COVID-19 Commons^™

A Longitudinal Analysis Of Hospital Consumer Evaluation In Virginia, Tulay Akmandor Inac

Health Services Research Dissertations

Suboptimal patient experience signals a need to improve clinical efficacy, patient safety, and healthcare quality. The COVID-19 pandemic intensified hospital resource and staffing demands, reducing hospitals’ capacity to invest in patient experience improvement. Prior studies remain limited because many lack longitudinal structure and organized theoretical models, making temporal inference difficult and weakening analyses of patient experience disparities. To address these limitations, this dissertation incorporates three studies examining patient experience and pandemic-related effects.

In state-level markets comparable to Virginia, limited research has examined longitudinal patient experience trends across regional hospital systems using HCAHPS scores. The first study uses descriptive trend analysis …

Cultural Traits May Replace Human Mobility Data In Forecasting Covid-19 Mortality: A Deep Learning Approach, Saif Abbas, Tamer Oraby, Michael G. Tyshenko, Samit Bhattacharyya

School of Mathematical & Statistical Sciences Faculty Publications

The COVID-19 pandemic highlighted the need for accurate epidemic forecasting to support public health decision-making. Most existing approaches depend heavily on human mobility data, while largely neglecting population behavior shaped by socio-cultural norms. In this study, we analyze daily COVID-19 mortality and Google mobility data from 72 countries during the first 130 d of the pandemic, a period characterized by high uncertainty and behavioral heterogeneity. In particular, we examine whether Hofstede’s country-level cultural dimensions can serve as latent behavioral forecasters of mortality in lieu of dynamic mobility indicators. Using 100 d for training and 30 d for forecasting, we employ …

Utilizing Machine Learning Techniques For Computer-Aided Covid-19 Screening Based On Clinical Data, Honglun Xu, Andrews T. Anum, Michael Pokojovy, Sreenath Chalil Madathil, Yuxin Wen, Md. Fashiar Rahman, Tzu-Liang Bill Tseng, Scott Moen, Eric Walser

Engineering Faculty Articles and Research

The COVID-19 pandemic has highlighted the importance of rapid clinical decision-making to facilitate the efficient usage of healthcare resources. Over the past decade, machine learning (ML) has caused a tectonic shift in healthcare, empowering data-driven prediction and decision-making. Recent research demonstrates how ML was used to respond to the COVID-19 pandemic. This paper puts forth new computer-aided COVID-19 disease screening techniques using six classes of ML algorithms (including penalized logistic regression, random forest, artificial neural networks, and support vector machines) and evaluates their performance when applied to a real-world clinical dataset containing patients’ demographic information and vital indices (such as …

Optimal Intervention Strategies In Age-Structured Sirvd Model: Epidemiological And Economic Analysis Of Covid-19 In Korea, Joon Chun, Melisa Hendrata

Spora: A Journal of Biomathematics

This study employed an age-structured Susceptible-Infected-Recovered-Vaccinated-Deceased (SIRVD) model to design optimal COVID‑19 intervention strategies by integrating epidemiological dynamics with economic costs. Using empirical data from South Korea, we estimated transmission parameters and analyzed quarantine-based non-pharmaceutical interventions (NPIs) alongside targeted vaccination scenarios. Our results indicated that a stronger form of mild NPI (upper range of Level I), when combined with targeted vaccination that prioritized seniors, achieved substantial reductions in infection peaks and overall economic burden. These findings underscore the effectiveness of age-specific strategies in epidemic management and offer critical insights for policymakers seeking balanced, resource-efficient approaches.

Barriers To Immunity: Understanding Covid-19 Vaccine Uptake In Africa, Emilia Blechschmidt

Honors Theses

This thesis examines the factors influencing COVID-19 vaccine uptake across African countries, with a focus on structural, informational, and behavioral barriers to immunization. Drawing on cross-country data, the study analyzes how access to transportation, reliable information, and healthcare resources shape vaccination rates, alongside the effect of demographics and institutional factors in shaping individual perceptions of risk and vaccine safety.

