Digital Commons Network^™

Analytical And Numerical Analysis Of The Sirs Model, Catherine Nguyen

Student Research Submissions

Mathematical models in epidemiology describe how diseases affect and spread within a population. By understanding the trends of a disease, more effective public health policies can be made. In this paper, the Susceptible-Infected-Recovered-Susceptible (SIRS) Model was examined analytically and numerically to compare with the data for Coronavirus Disease 2019 (COVID-19). Since the SIRS model is a complex model, analytical techniques were used to solve simplified versions of the SIRS model in order to understand general trends that occur. Then by Euler's Method, the Runge-Kutta Method, and the Predictor-Corrector Method, computational approximations were obtained to solve and plot the SIRS model. …

Tools For Biomolecular Modeling And Simulation, Xin Yang

Mathematics Theses and Dissertations

Electrostatic interactions play a pivotal role in understanding biomolecular systems, influencing their structural stability and functional dynamics. The Poisson-Boltzmann (PB) equation, a prevalent implicit solvent model that treats the solvent as a continuum while describes the mobile ions using the Boltzmann distribution, has become a standard tool for detailed investigations into biomolecular electrostatics. There are two primary methodologies: grid-based finite difference or finite element methods and body-fitted boundary element methods. This dissertation focuses on developing fast and accurate PB solvers, leveraging both methodologies, to meet diverse scientific needs and overcome various obstacles in the field.

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 …

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 …

Bioanalytical Studies Of Disease Protein Profiles: Maldi-Tof Ms, Prajkta Satish Chivte

Graduate Research Theses & Dissertations

Coronavirus disease-2019 (COVID-19), which is caused by a novel coronavirus named severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has ravaged the world for the past 3 years. Even today, there still exists a need for rapid, accurate, economical and non-invasive diagnostic testing platforms that yield high specificity and sensitivity towards the constantly mutating SARS-CoV-2. Research has consistently indicated saliva to be a more amenable specimen type for early detection of SARS-CoV-2, compared to the oral and nasopharyngeal swabs. Considering the limitations and high demand of the existing COVID-19 testing platforms, this dissertation work studies used MALDI-ToF MS (matrix-assisted laser desorption/ionization-time of …

How Government Organizations Can Sustain Remote Work Post Covid-19, Chikwendu Pius Nweke

Walden Dissertations and Doctoral Studies

AbstractGovernment organizations are unprepared to sustain remote work post-COVID-19. Even though COVID-19 seems to be under control, organizations are still struggling with the aftermath of the pandemic and the need to sustain remote work. Challenges include lack of necessary information technology tools, software, technological skills, strategies for remote work, leadership skills, real-time communication; activity planning and program implementation, scheduling meetings, organizing child care, managing caseloads, fostering team work, and effective supervision. A conceptual framework based on organizational adaptation theory was used to guide this qualitative case study. Since the study was to ascertain how government organizations can sustain remote work …

Critically Observing The Challenges And Changes: An Analysis On Covid-19’S Impact With An Emphasis On Students In Higher Education, Landon Perkins

Honors Theses

This project involves comparing different visualizations related to COVID-19 and higher education in order to determine key impacts of the COVID-19 pandemic on students in higher education, as well as higher education as a whole. The main metrics used to determine the impact were mental health indicators for anxiety or depressive disorders, enrollment numbers by control type (public, private non-profit, or private for-profit) and state for 2020 and 2021, and state mandate lift dates for a variety of mandates implemented across the United States. These metrics were analyzed both individually and against each other to determine if they had any …

Functional Data Analysis Of Covid-19, Nichole L. Fluke

Mathematics & Statistics ETDs

This thesis deals with Functional Data Analysis (FDA) on COVID data. The Data involves counts for new COVID cases, hospitalized COVID patients, and new COVID deaths. The data used is for all the states and regions in the United States. The data starts in March 1^st, 2020 and goes through March 31^st, 2021. The FDA smooths the data and looks to see if there are similarities or differences between the states and regions in the data. The data also shows which states and regions stand out from the others and which ones are similar. Also shown …

A Data Driven Model To Promote Preparedness And Respond Intelligently To Pandemic Outbreaks, Safea Mohammed Al Senani

Theses

The COVID-19 pandemic has had a major effect on various vital sectors of the economy, including education healthcare, and the industry. Governments have imposed strict regulations to reduce the spread of this global disease outbreak. Consequently, working from home, online learning, social distancing and various control measures were enforced. In response, many schools shifted to distance learning, although most of these schools were neither technically ready nor administratively prepared for the online transition. Despite recent progress, countries are still experiencing daunting challenges to control the infection rate and magnitude, stabilize the economy, and relax socialization and public life activities. Decision-makers …

