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  • Identifying determinants of heterogeneous transmission dynamics of the Middle East respiratory syndrome (MERS) outbreak in the Republic of Korea, 2015: a retrospective epidemiological analysis

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Infectious diseases
Research
Identifying determinants of heterogeneous transmission dynamics of the Middle East respiratory syndrome (MERS) outbreak in the Republic of Korea, 2015: a retrospective epidemiological analysis
  1. Hiroshi Nishiura1,2,3,
  2. Akira Endo1,
  3. Masaya Saitoh1,2,4,
  4. Ryo Kinoshita1,2,3,
  5. Ryo Ueno1,
  6. Shinji Nakaoka1,2,
  7. Yuichiro Miyamatsu1,2,3,
  8. Yueping Dong1,2,
  9. Gerardo Chowell5,6,
  10. Kenji Mizumoto2,3,7
  1. 1Infectious Disease Epidemiology team, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
  2. 2CREST, Japan Science and Technology Agency, Saitama, Japan
  3. 3Graduate School of Medicine, Hokkaido University, Sapporo-shi, Hokkaido, Japan
  4. 4The Institute of Statistical Mathematics, Tokyo, Japan
  5. 5School of Public Health, Georgia State University, Atlanta, Georgia, USA
  6. 6Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, USA
  7. 7Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
  1. Correspondence to Dr Hiroshi Nishiura; nishiurah{at}gmail.com

Abstract

Objectives To investigate the heterogeneous transmission patterns of Middle East respiratory syndrome (MERS) in the Republic of Korea, with a particular focus on epidemiological characteristics of superspreaders.

Design Retrospective epidemiological analysis.

Setting Multiple healthcare facilities of secondary and tertiary care centres in an urban setting.

Participants A total of 185 laboratory-confirmed cases with partially known dates of illness onset and most likely sources of infection.

Primary and secondary outcome measures Superspreaders were identified using the transmission tree. The reproduction number, that is, the average number of secondary cases produced by a single primary case, was estimated as a function of time and according to different types of hosts.

Results A total of five superspreaders were identified. The reproduction number throughout the course of the outbreak was estimated at 1.0 due to reconstruction of the transmission tree, while the variance of secondary cases generated by a primary case was 52.1. All of the superspreaders involved in this outbreak appeared to have generated a substantial number of contacts in multiple healthcare facilities (association: p<0.01), generating on average 4.0 (0.0–8.6) and 28.6 (0.0–63.9) secondary cases among patients who visited multiple healthcare facilities and others. The time-dependent reproduction numbers declined substantially below the value of 1 on and after 13 June 2015.

Conclusions Superspreaders who visited multiple facilities drove the epidemic by generating a disproportionate number of secondary cases. Our findings underscore the need to limit the contacts in healthcare settings. Contact tracing efforts could assist early laboratory testing and diagnosis of suspected cases.

  • EPIDEMIOLOGY

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

https://doi.org/10.1136/bmjopen-2015-009936

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