Mathematical Modeling Based Study and Prediction of COVID-19 Epidemic Dissemination Under the Impact of Lockdown in India
India, covid-19, lockdown, underreporting, SEIRD model, epidemic peak
COVID-19 (SARS-CoV-2) is rapidly spreading in South Asian countries, especially in India. India is the fourth most COVID-19 affected country at present i.e., until July 10, 2020. With limited medical facilities and high transmission rate, the study of COVID-19 progression and its subsequent trajectory needs to be analyzed in India. Epidemiologic mathematical models have the potential to predict the epidemic peak of COVID-19 under different scenarios. Lockdown is one of the most effective mitigation policies adopted worldwide to control the transmission rate of COVID-19 cases. In this study, we use an improvised five compartment mathematical model, i.e., Susceptible (S)-Exposed (E)-Infected (I)-Recovered (R)-Death (D) (SEIRD) to investigate the progression of COVID-19 and predict the epidemic peak under the impact of lockdown in India. The aim of this study is to provide a more precise prediction of epidemic peak and to evaluate the impact of lockdown on epidemic peak shift in India. For this purpose, we examine the most recent data (from January 30, 2020 to July 10, 2020 i.e., 160 days) to enhance the accuracy of outcomes obtained from the proposed model. The model predicts that the total number of COVID-19 active cases would be around 5.8 × 105 on August 15, 2020 under current circumstances. In addition, our study indicates the existence of under-reported cases i.e., 105 during the post-lockdown period in India. Consequently, this study suggests that a nationwide public lockdown would lead to epidemic peak suppression in India. It is expected that the obtained results would be beneficial for determining further COVID-19 mitigation policies not only in India but globally as well.
Vipin Tiwari, Namrata Deyal, Nandan S. Bisht