Matching Items (114)
Description
Mathematical modeling of infectious diseases can help public health officials to make decisions related to the mitigation of epidemic outbreaks. However, over or under estimations of the morbidity of any infectious disease can be problematic. Therefore, public health officials can always make use of better models to study the potential implication of their decisions and strategies prior to their implementation. Previous work focuses on the mechanisms underlying the different epidemic waves observed in Mexico during the novel swine origin influenza H1N1 pandemic of 2009 and showed extensions of classical models in epidemiology by adding temporal variations in different parameters that are likely to change during the time course of an epidemic, such as, the influence of media, social distancing, school closures, and how vaccination policies may affect different aspects of the dynamics of an epidemic. This current work further examines the influence of different factors considering the randomness of events by adding stochastic processes to meta-population models. I present three different approaches to compare different stochastic methods by considering discrete and continuous time. For the continuous time stochastic modeling approach I consider the continuous-time Markov chain process using forward Kolmogorov equations, for the discrete time stochastic modeling I consider stochastic differential equations using Wiener's increment and Poisson point increments, and also I consider the discrete-time Markov chain process. These first two stochastic modeling approaches will be presented in a one city and two city epidemic models using, as a base, our deterministic model. The last one will be discussed briefly on a one city SIS and SIR-type model.
ContributorsCruz-Aponte, Maytee (Author) / Wirkus, Stephen A. (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Camacho, Erika T. (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Effect of a Wii Fit® intervention on balance, muscular fitness, and bone health in middle-aged women
Description
Sustaining a fall can be hazardous for those with low bone mass. Interventions exist to reduce fall-risk, but may not retain long-term interest. "Exergaming" has become popular in older adults as a therapy, but no research has been done on its preventative ability in non-clinical populations. The purpose was to determine the impact of 12-weeks of interactive play with the Wii Fit® on balance, muscular fitness, and bone health in peri- menopausal women. METHODS: 24 peri-menopausal-women were randomized into study groups. Balance was assessed using the Berg/FICSIT-4 and a force plate. Muscular strength was measured using the isokinetic dynamometer at 60°/180°/240°/sec and endurance was assessed using 50 repetitions at 240°/sec. Bone health was tracked using dual-energy x-ray absorptiometry (DXA) for the hip/lumbar spine and qualitative ultrasound (QUS) of the heel. Serum osteocalcin was assessed by enzyme immunoassay. Physical activity was quantified using the Women's Health Initiative Physical Activity Questionnaire and dietary patterns were measured using the Nurses' Health Food Frequency Questionnaire. All measures were repeated at weeks 6 and 12, except for the DXA, which was completed pre-post. RESULTS: There were no significant differences in diet and PA between groups. Wii Fit® training did not improve scores on the Berg/FICSIT-4, but improved center of pressure on the force plate for Tandem Step, Eyes Closed (p-values: 0.001-0.051). There were no significant improvements for muscular fitness at any of the angular velocities. DXA BMD of the left femoral neck improved in the intervention group (+1.15%) and decreased in the control (-1.13%), but no other sites had significant changes. Osteocalcin indicated no differences in bone turnover between groups at baseline, but the intervention group showed increased bone turnover between weeks 6 and 12. CONCLUSIONS: Findings indicate that WiiFit® training may improve balance by preserving center of pressure. QUS, DXA and osteocalcin data confirm that those in the intervention group were experiencing more bone turnover and bone formation than the control group. In summary, twelve weeks of strength /balance training with the Wii Fit® shows promise as a preventative intervention to reduce fall and fracture risk in non-clinical middle aged women who are at risk.
