A Delay Differential Model for Antiviral Treatment and Rebound Dynamics.

Publication date: Jul 08, 2026

Rebound, arising from an increase in viral load after initial treatment to levels sufficient for renewed infectiousness, has been observed in COVID-19 patients, prompting concerns about patient outcomes and potential implications for transmission and disease control. To assess the impact of viral rebound on post-treatment transmission dynamics, we developed a delay differential model parameterised with characteristics of SARS-CoV-2 infection and the rebound risk observed during treatment with Paxlovid. The model explicitly accounts for the timing of treatment initiation relative to symptom onset and the duration of treatment. By varying the relative transmissibility of individuals experiencing rebound, our simulations show that rebound events comprise only a small proportion of treated cases when treatment initiation is delayed after symptom onset or when treatment duration is extended beyond the standard five-day course. However, as the proportion of symptomatic individuals receiving treatment increases, the transmissibility of rebound infections becomes a dominant factor in disease spread. A short, five-day treatment course can amplify rebound-associated transmission and substantially increase total infections when rebound transmissibility is high. In contrast, extending treatment duration from five to eight days markedly reduces the contribution of rebound cases to overall spread. Both delayed initiation and extended treatment duration decrease the risk of viral rebound, underscoring a trade-off between reducing acute transmission and mitigating post-treatment resurgence. These findings highlight the importance of integrating rebound risk into antiviral deployment strategies to improve patient outcomes and enhance population-level disease control.

Semantics

Original Article