Browsing by Subject "Infectious disease"
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Item Analyses of infectious disease data with attention to heterogeneity(2013-08) O'Dea, Eamon Brendin; Wilke, C. (Claus); Meyers, Lauren AncelThis work comprises three projects that extend previous models to include features of practical significance for the statistical analysis of infectious disease data. In the first, we find from a simulation study how the degree of heterogeneity in the number contacts that individuals have affects the relationship between estimates of a pathogen's effective population size based on coalescent theory and the true prevalence and incidence of that pathogen. In the second, we find that aggregating data from many small outbreaks allows the parameters of stochastic epidemic models to be consistently estimated with a generalized linear model. Application of this method to a set of 77 small norovirus outbreaks reveals interesting differences in the transmission parameters between hospital and nursing-home outbreaks. In the third project, we gain insight into HIV contact networks in the United States by fitting data from a number of surveys to a simple stochastic model of a dynamic network.Item Infectious disease and the South Texas colonias(2016-12) Knab, Brian Russell; Sarkar, SahotraIn this study, I investigated infectious disease in Texas, with a focus on the impacts of poverty and lack of infrastructure in the South Texas colonias on rates of infectious disease. I used Bayesian statistical methods, and in particular, hierarchical conditional autoregressive Poisson regression to model county-level rates of hospitalization across the state. According to that model, and with at least 97.5% probability, the average risk of hospitalization is greater in counties containing colonias as compared to counties which do not for the following infectious disease categories tracked by the Texas Department of State Health Services: Amebiasis, Brucellosis, Candidiasis, Chickenpox, Coccidoidomycosis, Ill defined intestinal infections, Intestinal infections due to other organisms, Bacterial food poisoning, Rickettsioses, Salmonella infections, Typhus, Viral Exanthemata, Pulmonary tuberculosis, Septicemia, Shigellosis, Diseases due to Coxsackie virus, Typhoid and paratyphoid fevers, and Whooping coughItem Network based prediction models for coupled transportation-epidemiological systems(2011-05) Gardner, Lauren Marie; Waller, S. Travis; Sarkar, Sahotra; Walton, Michael; Damnjanovic, Ivan; Zhang, Zhanmin; Lasdon, LeonThe modern multimodal transportation system provides an extensive network for human mobility and commodity exchange around the globe. As a consequence these interactions are often accompanied by disease and other biological infectious agents. This dissertation highlights the versatility of network models in quantifying the combined impact transportation systems, ecological systems and social networks have on the epidemiological process. A set of predictive models intended to compliment the current mathematical and simulation based modeling tools are introduced. The main contribution is the incorporation of dynamic infection data, which is becoming increasingly available, but is not accounted for in previous epidemiological models. Three main problems are identified. The objective of the first problem is to identify the path of infection (for a specific disease scenario) through a social contact network by invoking the use of network based optimization algorithms and individual infection reports. This problem parallels a novel and related problem in phylodynamics, which uses genetic sequencing data to reconstruct the most likely spatiotemporal path of infection. The second problem is a macroscopic application of the methodology introduced in the first problem. The new objective is to identify links in a transportation network responsible for spreading infection into new regions (spanning from a single source) using regional level infection data (e.g. when the disease arrived at a new location). The new network structure is defined by nodes which represent regions (cites, states, countries) and links representing travel routes. The third research problem is applicable to vector-borne diseases; those diseases which are transmitted to humans through the bite of an infected vector (i.e. mosquito), including dengue and malaria. The role of the vector in the infection process inherently alters the spreading process (compared to human contact diseases), which must be addressed in prediction models. The proposed objective is to quantify the risk posed by air travel in the global spread of these types of diseases.Item Overlooked casualties : stories of families affected by vaccine-preventable diseases(2012-05) Haelle, Tara Susan; Darling, Dennis Carlyle; Minutaglio, BillThe invention of the vaccine has been one of the greatest public health triumphs of the modern world. Each new vaccine has saved thousands - even millions - of lives worldwide, but this success has been fraught with controversy over the safety and even the effectiveness of vaccines. Vaccines have not always had a spotless safety record, but today’s vaccines are incredibly safe and continue to protect millions of people against diseases that have significantly declined or nearly disappeared from the developing world. It is this very success that has led many people to forget, or never discover, what those diseases are and how destructive they can be. This report tells the story of several families whose lives were deeply affected by vaccine-preventable diseases, accompanied with images that help tell their story. Following these stories is a broader discussion of the issues related to vaccines, the misunderstandings and misinformation that often circulate about them, a brief mention of their safety and efficacy, and a general discussion of many of the diseases they can prevent.