Abstract
Dengue fever is now a serious problem for public health. The number of dengue affected cases has dramatically increased worldwide in recent years. There was an ongoing rise in the number of cases that were reported, particularly in Bangladesh. The objective of the study is to determine the best dengue prediction model using time series data and to forecast monthly dengue occurrence in 2022. The monthly data gathered from January 2017 to December 2021 have been validated using Seasonal Autoregressive Integrated Moving Average (SARIMA) models. Based on a number of factors, the SARIMA (1,0,0)(1,1,1)12 model was selected as the best fit model and used to predict the next epidemic for the period from January 2022 to December 2022. The outcome indicates a rise in dengue fever cases during August 2022, with an anticipated 6,410 cases. The acquired model will be utilized as a tool for the forecast of dengue cases.
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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Mohammed, N., Rahman, M. (2023). Forecasting Dengue Incidence in Bangladesh Using Seasonal ARIMA Model, a Time Series Analysis. In: Satu, M.S., Moni, M.A., Kaiser, M.S., Arefin, M.S. (eds) Machine Intelligence and Emerging Technologies. MIET 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 491. Springer, Cham. https://doi.org/10.1007/978-3-031-34622-4_47
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DOI: https://doi.org/10.1007/978-3-031-34622-4_47
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