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Impact Of Covid-19 On Recruitment Of High School Athletes To Di Track And Field, Christopher Haub, Jon Paugh, Alonso Salcido, Monnie Mcgee

SMU Data Science Review

Due to COVID-19, in the spring of 2020, the NCAA gave scholarship athletes an extra year of eligibility but did not increase the number of scholarships a school could issue. This potentially led to increased competition for scholarships as coaches could choose between retaining athletes or recruiting new ones. Furthermore, the Spring 2020 track and field season for high school seniors ended early – limiting high school athletes’ chance to get their best scores, and interrupting student to college interaction. This research looks specifically at the impact of COVID-19, and the resulting NCAA policy changes, on the recruitment to DI …

Raman Spectroscopic Analysis Of Human Serum Samples Of Convalescing Covid-19 Positive Patients, Hugh Byrne, Naomi Jackson, Jaythoon Hassan

Articles

Rapid screening, detection and monitoring of viral infection is of critical importance, as exemplified by the rapid spread of SARS-CoV-2, leading to the worldwide pandemic of COVID-19. This is equally the case for the stages of patient convalescence as for the initial stages of infection, to understand the medium and long terms effects, as well as the efficacy of therapeutic interventions. Optical spectroscopic techniques potentially offer an alternative to currently employed techniques of screening for the presence, or the response to infection. In this study, the ability of Raman spectroscopy to distinguish between samples of the serum of convalescent COVID-19 …

(R2059) Modeling The Spread Of Coronavirus With Self-Protection And Quarantine Effect, Dileep Sharma, Agraj Tripathi, Ram Naresh Tripathi

Applications and Applied Mathematics: An International Journal (AAM)

A nonlinear mathematical model to study the effect of transmission dynamics of COVID-19 virus in a population with variable size structure is proposed and analyzed. The model divides the total human population into five subclasses: susceptibles, self-protected susceptibles, infectives, quarantined infectives, and recovered population including a class representing cumulative density of coronavirus in the environmental reservoir. The model exhibits two equilibria, namely, the diseasefree and the endemic equilibrium. Model analysis reveals the global dynamics of the spread of COVID-19 is completely determined by the basic reproduction number. If basic reproduction number is greater than one, the endemic equilibrium is locally …

The Impacts Of The Covid-19 Pandemic On Mental Health Across Different Genders And Sexualities, Jiale Zhu, Jonas Katona

Undergraduate Research Journal for the Human Sciences

Current studies report an increase in psychological distress as a result of the COVID-19 pandemic. This study is interested in examining mental health disparities and how the COVID-19 pandemic has disproportionately impacted marginalized groups—and more specifically, those identified by sex, gender, and sexuality—compared with the general population. This study also considers the effects and ramifications of different policy measures taken during the course of the pandemic. We perform exploratory data modeling and analysis on several important and publicly available datasets taken during the pandemic on mental health and COVID-19 infection data across various identity groups to look for significant disparities, …

Promoting Data Harmonization To Evaluate Vaccine Hesitancy In Lmics: Approach And Applications, Ryan Rego, Yuri Zhukov, Kyrani Reneau, Amy Pienta, Kristina L. Rice, Patrick Brady, Geoffrey Siwo, Peninah Wachira, Amina Abubakar, Ken Kollman

Institute for Human Development

Background: Factors influencing the health of populations are subjects of interdisciplinary study. However, datasets relevant to public health often lack interdisciplinary breath. It is difficult to combine data on health outcomes with datasets on potentially important contextual factors, like political violence or development, due to incompatible levels of geographic support; differing data formats and structures; differences in sampling procedures and wording; and the stability of temporal trends. We present a computational package to combine spatially misaligned datasets, and provide an illustrative analysis of multi-dimensional factors in health outcomes.

