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

Samat, NA and Percy, DF 2012, 'Vector borne infectious disease mapping with stochastic difference equations: An analysis of dengue disease in Malaysia' , Journal of Applied Statistics, 39 (9) , pp. 2029-2046. (In Press)

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Abstract

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. Firstly, we describe deterministic compartmental SIR-SI models that are suitable for dengue disease transmission. We then adapt these to develop corresponding discrete timespace 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 to 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.

Item Type: Article
Themes: Health and Wellbeing
Schools: Colleges and Schools > College of Business & Law
Colleges and Schools > College of Business & Law > Salford Business School > Management Science and Statistics
Colleges and Schools > College of Business & Law > Salford Business School
Journal or Publication Title: Journal of Applied Statistics
Publisher: Taylor & Francis
Refereed: Yes
ISSN: 0266-4763
Related URLs:
Funders: Ministry of Health, Malaysia
Depositing User: Professor David F. Percy
Date Deposited: 10 May 2012 14:22
Last Modified: 18 Sep 2013 11:38
URI: http://usir.salford.ac.uk/id/eprint/22616

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