Modeling Intervention Strategies to Control Hepatitis C Outbreak and Related Mortality in Bangladesh

Hepatitis C virus (HCV) remains a critical public health concern globally, including in Bangladesh. In this study, we employed a mathematical modeling framework to analyze the national dynamics of HCV infections and associated mortality in Bangladesh. Utilizing surveillance data from the Directorate General of Health Services, we examined the epidemiological trajectory of HCV and assessed the impact of various intervention strategies. The Next Generation Matrix approach was employed to derive basic reproduction numbers, and the model was calibrated with observed HCV incidence data to estimate some model parameter values. We conducted sensitivity analysis to assess how variations in model parameters affect HCV prevalence, revealing that transmission rates of both drug-susceptible and drug-resistant strains have the greatest impact. Additionally, bifurcation analysis was performed to examine parameter thresholds and assess the stability of the system. We then used the model to estimate the impacts of various intervention policies on reducing HCV cases and deaths. Among single interventions, increased effective treatment for drug-susceptible cases proved to be the most rapid and effective strategy for reducing the total number of both drug-susceptible and drug-resistant HCV cases, as well as mortality. Additionally, our results imply that combining interventions increases their overall effectiveness, achieving substantial reductions in cases and deaths with relatively modest investment. However, complete eradication of HCV in Bangladesh would require significantly greater resources.