Methods: We rely on a new software toolkit, Sub-National Geospatial Data Archive …

Machine Learning Techniques For The Identification Of Risk Factors Associated With Food Insecurity Among Adults In Arab Countries During The Covid-19 Pandemic, Radwan Qasrawi, Maha Hoteit, Reema Tayyem, Khlood Bookari, Haleama Al Sabbah, Iman Kamel, Somaia Dashti, Sabika Allehdan, Hiba Bawadi, Mostafa Waly, Mohammed O. Ibrahim, Stephanny Vicuna Polo, Diala Abu Al-Halawa

All Works

BACKGROUND: A direct consequence of global warming, and strongly correlated with poor physical and mental health, food insecurity is a rising global concern associated with low dietary intake. The Coronavirus pandemic has further aggravated food insecurity among vulnerable communities, and thus has sparked the global conversation of equal food access, food distribution, and improvement of food support programs. This research was designed to identify the key features associated with food insecurity during the COVID-19 pandemic using Machine learning techniques. Seven machine learning algorithms were used in the model, which used a dataset of 32 features. The model was designed to …

The Public Health Impact Of Paxlovid Covid-19 Treatment In The United States, Yuan Bai, Zhanwei Du, Lin Wang, Eric H. Y. Lau, Isaac Fung, Petter Holme, Ben Cowling, Alison Galvani, Robert Krug, Lauren Ancel Meyers

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

The antiviral drug Paxlovid has been shown to rapidly reduce viral load. Coupled with vaccination, timely administration of safe and effective antivirals could provide a path towards managing COVID-19 without restrictive non-pharmaceutical measures. Here, we estimate the population-level impacts of expanding treatment with Paxlovid in the US using a multi-scale mathematical model of SARS-CoV-2 transmission that incorporates the within-host viral load dynamics of the Omicron variant. We find that, under a low transmission scenario (Re∼1.2) treating 20% of symptomatic cases would be life and cost saving, leading to an estimated 0.26 (95% CrI: 0.03, 0.59) million hospitalizations averted, 30.61 (95% …

Detecting Mental Distresses Using Social Behavior Analysis In The Context Of Covid-19: A Survey, Sahraoui Dhelim, Liming Chen, Sajal K. Das, Huansheng Ning, Chris Nugent, Gerard Leavey, Dirk Pesch, Eleanor Bantry-White, Devin Michael Burns

Computer Science Faculty Research & Creative Works

Online social media provides a channel for monitoring people's social behaviors from which to infer and detect their mental distresses. During the COVID-19 pandemic, online social networks were increasingly used to express opinions, views, and moods due to the restrictions on physical activities and in-person meetings, leading to a significant amount of diverse user-generated social media content. This offers a unique opportunity to examine how COVID-19 changed global behaviors regarding its ramifications on mental well-being. In this article, we surveyed the literature on social media analysis for the detection of mental distress, with a special emphasis on the studies published …

Institute For Global Health And Development : Issue 5 - July 2023, Institute For Global Health And Development

IGHD Newsletter

• Research Highlights
• Key Publications
• IGHD in the News
• Webinars, Academics & Conferences
• ‘Choice’ Programme - Technical Advisory Group
• Welcome New Team Members
• Mark your Calendars: Upcoming Event
• Congratulations Team IGHD
• Collaborate With Us

Artificial Intelligence Tool For The Study Of Covid-19 Microdroplet Spread Across The Human Diameter And Airborne Space, Hesham H. Alsaadi, Monther Aldwairi, Faten Yasin, Sandra C.P. Cachinho, Abdullah Hussein

All Works

The 2019 novel coronavirus (SARS-CoV-2 / COVID-19), with a point of origin in Wuhan, China, has spread rapidly all over the world. It turned into a raging pandemic wrecking havoc on health care facilities, world economy and affecting everyone’s life to date. With every new variant, rate of transmission, spread of infections and the number of cases continues to rise at an international level and scale. There are limited reliable researches that study microdroplets spread and transmissions from human sneeze or cough in the airborne space. In this paper, we propose an intelligent technique to visualize, detect, measure the distance …

(R1954) Fractional Order On Modeling The Transmission Of Devastative Covid-19 Infection: Efficacy Of Vaccination, Ashutosh Rajput, Tanvi ., Rajiv Aggarwal, Arpana Sharma, Shiv Kumar Sahdev, Manoj Kumar, Jaimala .

