A seasonal autoregressive integrated moving average model to predict incidence of dengue cases in Kuantan, Malaysia
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Abstract
A time series analysis model. Could provide useful information to facilitate the planning of public health interventions to minimize the frequency of dengue fever (DF) outbreaks. The objectives of this study were to analyze the trend of monthly DF cases from Kuantan, Malaysia during 2011-2019 to develop a seasonal autoregressive integrated moving average (SARIMA) model, test the accuracy of model parameters by forecasting monthly cases of DF in 2018 and comparing it with actual monthly cases of DF in 2018, and construct a SARIMA model, by adopting the Box-Jenkins method, to forecast the monthly DF cases in 2019. Monthly-confirmed DF cases from 2011 to 2018 fit the model while the prediction was validated using epidemiological data from January 2018 to December 2018. The study concluded that the SARIMA (0,1,0) (3,0,2)12 model was the best-fit and could be used to extrapolate case numbers up to 12 months in advance. Our predicted number of monthly DF cases in 2019 was relatively close to the actual number of monthly DF cases and fell within the confidence interval. Therefore, the SARIMA model developed by this study is capable of accurately forecasting and predicting future DF cases. This can help improve existing intervention programs, which are an integral component of minimizing the burden of the disease in Kuantan.
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References
Ahmad, N. M. G., Rozita, H., Mazrura, S., Zainudin, M. A., Hidayatulfathi, O., Faridah, M. Z., Ismail, N., and Choy, E. A. (2012). Dengue infections and circulating serotypes in Negeri Sembilan, Malaysia. Malaysian Journal of Public Health Medicine, 12(1), 21-30.
Bhatia, R., Dash, A. P., and Sunyoto, T. (2013). Changing epidemiology of dengue in South-East Asia. WHO South-East Asia Journal of Public Health, 2(1), 23-27.
Boudrioua, M. S., and Boudrioua, A. (2020). Modeling and forecasting the algerian stock exchange using the Box-Jenkins methodology. Journal of Economics, Finance and Accounting Studies, 1(1), 1-15.
Box, G. E., Jenkins, G. M., Reinsel, G. C., and Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control, 5th, New Jersey: John Wiley & Sons, pp. 52.
Bujang, M. A., Mudin, R. M. B., Haniff, J., Ikhwan, T. M., Sidik, T. A. B., Nordin, N. A. M., Sulaiman, N., Md-Sani, S. S., Kadir, S. S. A., Mohammed, S., and Pin, G. P. (2017). Trend of dengue infection in Malaysia and the forecast up until year 2040. International Medical Journal, 24(6), 438-441.
Chew, M. H., Rahman, M. M., Jelip, J., Hassan, M. R., and Isahak, I. (2012). All serotypes of dengue viruses circulating in Kuala Lumpur, Malaysia. Current Research Journal of Biological Sciences, 4(2), 229-234.
Cryer, J. D., and Chan, K. S. (2008). Time Series Analysis: with Applications in R, 2nd, New York: Springer Science & Business Media, pp. 191.
Dom, N. C., Hassan, A. A., Abd Latif, Z., and Ismail, R. (2013). Generating temporal model using climate variables for the prediction of dengue cases in Subang Jaya, Malaysia. Asian Pacific Journal of Tropical Disease, 3(5), 352-361.
Gjenero-Margan, I., Aleraj, B., Krajcar, D., Lesnikar, V., Klobučar, A., Pem-Novosel, I., Kurečić-Filipović, S., Komparak, S., Martić, R., Đuričić, S., Betica-Radić, L., Okmadžić, J., Vilibić-Čavlek, T., Babić-Erceg, A., Turković, B., Avšić-Županc, T., Radić, I., Ljubić, M., Šarac, K., Benić, N., and Mlinarić-Galinović, G. (2011). Autochthonous dengue fever in Croatia, August-September 2010. Eurosurveillance, 16(9), 19805.
Holmes, E. C., Tio, P. H., Perera, D., Muhi, J., and Cardosa, J. (2009). Importation and co-circulation of multiple serotypes of dengue virus in Sarawak, Malaysia. Virus Research, 143(1), 1-5.
Mia, M. S., Begum, R. A., Er, A. C., Abidin, R. D. Z. R., and Pereira, J. J. (2013). Trends of dengue infections in Malaysia, 2000-2010. Asian Pacific Journal of Tropical Medicine, 6(6), 462-466.
Mudin, R. N. (2015). Dengue incidence and the prevention and control program in Malaysia. IIUM Medical Journal Malaysia, 14(1), 5-9.
Nisalak, A., Clapham, H. E., Kalayanarooj, S., Klungthong, C., Thaisomboonsuk, B., Fernandez, S., Reiser, J., Srikiatkhachorn, A., Macareo, L. R., Lessler, J. T., Cummings, D. A. T., and Yoon, I. K., (2016). Forty years of dengue surveillance at a tertiary pediatric hospital in Bangkok, Thailand, 1973-2012. The American Journal of Tropical Medicine and Hygiene, 94(6), 1342-1347.
Phuthomdee, S., Soontornpipit, P., Viwatwongkasem, C., and Sillabutra, J. (2018). Dengue forecasting model using SARIMA model to predict the incidence of dengue in Thailand. Current Applied Science and Technology, 18(2), 58-65.
Skae, F. M. T. (1902). Dengue fever in Penang. British Medical Journal, 2(2185), 1581-1582.
Ler, T. S., Ang, L. W., Yap, G. S. L., Ng, L. C., Tai, J. C., James, L., and Goh, K. T. (2011). Epidemiological characteristics of the 2005 and 2007 dengue epidemics in Singapore – similarities and distinctions. Western Pacific Surveillance and Response Journal, 2(2), 24-29.
Thiruchelvam, L., Dass, S. C., Zaki, R., Yahya, A., and Asirvadam, V. S. (2018). Correlation analysis of air pollutant index levels and dengue cases across five different zones in Selangor, Malaysia. Geospatial Health, 13(1), 613.
Vaughn, D. W., Green, S., Kalayanarooj, S., Innis, B. L., Nimmannitya, S., Suntayakorn, S., Endy, T. P., Raengsakulrach, B., Rothman, A. L., Ennis, F. A., and Nisalak, A. (2000). Dengue viremia titer, antibody response pattern, and virus serotype correlate with disease severity. The Journal of Infectious Diseases, 181(1), 2-9.
Wallace, H. G., Lim, T. W., Rudnick, A., Knudsen, A. B., Cheong, W. H., and Chew, V. (1980). Dengue hemorrhagic fever in Malaysia: the 1973 epidemic. The Southeast Asian Journal of Tropical Medicine and Public Health, 11(1), 1-13.