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@article{Blake:2016:10.3201/eid2203.151394,
author = {Blake, IM and Chenoweth, P and Okayasu, H and Donnelly, C and Aylward, RB and Grassly, NC},
doi = {10.3201/eid2203.151394},
journal = {Emerging Infectious Diseases},
pages = {449--456},
title = {Faster Detection of Poliomyelitis Outbreaks to Support Polio Eradication},
url = {http://dx.doi.org/10.3201/eid2203.151394},
volume = {22},
year = {2016}
}

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TY  - JOUR
AB  - As the global eradication of poliomyelitis approaches the final stages, prompt detection of new outbreaks is critical to enable a fast and effective outbreak response. Surveillance relies on reporting of acute flaccid paralysis (AFP) cases and laboratory confirmation through isolation of poliovirus from stool. However, delayed sample collection and testing can delay outbreak detection. We investigated whether weekly testing for clusters of AFP by location and time, using the Kulldorff scan statistic, could provide an early warning for outbreaks in 20 countries. A mixed-effects regression model was used to predict background rates of nonpolio AFP at the district level. In Tajikistan and Congo, testing for AFP clusters would have resulted in an outbreak warning 39 and 11 days, respectively, before official confirmation of large outbreaks. This method has relatively high specificity and could be integrated into the current polio information system to support rapid outbreak response activities.
AU  - Blake,IM
AU  - Chenoweth,P
AU  - Okayasu,H
AU  - Donnelly,C
AU  - Aylward,RB
AU  - Grassly,NC
DO  - 10.3201/eid2203.151394
EP  - 456
PY  - 2016///
SN  - 1080-6040
SP  - 449
TI  - Faster Detection of Poliomyelitis Outbreaks to Support Polio Eradication
T2  - Emerging Infectious Diseases
UR  - http://dx.doi.org/10.3201/eid2203.151394
UR  - http://hdl.handle.net/10044/1/29950
VL  - 22
ER  -

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Professor Christl Donnelly CBE FMedSci FRS

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