Respiratory Pattern Analysis For Covid-19 Digital Screening Using Ai Techniques, Annita Tahsin Priyoti

Electronic Thesis and Dissertation Repository

Corona Virus (COVID-19) is a highly contagious respiratory disease that the World Health Organization (WHO) has declared a worldwide epidemic. This virus has spread worldwide, affecting various countries until now, causing millions of deaths globally. To tackle this public health crisis, medical professionals and researchers are working relentlessly, applying different techniques and methods. In terms of diagnosis, respiratory sound has been recognized as an indicator of one’s health condition. Our work is based on cough sound analysis. This study has included an in-depth analysis of the diagnosis of COVID-19 based on human cough sound. Based on cough audio samples from …

Machine Learning Model Comparison And Arma Simulation Of Exhaled Breath Signals Classifying Covid-19 Patients, Aaron Christopher Segura

Mathematics & Statistics ETDs

This study compared the performance of machine learning models in classifying COVID-19 patients using exhaled breath signals and simulated datasets. Ground truth classification was determined by the gold standard Polymerase Chain Reaction (PCR) test results. A residual bootstrapped method generated the simulated datasets by fitting signal data to Autoregressive Moving Average (ARMA) models. Classification models included neural networks, k-nearest neighbors, naïve Bayes, random forest, and support vector machines. A Recursive Feature Elimination (RFE) study was performed to determine if reducing signal features would improve the classification models performance using Gini Importance scoring for the two classes. The top 25% of …

Relationships Between Covid-19 Infection Rates, Healthcare Access, Socioeconomic Status, And Cultural Diversity, Marghece P. J. Barnes

Boise State University Theses and Dissertations

The COVID-19 pandemic has had a disproportionate impact on racial and ethnic minority groups, with high infection rates throughout those communities. There are a complex set of factors that account for COVID-19 disparities. Focusing on infection and death rates alone without also examining health equity, underestimates the true impact of the pandemic. To gain a more clear understanding of COVID-19’s impact in these communities, we analyzed the relationship between state COVID-19 infection rates with social determinants of health: cultural diversity, health care access, and socioeconomic status. Our approach to identifying this relationship was to estimate infection rates by fitting John …

Regression Analysis Of Resilience And Covid-19 In Idaho Counties, Ishrat Zaman

Boise State University Theses and Dissertations

Global pandemic Coronavirus Disease 2019 (COVID-19) has serious harmful effects on our day-to-day lives. To overcome challenges such as this, critical preparedness, readiness, and response actions are required. This thesis uses estimates of community resilience available through the CRE Tool, published by the US Census Bureau, and COVID19 cases published by John Hopkins Coronavirus Research Center for Idaho counties. Simple linear regression analysis was performed to identify a correlation between COVID-19 cases and deaths in Idaho counties and measures of their resilience. Understanding this correlation could lead to better estimation and prediction of the effect of disasters in Idaho’s counties. …

Social Media Analytics With Applications In Disaster Management And Covid-19 Events, Md Yasin Kabir

Doctoral Dissertations

"Social media such as Twitter offers a tremendous amount of data throughout an event or a disastrous situation. Leveraging social media data during a disaster is beneficial for effective and efficient disaster management. Information extraction, trend identification, and determining public reactions might help in the future disaster or even avert such an event. However, during a disaster situation, a robust system is required that can be deployed faster and process relevant information with satisfactory performance in real-time. This work outlines the research contributions toward developing such an effective system for disaster management, where it is paramount to develop automated machine-enabled …

Mathematical Modeling Of Seir Model With Generalized Incidence Function And The Extension To Covid-19 Model, Shymaa Mohammad Dadoa

Theses

The COVID-19 pandemic had shown the importance of the SEIR model in predicting the outcome of the disease spread and to find the best strategies to contain the pandemic. As this type of model has a limited number of compartments, many other models were derived from the SEIR model to cover, to the maximum, the complex dynamics of the disease spread. These extensions of the SEIR model bring natural validity questions: How can we validate these models? and how far/close are these extended models from giving us real insights into the pandemic?

