Using models to identify routes of nosocomial infection: a large hospital outbreak of SARS in Hong Kong
Identifieur interne : 001848 ( Ncbi/Checkpoint ); précédent : 001847; suivant : 001849Using models to identify routes of nosocomial infection: a large hospital outbreak of SARS in Hong Kong
Auteurs : Kin On Kwok [République populaire de Chine] ; Gabriel M. Leung [République populaire de Chine] ; Wai Yee Lam [Royaume-Uni] ; Steven Riley [République populaire de Chine]Source :
- Proceedings of the Royal Society B: Biological Sciences [ 0962-8452 ] ; 2006.
Abstract
Two factors dominated the epidemiology of severe acute respiratory syndrome (SARS) during the 2002–2003 global outbreak, namely super-spreading events (SSE) and hospital infections. Although both factors were important during the first and the largest hospital outbreak in Hong Kong, the relative importance of different routes of infection has not yet been quantified. We estimated the parameters of a novel mathematical model of hospital infection using SARS episode data. These estimates described levels of transmission between the index super-spreader, staff and patients, and were used to compare three plausible hypotheses. The broadest of the supported hypotheses ascribes the initial surge in cases to a single super-spreading individual and suggests that the
Url:
DOI: 10.1098/rspb.2006.0026
PubMed: 17254984
PubMed Central: 2197207
Affiliations:
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<front><div type="abstract" xml:lang="en"><p>Two factors dominated the epidemiology of severe acute respiratory syndrome (SARS) during the 2002–2003 global outbreak, namely super-spreading events (SSE) and hospital infections. Although both factors were important during the first and the largest hospital outbreak in Hong Kong, the relative importance of different routes of infection has not yet been quantified. We estimated the parameters of a novel mathematical model of hospital infection using SARS episode data. These estimates described levels of transmission between the index super-spreader, staff and patients, and were used to compare three plausible hypotheses. The broadest of the supported hypotheses ascribes the initial surge in cases to a single super-spreading individual and suggests that the <italic>per capita</italic>
risk of infection to patients increased approximately one month after the start of the outbreak. Our estimate for the number of cases caused by the SSE is substantially lower than the previously reported values, which were mostly based on self-reported exposure information. This discrepancy suggests that the early identification of the index case as a super-spreader might have led to biased contact tracing, resulting in too few cases being attributed to staff-to-staff transmission. We propose that in future outbreaks of SARS or other directly transmissible respiratory pathogens, simple mathematical models could be used to validate preliminary conclusions concerning the relative importance of different routes of transmission with important implications for infection control.</p>
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