MATHEMATICAL MODEL OF DENGUE HEMORRHAGIC FEVER SPREAD WITH DIFFERENT LEVELS OF TRANSMISSION RISK - Herdicho, Faishal Farrel; Hakim, Nabil Azizul; Fatmawati, Fatmawati; Alfiniyah, Cicik; Akanni, John Olajide (PATTIMURA UNIVERSITY, 2025)
Dengue Haemorrhagic Fever (DHF) is a vector-borne disease caused by the dengue virus, transmitted to humans through the bite of an infected female Aedes aegypti mosquito. DHF is prevalent in tropical regions, necessitating mathematical modeling to better understand its dynamics and predict its spread. This study develops and analyzes a mathematical model for DHF transmission that incorporates seven compartments to reflect different transmission risk levels. Stability analysis of the disease-free and endemic equilibria was conducted, with the basic reproduction number used to classify the conditions under which DHF transmission is controlled or endemic . Key model parameters were estimated using DHF case data from East Java in 2018, employing a genetic algorithm (GA) to optimize the estimation process. The GA approach achieved a mean absolute percentage error (MAPE) of , ensuring high accuracy in parameter values. Furthermore, the basic reproduction number was determined to be , which is greater than one, confirming that DHF remains endemic in East Java. Sensitivity analysis identified the mosquito biting rate , mosquito mortality rate , and transmission rates as the most critical factors influencing . Numerical simulations demonstrated the effects of these key parameters on both and the symptomatic human population . An increase in , , or significantly amplified and , while a rise in had the opposite effect, reducing both transmission and infections. These results underscore the critical role of vector control strategies, such as increasing mosquito mortality and reducing breeding sites, in mitigating DHF outbreaks. This study highlights the utility of combining mathematical modeling with genetic algorithm-based parameter estimation to provide accurate insights into disease dynamics and inform effective control measures.