Applications and Applied Mathematics: An International Journal (AAM)

The second wave of COVID-19 is an unprecedented condition in India and began in mid February 2021. Individuals who were already suffering from other comorbidities were found with lung infection, and hence, the number of disease induced deaths were rising faster during the second wave in relation to the first wave. This paper has proposed a mathematical model with fractional order derivatives by correlating the model based number of infectives with the real number of infectives in India. For the system of fractional differential equations, a disease-free state has been computed and proved to be locally asymptotically stable with certain …

(R2025) Improving The Lda Linear Discriminant Analysis Method By Eliminating Redundant Variables For The Diagnosis Of Covid-19 Patients, Kianoush Fathi Vajargah, Hamid Mottaghi Golshan, Fazel Badakhshan Farahabadi

Applications and Applied Mathematics: An International Journal (AAM)

Nowadays, with the increase in data production speed, the process of data analysis has faced many problems because this big data is often accompanied by plug-in data and redundant data. Therefore, the use of dimensional methods in the pre-data analysis stage is necessary. In data mining, dimensional reduction is one of the most important steps in data pre-processing. Principal component analysis (PCA) and linear discriminant analysis (LDA) are often used to reduce dimensions in data mining. The LDA method is a monitored and controlled method but the PCA is not controlled method. When the number of samples in classes is …

Beyond Covid-19: Designing Inclusive Public Health Surveillance By Including Wastewater Monitoring, Rochelle H. Holm, Na'taki Osborne Jelks, Rebecca Schneider, Ted Smith

Faculty Scholarship

Wastewater-based epidemiology is a promising and expanding public health surveillance method. The current wastewater testing trajectory to monitor primarily at community wastewater treatment plants was necessitated by immediate needs of the pandemic. Going forward, specific consideration should be given to monitoring vulnerable and underserved communities to ensure inclusion and rapid response to public health threats. This is particularly important when clinical testing data are insufficient to characterize community virus levels and spread in specific locations. Now is a timely call to action for equitably protecting health in the United States, which can be guided with intentional and inclusive wastewater monitoring.

Covid-19 In Casinos: Analysis Of Covid-19 Contamination And Spread With Economic Impact Assessment, Anastasia (Stasi) D. Baran, Jason D. Fiege

International Conference on Gambling & Risk Taking

Abstract:

The COVID-19 pandemic caused tremendous disruption for casinos, with the virus causing various lengths of shutdowns, capacity restrictions, and social distancing strategies such as machine removals or section closures. Although most of the world has now eased off these measures, it is important to review lessons learned to understand, and better prepare for similar circumstances in the future. We present Monte Carlo slot floor simulation software customized to simulate players spreading COVID-19 on the slot floor. We simulate the amount of touch surface contamination; the number of potential surface contact exposure events per day, and a proximity exposures statistic …

Observational Study Of Organisational Responses Of 17 Us Hospitals Over The First Year Of The Covid-19 Pandemic, Esther K. Choo, Matthew Strehlow, Marina Del Rios, Evrim Oral, Ruth Pobee, Andrew Nugent, Stephen Lim, Christian Hext, Sarah Newhall, Diana Ko, Srihari V. Chari, Amy Wilson, Joshua J. Baugh, David Callaway, Mucio Kit Delgado, Zoe Glick, Christian J. Graulty, Nicholas Hall, Abdusebur Jemal, Madhav Kc, Aditya Mahadevan, Milap Mehta, Andrew C. Meltzer, Dar'ya Pozhidayeva, Daniel Resnick-Ault

