A novel compartmental model to capture the nonlinear trend of COVID-19

The COVID-19 pandemic took the world by surprise and surpassed the expectations of epidemiologists, governments, medical experts, and the scientific community as a whole. The majority of epidemiological models failed to capture the non-linear trend of the susceptible compartment and were unable to model this pandemic accurately. This study presents a variant of the well-known SEIRD model to account for social awareness measures, variable death rate, and the presence of asymptomatic infected individuals. The proposed SEAIRDQ model accounts for the transition of individuals between the susceptible and social awareness compartments. We tested our model against the reported cumulative infection and death data for different states in the US and observed over 98.8% accuracy. Results of this study give new insights into the prevailing reproduction number and herd immunity across the US.

Automated summary

The COVID-19 pandemic caught the world off guard and exceeded the predictions of experts. The proposed SEAIRDQ model, testing against US state data, showed over 98.8% accuracy and provided new insights into the pandemic control strategy.