Open AccessEstimating and modelling the transmissibility of Middle East Respiratory Syndrome CoronaVirus during the 2015 outbreak in the Republic of Korea
Author(s) -
Zhang XuSheng,
Pebody Richard,
Charlett Andre,
Angelis Daniela,
Birrell Paul,
Kang Hunseok,
Baguelin Marc,
Choi Yoon Hong
Publication year - 2017
Publication title -
influenza and other respiratory viruses
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.743
H-Index - 57
eISSN - 1750-2659
pISSN - 1750-2640
DOI - 10.1111/irv.12467
Subject(s) - outbreak , middle east respiratory syndrome coronavirus , middle east respiratory syndrome , transmissibility (structural dynamics) , basic reproduction number , transmission (telecommunications) , confidence interval , population , medicine , environmental health , demography , public health , geography , covid-19 , virology , infectious disease (medical specialty) , disease , computer science , telecommunications , physics , nursing , vibration isolation , quantum mechanics , sociology , vibration
Background Emerging respiratory infections represent a significant public health threat. Because of their novelty, there are limited measures available to control their early spread. Learning from past outbreaks is important for future preparation. The Middle Eastern Respiratory Syndrome CoronaVirus (MERS‐CoV ) 2015 outbreak in the Republic of Korea (ROK) provides one such opportunity. Objectives We demonstrated through quantitative methodologies how to estimate MERS‐CoV's transmissibility and identified the effective countermeasures that stopped its spread. Methods Using the outbreak data, statistical methods were employed to estimate the basic reproductive number R 0 , the average number of secondary cases produced by a typical primary case during its entire infectious period in a fully susceptible population. A transmission dynamics model was also proposed to estimate R 0 and to identify the most effective countermeasures. The consistency between results will provide cross‐validation of the approaches. Results R 0 ranged from 2.5 with 95% confidence interval (CI): [1.7, 3.1] (using the sequential Bayesian method) to 7.2 with 95% CI: [5.3, 9.4] (using the Nowcasting method). Estimates from transmission model were higher but overlapped with these. Personal protection and rapid confirmation of cases were identified as the most important countermeasures. Conclusions Our estimates were in agreement with others from the ROK outbreak, albeit significantly higher than estimates based on other small outbreaks and sporadic cases of MERS‐CoV. The large‐scale outbreak in the ROK was jointly due to the high transmissibility in the healthcare‐associated setting and the Korean culture‐associated contact behaviour. Limiting such behaviour by rapidly identifying and isolating cases and avoiding high‐risk contacts effectively stopped further transmission.