ContributorsWherry, Sarah Jo (Author) / Swan, Pamela D (Thesis advisor) / Adams, Marc (Committee member) / Der Ananian, Cheryl (Committee member) / Sweazea, Karen (Committee member) / Vaughan, Linda (Committee member) / Arizona State University (Publisher)
Created2014
Description
Purpose: To examine: (1) whether Non-Hispanic Blacks (NHB) and Non-Hispanic Whites (NHW) with diagnosed arthritis differed in self-reported physical activity (PA) levels, (2) if NHB and NHW with arthritis differed on potential correlates of PA based on the Social Ecological Model (Mcleroy et al., 1988), and (3) if PA participation varied by race/ethnicity after controlling for age, gender, education, and BMI. Methods: This study was a secondary data analysis of data collected from 2006-2008 in Chicago, IL as part of the Midwest Roybal Center for Health Promotion. Bivariate analyses were used to assess potential differences between race in meeting either ACR or ACSM PA guidelines. Comparisons by race between potential socio-demographic correlates and meeting physical activity guidelines were assessed using Chi-squares. Potential differences by race in psychosocial, arthritis, and health-related and environmental correlates were assessed using T-tests. Finally, logistic regression analyses were used to examine if race was still associated with PA after controlling for socio-demographic characteristics. Results: A greater proportion of NHW (68.1% and 35.3%) than NHB (46.5% and 20.9%) met both the arthritis-specific and the American College of Sports Medicine (ACSM) recommendations for physical activity, respectively. NHB had significantly lower self-efficacy for exercise and reported greater impairments in physical function compared to NHW. Likewise, NHB reported more crime and less aesthetics within their neighborhood. NHW were 2.56 times more likely to meet arthritis-specific PA guidelines than NHB after controlling for age, gender, education, marital status, and BMI. In contrast, after controlling for sociodemographic characteristics, age and gender were the only significant predictors of meeting ACSM PA guidelines. Discussion: There were significant differences between NHB and NHW individuals with arthritis in meeting PA guidelines. After controlling for age, gender, education, and BMI non-Hispanic White individuals were still significantly more likely to meet PA guidelines. Interventions aimed at promoting higher levels of physical activity among individuals with arthritis need to consider neighborhood aesthetics and crime when designing programs. More arthritis-specific programs are needed in close proximity to neighborhoods in an effort to promote physical activity.
ContributorsChuran, Christopher (Author) / Der Ananian, Cheryl (Thesis advisor) / Adams, Marc (Committee member) / Campbell, Kathryn (Committee member) / Arizona State University (Publisher)
Created2013
Description
Background: Childhood obesity is one of the most serious public health concerns in the United States and has been associated with low levels of physical activity. Schools are ideal physical activity promotion sites but school physical activity opportunities have decreased due the increased focus on academic performance. Before-school programs provide a good opportunity for children to engage in physical activity as well as improve their readiness to learn. Purpose: The purpose of this study was to examine the effect of a before-school running/walking club on children's physical activity and on-task behavior. Methods: Participants were third and fourth grade children from two schools in the Southwestern United States who participated in a before-school running/walking club that met two times each week. The study employed a two-phase experimental design with an initial baseline phase and an alternating treatments phase. Physical activity was monitored using pedometers and on-task behavior was assessed through systematic observation. Data analysis included visual analysis, descriptive statistics, as well as multilevel modeling. Results: Children accumulated substantial amounts of physical activity within the before-school program (School A: 1731 steps, 10:02 MVPA minutes; School B: 1502 steps, 8:30 MVPA minutes) and, on average, did not compensate by decreasing their physical activity during the rest of the school day. Further, on-task behavior was significantly higher on days the children attended the before-school program than on days they did not (School A=15.78%, pseudo-R2=.34 [strong effect]; School B=14.26%, pseudo-R2=.22 [moderate effect]). Discussion: Results provide evidence for the positive impact of before-school programs on children's physical activity and on-task behavior. Such programs do not take time away from academics and may be an attractive option for schools.
ContributorsStylianou, Michalis (Author) / Kulinna, Pamela H. (Thesis advisor) / Van Der Mars, Hans (Committee member) / Amazeen, Eric (Committee member) / Adams, Marc (Committee member) / Mahar, Matthew T. (Committee member) / Arizona State University (Publisher)
Created2014
Description
In the field of infectious disease epidemiology, the assessment of model robustness outcomes plays a significant role in the identification, reformulation, and evaluation of preparedness strategies aimed at limiting the impact of catastrophic events (pandemics or the deliberate release of biological agents) or used in the management of disease prevention strategies, or employed in the identification and evaluation of control or mitigation measures. The research work in this dissertation focuses on: The comparison and assessment of the role of exponentially distributed waiting times versus the use of generalized non-exponential parametric distributed waiting times of infectious periods on the quantitative and qualitative outcomes generated by Susceptible-Infectious-Removed (SIR) models. Specifically, Gamma distributed infectious periods are considered in the three research projects developed following the applications found in (Bailey 1964, Anderson 1980, Wearing 2005, Feng 2007, Feng 2007, Yan 2008, lloyd 2009, Vergu 2010). i) The first project focuses on the influence of input model parameters, such as the transmission rate, mean and variance of Gamma distributed infectious periods, on disease prevalence, the peak