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Superspreading and heterogeneity in transmission of SARS, MERS, and COVID-19: A systematic review.
Wang, Jingxuan; Chen, Xiao; Guo, Zihao; Zhao, Shi; Huang, Ziyue; Zhuang, Zian; Wong, Eliza Lai-Yi; Zee, Benny Chung-Ying; Chong, Marc Ka Chun; Wang, Maggie Haitian; Yeoh, Eng Kiong.
  • Wang J; JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Chen X; School of Public Health, Zhejiang University, Hangzhou, China.
  • Guo Z; JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Zhao S; JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Huang Z; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.
  • Zhuang Z; Mianyang Maternal and Child Health Care Hospital, Mianyang, China.
  • Wong EL; Department of Biostatistics, University of California Los Angeles Fielding School of Public Health, Los Angeles, CA, USA.
  • Zee BC; JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Chong MKC; CUHK Institute of Health Equity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Wang MH; Centre for Health Systems and Policy Research, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Yeoh EK; JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
Comput Struct Biotechnol J ; 19: 5039-5046, 2021.
Article in English | MEDLINE | ID: covidwho-1385373
ABSTRACT

BACKGROUND:

Severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and coronavirus disease 2019 (COVID-19) have caused substantial public health burdens and global health threats. Understanding the superspreading potentials of these viruses are important for characterizing transmission patterns and informing strategic decision-making in disease control. This systematic review aimed to summarize the existing evidence on superspreading features and to compare the heterogeneity in transmission within and among various betacoronavirus epidemics of SARS, MERS and COVID-19.

METHODS:

PubMed, MEDLINE, and Embase databases were extensively searched for original studies on the transmission heterogeneity of SARS, MERS, and COVID-19 published in English between January 1, 2003, and February 10, 2021. After screening the articles, we extracted data pertaining to the estimated dispersion parameter (k) which has been a commonly-used measurement for superspreading potential.

FINDINGS:

We included a total of 60 estimates of transmission heterogeneity from 26 studies on outbreaks in 22 regions. The majority (90%) of the k estimates were small, with values less than 1, indicating an over-dispersed transmission pattern. The point estimates of k for SARS and MERS ranged from 0.12 to 0.20 and from 0.06 to 2.94, respectively. Among 45 estimates of individual-level transmission heterogeneity for COVID-19 from 17 articles, 91% were derived from Asian regions. The point estimates of k for COVID-19 ranged between 0.1 and 5.0.

CONCLUSIONS:

We detected a substantial over-dispersed transmission pattern in all three coronaviruses, while the k estimates varied by differences in study design and public health capacity. Our findings suggested that even with a reduced R value, the epidemic still has a high resurgence potential due to transmission heterogeneity.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Diagnostic study / Reviews / Systematic review/Meta Analysis Language: English Journal: Comput Struct Biotechnol J Year: 2021 Document Type: Article Affiliation country: J.csbj.2021.08.045

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Diagnostic study / Reviews / Systematic review/Meta Analysis Language: English Journal: Comput Struct Biotechnol J Year: 2021 Document Type: Article Affiliation country: J.csbj.2021.08.045