One major aim of statistics is to systematically study outcomes of interest in a population by observing the properties of a sample of that population. Some outcomes, such as the total number of people infected in an epidemic, can depend on properties of the whole population, such as the structure of contacts among the individuals, or contact network. A network is a collection of individuals as well as the pairwise connections between them. This dissertation explores how the effects of network structure on infectious outcomes yield challenges for statistical analysis, and suggests strategies to address them. In Section I, we consider an intervention to reduce the spread of an epidemic on a collection of individuals in partially-connected networks, and show how network structure and mixing across networks can reduce the probability of observing true intervention effects, or statistical power. In Section II, we show how accounting for estimated properties of an epidemic contact network can improve statistical power, and that this improvement depends on the properties of the whole network as well as the epidemic spreading through them. Finally, in Section III, we derive the conditions under which a particular kind of network - the Degree-Corrected Stochastic Blockmodel - is susceptible to extensive epidemic spread, enabling statistical analysts to estimate when and to what extent the challenges and corrections explored here require consideration. We will conclude with a discussion of how the estimates and derivations in the final two sections can be used as adjustment covariates when assessing the effect of treatment on epidemic spread. / Biostatistics

In this thesis, I investigate policies and programs to improve reproductive health. My thesis makes a substantive contribution to reproductive health policy and a methodological contribution to quasi-experimental research. In chapter 1, I evaluate the impact of a mobile phone intervention for adolescent girls. I design and implement a randomized controlled trial in Ghana to test whether sending information via mobile phones is an effective way to improve girls’ knowledge of sexual health and to ultimately reduce teenage pregnancy. I find that mobile phone programs are effective not only in increasing knowledge, but also in decreasing risk of pregnancy among sexually active adolescents. I discuss the results in the context of sexual education policy in Ghana. In chapter 2, I explore the complex interactions between migration and reproductive health. I reconstruct the complete migration and reproductive health histories of women residing in the urban slums of Accra, Ghana. Using individual fixed effects to reduce selection bias, I find an increased risk of pregnancy, miscarriage, and abortion in the 48 months after migration, with no significant increase in the chance of live birth during this time period. With half of abortions in Ghana classified as unsafe, these results suggest that policies which target the rapidly growing number of urban migrants by providing access to contraception and public hospital services may reduce unsafe abortion and improve maternal health outcomes. In chapter 3, I investigate the bias of standard errors in difference-in-difference estimation, which typically evaluates the effect of a group-level intervention on individual data. Common modeling adjustments for grouped data, such as cluster-robust standard errors, are biased when the number of clusters is small. I run Monte Carlo simulations to investigate both the coverage and power of a wide variety of modeling solutions from the econometric and biostatistics fields, while varying the balance of cluster sizes, the degree of error correlation, and the proportion of treated clusters. I then apply my results to re-evaluate a recently published study on the effect of emergency contraception on adolescent sexual behavior. I find that the study’s results claiming that emergency contraception increases risky sexual behavior may be spurious once proper adjustments for grouped data are applied. / Health Policy

As the number and percentage of elderly Canadians increase, it becomes imperative to understand successful aging in order to keep this growing segment of our population healthy and productive. Conceptual models of successful aging have been proposed in a number of disciplines (biology, psychology, sociology, epidemiology), but these have yet to be integrated. There is not even agreement on how to define successful aging, or on whether it is a state of being or an adaptive process. To date, there have been relatively few interventions to promote successful aging, and the lack of a theoretical approach makes it more difficult to design them and to assess the results of any interventions that have been attempted. In this thesis, I build upon the insights from existing literatures, and I propose a conceptual model for successful aging. I then discuss the application of this model to guide community interventions for Successful Aging Ottawa.

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The purpose of this study was to develop methodology involving the use of biological monitoring of exhaled air to determine respirator protection factors. The concentration of fluorocarbon 113 in breath was correlated to the original exposure concentration while wearing a full facepiece negative pressure respirator. Protection factors calculated from breath sampling were compared to fit factors derived from a negative pressure test device. Although biological monitoring indicated a nearly three fold increase in fluorocarbon 113 penetration rates compared to the negative pressure fit test results, a correlation of 0.86 suggests that this methodology may be used in the design of a workplace protection study. No correlation was found between the biological and quantitative mask sampling methods.