The findings emphasize that the broader strength and preparedness of national health systems strongly influence vaccine uptake. Countries that demonstrated higher coverage of routine childhood immunizations, such as polio and hepatitis B, also tended to perform better in COVID-19 uptake efficiency …

Nirmatrelvir-Ritonavir Targeting Viral Persistence In Post-Covid-19 Condition (Long Covid) In The Usa (Recover-Vital): A Randomized, Double-Blind, Placebo Controlled, Phase 2 Trial, Lindsey R. Baden, Nirav S. Shah, Sean T. H. Liu, Jonathan Cohen, James May, Andre Kumar, Grace A. Mccomsey, Peter Chen, Michelle Floris-Moore, Nora G. Singer, Inti Fernandez, Alex J. Slandzicki, Zanthia Wiley, Alexandra Kadl, David A. Kaminsky, Harvey Hsu, Tiffany A. Walker, Aluko A. Hope, Luis Ostrosky-Zeichner, Jason D. Goldman, Michael J. Peluso, Thomas F. Patterson, Sairam Parthasarathy, Janet M. Mullington, Paul Bolin Jr., Sarah E. Jolley, Jerry A. Krishnan, Mario Castro, Sally L. Hodder, Priscilla Pemu, Helen Y. Chu, Michael G. Risbano, Maya R. Jerath, Eleftherios Mylonakis, Ryan T. Hurt, Radica Alicic, Nabila S. Azad, Marc A. Sala, Michelle S. Harkins, Jeffrey Parsonnet, Neil Stafford, Philip Robinson, Sabiha Hussain, Xian Qiao, Sophie Two Hawk, Michael Lillestol, Nathan Erdmann, Kelly A. Gebo, Praveen Sudhindra, Joseph Sassine, Gailen D. Marshall, Tulika Chatterjee, Caryn G. Morse, Eyal Kedar, William W. Stringer, Jennifer A. Frontera, Michael Jordon, Caitlin Blaskewicz, Jorge L. Santana, Rachel A. Foot, Cherry Wongtrakool, Matthew William Mccarthy, Alem Mehari, Arch Amon, Alison K. Cohen, Nita Jain, Christine Maughan, Doug Lindsay, Rachel Olson, Samuel Broderick, Pearl Rowe, Sean M. O'Brien, David R. Walt, Bruce D. Levy, Leonard A. Jason, Phillip A. Low, Cyndya A. Shibao, Barry Make, Lucinda Bateman, Susan Redline, David Knopman, Adrian F. Hernandez, Tracy L. Nolen, Craig Reist, Lisa Berdan, Richard Whitley, Kanecia O. Zimmerman, For The Recover-Vital Clinical Trial Group

Department of Medicine Faculty Publications

Background

Post-acute sequelae of SARS-CoV-2 infection, more commonly known as long COVID, has emerged as a major health problem. The pathogenesis of long COVID is unknown, but among the leading hypotheses is viral persistence. We aimed to investigate whether the use of the SARS-CoV-2 antiviral nirmatrelvir-ritonavir improved long COVID symptoms.

Methods

We conducted a double-blind, placebo-controlled, randomised trial involving adults who had developed persistent symptoms (≥12 weeks) associated with three major symptom phenotypes (cognitive, autonomic, or exercise) after acute SARS-CoV-2 infection at 69 US sites. Participants were eligible if they were 18 years or older and had a previous suspected, …

Multi-Resolution Graph Neural Networks For Spread Prediction, Petr Kisselev

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

The Science Of Sound: Studying The Cognitive, Emotional, And Physiological Effects Of Frequency, Genre, And Music, Jett Yarborough

Senior Honors Theses

Music influences emotion, physiology, and cognition, yet little is known about how the frequency it is tuned to affects these influences. Prior research has shown that music tuned to 432 Hz can reduce stress, lower blood pressure, and improve sleep. My colleagues and I conducted two studies to investigate this. Our research found that music tuned to 432 Hz promotes a significant increase in memory retention and induces a state of focus and relaxation. These results suggest that shifting from the standard tuning frequency of 440 Hz to 432 Hz could have a profoundly positive impact on our daily lives. …

Dynamic Mutational Profiling Of Binding Interactions And Allosteric Networks In Conformational Ensembles Of The Sars-Cov-2 Spike Protein Complexes With Classes Of Antibodies Targeting Cryptic Binding Sites: Confluence Of Binding And Allostery Determines Molecular Mechanisms And Hotspots Of Immune Escape, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

