Coupling the within-host process and between-host transmission of COVID-19 suggests vaccination and school closures are critical
We develop a data-driven COVID-19 model linking the within-host viral dynamics to the between-host transmission dynamics on a multi-layer contact network to investigate the potential factors driving transmission dynamics and to inform how school closures and antiviral treatment influence the epidemic. Using multi-source data, we initially determine the viral dynamics and estimate the relationship between viral load and infectiousness. Then, we embed the viral dynamics model into a four-layer contact network and formulate an agent-based model to simulate between-host transmission. The results illustrate that the heterogeneity of immune response between children and adults and between vaccinated and unvaccinated infections can reproduce different transmission patterns. We find that school closures play a significant effect on mitigating the pandemic as more adults get vaccinated and the virus mutates. If enough infected individuals are diagnosed by testing before symptom onset and then treated quickly, the transmssion can also be effectively curbed. Our multiscale model reveals the critical role played by younger individuals and antiviral treatment with testing in controlling the epidemic.