This thesis investigates the SEIR epidemic model and …

Could Cultures Determine The Course Of Epidemics And Explain Waves Of Covid-19?, Md Salman Rahman

Theses and Dissertations

Coronavirus Disease (COVID-19), caused by the SARS-CoV-2 virus, is an infectious disease that quickly became a pandemic spreading with different patterns in each country. Travel bans, lockdowns, social distancing, and non-essential business closures caused significant economic disruptions and stalled growth worldwide in the pandemic’s first year. In almost every country, public health officials forced and/or encouraged Nonpharmaceutical Interventions (NPIs) such as contact tracing, social distancing, masks, and quarantine. Human behavioral decision-making regarding social isolation significantly impedes global success in containing the pandemic. This thesis focuses on human behaviors and cultures related to the decision-making of social isolation during the pandemic. …

Three Dimensional Spatio-Temporal Cluster Analysis Of Sars-Cov-2 Infections, Keith W. Allison

Masters Theses

The COVID-19 pandemic has heightened the need for fine-scale analysis of the clustering of cases of infectious disease in order to better understand and prevent the localized spread of infection. The students living on the University of Massachusetts, Amherst campus provided a unique opportunity to do so, due to frequent mandatory testing during the 2020-2021 academic year, and dense living conditions. The South-West dormitory area is of particular interest due to its extremely high population density, housing around half of students living on campus during normal conditions. Using data gathered by the Public Health Promotion Center (PHPC), we analyzed the …

A Network Analysis Of Covid-19 In The United States, Joseph C. Mcguire

Master's Theses

Through methods in network theory and time-series analysis, we will analyze the spread of COVID-19 in the United States by determining trends in state-by-state daily cases through a network construction. Previous researchers have found frameworks for approximating the spread of the COVID-19 pandemic and identifying potential rises in cases by a network construction based on correlation of cases between regions [1]. Applying this network construction we determine how this network and its structure act as a predictor for overall COVID-19 cases in the United States by preforming a trend analysis on a variety of network statistics and US COVID-19 cases.

A Multi-Criteria Decision-Making (Mcdm) Approach For Data-Driven Distance Learning Recommendations, Aysha Meshaal Alshamsi

Theses

Distance learning has been adopted as an alternative learning strategy to the dominant face-to-face teaching methodology. It has been largely implemented by many governments worldwide due to the spread of the COVID-19 pandemic and the implication in enforcing lockdown and social distancing. In emergency situations distance learning is referred to as Emergency Remote Teaching (ERT). Due to this dynamic, sudden shift, and scaling demand in distance learning, many challenges have been accentuated. These include technological adoption, student commitments, parent involvement, and teacher extra burden management, changes in the organization methodology, in addition to government development of new guidelines and regulations …

Mapping The Covid-19 Pandemic In Staten Island, Vincenzo Mezzio

Student Theses

COVID-19 has had diverging effects in New York City. Out of the five boroughs, Staten Island has one of the largest percentages of COVID-19 cases relative to population. This research examines key social and spatial factors that contribute to the increase in COVID-19 cases in Staten Island). It asks: Which parts of Staten Island have higher rates of transmission of COVID-19? Which parts of the borough have higher population who are more vulnerable to COVID-19? What is the relationship between the location of vaccination centers with the rates of COVID-19 cases? Using Geographic Information Systems (GIS), this research examines the …

The Impact Of Virtual Learning Modalities On The Academic Success Of Students In One Arkansas School District, Diane F. Richards

ATU Theses and Dissertations 2021 - Present

The COVID-19 pandemic changed the way Arkansas public schools’ offered students an education. While moving through this pandemic, many Arkansas schools implemented optional methods of delivery for their students. Some schools tried to maintain face-to-face classes, while others offered completely online classes. Still, others offered a hybrid format where students attended some face-to-face classes and online classes. One Arkansas school district offered all three options. School districts need guidance as to which teaching methods worked well. The long-term effects of the educational impact of COVID-19 are not known at this time. Schools could benefit from a guide with useful strategies …

The Efficacy Of The Covid-19 Vaccine In Mississippi, Ilyse Miriam Levy

Honors Theses

The Efficacy of The COVID-19 Vaccine in Mississippi

(Under the direction of Dr. Xin Dang)

By tracking and analyzing fifty-three weeks of COVID-19 data, this thesis analyzes the efficacy of the COVID-19 vaccine within the State of Mississippi. Over the course of these fifty-three weeks, I have also been able to calculate the confidence intervals for vaccination efficacy and the risk reduction due to vaccination by using data regarding the correlations between deaths and vaccination status, provided to me by the Mississippi Office of Epidemiology. My analysis demonstrates that the COVID-19 vaccine is effective not only in Mississippi but also …

Design And Development Of The Urban Population Health Observatory To Improve Disease Surveillance And Response, Whitney Brakefield

Doctoral Dissertations

Chronic and infectious diseases have a profound impact on the quality and length of life of populations that suffer from these conditions. Scientists, physicians, and health officials are seeking innovative approaches to decrease the morbidity and mortality of deadly diseases. Incorporating artificial intelligence and data science techniques across the health science domain could improve disease surveillance, intervention planning, and policymaking. In this dissertation, we describe the design and development of the Urban Population Health Observatory (UPHO), an explainable knowledge-based multimodal big data analytics platform. A common challenge for conducting multimodal big data analytics is integrating multidimensional heterogeneous data sources, which …

