Dynamics and management of vector-borne viral epidemics

Abstract

In this thesis, we model the dynamics of vector-borne viral epidemics. We choose dengue fever as the specific viral epidemic for the study, which is a mosquito-borne viral infection caused by the dengue virus. Dengue virus relies on the human-vector interaction to spread; thus, we need to model a host-vector system. We use system dynamics methodology and construct a dynamic model. We choose Rio de Janeiro as the area. We obtain the average parameter values from the relevant literature or use our close estimations. We observe that the number of infectious human and infected vectors converge to zero in the model, which means the virus decays and eradicates. However, the viral epidemic of dengue is persistent in the region. We try to understand the reasons behind the persistent existence of this specific viral epidemic. We identify the leverage parameters, and calibrate them to obtain persistence in the epidemic. We compare the outputs with the data for validation to show that the model can reproduce the dynamics of the real system with its own internal causal feedback structure. The model we construct does not only aim to generate valid dynamics, but it also goes beyond the existing models in the sense that it serves as an experimental platform for scenario analyses to support the understanding and management of the disease. The second aim is to demonstrate at a conceptual level that the internal structure of our model makes scenario analyses possible. In scenario experiments, we try to eliminate the virus with two parameters related to the biting rates and vector births. Biting rates and vector births can be decreased by taking precautions such as wearing clothes with more skin coverage, using repellents, and cleaning the water storages regularly. We conclude that the virus can be eliminated if humans take precautions against the interaction with vectors or against vector breeding areas.