School of Public Health Faculty Publications

Objectives The COVID-19 pandemic has required significant modifications of hospital care. The objective of this study was to examine the operational approaches taken by US hospitals over time in response to the COVID-19 pandemic. Design, setting and participants This was a prospective observational study of 17 geographically diverse US hospitals from February 2020 to February 2021. Outcomes and analysis We identified 42 potential pandemic-related strategies and obtained week-to-week data about their use. We calculated descriptive statistics for use of each strategy and plotted percent uptake and weeks used. We assessed the relationship between strategy use and hospital type, geographic region …

Wearing Masks Implies Refuting Trump?: Towards Target-Specific User Stance Prediction Across Events In Covid-19 And Us Election 2020, Hong Zhang, Haewoon Kwak, Wei Gao, Jisun An

Research Collection School Of Computing and Information Systems

People who share similar opinions towards controversial topics could form an echo chamber and may share similar political views toward other topics as well. The existence of such connections, which we call connected behavior, gives researchers a unique opportunity to predict how one would behave for a future event given their past behaviors. In this work, we propose a framework to conduct connected behavior analysis. Neural stance detection models are trained on Twitter data collected on three seemingly independent topics, i.e., wearing a mask, racial equality, and Trump, to detect people’s stance, which we consider as their online behavior in …

Volatility Modeling Of Time Series Using Fractal And Self-Similarity Models, William Kubin

Open Access Theses & Dissertations

The study uses various methods to compare financial and geophysical time series scaling parameters and long-term memory behavior. The Cantor Detrended Fluctuation Analysis (CDFA) method is proposed to provide more accurate estimates of Hurst exponents. The CDFA method is applied to real-time series and the results are verified. The study also analyzes the memory behavior of daily Covid-19 cases before and after the announcement of effective vaccines. Low and high-frequency dataâ??s influence on the Hurst Index estimation is investigated, and a new PCDFA method is proposed. The stability of the Dow Jones Industrial Average is analyzed using a multi-scale normalized …

Online Dashboards For Sars-Cov-2 Wastewater Data Need Standard Best Practices: An Environmental Health Communication Agenda, Colleen C. Naughton, Rochelle H. Holm, Nancy J. Lin, Brooklyn P. James, Ted Smith

Faculty Scholarship

The COVID-19 pandemic has highlighted the benefits of wastewater surveillance to supplement clinical data. Numerous online information dashboards have been rapidly, and typically independently, developed to communicate environmental surveillance data to public health officials and the public. In this study, we review dashboards presenting SARS-CoV-2 wastewater data and propose a path toward harmonization and improved risk communication. A list of 127 dashboards representing 27 countries was compiled. The variability was high and encompassed aspects including the graphics used for data presentation (e.g., line/bar graphs, maps, and tables), log versus linear scale, and 96 separate ways of labeling SARS-CoV-2 wastewater concentrations. …

A Pharmacoepidemiological Study Of Myocarditis And Pericarditis Following The First Dose Of Mrna Covid-19 Vaccine In Europe, Joana Tome, Logan Cowan, Isaac Fung

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

This study assessed the myocarditis and pericarditis reporting rate of the first dose of mRNA COVID-19 vaccines in Europe. Myocarditis and pericarditis data pertinent to mRNA COVID19 vaccines (1 January 2021–11 February 2022) from EudraVigilance database were combined with European Centre for Disease Prevention and Control (ECDC)’s vaccination tracker data. The reporting rate was expressed as events (occurring within 28 days of the first dose) per 1 million individuals vaccinated. An observed-to-expected (OE) analysis quantified excess risk for myocarditis or pericarditis following the first mRNA COVID-19 vaccination. The reporting rate of myocarditis per 1 million individuals vaccinated was 17.27 (95% …

The Compound Risk Of Heat And Covid-19 In New York City: Riskscapes, Physical And Social Factors, And Interventions, Janelle Knox-Hayes, Juan Camilo Osorio, Natasha Stamler, Maria Dombrov, Rose Winer, Mary Hannah Smith, Reginald Blake, Cynthia Rosenzweig

