Linking within-host immune dynamics to between-host transmission and reinfection risk.

The link between the virus and antibody dynamics of an infected host to the transmission of the virus to a susceptible population remains a central problem in science as it involves several complex and dynamic processes at different scales. In this study, we integrate deterministic and stochastic within-host models to explore multiscale transmission dynamics. Our methodology accounts for encounter frequency, within-host variability, and reinfection dynamics to assess their impact on epidemic progression. Our results show that within-host stochasticity disrupts synchronized viral peaks, leading to a more uniform transmission pattern and reducing the effectiveness of interventions targeting peak viral load. Considering the half-life of antibodies is 25 days, cycles of reinfections cannot be maintained in small populations, but reinfections become self-sustaining when a circular network exceeds 21 nodes, allowing indefinite circulation. These findings emphasize the need for integrating within-host dynamics in epidemic research.