Multidrug-resistant Mycobacterium tuberculosis (MDR-TB) is a leading cause of morbidity and mortality in the Philippines. The purpose of this study was to gain knowledge about the relationship between potential risk factors and MDR-TB. Risk factors (the independent variables) for MDR-TB (the dependent variable) include previous TB treatment, infection with HIV, exposure to patients with drug-susceptible TB/MDR-TB, delays in diagnosis and treatment, employment status, smoking, imprisonment, alcohol abuse, and poor compliance with TB treatment regimens. The study was based on the epidemiological approach to causal inference work. A case-control study design was used wherein a quantitative method was applied in data analysis to assess the strength of the pre-identified possible risk factor(s) association to MDR-TB infection. Data were collected using survey questionnaires that were administered to patients (N = 172) from health centers in Leyte, San Mateo Rizal, and San Lazaro. Hypotheses were tested using chi-square analysis, Fisher's exact test, and an odd ratio. Drug-susceptible TB respondents who smoked on a daily basis were three times more likely (95% CI 1.021-13.341, OR 3.69) to develop an MDR-TB infection than were other respondents. Respondents who did not comply with the anti-TB treatment regimen were nine times more likely (95% CI 2.104-43.059, OR 9.519) to develop an MDR-TB infection than other respondents. Health care providers may be able to use study findings to develop programs to help drug-susceptible TB patients stop smoking and better comply with treatment regimens designed to prevent MDR-TB infection, resulting, potentially, in improved public health outcomes for patients.

Philosophiae Doctor - PhD / Tuberculosis is a bacterial infection which is a major cause of death worldwide. TB is a curable disease, however the bacterium can become resistant to the first line treatment against the disease. This leads to a disease called drug resistant TB that is difficult and expensive to treat. It is well-known that TB disease thrives in communities in overcrowded environments with poor ventilation, weak nutrition, inadequate or inaccessible medical care, etc, such as in some prisons or some refugee camps. In particular, the World Health Organization discovered that a number of prisoners come from socio-economic disadvantaged population where the burden of TB disease may be already high and access to medical care may be limited. In this dissertation we propose compartmental models of systems of differential equations to describe the population dynamics of TB disease under conditions of crowding. Such models can be used to make quantitative projections of TB prevalence and to measure the effect of interventions. Indeed we apply these models to specific regions and for specific purposes. The models are more widely applicable, however in this dissertation we calibrate and apply the models to prison populations.