Publications and Research

Climate change is disrupting the fundamental conditions of human life and exacerbating existing inequity by placing further burdens on communities that are already vulnerable. Risk exposure varies by where people live and work. In this article, we examine the spatial overlap of the compound risks of COVID-19 and extreme heat in New York City. We assess the relationship between socio-demographic and natural, built and social environmental characteristics, and the spatial correspondence of COVID-19 daily case rates across three pandemic waves. We use these data to create a compound risk index combining heat, COVID-19, density and social vulnerability. Our findings demonstrate …

Higher Education Students’ Perceptions Of Online Learning During The Covid-19 Pandemic, Abby O’Bryant

Butler Journal of Undergraduate Research

This article focuses on the impacts of online learning during the COVID-19 pandemic on students at the University of Hawai‘i at Hilo. Using survey data (n = 64) and semistructured interviews with currently enrolled students (n = 17), key impacts of online learning on the student body were analyzed. The respondents reported disengagement in lectures, negative impacts on their mental and physical health, negative thoughts about dropping out and transferring, apprehension about the quality of course content, and dissatisfaction with tuition. The paper utilizes qualitative data analysis to report the findings.

The Effect Of Covid-19 On Substance Use And Mental Health On A College Campus, Georgia L. Coffman

Butler Journal of Undergraduate Research

In this research, the author surveyed a university population to determine the impact that COVID-19 has had on substance use and mental health. Current research provides significant data indicating worsening mental health and substance use. This paper looks at how applicable those trends are to a small private university in Indianapolis, Indiana. The data included 261 respondents composed of students, faculty, and staff of the university. The results reveal that college students, faculty, and staff experienced statistically significant increases in feelings of unhappiness, depression, loneliness, hopelessness, agitation, and irritability during the pandemic compared to before the pandemic. Data analysis of …

Assessing The Impact Of The Covid-19 Pandemic On Project Management Methodologies, Adrian Leung

LMU/LLS Theses and Dissertations

This research paper explores the impact of COVID-19 and the shift to remote work on project management practices across multiple industries. Through interviews with project managers, the study finds that companies with pre-existing remote work policies were better equipped to handle the transition to remote work. In contrast, companies without pre-existing policies faced increased challenges in communication, team morale, and workload management. The study also highlights the struggle to maintain work-life balance, the importance of communication, and the need to address technical difficulties. Project managers emphasized the importance of accountability and maintaining productivity during remote work. Overall, the study finds …

Prevalence Of Sars-Cov-2 Antibodies In Liberty University Student Population, Emily Bonus

Senior Honors Theses

In 2020, the virus SARS-CoV-2 gained attention as it spread around the world. Its antibodies are poorly understood, and little research focuses on those with few COVID-19 complications yet large numbers of close contacts: university students. This longitudinal study recorded SARS-CoV-2 antibody presence in 107 undergraduate Liberty University students twice during early 2021. After extensive data cleaning and the application of various statistical tests and ANOVAs, the data seems to show that in the case of COVID-19 infections, SARS-CoV-2 IgM antibodies are immediately produced, and then IgG antibodies follow later. However, the COVID-19 vaccine causes the production of both IgM …

Virtual And In Vitro Screening Of Natural Products Identifies Indole And Benzene Derivatives As Inhibitors Of Sars-Cov-2 Main Protease (MPro), Dony Ang, Riley Kendall, Hagop S. Atamian

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The rapid spread of the coronavirus disease 2019 (COVID-19) resulted in serious health, social, and economic consequences. While the development of effective vaccines substantially reduced the severity of symptoms and the associated deaths, we still urgently need effective drugs to further reduce the number of casualties associated with SARS-CoV-2 infections. Machine learning methods both improved and sped up all the different stages of the drug discovery processes by performing complex analyses with enormous datasets. Natural products (NPs) have been used for treating diseases and infections for thousands of years and represent a valuable resource for drug discovery when combined with …

Sustainable Management Of Facemask Waste Generated From Covid-19 Pandemic In Bhutan, Tshering Yangdon, Twisuk Punpeng, Sirima Mongkolosomit, Kampol Nanthapong, Kinzang Yangden

Journal of Health Research

Background: The rise in facemask waste with the uncertainty of deposition data and all its concomitant pressure on management has resulted in new risks and challenges for achieving sustainable development goals (SDGs). The purpose of this mixed methods study was to estimate facemask waste generation and examine management in Bhutan since the COVID-19 pandemic.

