Assessing Weather Effects on Dengue Disease in Malaysia

Yoon Ling Cheong, Katrin Burkart, Pedro J. Leitão and Tobia Lakes
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Yoon Ling Cheong: Geoinformation Science Lab, Department of Geography, Humboldt-Universität zu Berlin, Unter den Linden 6, Berlin 10099, Germany
Katrin Burkart: Climatological Section, Department of Geography, Humboldt-Universität zu Berlin, Unter den Linden 6, Berlin 10099, Germany
Pedro J. Leitão: Geomatics Lab, Department of Geography, Humboldt-Universität zu Berlin, Unter den Linden 6, Berlin 10099, Germany
Tobia Lakes: Geoinformation Science Lab, Department of Geography, Humboldt-Universität zu Berlin, Unter den Linden 6, Berlin 10099, Germany

IJERPH, 2013, vol. 10, issue 12, 1-16

Abstract: The number of dengue cases has been increasing on a global level in recent years, and particularly so in Malaysia, yet little is known about the effects of weather for identifying the short-term risk of dengue for the population. The aim of this paper is to estimate the weather effects on dengue disease accounting for non-linear temporal effects in Selangor, Kuala Lumpur and Putrajaya, Malaysia, from 2008 to 2010. We selected the weather parameters with a Poisson generalized additive model, and then assessed the effects of minimum temperature, bi-weekly accumulated rainfall and wind speed on dengue cases using a distributed non-linear lag model while adjusting for trend, day-of-week and week of the year. We found that the relative risk of dengue cases is positively associated with increased minimum temperature at a cumulative percentage change of 11.92% (95% CI: 4.41–32.19), from 25.4 °C to 26.5 °C, with the highest effect delayed by 51 days. Increasing bi-weekly accumulated rainfall had a positively strong effect on dengue cases at a cumulative percentage change of 21.45% (95% CI: 8.96, 51.37), from 215 mm to 302 mm, with the highest effect delayed by 26–28 days. The wind speed is negatively associated with dengue cases. The estimated lagged effects can be adapted in the dengue early warning system to assist in vector control and prevention plan.

Keywords: dengue risk; weather effects; time-lag effects; generalized additive model (GAM); distributed non-linear lag model (DLNM); time series analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:10:y:2013:i:12:p:6319-6334:d:30760

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