Abstract

The COVID-19 pandemic brought a big shock to public health systems in many countries. In this article, we aim to provide guidance to the COVID-19 control and mitigation plan that consist of vaccination and testing measures. We developed a compartmental model that was parameterized with US demographics data. The model presents a decision-analytic approach for estimating the testing needed with existing vaccination rates and ICU capacity of a population. Firstly, our results show that vaccination strategy can effectively reduce the peak, and testing strategy can effectively delay the occurrence of peak infection while mitigating the peak infection. Secondly, our results indicate that a strategical combination of testing and vaccination plan can help the U.S to achieve herd immunity at a different stage of the pandemic. Thirdly, our approach can suggest the testing need to decision makers based on the local ICU capacity of different places. Most importantly, with unpredictable COVID-19 waves, our approach can provide a real-time solution to help decision makers adequately optimize the scarce public health resources and increase the impact of the mitigation plan.