Browsing by Subject "Bayesian modeling"

Now showing 1 - 4 of 4
  • Thumbnail Image
    Item
    Applying Bayesian Cognitive Models to Decisions to Drive after Drinking
    (Wiley, 2021) McCarthy, Denis M.; McCarty, Kayleigh N.; Hatz, Laura E.; Prestigiacomo, Christiana J.; Park, Sanghyuk; Davis-Stober, Clintin P.; Psychology, School of Science
    Background and aims: Despite widespread negative perceptions, the prevalence of alcohol-impaired driving (AID) in the United States remains unacceptably high. This study used a novel decision task to evaluate whether individuals considered both ride service cost and alcohol consumption level when deciding whether or not to drive, and whether the resulting strategy was associated with engagement in AID. Design: A two-sample study, where sample 1 developed a novel AID decision task to classify participants by decision strategy. Sample 2 was used to cross-validate the task and examine whether decision strategy classifications were predictive of prior reported AID behavior. Setting: A laboratory setting at the University of Missouri, USA. Participants: Sample 1 included 38 student participants from introductory psychology classes at the University of Missouri. Sample 2 included 67 young adult participants recruited from the local community. Measurements: We developed a decision task that presented hypothetical drinking scenarios that varied in quantity of alcohol consumption (one to six drinks) and the cost of a ride service ($5-25). We applied a Bayesian computational model to classify choices as consistent with either: integrating both ride cost and consumption level (compensatory) or considering only consumption level (non-compensatory) when making hypothetical AID decisions. In sample 2, we assessed established AID risk factors (sex, recent alcohol consumption, perceived safe limit) and recent (past 3 months) engagement in AID. Findings: In sample 1, the majority of participants were classified as using decision strategies consistent with either a compensatory or non-compensatory process. Results from sample 2 replicated the overall classification rate and demonstrated that participants who used a compensatory strategy were more likely to report recent AID, even after accounting for study covariates. Conclusions: In a hypothetical alcohol-impaired driving (AID) decision task, individuals who considered both consumption level and ride service cost were more likely to report recent AID than those who made decisions based entirely on consumption level.
  • Thumbnail Image
    Item
    Bayesian multivariate longitudinal model for immune responses to Leishmania: A tick-borne co-infection study
    (Wiley, 2023-09-20) Pabon-Rodriguez, Felix M.; Brown, Grant D.; Scorza, Breanna M.; Petersen, Christine A.; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public Health
    While many Bayesian state-space models for infectious disease processes focus on population infection dynamics (eg, compartmental models), in this work we examine the evolution of infection processes and the complexities of the immune responses within the host using these techniques. We present a joint Bayesian state-space model to better understand how the immune system contributes to the control of Leishmania infantum infections over the disease course. We use longitudinal molecular diagnostic and clinical data of a cohort of dogs to describe population progression rates and present evidence for important drivers of clinical disease. Among these results, we find evidence for the importance of co-infection in disease progression. We also show that as dogs progress through the infection, parasite load is influenced by their age, ectoparasiticide treatment status, and serology. Furthermore, we present evidence that pathogen load information from an earlier point in time influences its future value and that the size of this effect varies depending on the clinical stage of the dog. In addition to characterizing the processes driving disease progression, we predict individual and aggregate patterns of Canine Leishmaniasis progression. Both our findings and the application to individual-level predictions are of direct clinical relevance, presenting possible opportunities for application in veterinary practice and motivating lines of additional investigation to better understand and predict disease progression. Finally, as an important zoonotic human pathogen, these results may support future efforts to prevent and treat human Leishmaniosis.
  • Thumbnail Image
    Item
    Chronology of a Fortified Mississippian Village in the Central Illinois River Valley
    (Cambridge, 2019-06) Krus, Anthony M.; Hermann, Edward W.; Pike, Matthew D.; Monaghan, G. William; Wilson, Jeremy J.; Geography, School of Liberal Arts
    Geophysical survey and excavations from 2010–2016 at Lawrenz Gun Club (11CS4), a late pre-Columbian village located in the central Illinois River valley in Illinois, identified 10 mounds, a central plaza, and dozens of structures enclosed within a stout 10 hectare bastioned palisade. Nineteen radiocarbon (14C) measurements were taken from single entities of wood charcoal, short-lived plants, and animal bones. A site chronology has been constructed using a Bayesian approach that considers the stratigraphic contexts and feature formation processes. The village was host to hundreds of years of continuous human activity during the Mississippi Period. Mississippian activity at the site is estimated to have begun in cal AD 990–1165 (95% probability), ended in cal AD 1295–1450 (95% probability), and lasted 150–420 yr (95% probability) in the primary Bayesian model with similar results obtained in two alternative models. The palisade is estimated to have been constructed in cal AD 1150–1230 (95% probability) and was continuously repaired and rebuilt for 15–125 yr (95% probability), probably for 40–85 yr (68% probability). Comparison to other studies demonstrates that the bastioned palisade at Lawrenz was one of the earliest constructed in the midcontinental United States.
  • Thumbnail Image
    Item
    Within-host bayesian joint modeling of longitudinal and time-to-event data of Leishmania infection
    (PLOS, 2024-02-09) Pabon-Rodriguez, Felix M.; Brown, Grant D.; Scorza, Breanna M.; Petersen, Christine A.; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public Health
    The host immune system plays a significant role in managing and clearing pathogen material during an infection, but this complex process presents numerous challenges from a modeling perspective. There are many mathematical and statistical models for these kinds of processes that take into account a wide range of events that happen within the host. In this work, we present a Bayesian joint model of longitudinal and time-to-event data of Leishmania infection that considers the interplay between key drivers of the disease process: pathogen load, antibody level, and disease. The longitudinal model also considers approximate inflammatory and regulatory immune factors. In addition to measuring antibody levels produced by the immune system, we adapt data from CD4+ and CD8+ T cell proliferation, and expression of interleukin 10, interferon-gamma, and programmed cell death 1 as inflammatory or regulatory factors mediating the disease process. The model is developed using data collected from a cohort of dogs naturally exposed to Leishmania infantum. The cohort was chosen to start with healthy infected animals, and this is the majority of the data. The model also characterizes the relationship features of the longitudinal outcomes and time-to-death due to progressive Leishmania infection. In addition to describing the mechanisms causing disease progression and impacting the risk of death, we also present the model’s ability to predict individual trajectories of Canine Leishmaniosis (CanL) progression. The within-host model structure we present here provides a way forward to address vital research questions regarding the understanding of the progression of complex chronic diseases such as Visceral Leishmaniasis, a parasitic disease causing significant morbidity worldwide.