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dc.contributor.authorTeklehaimanot, Hailay D
dc.contributor.authorTeklehaimanot, Awash
dc.contributor.authorSchwartz, Joel David
dc.contributor.authorLipsitch, Marc
dc.date.accessioned2012-01-22T01:57:04Z
dc.date.issued2004
dc.identifier.citationTeklehaimanot, Hailay D., Joel Schwartz, Awash Teklehaimanot, and Marc Lipsitch. 2004. Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions. Malaria Journal 3: 44.en_US
dc.identifier.issn1475-2875en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:8000925
dc.description.abstractBackground: Timely and accurate information about the onset of malaria epidemics is essential for effective control activities in epidemic-prone regions. Early warning methods that provide earlier alerts (usually by the use of weather variables) may permit control measures to interrupt transmission earlier in the epidemic, perhaps at the expense of some level of accuracy. Methods: Expected case numbers were modeled using a Poisson regression with lagged weather factors in a 4th-degree polynomial distributed lag model. For each week, the numbers of malaria cases were predicted using coefficients obtained using all years except that for which the prediction was being made. The effectiveness of alerts generated by the prediction system was compared against that of alerts based on observed cases. The usefulness of the prediction system was evaluated in cold and hot districts. Results: The system predicts the overall pattern of cases well, yet underestimates the height of the largest peaks. Relative to alerts triggered by observed cases, the alerts triggered by the predicted number of cases performed slightly worse, within 5% of the detection system. The prediction-based alerts were able to prevent 10–25% more cases at a given sensitivity in cold districts than in hot ones. Conclusions: The prediction of malaria cases using lagged weather performed well in identifying periods of increased malaria cases. Weather-derived predictions identified epidemics with reasonable accuracy and better timeliness than early detection systems; therefore, the prediction of malarial epidemics using weather is a plausible alternative to early detection systems.en_US
dc.language.isoen_USen_US
dc.publisherBioMed Centralen_US
dc.relation.isversionofdoi:10.1186/1475-2875-3-44en_US
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC535541/pdf/en_US
dash.licenseLAA
dc.titleWeather-Based Prediction of Plasmodium Falciparum Malaria in Epidemic-Prone Regions of Ethiopia II. Weather-Based Prediction Systems Perform Comparably to Early Detection Systems in Identifying Times for Interventionsen_US
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden_US
dc.relation.journalMalaria Journalen_US
dash.depositing.authorSchwartz, Joel David
dc.date.available2012-01-22T01:57:04Z
dash.affiliation.otherHMS^Medicine-Brigham and Women's Hospitalen_US
dash.affiliation.otherSPH^Exposure Epidemiology and Risk Programen_US
dash.affiliation.otherSPH^Epidemiologyen_US
dc.identifier.doi10.1186/1475-2875-3-44*
dash.authorsorderedfalse
dash.contributor.affiliatedLipsitch, Marc
dash.contributor.affiliatedSchwartz, Joel
dc.identifier.orcid0000-0002-2557-150X


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