Modeling the population effects of epitope specific escape mutations in SARS-CoV-2 to guide vaccination strategies
Published Web Locationhttps://doi.org/10.1101/2021.01.19.21250114
Escape mutations (EM) to SARS-Cov-2 have been detected and are spreading. Vaccines may need adjustment to respond to these or future mutations. We designed a population level model integrating both waning immunity and EM. We also designed a set of criteria for elaborating and fitting this model to cross-neutralization and other data in a manner that minimizes vaccine decision errors. We formulated four model variations. These define criteria for which prior infections provide immunity that can be escaped. They also specify different sequences where one EM follows another. At all reasonable parameter values, these model variations led to patterns where: 1) EM were rare in the first epidemic, 2) rebound epidemics after the first epidemic were accelerated more by increasing drifting than by increasing waning (with some exceptions), 3) the long term endemic level of infection was determined mostly by waning rates with small effects of the drifting parameter, 4) EM caused loss of vaccine effectiveness and under some conditions, vaccines induced EM that caused higher levels of infection with vaccines than without them. The differences and similarities across the four models suggest paths for developing models specifying the epitopes where EM act. This model is a base on which to construct epitope specific evolutionary models using new high-throughput assay data from population samples to guide vaccine decisions.