The ongoing evolution of SARS-CoV-2 variants has underscored the need to understand not only the structural basis of antibody recognition but also the dynamic and allosteric mechanisms that could underlie complexity of broad and escape-resistant neutralization. In this study, we employed a multi-scale approach integrating structural analysis, hierarchical molecular simulations, mutational scanning and network-based allosteric modeling to dissect how Class 4 antibodies (represented by S2X35, 25F9, and SA55) and Class 5 antibodies (represented by S2H97, WRAIR-2063 and WRAIR-2134) can modulate conformational behavior, binding energetics, allosteric interactions and immune escape patterns of the SARS-CoV-2 spike protein. Using hierarchical simulations of the …

Multiscale Modeling And Dynamic Mutational Profiling Of Binding Energetics And Immune Escape For Class I Antibodies With Sars-Cov-2 Spike Protein: Dissecting Mechanisms Of High Resistance To Viral Escape Against Emerging Variants, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

The rapid evolution of SARS-CoV-2 has underscored the need for a detailed understanding of antibody binding mechanisms to combat immune evasion by emerging variants. In this study, we investigated the interactions between Class I neutralizing antibodies—BD55-1205, BD-604, OMI-42, P5S-1H1, and P5S-2B10—and the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein using multiscale modeling, which combined molecular simulations with the ensemble-based mutational scanning of the binding interfaces and binding free energy computations. A central theme emerging from this work is that the unique binding strength and resilience to immune escape of the BD55-1205 antibody are determined by leveraging a broad epitope …

Modeling, Analysis, And Prediction Of Covid-19 Dynamics With Interacting Subpopulations And Implicit Behavior Using Physics-Informed Neural Networks, Naima Aubry-Romero, Alonso Ogueda-Oliva, Padmanabhan Seshaiyer

Spora: A Journal of Biomathematics

In this paper, we consider an extended SEIR compartmental model that incorporates young and old interacting subpopulations, allowing for cross-group transmission dynamics. Implicit behavioral changes are included to determine the influence of social behavior on coronavirus transmission dynamics. The basic reproduction number, the average number of secondary cases of infection produced by a single primary case, is derived for both the explicit and implicit model using the next-generation matrix method. We solve the associated differential equation systems and estimate useful parameters in the explicit model using physics-informed neural networks (PINNs). Our results point to how the PINNs approach offers an …

Opioid Epidemic In Maine: An Analysis Of Increasing Overdose-Related Deaths Following The Coronavirus, Aysel S. Hamlin

Thinking Matters Symposium

The rate of drug overdose resulting in death doubled in Maine following the COVID-19 pandemic from the onset of the COVID-19 pandemic in late 2019 through 2022. The correlation between increased isolation during the pandemic and overdose death rates sheds a concerning light on the insufficient resources for people struggling with Opioid Use Disorder (OUD) throughout Maine. The increasing trade and access to fentanyl following the pandemic accounted for the majority of drug-related deaths in Maine in 2021 and 2022. This study examines the need for long-term access to drug treatment in rural and urban Maine, both environments with varying …

Differences In Covid-19 Deaths Amongst Cancer Patients And Possible Mediators For This Relationship, Leah Vaidya, Nubaira Rizvi, Xiao Cheng Wu, Lauren S. Maniscalco, Yong Yi, Augusto Ochoa, Qingzhao Yu

School of Public Health Faculty Publications

Previous research demonstrated Non-Hispanic Black populations experience higher COVID-19 mortality rates than Non-Hispanic White individuals. Additionally, cancer status is a known risk factor for COVID-19 death. While prior studies investigated comorbidities as exploratory variables in differences in COVID-19 hospitalization, none have explored their role in COVID-19-related deaths. This study aimed to evaluate whether Charlson Comorbidity Index (CCI) and subsequently, individual diseases are potential explanatory variables for this relationship. The analysis focused on Non-Hispanic Black and Non-Hispanic White cancer patients aged 20 or older, diagnosed between 2011 and 2019, who tested positive for COVID-19 from the start of pandemic through June …

Critical Appraisal Of Multidrug Therapy In The Ambulatory Management Of Patients With Covid-19 And Hypoxemia. Part Ii: Causal Inference Using The Bradford Hill Criteria, Eleftherios Gkioulekas, Peter A. Mccullough, Colleen Aldous

