Year of Award
Master of Arts (MA)
Other Degree Name/Area of Focus
Department or School/College
Dr. Jonathan Graham, Dr. Erin Landguth, Dr. David Patterson
Influenza, particulate matter, spatio-temporal modeling, generalized linear models, epidemiology
University of Montana
Applied Statistics | Biostatistics | Statistical Methodology | Statistical Models | Statistical Theory | Vital and Health Statistics
Studying air pollution and public health has been a historically important question in science. It has long been hypothesized that severe air pollution conditions lead to negative implications in basic human health. Primarily, areas thats are prone to severe degrees of human pollution are the focus of such studies. Such research relating to less populated areas are scarce, and this scarcity raises the question of how such pollution dynamics (human-made and natural) influence human health in more rural areas.
The aim of this study is to explore this hole in research; in particular we explore possible links between air pollution and Influenza-like-illness in Montana. We begin with a discussion of our starting hypotheses, the data we have accumulated to test these hypotheses, and some exploratory analysis of these data. The body of this research is based on modeling of the natural factors that influence influenza dynamics in general and how these factors apply in the state of Montana. Here, we will explore different modeling approaches and how to apply them to the given data. To conclude this research, a summary is provided and the implications this has for the state of Montana.
Stark, Benjamin A., "Statistical Modeling of Influenza-Like-Illness in Montana using Spatial and Temporal Methods" (2019). Graduate Student Theses, Dissertations, & Professional Papers. 11410.
© Copyright 2019 Benjamin A. Stark