Seroprevalence and attainment of herd immunity against SARS CoV-2: A modelling study

Paul, A.; Kadnur, H. B.; Ray, A.; Chatterjee, S.

Objective: The present study is aims to predict the likelihood of and likely time required to attain herd immunity against COVID-19 in New Delhi due to natural infection. Method: An ODE based mathematical model was constructed by extending the classical SEIR model to predict the seroprevalence rate in Delhi. We estimated the parameter values for Delhi using available data (reported cases and the seroprevalence rate) and used them for future prediction. We also attempted to capture the changes in the seroprevalence rate with different possibilities of reinfection. Results: Maximum seroprevalence rate obtained through our model is 31.65% and also a reduction in the seroprevalence rate was observed for the upcoming one month (month of January, 2021) due to the reduced transmission rate. After increasing the transmission rate to the value same as the third wave in New Delhi, we obtained a maximum value of 54.96%. This maximum value significantly decreased with the reduction in the reinfection possibilities. Also, a little impact of the duration of persistence of antibodies, 180 vs 105 days, was observed on the maximum seroprevalence. Conclusion: This modelling study suggests that natural infection alone, as gauged by serial sero-surveys, will not result in attainment of herd immunity in the state of Delhi.