Mathematical Modeling of Malaria Transmission in Remote and Underserved Regions: Integrating Healthcare Access and Environmental Management Strategy - Sigit Sugiarto; Gusti Arviana Rahman; Taufan Talib (Department of Mathematics, Universitas Negeri Gorontalo, 2026)
Mathematical modeling of malaria transmission remains essential for understanding disease dynamics in remote and underserved regions, where limited access to healthcare and environmental conditions jointly sustain vector-borne transmission. This study develops a mathematical model of malaria transmission that integrates healthcare access constraints and environmental management strategies as key intervention components. The transmission dynamics are formulated as a coupled eight-dimensional nonlinear system representing human SEIRS dynamics and mosquito populations across aquatic and adult (SEI) stages. The model is analyzed by establishing positivity and boundedness of solutions, characterizing equilibrium points, and deriving the basic reproduction number R_0 using the next-generation matrix method. Local stability analysis is conducted using the Routh–Hurwitz criterion, while bifurcation behavior is examined following the Castillo–Chavez and Song framework. The results show that the disease-free equilibrium is locally asymptotically stable when R_0 < 1, whereas endemic persistence occurs when R_0 > 1. Sensitivity analysis indicates that mosquito-related parameters, particularly transmission rate and mortality rates, are the dominant factors that influence R_0. Importantly, integration of healthcare access improvement and environmental management produces a nonlinear synergistic reduction in R_0, with aquatic-stage environmental interventions having a stronger marginal effect on transmission reduction. These findings suggest that effective malaria control in remote and underserved regions requires a balanced integration of clinical access improvement and environmental vector control strategies. Numerical simulations confirm the analytical results and demonstrate the existence of a combined intervention threshold under which malaria elimination becomes achievable in remote and underserved regions. The proposed model provides a more realistic and policy-relevant framework for understanding malaria transmission dynamics and supports integrated control strategies that combine healthcare access and environmental management in geographically constrained settings.