The role of superspreading in Middle East respiratory syndrome coronavirus (MERS-CoV) transmission-Reference-Cited by-同舟云学术

The role of superspreading in Middle East respiratory syndrome coronavirus (MERS-CoV) transmission

Published:2015-06-25 Issue:25 Volume:20 Page:
ISSN:1560-7917
Container-title:Eurosurveillance
language:en
Short-container-title:

Author:

Kucharski A J¹,Althaus C L²

Affiliation:

1. Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom

2. Institute of Social and Preventive Medicine (ISPM), University of Bern, Berne, Switzerland

Abstract

As at 15 June 2015, a large transmission cluster of Middle East respiratory syndrome coronavirus (MERS-CoV) was ongoing in South Korea. To examine the potential for such events, we estimated the level of heterogeneity in MERS-CoV transmission by analysing data on cluster size distributions. We found substantial potential for superspreading; even though it is likely that R0 < 1 overall, our analysis indicates that cluster sizes of over 150 cases are not unexpected for MERS-CoV infection.

Publisher

European Centre for Disease Control and Prevention (ECDC)

Subject

Virology,Public Health, Environmental and Occupational Health,Epidemiology

Reference14 articles.

1. European Centre for Disease Prevention and Control (ECDC). Middle East respiratory syndrome coronavirus (MERS-CoV). 17th update, 11 June 2015. Rapid risk assessment. Stockholm: ECDC; 2015. Available from: http://ecdc.europa.eu/en/publications/Publications/middle-east-respiratory-syndrome-coronavirus-rapid-risk-assessment-11-June-2015.pdf

2. World Health Organization (WHO). Middle East respiratory syndrome coronavirus (MERS-CoV), 15 June 2015. Geneva: WHO. [Accessed 15 Jun 2015]. Available from: http://www.who.int/csr/disease/coronavirus_infections/en/

3. Superspreading and the effect of individual variation on disease emergence

4. Maximum Likelihood Estimation of the Negative Binomial Dispersion Parameter for Highly Overdispersed Data, with Applications to Infectious Diseases

5. Assessment of the Middle East respiratory syndrome coronavirus (MERS-CoV) epidemic in the Middle East and risk of international spread using a novel maximum likelihood analysis approach

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