Title

Dynamical Modeling of Measles Epidemics Using a Networked Metapopulation Approach

Date of Award

2019

Document Type

Thesis

Degree Name

Master of Science in Chemistry, Straight Program

Department

Information Systems & Computer Science

First Advisor

Ma. Regina Justina E. Estuar, PhD

Abstract

The burden of measles continues to afflict many developing countries, where medical resources are limited and communicable diseases can develop rapidly within a population. The ability to model and forecast epidemic trans- mission within and between communities given levels of vaccination can lead to better disease surveillance and public health response. This study imple- mented hybrid networked metapopulation models for measles spreading and introduced methods for segmenting historical incidence, estimating disease pa- rameters, and approximating inter-subpopulation interactions between individ- uals. The flux movement of individuals can be approximated using the ideal flow of a transportation network. Results show that hybrid models that incorporate estimations of human movement can be used as alternative implementations for classical compartmental models. Geographical interpolation also suggest a re- lationship between measles incidence and the presence of roads and highways. Analysis also reveal that the rate of transmission and recovery from measles influence the spreading of the virus the most.

This document is currently not available here.

Share

COinS