Analysis of mitigation strategies for respiratory syncytial virus: perspectives from mathematical modeling

Respiratory Syncytial Virus (RSV) continues to pose a serious threat to global health, especially for young children, older adults, and people with weakened immune systems. Despite its impact, no vaccine has been licensed to prevent the disease, and there are many unanswered questions about the most effective ways to contain its spread, particularly when it comes to non-pharmaceutical measures. In this study, we developed a detailed mathematical model that captures the RSV transmission dynamics, including the often-overlooked roles of asymptomatic and post-symptomatic individuals. The model was comprehensively analyzed to confirm its well-posedness and analytical solutions, the basic reproduction number ( R 0 ) was determined, and used to determine whether the disease will fade out or persist in a population. Sensitivity analysis was performed using the Latin Hypercube Sampling (LHS) scheme to determine the factors that strongly influence the disease severity. Our findings show that reducing close contact between people, through measures like physical distancing or improved hygiene, has the greatest influence in containing the disease spread. On the other hand, efforts like widespread screening and isolating asymptomatic individuals only make a noticeable difference if contact rates are kept stable, and even then, their effect is limited. Simulations further revealed that early action is key where introducing preventive measures at the start of an outbreak can delay and lower the peak, easing pressure on healthcare systems. These insights suggest that public health policies should prioritize early, broad-based interventions and long-term solutions like vaccination over labor-intensive isolation strategies.