Dengue in Tomorrow: Predictive Insights From ARIMA and SARIMA Models in Bangladesh: A Time Series Analysis
Year: 2024
Type: article
Abstract: ABSTRACT Backgrounds and Aims Dengue fever has been a continued public health problem in Bangladesh, with a recent surge in cases. The aim of this study was to train ARIMA and SARIMA models for time series analysis on the monthly prevalence of dengue in Bangladesh and to use these models to forecast the dengue prevalence for the next 12 months. Methods This secondary data‐based study utilizes AutoRegressive Integrated Moving Average (ARIMA) and Seasonal AutoRegressive Integrated Moving Average (SARIMA) models to forecast dengue prevalence in Bangladesh. Data was sourced from the Institute of Epidemiology Disease Control and Research (IEDCR) and the Directorate General of Health Services (DGHS). STROBE Guideline for observational studies was followed for reporting this study. Results The ARIMA (1,1,1) and SARIMA (1,1,2) models were identified as the best‐performing models. The forecasts indicate a steady dengue prevalence for 2024 according to ARIMA, while SARIMA predicts significant fluctuations. It was observed that ARIMA (1,1,1) and SARIMA (1,2,2) (1,1,2) 12 were the most suitable models for prediction of dengue prevalence. Conclusion These models offer valuable insights for healthcare planning and resource allocation, although external factors and complex interactions must be considered. Dengue prevalence is expected to rise in future in Bangladesh.
Source: Health Science Reports
DOI: 10.1002/hsr2.70276
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,120
OpenAlex ID: W4405547795