School of Mathematical & Statistical Sciences Faculty Publications

We continue the critical appraisal of three published case series of 119 COVID-19 patients with hypoxemia, treated in the United States, Zimbabwe, and Nigeria with similar ivermectin-based multidrug treatments, to assess the available evidence supporting a causal relationship between treatment and reduction in hospitalizations and mortality. A narrative review was conducted to assess the Bradford Hill criteria for a causal association. We used a previously proposed refinement of the Bradford Hill criteria that reorganized them into three categories of direct, mechanistic, and parallel evidence. The efficacy of the two most aggressive ivermectin-based multidrug protocols is supported by the Bradford Hill …

Critical Appraisal Of Multidrug Therapy In The Ambulatory Management Of Patients With Covid-19 And Hypoxemia Part I. Evidence Supporting The Strength Of Association, Eleftherios Gkioulekas, Peter A. Mccullough, Colleen Aldous

School of Mathematical & Statistical Sciences Faculty Publications

This critical appraisal is focused on three published case series of 119 COVID-19 patients with hypoxemia who were successfully treated in the United States, Zimbabwe, and Nigeria with similar off-label ivermectin-based multidrug treatments that may include ivermectin, nebulized nanosilver, doxycycline, zinc, Vitamins C, and Vitamin D, resulting in rapid recovery of oxygen levels. We used a simplified self-controlled case series method to investigate the association between treatment and the existence of hospitalization rate reduction. External controls of hospitalized patients were compared against the subgroup of patients with baseline room air SpO2 ≤ 90% to investigate the association between treatment and …

Precision Phenotyping For Curating Research Cohorts Of Patients With Unexplained Post-Acute Sequelae Of Covid-19, Alaleh Azhir, Jonas Hügel, Jiazi Tian, Jingya Cheng, Ingrid V Bassett, Douglas S Bell, Elmer V Bernstam, Maha R Farhat, Darren W Henderson, Emily S Lau, Michele Morris, Yevgeniy R Semenov, Virginia A Triant, Shyam Visweswaran, Zachary H Strasser, Jeffrey G Klann, Shawn N Murphy, Hossein Estiri

Faculty, Staff and Student Publications

BACKGROUND: Scalable identification of patients with post-acute sequelae of COVID-19 (PASC) is challenging due to a lack of reproducible precision phenotyping algorithms, which has led to suboptimal accuracy, demographic biases, and underestimation of the PASC.

METHODS: In a retrospective case-control study, we developed a precision phenotyping algorithm for identifying cohorts of patients with PASC. We used longitudinal electronic health records data from over 295,000 patients from 14 hospitals and 20 community health centers in Massachusetts. The algorithm employs an attention mechanism to simultaneously exclude sequelae that prior conditions can explain and include infection-associated chronic conditions. We performed independent chart reviews …

False Narratives, Real Consequences, Russell W. Cantrell, Matt Campbell

Shelby Hall Graduate Research Forum Posters

Social media is an increasingly significant tool in modern cyber warfare, capable of rapidly shaping public opinion. The swift dissemination of information complicates efforts to distinguish fact from fiction [1]. During public health crises, healthcare professionals use these platforms to share updates, yet their credible content must contend with false or deliberately misleading narratives [2]. This environment creates an opportunity for cyberattacks through social media influence campaigns [3]. While disinformation's role in political interference has been widely studied, its potential to destabilize healthcare remains largely unexplored. Prior research primarily focuses on how vaccine misinformation affects the general public [4]. This …

Mutational Scanning And Binding Free Energy Computations Of The Sars-Cov-2 Spike Complexes With Distinct Groups Of Neutralizing Antibodies: Energetic Drivers Of Convergent Evolution Of Binding Affinity And Immune Escape Hotspots, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Nishank Raisinghani, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

The rapid evolution of SARS-CoV-2 has led to the emergence of variants with increased immune evasion capabilities, posing significant challenges to antibody-based therapeutics and vaccines. In this study, we conducted a comprehensive structural and energetic analysis of SARS-CoV-2 spike receptor-binding domain (RBD) complexes with neutralizing antibodies from four distinct groups (A–D), including group A LY-CoV016, group B AZD8895 and REGN10933, group C LY-CoV555, and group D antibodies AZD1061, REGN10987, and LY-CoV1404. Using coarse-grained simplified simulation models, rapid energy-based mutational scanning, and rigorous MM-GBSA binding free energy calculations, we elucidated the molecular mechanisms of antibody binding and escape mechanisms, identified key …

