Abstract
BackgroundDengue remains an important public health problem in Timor-Leste, with several major epidemics occurring over the last 10 years. The aim of this study was to identify dengue clusters at high geographical resolution and to determine the association between local environmental characteristics and the distribution and transmission of the disease.MethodsNotifications of dengue cases that occurred from January 2005 to December 2013 were obtained from the Ministry of Health, Timor-Leste. The population of each suco (the third-level administrative subdivision) was obtained from the Population and Housing Census 2010. Spatial autocorrelation in dengue incidence was explored using Moran’s I statistic, Local Indicators of Spatial Association (LISA), and the Getis-Ord statistics. A multivariate, Zero-Inflated, Poisson (ZIP) regression model was developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using Bayesian Markov chain Monte Carlo (MCMC) simulation with Gibbs sampling.ResultsThe analysis used data from 3206 cases. Dengue incidence was highly seasonal with a large peak in January. Patients ≥ 14 years were found to be 74% [95% credible interval (CrI): 72–76%] less likely to be infected than those < 14 years, and females were 12% (95% CrI: 4–21%) more likely to suffer from dengue as compared to males. Dengue incidence increased by 0.7% (95% CrI: 0.6–0.8%) for a 1 °C increase in mean temperature; and 47% (95% CrI: 29–59%) for a 1 mm increase in precipitation. There was no significant residual spatial clustering after accounting for climate and demographic variables.ConclusionsDengue incidence was highly seasonal and spatially clustered, with positive associations with temperature, precipitation and demographic factors. These factors explained the observed spatial heterogeneity of infection.
Highlights
Dengue remains an important public health problem in Timor-Leste, with several major epidemics occurring over the last 10 years
Using geographical information system (GIS) and a Bayesian statistical framework, the present study aims to quantify the spatio-temporal patterns of notified dengue incidence in Timor-Leste between 2005 and 2013, to identify dengue clusters in the country at a high geographical resolution and to visualise smoothed patterns of dengue risk
In the best-fit model (Model I), individuals aged ≥ 14 years were found to be 74% (95% credible interval (CrI): 72–76%) less likely to have a dengue infection than children aged < 14 years, and females were 12% (95% CrI: 4–21%) more likely to suffer from dengue when compared to males
Summary
Dengue remains an important public health problem in Timor-Leste, with several major epidemics occurring over the last 10 years. Aedes mosquitoes commonly breed in Dengue fever (DF) is the most common mosquito-borne viral disease in the world, with an estimated 20,000 deaths occurring per year as a result of severe cases of dengue, 50–100 million people being infected each year and 2.5 billon people living in at risk areas [12,13,14]. In the 1970s only nine countries were affected by dengue epidemics; epidemics are reported in more than 100 countries, making dengue an international public health problem with an increasing disease burden and an expanding geographical range [12, 13, 15]. Dengue transmission occurs in all countries of the World Health Organization (WHO) South-East Asia region (SEAR), except North Korea, accounting for up to two-thirds of the global
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