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dc.contributor.authorDung, Phung
dc.contributor.authorHuang, Cunrui
dc.contributor.authorRutherford, Shannon
dc.contributor.authorChu, Cordia
dc.contributor.authorWang, Xiaoming
dc.contributor.authorMinh, Nguyen
dc.contributor.authorNga, Huy Nguyen
dc.contributor.authorCuong, Do Manh
dc.date.accessioned2018-01-04T04:22:23Z
dc.date.available2018-01-04T04:22:23Z
dc.date.issued2015
dc.identifier.issn0001-706X
dc.identifier.doi10.1016/j.actatropica.2014.10.005
dc.identifier.urihttp://hdl.handle.net/10072/141607
dc.description.abstractThe Mekong Delta is highly vulnerable to climate change and a dengue endemic area in Vietnam. This study aims to examine the association between climate factors and dengue incidence and to identify the best climate prediction model for dengue incidence in Can Tho city, the Mekong Delta area in Vietnam. We used three different regression models comprising: standard multiple regression model (SMR), seasonal autoregressive integrated moving average model (SARIMA), and Poisson distributed lag model (PDLM) to examine the association between climate factors and dengue incidence over the period 2003–2010. We validated the models by forecasting dengue cases for the period of January–December, 2011 using the mean absolute percentage error (MAPE). Receiver operating characteristics curves were used to analyze the sensitivity of the forecast of a dengue outbreak. The results indicate that temperature and relative humidity are significantly associated with changes in dengue incidence consistently across the model methods used, but not cumulative rainfall. The Poisson distributed lag model (PDLM) performs the best prediction of dengue incidence for a 6, 9, and 12-month period and diagnosis of an outbreak however the SARIMA model performs a better prediction of dengue incidence for a 3-month period. The simple or standard multiple regression performed highly imprecise prediction of dengue incidence. We recommend a follow-up study to validate the model on a larger scale in the Mekong Delta region and to analyze the possibility of incorporating a climate-based dengue early warning method into the national dengue surveillance system.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherElsevier
dc.publisher.placeNetherlands
dc.relation.ispartofpagefrom88
dc.relation.ispartofpageto96
dc.relation.ispartofissuePart A
dc.relation.ispartofjournalActa Tropica
dc.relation.ispartofvolume141
dc.subject.fieldofresearchBiological sciences
dc.subject.fieldofresearchBiomedical and clinical sciences
dc.subject.fieldofresearchHealth sciences
dc.subject.fieldofresearchcode31
dc.subject.fieldofresearchcode32
dc.subject.fieldofresearchcode42
dc.titleIdentification of the prediction model for dengue incidence in Can Tho city, a Mekong Delta area in Vietnam
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Sciences, Griffith School of Environment
gro.hasfulltextNo Full Text
gro.griffith.authorChu, Cordia M.
gro.griffith.authorRutherford, Shannon
gro.griffith.authorPhung, Dung T.


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