Method: One thousand five hundred and twenty-seventh (1,527) consenting members of the public from Class A Thromdes (self-governing municipalities) were surveyed online from February to April 2022, to estimate mask waste using descriptive statistics. This was supported by the waste characterization conducted in Memelhakha, the biggest …

Observing Human Mobility Internationally During Covid-19, Shane Allcroft, Mohammed Metwaly, Zachery Berg, Isha Ghodgaonkar, Fischer Bordwell, Xinxin Zhao, Xinglei Liu, Jiahao Xu, Subhankar Chakraborty, Vishnu Banna, Akhil Chinnakotla, Abhinav Goel, Caleb Tung, Gore Kao, Wei Zakharov, David A. Shoham, George K. Thiruvathukal, Yung-Hsiang Lu

Computer Science: Faculty Publications and Other Works

This article analyzes visual data captured from five countries and three U.S. states to evaluate the effectiveness of lockdown policies for reducing the spread of COVID-19. The main challenge is the scale: nearly six million images are analyzed to observe how people respond to the policy changes.

Spatio-Temporal Heterogeneity In The International Trade Resilience During Covid-19, Wei Luo, Lingfeng He, Zihui Yang, Shirui Zhang, Yong Wang, Dianbo Liu, Sheng Hu, Li He, Jizhe Xia, Min Chen

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic and subsequent lockdowns have created immeasurable health and economic crises, leading to unprecedented disruptions to world trade. The COVID-19 pandemic shows diverse impacts on different economies that suffer and recover at different rates and degrees. This research aims to evaluate the spatio-temporal heterogeneity of international trade network vulnerabilities in the current crisis to understand the global production resilience and prepare for the future crisis. We applied a series of complex network analysis approaches to the monthly international trade networks at the world, regional, and country scales for the pre- and post- COVID-19 outbreak period. The spatio-temporal patterns …

An Exploratory Study On Museum Visitor Ship Trends In Singapore, Aldy Gunawan, Chentao Liu, Heranshan S/O Subramaniam, Melissa Tan, Ranice Tan, Clarence Tay, Tasaporn. Visawameteekul

Research Collection School Of Computing and Information Systems

The COVID-19 outbreak has unpredictably disrupted the operations of numerous museums. Museum visitor experience has a physical, personal, and social context, which are not achievable during the pandemic. Despite the depreciation during the Circuit Breaker period, the disruption also presents an opportunity for local museums to develop new strategies of audience engagement to accommodate the altered audience behavior. This exploratory study analyses data from six Singapore-based museums to understand the visitorship patterns across different ages and genders. The impact of COVID-19 is also analysed. Using R-studio and relevant packages, we conducted statistical tests such as hypothesis testing, Chi-square testing and …

Presidential Vote Share And Covid-19 Vaccination Rate In Indonesia: A District-Level Cross-Sectional Ecological Study, Gede Benny Setia Wirawan, Ni Luh Zallila Gustina, Ivy Cerelia Valerie, I Gusti Ayu Indah Pradnyani Rs, Muchamad Zaenal Arifin, Pande Putu Januraga

Kesmas

Political affiliation has been reported as a determinant of COVID-19 vaccine acceptance in some countries, although few studies have examined the Asian context. This study aims to fill this gap by employing an ecological study design using Indonesian regions as data points. Political affiliation was represented by incumbent President Jokowi’s vote share in the 2019 presidential election. Potential confounders included population density, human development index, availability of hospitals and primary health care, 2019–2020 economic growth, COVID-19 mortality rate, and proportion of Muslims in the population. The final analysis included 201 out of 501 districts and cities in Indonesia. Controlling for …