Bayesian spatial and spatio-temporal approaches to modelling dengue fever: a systematic review

Aswi, Aswi and Cramb, Susanna and Moraga, Paula and Mengersen, Kerrie L. (2018) Bayesian spatial and spatio-temporal approaches to modelling dengue fever: a systematic review. Epidemiology and Infection, 147 (e33). pp. 1-14.

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Abstract

Dengue fever (DF) is one of the world’s most disabling mosquito-borne diseases, with avariety of approaches available to model its spatial and temporal dynamics. This paperaims to identify and compare the different spatial and spatio-temporal Bayesian modelling methods that have been applied to DF and examine influential covariates that have been reportedly associated with the risk of DF. A systematic search was performed in December 2017, using Web of Science, Scopus, ScienceDirect, PubMed, ProQuest and Medline (via Ebscohost) electronic databases. The search was restricted to refereed journal articles pub�lished in English from January 2000 to November 2017. Thirty-one articles met the inclusion criteria. Using a modified quality assessment tool, the median quality score across studies was 14/16. The most popular Bayesian statistical approach to dengue modelling was a generalised linear mixed model with spatial random effects described by a conditional autoregressive prior. A limited number of studies included spatio-temporal random effects. Temperature and precipitation were shown to often influence the risk of dengue. Developing spatio-tem�poral random-effect models, considering other priors, using a dataset that covers an extended time period, and investigating other covariates would help to better understand and control DF transmission

Item Type:	Article
Uncontrolled Keywords:	Bayesian model; dengue; spatial; spatio-temporal; systematic review
Subjects:	FMIPA > STATISTIKA - (S1) FMIPA KARYA ILMIAH DOSEN Universitas Negeri Makassar > KARYA ILMIAH DOSEN
Divisions:	KOLEKSI KARYA ILMIAH UPT PERPUSTAKAAN UNM MENURUT FAKULTAS > KARYA ILMIAH DOSEN KARYA ILMIAH DOSEN
Depositing User:	Dr. Aswi Aswi
Date Deposited:	05 Oct 2021 06:44
Last Modified:	02 Aug 2022 10:05
URI:	http://eprints.unm.ac.id/id/eprint/21178

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