Breakpoint Estimation Using Age-Based SIR Model on COVID -19 Epidemic in Bangladesh

COVID-19 has disrupted the harmonic rhythm of civilized societies worldwide, including Bangladesh. The impact of this all-encompassing pandemic situation has spread across the globe and has also affected Bangladesh. COVID-19 prediction and breakpoint estimation have garnered significant attention for facilitating the recovery of a normal and healthy life. The SIR (Susceptible-Infected-Removed/Recovered) model is a widely-used epidemiological model employed for breakpoint estimation and prediction. Breakpoint estimation represents the point at which the curve reaches its highest peak position. In this study, we propose a variant of the SIR model, specifically an age-based SIR model, to estimate the breakpoint of the COVID-19 pandemic in Bangladesh. Our approach considers the age distribution of the population, recognizing its significant impact on disease spread and mortality rates. We focus on the effectiveness of age-specific contamination and treatment efforts to assess their role in combating the pandemic. To examine the impact of age categories, we compare results across selected groups based on different population factors. The findings indicate that middle-aged people are the most vulnerable group. Consequently, we excluded the less vulnerable groups and estimated the breakpoint using data from the most vulnerable age groups. The results from the age-based SIR model demonstrate a minimization of the gap between the predicted model and actual data points. Thus, the selected age groups exhibit better performance compared to considering all populations. This prediction serves to raise awareness among people, helping them understand the severity of this pandemic.