Modeling Host Immune Responses in Infectious Diseases

dc.contributor.authorVerma, Meghnaen
dc.contributor.committeechairBassaganya-Riera, Josepen
dc.contributor.committeememberHoops, Stefanen
dc.contributor.committeememberAbedi, Vidaen
dc.contributor.committeememberHontecillas-Magarzo, Raquelen
dc.contributor.departmentGraduate Schoolen
dc.date.accessioned2019-12-18T09:00:26Zen
dc.date.available2019-12-18T09:00:26Zen
dc.date.issued2019-12-17en
dc.description.abstractInfectious diseases caused by bacteria, fungi, viruses and parasites have affected humans historically. Infectious diseases remain a major cause of premature death and a public health concern globally with increased mortality and significant economic burden. Unvaccinated individuals, people with suppressed and compromised immune systems are at higher risk of suffering from infectious diseases. In spite of significant advancements in infectious diseases research, the control or treatment process faces challenges. The mucosal immune system plays a crucial role in safeguarding the body from harmful pathogens, while being constantly exposed to the environment. To develop treatment options for infectious diseases, it is vital to understand the immune responses that occur during infection. The two infectious diseases presented here are: i) Helicobacter pylori infection and ii) human immunodeficiency (HIV) and human papillomavirus (HPV) co-infection. H pylori, is a bacterium that colonizes the stomach and causes gastric cancer in 1-2% but is beneficial for protection against allergies and gastroesophageal diseases. An estimated 85% of H pylori colonized individuals show no detrimental effects. HIV is a virus that causes AIDS, one of the deadliest and most persistent epidemics. HIV-infected patients are at an increased risk of co-infection with HPV, and report an increased incidence of oral cancer. The goal of this thesis is to elucidate the host immune responses in infectious diseases via the use of computational and mathematical models. First, the thesis reviews the need for computational and mathematical models to study the immune responses in the course of infectious diseases. Second, it presents a novel sensitivity analysis method that identifies important parameters in a hybrid (agent-based/equation-based) model of H. pylori infection. Third, it introduces a novel model representing the HIV/HPV coinfection and compares the simulation results with a clinical study. Fourth, it discusses the need of advanced modeling technologies to achieve a personalized systems wide approach and the challenges that can be encountered in the process. Taken together, the work in this dissertation presents modeling approaches that could lead to the identification of host immune factors in infectious diseases in a predictive and more resource-efficient manner.en
dc.description.abstractgeneralInfectious diseases caused by bacteria, fungi, viruses and parasites have affected humans historically. Infectious diseases remain a major cause of premature death and a public health concern globally with increased mortality and significant economic burden. These infections can occur either via air, travel to at-risk places, direct person-to-person contact with an infected individual or through water or fecal route. Unvaccinated individuals, individuals with suppressed and compromised immune system such as that in HIV carriers are at higher risk of getting infectious diseases. In spite of significant advancements in infectious diseases research, the control and treatment of these diseases faces numerous challenges. The mucosal immune system plays a crucial role in safeguarding the body from harmful pathogens, while being exposed to the environment, mainly food antigens. To develop treatment options for infectious diseases, it is vital to understand the immune responses that occur during infection. In this work, we focus on gut immune system that acts like an ecosystem comprising of trillions of interacting cells and molecules, including membars of the microbiome. The goal of this dissertation is to develop computational models that can simulate host immune responses in two infectious diseases- i) Helicobacter pylori infection and ii) human immunodeficiency virus (HIV)-human papilloma virus (HPV) co-infection. Firstly, it reviews the various mathematical techniques and systems biology based methods. Second, it introduces a "hybrid" model that combines different mathematical and statistical approaches to study H. pylori infection. Third, it highlights the development of a novel HIV/HPV coinfection model and compares the results from a clinical trial study. Fourth, it discusses the challenges that can be encountered in adapting machine learning based computational technologies. Taken together, the work in this dissertation presents modeling approaches that could lead to the identification of host immune factors in infectious diseases in a predictive and more resourceful way.en
dc.description.degreeDoctor of Philosophyen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:22861en
dc.identifier.urihttp://hdl.handle.net/10919/96019en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectimmune-systemen
dc.subjectinfectious diseasesen
dc.subjectcomputational modelsen
dc.subjectagent-based modelsen
dc.subjectordinary differential equationsen
dc.subjectsensitivity analysisen
dc.subjectcalibrationen
dc.subjectHelicobacter pylorien
dc.titleModeling Host Immune Responses in Infectious Diseasesen
dc.typeDissertationen
thesis.degree.disciplineTranslational Biology, Medicine and Healthen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.nameDoctor of Philosophyen
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