Work

Mathematical Modeling of Vaccines That Prevent SARS-CoV-2 Transmission

Year: 2021

Type: article

Abstract: Ongoing SARS-CoV-2 vaccine trials assess vaccine efficacy against disease (VE DIS ), the ability of a vaccine to block symptomatic COVID-19. They will only partially discriminate whether VE DIS is mediated by preventing infection as defined by the detection of virus in the airways (vaccine efficacy against infection defined as VE SUSC ), or by preventing symptoms despite breakthrough infection (vaccine efficacy against symptoms or VE SYMP ). Vaccine efficacy against infectiousness (VE INF ), defined as the decrease in secondary transmissions from infected vaccine recipients versus from infected placebo recipients, is also not being measured. Using mathematical modeling of data from King County Washington, we demonstrate that if the Moderna and Pfizer vaccines, which have observed VE DIS >90%, mediate VE DIS predominately by complete protection against infection, then prevention of a fourth epidemic wave in the spring of 2021, and associated reduction of subsequent cases and deaths by 60%, is likely to occur assuming rapid enough vaccine roll out. If high VE DIS is explained primarily by reduction in symptoms, then VE INF >50% will be necessary to prevent or limit the extent of this fourth epidemic wave. The potential added benefits of high VE INF would be evident regardless of vaccine allocation strategy and would be enhanced if vaccine roll out rate is low or if available vaccines demonstrate waning immunity. Finally, we demonstrate that a 1.0 log vaccine-mediated reduction in average peak viral load might be sufficient to achieve VE INF =60% and that human challenge studies with 104 infected participants, or clinical trials in a university student population could estimate VE SUSC , VE SYMP and VE INF using viral load metrics.

Source: Viruses

DOI: 10.3390/v13101921