Theses and Dissertations

Date of Award

12-2020

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Mathematics

First Advisor

Dr. Tamer Oraby

Second Advisor

Dr. George Yanev

Third Advisor

Dr. Hansapani Rodrigo

Abstract

Researchers use stochastic models like continuous-time Markov chains (CTMC) to model progression of morbidities of public health impact, like HIV and Hepatitis C. Most of the research in that area is done for a single disease. In this research, we use a bivariate continuous-time Markov chain (CTMC) to model progression of co-morbidities. In particular, we use a bivariate CTMC to model the joint progression of Irritable Bowel Syndrome (IBS) and abdominal pain. Symptoms of IBS are known to change throughout the duration of the disorder. Hence, patients are normally asked to make a journal of the stool type, symptoms, and medicines to find the cause of severe symptoms and to find a stable way of living with IBS. The bivariate CTMC model that we use to model IBS and abdominal pain takes into account treatment for IBS and abdominal pain. Clinical data from Mexican Physicians' patients is used to estimate the intensity matrices that involve the rates of transition between the different stages of the diseases. We use them to test some related health research hypotheses like the effect of treatment on the progression of IBS. We also use it to test dependence between IBS and pain and whether IBS is driving the pain up or not.

Comments

Copyright 2020 Ricardo Reyna Jr. All Rights Reserved.

https://go.openathens.net/redirector/utrgv.edu?url=https://www.proquest.com/dissertations-theses/bivariate-markov-chain-model-irritable-bowel/docview/2557506330/se-2?accountid=7119

Download

Share

COinS