Modeling the SARS-CoV-2 epidemic and the efficacy of different vaccines across different network structures

Abstract

We developed a network-based SEIRV model to test different vaccine efficacies on SARS-CoV-2 ( Betacoronavirus pandemicum ) dynamics in a naive population of 25,000 susceptible adults. Different vaccine efficacies, derived from data, were administered at different rates across a range of different Watts-Strogatz network structures. The model suggests that differences among vaccines were of minor importance compared to vaccination rates and network structure. Additionally, we tested the effect of strain differences in transmissibility ( R 0 values of 2.5 and 5.0) and found that this was the most important factor influencing the number of individuals ultimately infected. However, network structure was most important in affecting the maximum number of individuals that were infectious during the epidemic peak. The interaction of network structure, vaccination effort, and difference in strain transmissibility was highly significant for all epidemic metrics. The model suggests that differences in vaccine efficacy are not as important as vaccination rate in reducing epidemic sizes. Further, the importance of the evolution of viral transmission rates and our ability to develop effective vaccines to combat these strains will be of primary concern for our ability to control future disease epidemics.