Viral dynamics of the Respiratory Syncytial Virus during experimental challenge infections: insights for transmission and treatment
Clarisse Schumer1, Pascal Lukas2, Frederik Graw2, Slim Fourati3,4, Alex Mann5, Jérémie Guedj1
1Université Paris Cité, IAME, INSERM F, 2Department of Medicine 5, Friedrich-Alexander-University Erlangen-Nürnberg and Universitätsklinikum Erlangen, 3IMRB INSERM U955, Team « Viruses, Cancer », Hepatology, 4Department of Virology, Hôpitaux Universitaires Henri Mondor, Assistance Publique – Hôpitaux de Paris,INSERM U955 France , 5hVivo, London, United Kingdom
Introdu+E3:E26ction: Respiratory syncytial virus (RSV) is a major public health concern, particularly in infants and elderly (1). Despite its epidemiological burden, the severity of RSV infection is largely underestimated, and the scarcity of data available has limited the development of mathematical models to characterize host-pathogen interaction in RSV infection. Consequently fundamental aspects of virus pathogenesis remain poorly understood, such as its viral dynamics, the duration of infectiousness, the onset of adaptive immunity or the optimal treatment window for potential antiviral treatment strategies (2)(3)(4). In that perspective, experimental challenge studies provide unique insights to characterize in detail within-host infection kinetics, as shown during Covid-19 Pandemic (5). Objective: Here we aimed to couple a mathematical modelling approach with high-resolution experimental challenge study data to uncover fundamental aspects of RSV infection: •Characterize RSV viral dynamics and its variability in the population •Estimate basic within-host and epidemiological metrics •Anticipate the antiviral efficacy of direct antiviral agents and monoclonal antibodies Methods: We analyzed data from 252 RSV infected individuals aged between 18 and 45 years who participated in experimental challenge studies with frequent sampling of both RNA viral load (V) and infectious virus (VI). For the construction of the model, we started with a target cell limited (TCL) model and sequentially incorporated innate and adaptive immune responses. We also defined the relationship between VI and V. Model selection was done by using the corrected Bayesian Information Criterion (BICc.) We computed key metrics, including area under viral curve (AUC), time to viral peak, time to viral clearance and the generation time which is the mean interval between infection of a primary case and his secondary case. Finally, we evaluated the efficacy of different antiviral treatment strategies, depending on the timing of administration (prior or after exposure), the mechanism of action (neutralizing virus or blocking viral production), the drug EC50 and the duration of protection. Results: Our analysis reveals that infectious titers increase sub-linearly relative to viral RNA levels. Adaptive immunity was estimated to start around day 7 post-infection, with humoral immunity driving a decrease in infectivity and cell-mediated immunity significantly reducing cell lifespan (infected cell half-life) decreasing from 1.38 to 0.12 days. Infectious virus was cleared by day 8 (95% prediction interval: 5-10 days), while viral RNA persisted until day 12 (95% prediction interval: 8-15 days.) The probability of detectable infectious virus was close to 0 after day 8, regardless of viral load level. Using the model to simulate post-exposure prophylaxis of a putative drug, we found that a 7-day treatment with average drug concentrations greater than the drug EC90 was required to reduce AUC of viral load and infectiousness by more than 80%, but the impact on the time to viral clearance was more modest. Pre-exposure prophylaxis with monoclonal antibodies could achieve more than 80% on both AUC and time to clearance. Conclusion: The combination of a rich dataset and a mathematical model enables the first detailed characterization of RSV within-host dynamics, capturing both population-level trends and individual variability. Our findings suggest that an 8-day isolation period post-infection could limit RSV transmission. Additionally, our treatment simulations highlight the challenges in achieving optimal virological efficacy. These results offer valuable guidance for the optimization of RSV treatment strategies in clinical trials.