Developing And Applying Computational Algorithms To Reveal Health-Related Biomolecular Interactions, Yixin Xie

Open Access Theses & Dissertations

Computational biology is an interdisciplinary area that applies computational approaches in biological big data, including protein amino acid sequences, genetic sequences, etc., which is widely used to analyze protein-protein interactions, make predictions in drug discovery, develop vaccines, etc. Popular methods include mathematical modeling, molecular dynamics simulations, data science mythology, etc. With the help of computational algorithms and applications, drug development is much faster than traditional processes, as it reduces risks early on in a drug discovery process and helps researchers select target candidates that have the highest potential for success. In my doctoral research, I applied multi-scale computational approaches to …

Covid Synergy: A Machine Learning Approach Uncovering Potential Treatment Combinations For Sars-Cov-2, Jason Eden Sanchez

Open Access Theses & Dissertations

For more than two years, the COVID-19 pandemic has upended the lives of billions of individualsworldwide leading to disruptions in healthcare, the economy and society at large. As the pandemic enters its third year, the human impact cannot be overstated and the need to develop effective pharmaceuticals remains. Though there currently exits FDA-approved medications for COVID-19, the emergence of novel variants, such as Omicron, highlights the importance of discovering new therapies which will continue to be effective regardless of the pandemicâ??s progression. Because discovering new medications is a costly and timeintensive endeavor, my approach entails drug repurposing to test medications …

Assessing The Influence Of Health Policy And Population Mobility On Covid-19 Spread In Arkansas, Tayden Barretto

Industrial Engineering Undergraduate Honors Theses

The outbreak of COVID-19 has created a major crisis across the world since its start in 2019, and its influence on every realm of society is undeniable. Globally, more than 500 million cases have been recorded since March 2020, with almost 6 million deaths. In the wake of this crisis, many governments and health organizations have taken steps and precautions to mitigate its spread. These steps involve public mandates of information, reducing frequency of personal contact, and use of masks to minimize the risk of transmission. Current access to mobility data released from Google detailing population movements has provided a …

An Application Of Matrices To The Spread Of The Covid 19, Selena Suarez

Theses and Dissertations

We represented a restaurant seating arrangement using matrices by using 0 entry for someone without covid and 1 entry for someone with covid. Using the matrices we found the best seating arrangements to lessen the spread of covid. We also investigated if there was a factor needed to create a formula that could calculate the matrix that shows who would be affected with covid with each seating arrangement. However, there did not seem to be a clear pattern within the factors. Aside from covid applications, we also investigated the symmetries in seating arrangements and the possible combinations with these arrangements …

Convolutional Neural Network For Covid-19 Detection In Chest X-Rays, Joshua Elliot Henderson

Honors Thesis

The COVID-19 pandemic has had a large effect on almost every facet of life. As COVID-19 was a disease only discovered in recent history, there is comparatively little data on the disease, how we detect it, and how we cure it. Deep learning is a powerful tool that can be used to learn to classify information in ways that humans might not be able to. This allows computers to learn on relatively little data and provide exceptional results. In this paper, I propose a novel convolutional neural network (CNN) for the detection of COVID-19 from chest X-rays called basicConv. This …

Decision-Analytic Models Using Reinforcement Learning To Inform Dynamic Sequential Decisions In Public Policy, Seyedeh Nazanin Khatami

Doctoral Dissertations

We developed decision-analytic models specifically suited for long-term sequential decision-making in the context of large-scale dynamic stochastic systems, focusing on public policy investment decisions. We found that while machine learning and artificial intelligence algorithms provide the most suitable frameworks for such analyses, multiple challenges arise in its successful adaptation. We address three specific challenges in two public sectors, public health and climate policy, through the following three essays. In Essay I, we developed a reinforcement learning (RL) model to identify optimal sequence of testing and retention-in-care interventions to inform the national strategic plan “Ending the HIV Epidemic in the US”. …

Classification And Keyword Identification Of Covid 19 Misinformation On Social Media: A Framework For Semantic Analysis, Grace Y. Smith

Theses and Dissertations

The growing surge of misinformation among COVID-19 communication can pose great hindrance to truth, magnify distrust in policy makers and/or degrade authorities’ credibility, and it can even harm public health. Classification of textual context on social media data relating to COVID-19 is an effective tool to combat misinformation on social media platforms. In this research, Twitter data was leveraged to 1) develop classification methods to detect misinformation and identify Tweet sentiment with respect to COVID-19 and 2) develop a human-in-the-loop interactive framework to enable identification of keywords associated with social context, here, being misinformation regarding COVID-19. 1) Six fusion-based classification …