and assessing the efficacy of the planned vaccination programme in the United States. Euro Surveill 14(41)2009 Oct;:19358. 19883540.
8. Feng Z., Towers S., Yang Y.. Modeling the effects of vaccination and treatment on pandemic influenza. AAPS J 13(4)2011 Sep;:427–437. 21656080.
9. Qiu Z., Feng Z.. Transmission dynamics of an influenza model with vaccination and antiviral treatment. Bull Math Biol 72(1)2010 Jan;:1–33. 19568726.
10. Chu C, Lee S. Assessment of intensive vaccination and antiviral treatment in 2009 influenza Pandemic in Korea. Osong Public Health Res Perspect. Feb;6(1):47–51.


This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article information Continued