epidemic size and its timing, final epidemic size, epidemic duration and basic reproduction number. Global uncertainty and sensitivity analyses are carried out using a deterministic Susceptible-Infectious-Recovered (SIR) model. The quantitative effect and qualitative relation between input model parameters and outcome variables are established using Latin Hypercube Sampling (LHS) and Partial rank correlation coefficient (PRCC) and Spearman rank correlation coefficient (RCC) sensitivity indices. We learnt that: For relatively low (R0 close to one) to high (mean of R0 equals 15) transmissibility, the variance of the Gamma distribution for the infectious period, input parameter of the deterministic age-of-infection SIR model, is key (statistically significant) on the predictability of the epidemiological variables such as the epidemic duration and the peak size and timing of the prevalence of infectious individuals and therefore, for the predictability these variables, it is preferable to utilize a nonlinear system of Volterra integral equations, rather than a nonlinear system of ordinary differential equations. The predictability of epidemiological variables such as the final epidemic size and the basic reproduction number are unaffected by (or independent of) the variance of the Gamma distribution for the infectious period and therefore for the choice on which type of nonlinear system for the description of the SIR model (VIE's or ODE's) is irrelevant. Although, for practical proposes, with the aim of lowering the complexity and number operations in the numerical methods, a nonlinear system of ordinary differential equations is preferred. The main contribution lies in the development of a model based decision-tool that helps determine when SIR models given in terms of Volterra integral equations are equivalent or better suited than SIR models that only consider exponentially distributed infectious periods. ii) The second project addresses the question of whether or not there is sufficient evidence to conclude that two empirical distributions for a single epidemiological outcome, one generated using a stochastic SIR model under exponentially distributed infectious periods and the other under the non-exponentially distributed infectious period, are statistically dissimilar. The stochastic formulations are modeled via a continuous time Markov chain model. The statistical hypothesis test is conducted using the non-parametric Kolmogorov-Smirnov test. We found evidence that shows that for low to moderate transmissibility, all empirical distribution pairs (generated from exponential and non-exponential distributions) for each of the epidemiological quantities considered are statistically dissimilar. The research in this project helps determine whether the weakening exponential distribution assumption must be considered in the estimation of probability of events defined from the empirical distribution of specific random variables. iii) The third project involves the assessment of the effect of exponentially distributed infectious periods on estimates of input parameter and the associated outcome variable predictions. Quantities unaffected by the use of exponentially distributed infectious period within low transmissibility scenarios include, the prevalence peak time, final epidemic size, epidemic duration and basic reproduction number and for high transmissibility scenarios only the prevalence peak time and final epidemic size. An application designed to determine from incidence data whether there is sufficient statistical evidence to conclude that the infectious period distribution should not be modeled by an exponential distribution is developed. A method for estimating explicitly specified non-exponential parametric probability density functions for the infectious period from epidemiological data is developed. The methodologies presented in this dissertation may be applicable to models where waiting times are used to model transitions between stages, a process that is common in the study of life-history dynamics of many ecological systems.
ContributorsMorales Butler, Emmanuel J (Author) / Castillo-Chavez, Carlos (Thesis advisor) / Aparicio, Juan P (Thesis advisor) / Camacho, Erika T (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Description
There has been important progress in understanding ecological dynamics through the development of the theory of ecological stoichiometry. This fast growing theory provides new constraints and mechanisms that can be formulated into mathematical models. Stoichiometric models incorporate the effects of both food quantity and food quality into a single framework that produce rich dynamics. While the effects of nutrient deficiency on consumer growth are well understood, recent discoveries in ecological stoichiometry suggest that consumer dynamics are not only affected by insufficient food nutrient content (low phosphorus (P): carbon (C) ratio) but also by excess food nutrient content (high P:C). This phenomenon, known as the stoichiometric knife edge, in which animal growth is reduced not only by food with low P content but also by food with high P content, needs to be incorporated into mathematical models. Here we present Lotka-Volterra type models to investigate the growth response of Daphnia to algae of varying P:C ratios. Using a nonsmooth system of two ordinary differential equations (ODEs), we formulate the first model to incorporate the phenomenon of the stoichiometric knife edge. We then extend this stoichiometric model by mechanistically deriving and tracking free P in the environment. This resulting full knife edge model is a nonsmooth system of three ODEs. Bifurcation analysis and numerical simulations of the full model, that explicitly tracks phosphorus, leads to quantitatively different predictions than previous models that neglect to track free nutrients. The full model shows that the grazer population is sensitive to excess nutrient concentrations as a dynamical free nutrient pool induces extreme grazer population density changes. These modeling efforts provide insight on the effects of excess nutrient content on grazer dynamics and deepen our understanding of the effects of stoichiometry on the mechanisms governing population dynamics and the interactions between trophic levels.
