Literature DB >> 25737823

Doing mathematics with aftermath of pandemic influenza 2009.

Hae-Wol Cho1, Chaeshin Chu1.   

Abstract

Entities:  

Year:  2015        PMID: 25737823      PMCID: PMC4346592          DOI: 10.1016/j.phrp.2015.01.001

Source DB:  PubMed          Journal:  Osong Public Health Res Perspect        ISSN: 2210-9099


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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.
  10 in total

1.  The signature features of influenza pandemics--implications for policy.

Authors:  Mark A Miller; Cecile Viboud; Marta Balinska; Lone Simonsen
Journal:  N Engl J Med       Date:  2009-05-07       Impact factor: 91.245

2.  Transmission dynamics of an influenza model with vaccination and antiviral treatment.

Authors:  Zhipeng Qiu; Zhilan Feng
Journal:  Bull Math Biol       Date:  2009-06-30       Impact factor: 1.758

3.  Modeling the effects of vaccination and treatment on pandemic influenza.

Authors:  Zhilan Feng; Sherry Towers; Yiding Yang
Journal:  AAPS J       Date:  2011-06-08       Impact factor: 4.009

4.  Pandemic H1N1 influenza: predicting the course of a pandemic and assessing the efficacy of the planned vaccination programme in the United States.

Authors:  S Towers; Z Feng
Journal:  Euro Surveill       Date:  2009-10-15

5.  The Emergence of Oseltamivir-Resistant Seasonal Influenza A (H1N1) Virus in Korea During the 2008-2009 Season.

Authors:  Woo-Young Choi; Inseok Yang; Sujin Kim; Namjoo Lee; Meehwa Kwon; Joo-Yeon Lee; Chun Kang
Journal:  Osong Public Health Res Perspect       Date:  2011-12

6.  Assessment of intensive vaccination and antiviral treatment in 2009 influenza pandemic in Korea.

Authors:  Chaeshin Chu; Sunmi Lee
Journal:  Osong Public Health Res Perspect       Date:  2014-12-24

7.  Modeling for Estimating Influenza Patients from ILI Surveillance Data in Korea.

Authors:  Joo-Sun Lee; Sun-Hee Park; Jin-Woong Moon; Jacob Lee; Yong Gyu Park; Yong Kyun Roh
Journal:  Osong Public Health Res Perspect       Date:  2011-08-04

8.  Sensitivity Analysis of the Parameters of Korea's Pandemic Influenza Preparedness Plan.

Authors:  Chaeshin Chu; Junehawk Lee; Dong Hoon Choi; Seung-Ki Youn; Jong-Koo Lee
Journal:  Osong Public Health Res Perspect       Date:  2011-12

9.  Pathogenesis and Chronologic Localization of the Human Influenza A (H1N1) Virus in Cotton Rats.

Authors:  Donghyok Kwon; Kyeongcheol Shin; Jin-Young Shin; Joo-Yeon Lee; Yooncheol Ha; Nam-Joo Lee; Hee-Bok Oh; Chanhee Chae; Chun Kang
Journal:  Osong Public Health Res Perspect       Date:  2011-04-13

Review 10.  Combination strategies for pandemic influenza response - a systematic review of mathematical modeling studies.

Authors:  Vernon J Lee; David C Lye; Annelies Wilder-Smith
Journal:  BMC Med       Date:  2009-12-10       Impact factor: 8.775

  10 in total

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