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dc.contributor.authorGomez-Elipe, A
dc.contributor.authorOtero, A
dc.contributor.authorVan Herp, M
dc.contributor.authorAguirre-Jaime, A
dc.date.accessioned2008-04-08T15:28:48Z
dc.date.available2008-04-08T15:28:48Z
dc.date.issued2007
dc.identifier.citationForecasting malaria incidence based on monthly case reports and environmental factors in Karuzi, Burundi, 1997-2003. 2007, 6:129 Malar. J.en
dc.identifier.issn1475-2875
dc.identifier.pmid17892540
dc.identifier.doi10.1186/1475-2875-6-129
dc.identifier.urihttp://hdl.handle.net/10144/22632
dc.description.abstractBACKGROUND: The objective of this work was to develop a model to predict malaria incidence in an area of unstable transmission by studying the association between environmental variables and disease dynamics. METHODS: The study was carried out in Karuzi, a province in the Burundi highlands, using time series of monthly notifications of malaria cases from local health facilities, data from rain and temperature records, and the normalized difference vegetation index (NDVI). Using autoregressive integrated moving average (ARIMA) methodology, a model showing the relation between monthly notifications of malaria cases and the environmental variables was developed. RESULTS: The best forecasting model (R2adj = 82%, p < 0.0001 and 93% forecasting accuracy in the range +/- 4 cases per 100 inhabitants) included the NDVI, mean maximum temperature, rainfall and number of malaria cases in the preceding month. CONCLUSION: This model is a simple and useful tool for producing reasonably reliable forecasts of the malaria incidence rate in the study area.
dc.language.isoenen
dc.publisherBMCen
dc.rightsPublished by BioMed Central, http://www.malariajournal.com/ Archived on this site by Open Access permissionen
dc.subject.meshAnimalsen
dc.subject.meshAnophelesen
dc.subject.meshArthropod Vectorsen
dc.subject.meshBurundien
dc.subject.meshDisease Outbreaksen
dc.subject.meshEpidemiologic Methodsen
dc.subject.meshForecastingen
dc.subject.meshGeographyen
dc.subject.meshHumansen
dc.subject.meshIncidenceen
dc.subject.meshMalaria, Falciparumen
dc.subject.meshModels, Statisticalen
dc.subject.meshPlantsen
dc.subject.meshPlasmodium falciparumen
dc.subject.meshRainen
dc.subject.meshTemperatureen
dc.titleForecasting malaria incidence based on monthly case reports and environmental factors in Karuzi, Burundi, 1997-2003.en
dc.contributor.departmentPublic Health Department, Universidad Autónoma de Madrid, C/Arzobispo Morcillo 2, 28029 Madrid, Spain. agomez.elipe@gmail.comen
dc.identifier.journalMalaria Journalen
refterms.dateFOA2019-03-04T09:50:35Z
html.description.abstractBACKGROUND: The objective of this work was to develop a model to predict malaria incidence in an area of unstable transmission by studying the association between environmental variables and disease dynamics. METHODS: The study was carried out in Karuzi, a province in the Burundi highlands, using time series of monthly notifications of malaria cases from local health facilities, data from rain and temperature records, and the normalized difference vegetation index (NDVI). Using autoregressive integrated moving average (ARIMA) methodology, a model showing the relation between monthly notifications of malaria cases and the environmental variables was developed. RESULTS: The best forecasting model (R2adj = 82%, p < 0.0001 and 93% forecasting accuracy in the range +/- 4 cases per 100 inhabitants) included the NDVI, mean maximum temperature, rainfall and number of malaria cases in the preceding month. CONCLUSION: This model is a simple and useful tool for producing reasonably reliable forecasts of the malaria incidence rate in the study area.


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