Structured models for dengue epidemiology

  • Hannah Woodall

Student thesis: Doctoral ThesisPhD

Abstract

Dengue is a vector-borne disease. Around 2.5 billion people are thought to be at risk of infection. It is spread primarily through the Aedes aegypti mosquito, and is endemic in tropical and subtropical regions. There are four distinct serotypes which co-circulate. Whilst infection from one serotype provides homologous immunity it does not provide heterologous immunity.In this thesis we use a range of modelling techniques to examine how the epidemiological dynamics of dengue are affected by immunological interaction between serotypes and age–dependent variation in the extent to which people are exposed to the mosquito population. We initially consider transmission dynamics for multi–serotype dengue infections and present a new framework for how secondary infections are modelled. We move on to consider age–structure and introduce a method to quantify differences between seroprevalence profiles when age–independent and age–dependent transmission rates are implemented. We combine these ideas and find that parameters associated with transmission of secondary infections can interact with age–structure and affect how easy it is to detect age–dependence in seroprevalence profiles. Finally we consider how age–dependent variation in the exposure people have to mosquitoes affects the probability of an epidemic and the optimal prevention strategy that should be implemented to ensure that the introduction of isolated infections does not lead to large epidemics.Our results show it is necessary to understand the underlying dynamics of dengue and implement the correct model, as dynamics can differ substantially. They also show the importance of public health strategies to ensure that all age–groups exposure to mosquitoes is as minimal as possible to decrease the risk of an epidemic. Therefore we have found relevant results that help to further understand the dynamics of dengue.
Date of Award14 Jan 2015
Original languageEnglish
Awarding Institution
  • University of Bath
SupervisorBen Adams (Supervisor)

Cite this

Structured models for dengue epidemiology
Woodall, H. (Author). 14 Jan 2015

Student thesis: Doctoral ThesisPhD