An Enhanced SEIR Model for Prediction of COVID-19 with Vaccination Effect

Currently, the spread of COVID-19 is running at a constant pace. The current situation is not so alarming, but every pandemic has a history of three waves. Two waves have been seen, and now expecting the third wave. Compartmental models are one of the methods that predict the severity of a pandemic. An enhanced SEIR model is expected to predict the new cases of COVID-19. The proposed model has an additional compartment of vaccination. This proposed model is the SEIRV model that predicts the severity of COVID-19 when the population is vaccinated. The proposed model is simulated with three conditions. The first condition is when social distancing is not incorporated, while the second condition is when social distancing is included. The third one condition is when social distancing is combined when the population is vaccinated. The result shows an epidemic growth rate of about 0.06 per day, and the number of infected people doubles every 10.7 days. Still, with imparting social distancing, the proposed model obtained the value of R-0 is 1.3. Vaccination of infants and kids will be considered as future work.

Automated summary

Currently, COVID-19 is spreading at a consistent pace with the expectation of a third wave. Compartmental models, such as the enhanced SEIRV model, are used to predict the severity of the pandemic. The proposed model incorporates vaccination as an additional compartment to analyze the impact on COVID-19 severity. Simulations under different conditions show that social distancing measures can slow down the epidemic growth rate. The vaccination of infants and children is considered for future work.