Quantitative Characterization And Prediction Of The Binding Determinants And Immune Escape Hotspots For Groups Of Broadly Neutralizing Antibodies Against Omicron Variants: Atomistic Modeling Of The Sars-Cov-2 Spike Complexes With Antibodies, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Nishank Raisinghani, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

A growing body of experimental and computational studies suggests that the cross-neutralization antibody activity against Omicron variants may be driven by the balance and tradeoff between multiple energetic factors and interaction contributions of the evolving escape hotspots involved in antigenic drift and convergent evolution. However, the dynamic and energetic details quantifying the balance and contribution of these factors, particularly the balancing nature of specific interactions formed by antibodies with epitope residues, remain largely uncharacterized. In this study, we performed molecular dynamics simulations, an ensemble-based deep mutational scanning of SARS-CoV-2 spike residues, and binding free energy computations for two distinct groups …

Association Between Lifetime Interpersonal Violence And Post– Covid-19 Condition Among Women In Kentucky, 2020-2022, Ayşe Güler, Heather M. Bush, Katie Schill, Nurlan Kussainov, Ann L. Coker

Biostatistics Faculty Publications

Objective: The COVID-19 pandemic increased the risk of interpersonal violence. We investigated the association between lifetime interpersonal violence experience and risk of post–COVID-19 condition (the persistence of symptoms of COVID-19 and severity of health problems associated with COVID-19 that last a few weeks, months, or years) among women with lifetime interpersonal violence experience.   Methods: Women participants aged ≥18 years in Kentucky’s Wellness, Health & You—COVID-19 study completed online quantitative surveys about the impacts of the pandemic, developing COVID-19, and symptoms of post–COVID-19 condition. We conducted cross-sectional analyses estimating rate ratios of developing COVID-19 and symptoms of post–COVID-19 condition during the …

Changes In Cancer Diagnosis And Survival In The United States During The Covid-19 Pandemic, Justin T. Burus

Theses and Dissertations--Epidemiology and Biostatistics

The COVID-19 Pandemic led to global societal disruptions as political leaders and public health authorities attempted to control the spread of the newly discovered SARS- CoV-2 virus. While these measures were designed to lessen morbidity and mortality from a novel pathogen, their impact was also felt in many other, often unintended ways. The purpose of this dissertation is to use cancer surveillance research methods to examine the association between COVID-19 Pandemic-related disruptions and changes in the normal diagnosis and care of cancer in the United States.

The first two studies of this dissertation analyzed reductions in cancer diagnoses in the …

Theoretical Foundations And Applied Performance Of Periodicity-Aware Imputation: Variable Bandpass Block Bootstrap Methods For Incomplete Time Series, Asmaa Ahmad

Electronic Theses & Dissertations (2024 - present)

Time series data are prevalent across a wide range of disciplines, including health surveillance, public policy, and environmental monitoring. In the presence of underlying cyclical patterns, the integrity of time series analysis depends critically on the ability to detect, model, and impute structured missing data without compromising the temporal structure. This dissertation introduces and validates a novel imputation framework that integrates the Variable Bandpass Periodic Block Bootstrap (VBPBB) into multiple imputation procedures, improving the accuracy, robustness, and interpretability of time series models under high rates of missingness and noise. The overarching goal of this dissertation was to develop and evaluate …

Improving Infectious Disease Predictions Through The Use Of Metapopulation Sir Modeling And Graph Convolutional Neural Networks, Petr Kisselev, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

A Case Demonstration Of The Open Health Natural Language Processing Toolkit From The National Covid-19 Cohort Collaborative And The Researching Covid To Enhance Recovery Programs For A Natural Language Processing System For Covid-19 Or Postacute Sequelae Of Sars Cov-2 Infection: Algorithm Development And Validation, Andrew Wen, Liwei Wang, Huan He, Sunyang Fu, Sijia Liu, David A Hanauer, Daniel R Harris, Ramakanth Kavuluru, Rui Zhang, Karthik Natarajan, Nishanth P Pavinkurve, Janos Hajagos, Sritha Rajupet, Veena Lingam, Mary Saltz, Corey Elowsky, Richard A Moffitt, Farrukh M Koraishy, Matvey B Palchuk, Jordan Donovan, Lora Lingrey, Garo Stone-Derhagopian, Robert T Miller, Andrew E Williams, Peter J Leese, Paul I Kovach, Emily R Pfaff, Mikhail Zemmel, Robert D Pates, Nick Guthe, Melissa A Haendel, Christopher G Chute, Hongfang Liu, National Covid Cohort Collaborative, Recover Initiative

Faculty, Staff and Student Publications

BACKGROUND: A wealth of clinically relevant information is only obtainable within unstructured clinical narratives, leading to great interest in clinical natural language processing (NLP). While a multitude of approaches to NLP exist, current algorithm development approaches have limitations that can slow the development process. These limitations are exacerbated when the task is emergent, as is the case currently for NLP extraction of signs and symptoms of COVID-19 and postacute sequelae of SARS-CoV-2 infection (PASC).

