COVID-19 pandemic in India: Modelling, forecasting and risk assessment
- Biometrics & Biostatistics International Journal
KK Jose,1,2 Jilby C Jose,1 Liji Anna Varghese,1 Vivek S Nair1
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Amid the relentless spread of COVID-19 pandemic, India spiked to the fifth rank among the nations on the daily increase of death toll during August 2020. In this scenario, the study mainly focuses on appalling and unprecedented COVID-19 mortality in India. The most adaptable epidemiological index for measuring the severity of the disease is Case Fatality Rate (CFR) and is estimated using the Yoshikura method. The estimated CFR of 10 states in India is compared along with the general formula of CFR and Kerala is found to be having the least CFR of 0.40% indicating the least severity of disease. The steadily increasing deaths in India are modelled using probability distributions such as Weibull, Gamma, and Lognormal in order to obtain the best fitted model with the data. The study demonstrated that the Gamma distribution is the best fitting probability model. Time-series modelling is used to analyse the trend and forecasting pattern of mortality. The ARIMA model indicates an ascending trend of death in upcoming days and this prescient model gives help to the administrative authorities and medical personnel in health care service and infrastructure arrangements in forthcoming days. The major mitigation step to resolve and restrain the pandemic is vaccination.
COVID-19, CFR, yoshikura method, distribution, time series analysis, ARIMA