Real-Time Tracking of Control Measures for Emerging Infections

dc.contributor.authorLipsitch, Marcen_US
dc.contributor.authorBergstrom, Carl T.en_US
dc.date.accessioned2004-10-18T20:57:36Zen_US
dc.date.accessioned2007-06-13T19:57:40Z
dc.date.available2004-10-18T20:57:36Zen_US
dc.date.available2007-06-13T19:57:40Z
dc.date.issued2004en_US
dc.description.abstractHealth officials faced a daunting task with the emergence of severe acute respiratory syndrome (SARS) last year: forecasting the trajectory of an emerging infectious disease and implementing effective control measures, even as the etiologic agent was still being identified. Investigators initially had little to go on beyond crude epidemiologic data such as the timing of new cases (the epidemic curve). With such limited data, it was difficult to disentangle two fundamental epidemiologic quantities: the time from one transmission of the infection to the next, known as the serial interval or generation time, and the average number of secondary cases resulting from each infection, known as the reproductive number....In the current issue of the Journal, Wallinga and Teunis present a statistical escape from this analytical Catch-22.en_US
dc.format.extent50832 bytesen_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationAmerican Journal of Epidemiology. 160:517-519en_US
dc.identifier.urihttp://hdl.handle.net/1773/1983en_US
dc.language.isoen_USen_US
dc.publisherAmerican Journal of Epidemiologyen_US
dc.subjectdisease outbreaksen_US
dc.subjectestimationen_US
dc.subjectinfectionen_US
dc.subjectstatistical modelsen_US
dc.subjectSARS virusen_US
dc.subjectsevere acute respiratory syndromeen_US
dc.titleReal-Time Tracking of Control Measures for Emerging Infectionsen_US
dc.typeArticleen_US

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