Simulasi Numerik Pengendalian Endemik Demam Berdarah Dengue di Kabupaten Minahasa menggunakan Pendekatan Model SIR-A

Abstract

Dengue Hemorrhagic Fever (DHF) persists as a critical threat to public health sectors within tropical ecosystems, including Indonesia. This study evaluates the epidemiological fluctuations of Dengue virus transmission in Minahasa Regency by formulating a SIR-A compartmental mathematical model, focusing on the contribution of strengthened clinical interventions to patient recovery rates. The developed dynamic framework incorporates interactions between human cohorts (susceptible, infected, and recovered phases) and an aquatic pre-adult vector group (mosquito larvae/pupae). The investigative procedure involves constructing a system of nonlinear ordinary differential equations, followed by establishing equilibrium states, calculating the basic reproduction number () threshold, and executing computational simulations via Wolfram Mathematica. Computational outputs demonstrate that an escalation in mosquito larvae density correlates positively with accelerated disease transmission rates. Conversely, optimizing clinical control by increasing the recovery parameter significantly reduces the active infected cohort and drives the system’s trajectory toward a stable disease-free equilibrium state. These insights indicate that accelerating patient care effectiveness and upgrading healthcare infrastructure are crucial policy instruments for suppressing DHF endemic risks in Minahasa Regency.