Predicting dengue fever cases using Time Series Model and Hidden Markov Model in Sri Lanka

Abstract

Dengue fever is one of Sri Lanka's most serious health problems, wreaking havoc on the country's social and economic infrastructure. Dengue fever is a mosquito-borne viral disease that has recently risen considerably. A few studies were conducted using time series analysis to investigate the dengue outbreak in Sri Lanka. It does not appear that the models' accuracy can be leveraged to produce more accurate forecasts. The objective of this study is to develop Markov and time series models for forecasting monthly dengue patients in Sri Lanka and identify the most suitable model. The findings of this study are critical for many stakeholders, including the medical community and policymakers, to allocate health resources and create prevention programs. According to the statistical analysis, the highest number of dengue cases were recorded in the western province. The highest number of dengue cases were recorded in July 2017 (41,121) when considering the data from 2010-January to 2021-August.