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dc.contributor.authorPhung, Dung
dc.contributor.authorTalukder, Mohammad Radwanur Rahman
dc.contributor.authorRutherford, Shannon
dc.contributor.authorChu, Cordia
dc.date.accessioned2018-01-04T04:37:45Z
dc.date.available2018-01-04T04:37:45Z
dc.date.issued2016
dc.identifier.issn1360-2276
dc.identifier.doi10.1111/tmi.12754
dc.identifier.urihttp://hdl.handle.net/10072/100473
dc.description.abstractObjective To develop a prediction score scheme useful for prevention practitioners and authorities to implement dengue preparedness and controls in the Mekong Delta region (MDR). Methods We applied a spatial scan statistic to identify high-risk dengue clusters in the MDR and used generalised linear-distributed lag models to examine climate–dengue associations using dengue case records and meteorological data from 2003 to 2013. The significant predictors were collapsed into categorical scales, and the β-coefficients of predictors were converted to prediction scores. The score scheme was validated for predicting dengue outbreaks using ROC analysis. Results The north-eastern MDR was identified as the high-risk cluster. A 1 °C increase in temperature at lag 1–4 and 5–8 weeks increased the dengue risk 11% (95% CI, 9–13) and 7% (95% CI, 6–8), respectively. A 1% rise in humidity increased dengue risk 0.9% (95% CI, 0.2–1.4) at lag 1–4 and 0.8% (95% CI, 0.2–1.4) at lag 5–8 weeks. Similarly, a 1-mm increase in rainfall increased dengue risk 0.1% (95% CI, 0.05–0.16) at lag 1–4 and 0.11% (95% CI, 0.07–0.16) at lag 5–8 weeks. The predicted scores performed with high accuracy in diagnosing the dengue outbreaks (96.3%). Conclusion This study demonstrates the potential usefulness of a dengue prediction score scheme derived from complex statistical models for high-risk dengue clusters. We recommend a further study to examine the possibility of incorporating such a score scheme into the dengue early warning system in similar climate settings.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherWiley-Blackwell
dc.relation.ispartofpagefrom1324
dc.relation.ispartofpageto1333
dc.relation.ispartofissue10
dc.relation.ispartofjournalTropical Medicine and International Health
dc.relation.ispartofvolume21
dc.subject.fieldofresearchHealth services and systems
dc.subject.fieldofresearchPublic health
dc.subject.fieldofresearchClinical sciences
dc.subject.fieldofresearchEpidemiology
dc.subject.fieldofresearchcode4203
dc.subject.fieldofresearchcode4206
dc.subject.fieldofresearchcode3202
dc.subject.fieldofresearchcode4202
dc.titleA climate-based prediction model in the high-risk clusters of the Mekong Delta region, Vietnam: towards improving dengue prevention and control
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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