OBJECTIVE: This study aims to highlight the current limitations of existing NLP algorithm development approaches that are exacerbated by NLP tasks surrounding emergent clinical concepts and …

Disparities And Protective Factors In Pandemic-Related Mental Health Outcomes: A Louisiana-Based Study, Ariane L. Rung, Evrim Oral, Tyler Prusisz, Edward S. Peters

School of Public Health Faculty Publications

Introduction: The COVID-19 pandemic has had a wide-ranging impact on mental health. Diverse populations experienced the pandemic differently, highlighting pre-existing inequalities and creating new challenges in recovery. Understanding the effects across diverse populations and identifying protective factors is crucial for guiding future pandemic preparedness. The objectives of this study were to (1) describe the specific COVID-19-related impacts associated with general well-being, (2) identify protective factors associated with better mental health outcomes, and (3) assess racial disparities in pandemic impact and protective factors. Methods: A cross-sectional survey of Louisiana residents was conducted in summer 2020, yielding a sample of 986 Black …

Gender-Specific Mental Health Outcomes In Central America: A Natural Experiment, Thea Nagasuru

Computer Science Summer Fellows

While COVID lockdown measures have had varying effects on the mental health of different demographics, several bodies of research have noted their disparate effect on women. Why is women's mental health more negatively impacted by lockdown measures, and how much more are they impacted than men? How can we predict and mitigate these negative effects on women? This paper aims to contribute to answering those questions by comparing COVID stringency measures and their effect on the gap in depression rates between men and women in two neighboring countries: Nicaragua and Honduras.

The Protective Efficacy Of A Sars-Cov-2 Vaccine Candidate B1351v Against Several Variant Challenges In K18-Hace2 Mice, Jie Yang, Huifen Fan, Anna Yang, Wenhui Wang, Xin Wan, Fengjie Lin, Dongsheng Yang, Jie Wu, Kaiwen Wang, Wei Li, Qian Cai, Lei You, Deqin Pang, Jia Lu, Changfu Guo, Jinrong Shi, Yan Sun, Xinguo Li, Kai Duan, Shuo Shen, Shengli Meng, Jing Guo, Zejun Wang

Faculty, Staff and Student Publications

The emergence of SARS-CoV-2 variants of concern (VOCs) with increased transmissibility and partial resistance to neutralization by antibodies has been observed globally. There is an urgent need for an effective vaccine to combat these variants. Our study demonstrated that the B.1.351 variant inactivated vaccine candidate (B.1.351V) generated strong binding and neutralizing antibody responses in BALB/c mice against the B.1.351 virus and other SARS-CoV-2 variants after two doses within 28 days. Immunized K18-hACE2 mice also exhibited elevated levels of live virus-neutralizing antibodies against various SARS-CoV-2 viruses. Following infection with these viruses, K18-hACE2 mice displayed a stable body weight, a high survival …

Ai-Assisted Study In Post Pandemic Disruptions Of Operations And Supply Chain Management Practices, Raouf G. Ghattas, Andrew Burnstine

Faculty and Staff Publications & Presentations

The presentation explored the nature of the Fashion Industry group, the disruptions, the impact on the industry as a whole, in terms of Profitability, Consumer preference, Demand, Logistics and Inventory positions, then discuss the mitigations adopted by each industry group, and finally strategies for the way forward.

The presentation explored the nature of the Fashion Industry group, the disruptions, the impact on the industry as a whole, in terms of Profitability, Consumer preference, Demand, Logistics and Inventory positions, then discuss the mitigations adopted by each industry group, and finally strategies for the way forward.

