ABSTRACT

Background: India was under a grave threat from the second wave of the COVID-19 pandemic, particularly at the beginning of March 2021. The situation became critical as the cases increased alarmingly around the months April to August 2021 compared to the first wave of coronavirus. The Indian government has implemented various control measures such as lockdowns putting travel restrictions at various stages to restrict the spread of the virus from the initial outbreak of the pandemic. Recently, we have studied the susceptible-exposed-Quarantined-infectious-removed (SEQIR) dynamic modeling of the epidemic evolution of COVID-19 in India with the help of appropriate parameters in this present article, we extend our analysis to estimate and analyze the number of infected individuals during the second wave of COVID-19 in India with the help of the above SEQIR model. Methods: We integrated the most updated COVID-19 epidemiological data into the Susceptible-Exposed-Quarantine-Infectious- Removed (SEQIR) model to derive the epidemic curve. We implemented parameter estimations to predict the nature of the epidemic. Results: Our findings show that the people’s effort along with governmental actions such as execution of restrictions is an important factor to control the pandemic in the present situation and the future. Conclusions: Our dynamic SEQIR model was effective in predicting the COVID-19 epidemic peaks and sizes. Keywords: Coronavirus disease 2019 (COVID-19; modeling; Susceptible-Exposed-Quarantined- Infectious-Removed (SEQIR)
Publication date: 01/02/2023

https://ijbpas.com/pdf/2023/February/MS_IJBPAS_2023_6846.pdf

Download PDF
https://doi.org/10.31032/IJBPAS/2023/12.2.6846