Spatiotemporal analysis of historical records (2001–2012) on dengue fever in Vietnam and development of a statistical model for forecasting risk

Simple item page
cg.authorship.typesCGIAR and developing country instituteen
cg.authorship.typesCGIAR and advanced research instituteen
cg.contributor.affiliationInternational Livestock Research Instituteen
cg.contributor.affiliationUppsala Universityen
cg.contributor.affiliationSwedish University of Agricultural Sciencesen
cg.contributor.affiliationHanoi University of Public Healthen
cg.contributor.affiliationVietnam Institute of Meteorology, Hydrology and Climate Changeen
cg.contributor.affiliationNational Institute of Hygiene and Epidemiology, Vietnamen
cg.contributor.affiliationMinistry of Health, Vietnamen
cg.contributor.crpAgriculture for Nutrition and Healthen
cg.contributor.crpClimate Change, Agriculture and Food Securityen
cg.coverage.countryVietnamen
cg.coverage.iso3166-alpha2VNen
cg.coverage.regionAsiaen
cg.coverage.regionSouth-eastern Asiaen
cg.creator.identifierBernard Bett: 0000-0001-9376-2941en
cg.creator.identifierDelia Grace: 0000-0002-0195-9489en
cg.creator.identifierHu Suk Lee: 0000-0002-8731-9836en
cg.creator.identifierJohanna Lindahl: 0000-0002-1175-0398en
cg.creator.identifierHung Nguyen-Viet: 0000-0003-1549-2733en
cg.howPublishedFormally Publisheden
cg.identifier.doihttps://doi.org/10.1371/journal.pone.0224353en
cg.isijournalISI Journalen
cg.issn1932-6203en
cg.issue11en
cg.journalPLOS ONEen
cg.reviewStatusPeer Reviewen
cg.subject.ilriANIMAL DISEASESen
cg.subject.ilriDISEASE CONTROLen
cg.subject.ilriHEALTHen
cg.volume14en
dc.contributor.authorBett, Bernard K.en
dc.contributor.authorGrace, Deliaen
dc.contributor.authorHu Suk Leeen
dc.contributor.authorLindahl, Johanna F.en
dc.contributor.authorHung Nguyen-Vieten
dc.contributor.authorPhuc Pham-Ducen
dc.contributor.authorNguyen Huu Quyenen
dc.contributor.authorTran Anh Tuen
dc.contributor.authorTran Dac Phuen
dc.contributor.authorDang Quang Tanen
dc.contributor.authorVu Sinh Namen
dc.date.accessioned2019-12-02T13:18:41Zen
dc.date.available2019-12-02T13:18:41Zen
dc.identifier.urihttps://hdl.handle.net/10568/105978
dc.titleSpatiotemporal analysis of historical records (2001–2012) on dengue fever in Vietnam and development of a statistical model for forecasting risken
dcterms.abstractBackground Dengue fever is the most widespread infectious disease of humans transmitted by Aedes mosquitoes. It is the leading cause of hospitalization and death in children in the Southeast Asia and western Pacific regions. We analyzed surveillance records from health centers in Vietnam collected between 2001–2012 to determine seasonal trends, develop risk maps and an incidence forecasting model. Methods The data were analyzed using a hierarchical spatial Bayesian model that approximates its posterior parameter distributions using the integrated Laplace approximation algorithm (INLA). Meteorological, altitude and land cover (LC) data were used as predictors. The data were grouped by province (n = 63) and month (n = 144) and divided into training (2001–2009) and validation (2010–2012) sets. Thirteen meteorological variables, 7 land cover data and altitude were considered as predictors. Only significant predictors were kept in the final multivariable model. Eleven dummy variables representing month were also fitted to account for seasonal effects. Spatial and temporal effects were accounted for using Besag-York-Mollie (BYM) and autoregressive (1) models. Their levels of significance were analyzed using deviance information criterion (DIC). The model was validated based on the Theil’s coefficient which compared predicted and observed incidence estimated using the validation data. Dengue incidence predictions for 2010–2012 were also used to generate risk maps. Results The mean monthly dengue incidence during the period was 6.94 cases (SD 14.49) per 100,000 people. Analyses on the temporal trends of the disease showed regular seasonal epidemics that were interrupted every 3 years (specifically in July 2004, July 2007 and September 2010) by major fluctuations in incidence. Monthly mean minimum temperature, rainfall, area under urban settlement/build-up areas and altitude were significant in the final model. Minimum temperature and rainfall had non-linear effects and lagging them by two months provided a better fitting model compared to using unlagged variables. Forecasts for the validation period closely mirrored the observed data and accurately captured the troughs and peaks of dengue incidence trajectories. A favorable Theil’s coefficient of inequality of 0.22 was generated. Conclusions The study identified temperature, rainfall, altitude and area under urban settlement as being significant predictors of dengue incidence. The statistical model fitted the data well based on Theil’s coefficient of inequality, and risk maps generated from its predictions identified most of the high-risk provinces throughout the country.en
dcterms.accessRightsOpen Accessen
dcterms.audienceScientistsen
dcterms.available2019-11-27en
dcterms.bibliographicCitationBett, B., Grace, D., Hu Suk Lee, Lindahl, J., Hung Nguyen-Viet, Phuc Pham-Duc, Nguyen Huu Quyen, Tran Anh Tu, Tran Dac Phu, Dang Quang Tan and Vu Sinh Nam. 2019. Spatiotemporal analysis of historical records (2001–2012) on dengue fever in Vietnam and development of a statistical model for forecasting risk. PLOS ONE 14(11): e0224353.en
dcterms.issued2019-11-27en
dcterms.languageenen
dcterms.licenseCC-BY-4.0en
dcterms.publisherPublic Library of Scienceen
dcterms.subjectdiseasesen
dcterms.subjectrisken
dcterms.subjecthealthen
dcterms.subjectanimal diseasesen
dcterms.typeJournal Articleen

Files

License bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.75 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

ILRI articles in journals
CRP A4NH outputs
ILRI A4NH improving human health flagship outputs ( (2012-2021)
ILRI animal and human health program outputs (2017–2024)