A novel malaria mathematical model: integrating vector and non-vector transmission pathways.

backgroundMalaria remains one of the most significant global health challenges, particularly in tropical and subtropical regions. Despite ongoing control efforts, malaria transmission persists due to complex biological, environmental, and socio-economic factors. Traditional malaria models have primarily focused on vector-borne transmission, overlooking the growing importance of non-vector transmission pathways, such as blood transfusions, congenital transmission, and human-to-human transmission through healthcare settings.

methodsA novel mathematical model was developed to integrate both vector-borne and non-vector transmission routes. The model expands the traditional Susceptible-Exposed-Infectious-Recovered (SEIR) framework by incorporating compartments for vaccinated and non-vector exposed human populations, as well as dynamics for both human and mosquito populations. Numerical simulations were performed using MATLAB to evaluate the impact of vaccination, vector control, non-vector control, and treatment strategies.

resultsThe results indicate that vaccination significantly reduces susceptibility to malaria, with numerical simulations showing an approximate 43% reduction in the susceptible human population. However, vector control remains critical in limiting exposure, and non-vector transmission pathways including blood transfusions, congenital transmission, and direct human-to-human transmission pose a substantial risk even in regions with effective mosquito control. This underscores the need for integrated strategies that address both vector and non-vector transmission routes.

conclusionsCombining vaccination efforts with robust vector control, improved healthcare practices, and stringent non-vector transmission prevention measures is essential to effectively reduce malaria transmission. Sustained interventions, including improved blood screening and safe medical practices, are necessary to prevent malaria resurgence, particularly in high-transmission settings. This model provides valuable insights into malaria dynamics and offers a framework for designing more effective public health policies and strategies for malaria eradication.