Modeling the influence of vaccine administration on COVID-19 testing strategies (preprint)

ABSTRACT

Vaccination is considered the best strategy for limiting and eliminating the COVID-19 pandemic. The success of this strategy relies on the rate of vaccine deployment and acceptance across the globe. As these efforts are being conducted, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus is continuously mutating, which leads to the emergence of variants with increased transmissibility, virulence, and lower response the vaccines. One important question is whether surveillance testing is still needed in order to limit SARS-CoV-2 transmission in an increasingly vaccinated population. In this study, we developed a multi-scale mathematical model of SARS-CoV-2 transmission in a vaccinated population and used it to predict the role of testing in an outbreak with alpha and delta variants. We found that, when the alpha variant is dominant, testing is effective when vaccination levels are low to moderate and its impact is diminished when vaccination levels are high. When the delta variant is dominant, widespread vaccination is necessary in order to prevent significant outbreaks. When only moderate vaccination can be achieved, frequent testing can significantly reduce the cumulative size of delta variant outbreak, with the impact of testing having maximum effects when focused on the non-vaccinated population.