Vector-borne infectious disease mapping with stochastic difference equations: an analysis of dengue disease in Malaysia

Few publications consider the estimation of relative risk for vector-borne infectious diseases. Most of these articles involve exploratory analysis that includes the study of covariates and their effects on disease distribution and the study of geographic information systems to integrate patient-rel...

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Published inJournal of applied statistics Vol. 39; no. 9; pp. 2029 - 2046
Main Authors Samat, N. A., Percy, D. F.
Format Journal Article
LanguageEnglish
Published Abingdon Taylor & Francis 01.09.2012
Taylor & Francis Ltd
Subjects
dengue disease
Dengue fever
disease mapping
Disease transmission
Estimating
Geographic information systems
Health risk assessment
Infectious diseases
Mapping
Mathematical analysis
Populations
relative risk
Risk
Satellite navigation systems
SIR-SI models
Stochastic models
Stochasticity
Studies
tract-count data
Vectors (Biology)
Malaysia
ISEW, Malaysia
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Summary:Few publications consider the estimation of relative risk for vector-borne infectious diseases. Most of these articles involve exploratory analysis that includes the study of covariates and their effects on disease distribution and the study of geographic information systems to integrate patient-related information. The aim of this paper is to introduce an alternative method of relative risk estimation based on discrete time-space stochastic SIR-SI models (susceptible-infective-recovered for human populations; susceptible-infective for vector populations) for the transmission of vector-borne infectious diseases, particularly dengue disease. First, we describe deterministic compartmental SIR-SI models that are suitable for dengue disease transmission. We then adapt these to develop corresponding discrete time-space stochastic SIR-SI models. Finally, we develop an alternative method of estimating the relative risk for dengue disease mapping based on these models and apply them to analyse dengue data from Malaysia. This new approach offers a better model for estimating the relative risk for dengue disease mapping compared with the other common approaches, because it takes into account the transmission process of the disease while allowing for covariates and spatial correlation between risks in adjacent regions.
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ISSN:0266-4763
1360-0532
DOI:10.1080/02664763.2012.700450