ContributorsPeace, Angela (Author) / Kuang, Yang (Thesis advisor) / Elser, James J (Committee member) / Baer, Steven (Committee member) / Tang, Wenbo (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Description
In 1968, phycologist M.R. Droop published his famous discovery on the functional relationship between growth rate and internal nutrient status of algae in chemostat culture. The simple notion that growth is directly dependent on intracellular nutrient concentration is useful for understanding the dynamics in many ecological systems. The cell quota in particular lends itself to ecological stoichiometry, which is a powerful framework for mathematical ecology. Three models are developed based on the cell quota principal in order to demonstrate its applications beyond chemostat culture.
First, a data-driven model is derived for neutral lipid synthesis in green microalgae with respect to nitrogen limitation. This model synthesizes several established frameworks in phycology and ecological stoichiometry. The model demonstrates how the cell quota is a useful abstraction for understanding the metabolic shift to neutral lipid production that is observed in certain oleaginous species.
Next a producer-grazer model is developed based on the cell quota model and nutrient recycling. The model incorporates a novel feedback loop to account for animal toxicity due to accumulation of nitrogen waste. The model exhibits rich, complex dynamics which leave several open mathematical questions.
Lastly, disease dynamics in vivo are in many ways analogous to those of an ecosystem, giving natural extensions of the cell quota concept to disease modeling. Prostate cancer can be modeled within this framework, with androgen the limiting nutrient and the prostate and cancer cells as competing species. Here the cell quota model provides a useful abstraction for the dependence of cellular proliferation and apoptosis on androgen and the androgen receptor. Androgen ablation therapy is often used for patients in biochemical recurrence or late-stage disease progression and is in general initially effective. However, for many patients the cancer eventually develops resistance months to years after treatment begins. Understanding how and predicting when hormone therapy facilitates evolution of resistant phenotypes has immediate implications for treatment. Cell quota models for prostate cancer can be useful tools for this purpose and motivate applications to other diseases.
First, a data-driven model is derived for neutral lipid synthesis in green microalgae with respect to nitrogen limitation. This model synthesizes several established frameworks in phycology and ecological stoichiometry. The model demonstrates how the cell quota is a useful abstraction for understanding the metabolic shift to neutral lipid production that is observed in certain oleaginous species.
Next a producer-grazer model is developed based on the cell quota model and nutrient recycling. The model incorporates a novel feedback loop to account for animal toxicity due to accumulation of nitrogen waste. The model exhibits rich, complex dynamics which leave several open mathematical questions.
Lastly, disease dynamics in vivo are in many ways analogous to those of an ecosystem, giving natural extensions of the cell quota concept to disease modeling. Prostate cancer can be modeled within this framework, with androgen the limiting nutrient and the prostate and cancer cells as competing species. Here the cell quota model provides a useful abstraction for the dependence of cellular proliferation and apoptosis on androgen and the androgen receptor. Androgen ablation therapy is often used for patients in biochemical recurrence or late-stage disease progression and is in general initially effective. However, for many patients the cancer eventually develops resistance months to years after treatment begins. Understanding how and predicting when hormone therapy facilitates evolution of resistant phenotypes has immediate implications for treatment. Cell quota models for prostate cancer can be useful tools for this purpose and motivate applications to other diseases.
ContributorsPacker, Aaron (Author) / Kuang, Yang (Thesis advisor) / Nagy, John (Committee member) / Smith, Hal (Committee member) / Kostelich, Eric (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Description
Pre-Exposure Prophylaxis (PrEP) is any medical or public health procedure used before exposure to the disease causing agent, its purpose is to prevent, rather than treat or cure a disease. Most commonly, PrEP refers to an experimental HIV-prevention strategy that would use antiretrovirals to protect HIV-negative people from HIV infection. A deterministic mathematical model of HIV transmission is developed to evaluate the public-health impact of oral PrEP interventions, and to compare PrEP effectiveness with respect to different evaluation methods. The effects of demographic, behavioral, and epidemic parameters on the PrEP impact are studied in a multivariate sensitivity analysis. Most of the published models on HIV intervention impact assume that the number of individuals joining the sexually active population per year is constant or proportional to the total population. In the second part of this study, three models are presented and analyzed to study the PrEP intervention, with constant, linear, and logistic recruitment rates. How different demographic assumptions can affect the evaluation of PrEP is studied. When provided with data, often least square fitting or similar approaches can be used to determine a single set of approximated parameter values that make the model fit the data best. However, least square fitting only provides point estimates and does not provide information on how strongly the data supports these particular estimates. Therefore, in the third part of this study, Bayesian parameter estimation is applied on fitting ODE model to the related HIV data. Starting with a set of prior distributions for the parameters as initial guess, Bayes' formula can be applied to obtain a set of posterior distributions for the parameters which makes the model fit the observed data best. Evaluating the posterior distribution often requires the integration of high-dimensional functions, which is usually difficult to calculate numerically. Therefore, the Markov chain Monte Carlo (MCMC) method is used to approximate the posterior distribution.
