Insights into Cytomegalovirus Transmission Dynamics: Bridging the Gap between Mathematical Modeling and Public Health Strategies

Abstract

This mini-review delves into the crucial role of mathematical modeling in understanding cytomegalovirus (CMV) transmission dynamics. While infectious disease modeling often focuses on the population level, it is essential to recognize that immune development takes place at the individual level. This review explores recent advancements in both stochastic and deterministic modeling approaches and their contributions to our understanding of CMV transmission. Stochastic modeling enables us to investigate the efficiency and risk factors associated with CMV transmission in high- risk populations, such as hematopoietic stem cell transplantation (HCT) recipients, shedding light on factors influencing transmission. Deterministic modeling emphasizes the importance of viral replication, immune response, transmission efficiency, and the role of vectors. It underlines the need for a comprehensive understanding of these factors to develop effective prevention and control strategies. Integrated deterministic and stochastic models offer a holistic perspective, explaining phenomena like prolonged oral CMV shedding during primary infection and highlighting the importance of timing and immune suppression levels in transplacental transmission risk. In conclusion, these modeling insights can be integrated into public health strategies for CMV management, including targeted pre- transplant screening, enhanced post-transplant surveillance, optimized immunebased interventions, minimized transmission risks in HCT, vector control, and timing-sensitive intervention guidelines. This comprehensive approach can substantially enhance CMV prevention and control efforts, benefiting vulnerable populations and the broader community.