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dc.contributor.authorTeklehaimanot, Hailay Desta
dc.contributor.authorTeklehaimanot, Awash
dc.contributor.authorSchwartz, Joel David
dc.contributor.authorLipsitch, Marc
dc.date.accessioned2013-01-30T17:19:44Z
dc.date.issued2004
dc.identifier.citationTeklehaimanot, Hailay Desta, Joel Schwartz, Awash Teklehaimanot, and Marc Lipsitch. 2004. Alert threshold algorithms and malaria epidemic detection. Emerging Infectious Diseases 10(7): 1220-1226.en_US
dc.identifier.issn1080-6040en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:10246864
dc.description.abstractWe describe a method for comparing the ability of different alert threshold algorithms to detect malaria epidemics and use it with a dataset consisting of weekly malaria cases collected from health facilities in 10 districts of Ethiopia from 1990 to 2000. Four types of alert threshold algorithms are compared: weekly percentile, weekly mean with standard deviation (simple, moving average, and log-transformed case numbers), slide positivity proportion, and slope of weekly cases on log scale. To compare dissimilar alert types on a single scale, a curve was plotted for each type of alert, which showed potentially prevented cases versus number of alerts triggered over 10 years. Simple weekly percentile cutoffs appear to be as good as more complex algorithms for detecting malaria epidemics in Ethiopia. The comparative method developed here may be useful for testing other proposed alert thresholds and for application in other populations.en_US
dc.language.isoen_USen_US
dc.publisherCenters for Disease Control and Preventionen_US
dc.relation.isversionofdoi:10.3201/eid1007.030722en_US
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3323320/pdf/en_US
dash.licenseLAA
dc.titleAlert Threshold Algorithms and Malaria Epidemic Detectionen_US
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden_US
dc.relation.journalEmerging Infectious Diseasesen_US
dash.depositing.authorLipsitch, Marc
dc.date.available2013-01-30T17:19:44Z
dc.identifier.doi10.3201/eid1007.030722*
dash.authorsorderedfalse
dash.contributor.affiliatedLipsitch, Marc
dash.contributor.affiliatedSchwartz, Joel


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