ContributorsZhao, Yuqin (Author) / Kuang, Yang (Thesis advisor) / Taylor, Jesse (Committee member) / Armbruster, Dieter (Committee member) / Tang, Wenbo (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Description
A functioning food web is the basis of a functioning community and ecosystem. Thus, it is important to understand the dynamics that control species behaviors and interactions. Alterations to the fundamental dynamics can prove detrimental to the future success of our environment. Research and analysis focus on the global dynamics involved in intraguild predation (IGP), a three species subsystem involving both competition and predation. A mathematical model is derived using differential equations based on pre-existing models to accurately predict species behavior. Analyses provide sufficient conditions for species persistence and extinction that can be used to explain global dynamics. Dynamics are compared for two separate models, one involving a specialist predator and the second involving a generalist predator, where systems involving a specialist predator are prone to unstable dynamics. Analyses have implications in biological conservation tactics including various methods of prevention and preservation. Simulations are used to compare dynamics between models involving continuous time and those involving discrete time. Furthermore, we derive a semi-discrete model that utilizes both continuous and discrete time series dynamics. Simulations imply that Holling's Type III functional response controls the potential for three species persistence. Complicated dynamics govern the IGP subsystem involving the white-footed mouse, gypsy moth, and oak, and they ultimately cause the synchronized defoliation of forests across the Northeastern United States. Acorn mast seasons occur every 4-5 years, and they occur simultaneously across a vast geographic region due to universal cues. Research confirms that synchronization can be transferred across trophic levels to explain how this IGP system ultimately leads to gypsy moth outbreaks. Geographically referenced data is used to track and slow the spread of gypsy moths further into the United States. Geographic Information Systems (GIS) are used to create visual, readily accessible, displays of trap records, defoliation frequency, and susceptible forest stands. Mathematical models can be used to explain both changes in population densities and geographic movement. Analyses utilizing GIS softwares offer a different, but promising, way of approaching the vast topic of conservation biology. Simulations and maps are produced that can predict the effects of conservation efforts.
ContributorsWedekin, Lauren (Author) / Kang, Yun (Thesis advisor) / Green, Douglas (Committee member) / Miller, William (Committee member) / Arizona State University (Publisher)
Created2012
Description
Salad bars are promoted as a means to increase fruit and vegetable consumption among school-age children; however, no study has assessed barriers to having salad bars. Further, it is not known if barriers differ across school level. This cross-sectional study investigated the barriers to having salad bars across school level among schools without salad bars in Arizona (n=177). Multivariate binominal regression models were used to determine differences between the barriers and school level, adjusting for years at current job, enrollment of school, free-reduced eligibility rate and district level clustering. The top five barriers were not enough staff (51.4%), lack of space for salad bars (49.7%), food waste concerns (37.9%), sanitation/food safety concerns (31.3%), and time to get through the lines (28.3%) Adjusted analyses indicated two significant differences between barriers across school level: time to get through lines (p=0.040) and outside caterer/vendor (p=0.018) with time to get through lines reported more often by elementary and middle school nutrition managers and outside caterer/vendor reported most often by high school nutrition managers. There were several key barriers reported and results indicate that having an outside vendor/caterer for their meal programs and time to get through the service lines varied across school level. High schools report a higher percent of the barrier outside caterer/vendors and elementary and middle schools report a higher percent of the barrier time to get through the lines. Results indicate that research determining the approximate time it takes students to get through salad bar lines will need to be considered. More research is needed to determine if the barrier time to get through the service lines is due to selection of food items or if it is due to the enrollment size of the lunch period. Future research interventions may consider investigating food safety and sanitation concerns of middle school nutrition managers. Findings may be used to guide ways to decrease barriers in schools without salad bars.
ContributorsKebric, Kelsey (Author) / Bruening, Meg (Thesis advisor) / Ohri-Vachaspati, Punam (Committee member) / Adams, Marc (Committee member) / Arizona State University (Publisher)
Created2016