Abstract—In this paper we analyze the time-series data to study the association between dengue incidence and weather variables such as temperature and humidity while taking into account the delayed effects and further discussing the differences between using short term data (yearly) and long term data in Singapore from 2000 to 2010. The time-series analysis and statistical analysis method are employed to determine the delay in timing between the incidence of dengue fever and weather variables. The results are not only consistent with previous results of other researchers, but also provide new findings. We analyze the data from each year (short term time series data) and 10-year data (long term time series data) and find that the use of both the short term data and the long term data can provide complementary insights into the relationship between dengue incidence and weather variables.
Index Terms—Dengue, temperature, time-lag, time series analysis.
Z. Wang, H. M. Chan, T. Y. Zhang and Gary Lee are with Department of Computing Science, the institute of high performance computing, Singapore (email: firstname.lastname@example.org; email@example.com; firstname.lastname@example.org; email@example.com)
Pauline Aw Poh Kim and Martin L. Hibberd are with Genome Institute of Singapore (e-mail: firstname.lastname@example.org; email@example.com).
Cite: Zhaoxia Wang, Hoong Maeng Chan, Tianyou Zhang, Pauline AW Poh Kim, Martin L. Hibberd, and Gary Kee Khoon Lee, "Delayed Effects of Weather Variables on Incidence of Dengue Fever in Singapore from 2000-2010," International Journal of Environmental Science and Development vol. 3, no. 2, pp. 194-198, 2012.