Mathematical Modeling of the Dynamics of Female Genital Schistosomiasis as a Risk Factor to Cervical Cancer

Female genital schistosomiasis (FGS), caused by chronic infection with Schistosoma haematobium , represents a significant but neglected gynecological condition that affects approximately 56 million women in sub‐Saharan Africa. This parasitic disease manifests itself through chronic inflammation and tissue damage in the female genital tract, leading to substantial morbidity and poor quality of life. Emerging epidemiological evidence suggests that FGS may function as an important cofactor in cervical carcinogenesis, potentially explaining the elevated burden of cervical cancer observed in schistosomiasis‐endemic regions. However, the population level impact of this relationship and optimal intervention strategies remains poorly quantified. This study develops a compartmental mathematical model that integrates the transmission dynamics of schistosomiasis with human papilloma virus (HPV)–induced cervical carcinogenesis pathways. The model explicitly incorporates key biological mechanisms including chronic inflammation, immunomodulation, and synergistic interactions between FGS and HPV infection. The analytical derivation of the basic reproduction number yields , with the bifurcation analysis confirming a forward transcritical bifurcation at R 0 = 1 (coefficients a < 0 and b > 0). This establishes R 0 < 1 as necessary and sufficient for the elimination of the disease, without backward bifurcation complications. Our findings demonstrate that FGS contributes substantially to cervical cancer burden, with population attributable fraction (PAF) estimates ranging from 20% to 30% in high endemic settings. Cost‐effectiveness analysis revealed that integrated interventions of mass drug administration (MDA), HPV vaccination, and cervical screening dominate vertical approaches, with incremental cost‐effectiveness ratios (ICERs) of $172 per disability‐adjusted living years averted from the model output. Sensitivity analysis identified the FGS risk ratio ( ρ ) as the most influential parameter, highlighting the critical need for better epidemiological characterization of this relationship. The model provides a robust platform for policy planning and resource allocation, demonstrating that coordinated control strategies addressing both neglected tropical diseases and noncommunicable diseases offer substantial synergistic benefits in reducing the dual burden of FGS and cervical cancer in endemic populations.