Epidemic modelling of dengue fever transmission dynamics

Dengue fever, caused by the dengue virus and transmitted by Aedes mosquitoes, presents a significant public health challenge, especially in tropical regions. We investigate its transmission dynamics using various epidemiological mathematical models, focusing on both host (humans) and vector (Aedes mosquitoes) populations. In order to highlight the importance of the climatic region for the disease spread, we analyze both models within a single area (one-node) and a model with a tropical and non-tropical area (two-nodes). The initial one-node model employs the Susceptible-Infected-Susceptible (SIS) framework for both populations, accounting for contagion and recovery rates. Further one-node models incorporate vector population dynamics using an open Susceptible-Infected (SI) framework, including birth and death rates while excluding recovery rates, to reflect mosquitoes' shorter lifespan. Control measures, such as vector control and health policies, are also integrated into these models as additional terms in the differential equations. The two-node model explores the impact of imported cases and international travel on disease dynamics, highlighting how interconnected regions can influence and enhance disease transmission. The two-node model is then tested through simulations with parameter values from the literature and some assumptions. What-if scenarios such as the potential survival of Aedes aegypti in non-tropical regions due to climate change are explored to predict future trends and outbreak risks. By identifying epidemic thresholds, analyzing effectiveness of controls and simulating various scenarios with the choice of parameters, this thesis offers insights into effective strategies for controlling dengue transmission and preventing outbreaks, contributing to the broader field of epidemiology.