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BibTex format

@article{Cauchemez:2012:10.3201/eid1201.050593.,
author = {Cauchemez, S and Boelle, PY and Donnelly, CA and Ferguson, NM and Thomas, G and Leung, GM and Hedley, AJ and Anderson, RM and Valleron, AJ},
doi = {10.3201/eid1201.050593.},
journal = {Emerging Infectious Diseases},
pages = {110--113},
title = {Real-time estimates in early detection of SARS},
url = {http://dx.doi.org/10.3201/eid1201.050593.},
volume = {12},
year = {2012}
}

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TY  - JOUR
AB  - We propose a Bayesian statistical framework for estimating the reproduction number R early in an epidemic. This method allows for the yet-unrecorded secondary cases if the estimate is obtained before the epidemic has ended. We applied our approach to the severe acute respiratory syndrome (SARS) epidemic that started in February 2003 in Hong Kong. Temporal patterns of R estimated after 5, 10, and 20 days were similar. Ninety-five percent credible intervals narrowed when more data were available but stabilized after 10 days. Using simulation studies of SARS-like outbreaks, we have shown that the method may be used for early monitoring of the effect of control measures.
AU  - Cauchemez,S
AU  - Boelle,PY
AU  - Donnelly,CA
AU  - Ferguson,NM
AU  - Thomas,G
AU  - Leung,GM
AU  - Hedley,AJ
AU  - Anderson,RM
AU  - Valleron,AJ
DO  - 10.3201/eid1201.050593.
EP  - 113
PY  - 2012///
SN  - 1080-6040
SP  - 110
TI  - Real-time estimates in early detection of SARS
T2  - Emerging Infectious Diseases
UR  - http://dx.doi.org/10.3201/eid1201.050593.
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000234419700020&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/48892
VL  - 12
ER  -

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Professor Sir Roy Anderson FRS, FMedSci

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