Increased Incidence Of Vestibular Disorders In Patients With Sars-Cov-2, Lawrance Lee, Evan French, Daniel H Coelho, Nauman F Manzoor, Adam B Wilcox, Adam M Lee, Alexis Graves, Alfred Anzalone, Amin Manna, Amit Saha, Amy Olex, Andrea Zhou, Andrew E Williams, Andrew Southerland, Andrew T Girvin, Anita Walden, Anjali A Sharathkumar, Benjamin Amor, Benjamin Bates, Brian Hendricks, Brijesh Patel, Caleb Alexander, Carolyn Bramante, Cavin Ward-Caviness, Charisse Madlock-Brown, Christine Suver, Christopher Chute, Christopher Dillon, Chunlei Wu, Clare Schmitt, Cliff Takemoto, Dan Housman, Davera Gabriel, David A Eichmann, Diego Mazzotti, Don Brown, Eilis Boudreau, Elaine Hill, Elizabeth Zampino, Emily Carlson Marti, Emily R Pfaff, Evan French, Farrukh M Koraishy, Federico Mariona, Fred Prior, George Sokos, Greg Martin, Harold Lehmann, Heidi Spratt, Hemalkumar Mehta, Hongfang Liu, Hythem Sidky, J W Awori Hayanga, Jami Pincavitch, Jaylyn Clark, Jeremy Richard Harper, Jessica Islam, Jin Ge, Joel Gagnier, Joel H Saltz, Joel Saltz, Johanna Loomba, John Buse, Jomol Mathew, Joni L Rutter, Julie A Mcmurry, Justin Guinney, Justin Starren, Karen Crowley, Katie Rebecca Bradwell, Kellie M Walters, Ken Wilkins, Kenneth R Gersing, Kenrick Dwain Cato, Kimberly Murray, Kristin Kostka, Lavance Northington, Lee Allan Pyles, Leonie Misquitta, Lesley Cottrell, Lili Portilla, Mariam Deacy, Mark M Bissell, Marshall Clark, Mary Emmett, Mary Morrison Saltz, Matvey B Palchuk, Melissa A Haendel, Meredith Adams, Meredith Temple-O'Connor, Michael G Kurilla, Michele Morris, Nabeel Qureshi, Nasia Safdar, Nicole Garbarini, Noha Sharafeldin, Ofer Sadan, Patricia A Francis, Penny Wung Burgoon, Peter Robinson, Philip R O Payne, Rafael Fuentes, Randeep Jawa, Rebecca Erwin-Cohen, Rena Patel, Richard A Moffitt, Richard L Zhu, Rishi Kamaleswaran, Robert Hurley, Robert T Miller, Saiju Pyarajan, Sam G Michael, Samuel Bozzette, Sandeep Mallipattu, Satyanarayana Vedula, Scott Chapman, Shawn T O'Neil, Soko Setoguchi, Stephanie S Hong, Steve Johnson, Tellen D Bennett, Tiffany Callahan, Umit Topaloglu, Usman Sheikh, Valery Gordon, Vignesh Subbian, Warren A Kibbe, Wenndy Hernandez, Will Beasley, Will Cooper, William Hillegass, Xiaohan Tanner Zhang

Faculty, Staff and Student Publications

OBJECTIVE: Determine the incidence of vestibular disorders in patients with SARS-CoV-2 compared to the control population.

STUDY DESIGN: Retrospective.

SETTING: Clinical data in the National COVID Cohort Collaborative database (N3C).

METHODS: Deidentified patient data from the National COVID Cohort Collaborative database (N3C) were queried based on variant peak prevalence (untyped, alpha, delta, omicron 21K, and omicron 23A) from covariants.org to retrospectively analyze the incidence of vestibular disorders in patients with SARS-CoV-2 compared to control population, consisting of patients without documented evidence of COVID infection during the same period.

RESULTS: Patients testing positive for COVID-19 were significantly more likely to have …

Supporting South Korea’S Aging Population: How Ai And Iot Acceptance Connects The Young And Old, Bobby Im

Master's Projects and Capstones

In 2024, South Korea surpassed every other nation by becoming the country with the lowest fertility rate (below 0.7%). Population decline will hinder future ability to care for their aging population and although the government and private corporations are investing millions of dollars on developing Artificial Intelligence-Internet of Things (AI-IoT) devices to support the aging, the acceptance levels and the amount of family support required is undervalued. By examining AI-IoT’s current use and role in South Korea’s public health system this paper shows how intergenerational support helps optimize existing procedures and equipment, increases the level of acceptance and use, and …