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Physical Sciences and Mathematics

2022

COVID-19

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Predictors Of Covid-19 Vaccination Rate In Usa: A Machine Learning Approach, Syed M. I. Osman, Ahmed Sabit Dec 2022

Predictors Of Covid-19 Vaccination Rate In Usa: A Machine Learning Approach, Syed M. I. Osman, Ahmed Sabit

WCBT Faculty Publications

In this study, we examine state-level features and policies that are most important in achieving a threshold level vaccination rate to curve the effects of the COVID-19 pandemic. We employ CHAID, a decision tree algorithm, on three different model specifications to answer this question based on a dataset that includes all the states in the United States. Workplace travel emerges as the most important predictor; however, the governors’ political affiliation (PA) replaces it in a more conservative feature set that includes economic features and the growth rate of COVID-19 cases. We also employ several alternative algorithms as a robustness check. …

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Examining The Impact Of Covid-19 On The Education And Development Of American Students, Riley Fortin '25 Dec 2022

Examining The Impact Of Covid-19 On The Education And Development Of American Students, Riley Fortin '25

Student Research

After the COVID-19 pandemic, the vast majority of American children have fallen behind on core subjects due to the ultimate ineffectiveness of remote learning. This study attempts to discover the degree to which children have fallen behind through the trends in the National Association of Educational Procurement’s two most recent testing years. A database accessed from Google has been analyzed, filtered by state and visualized in tables in order to indicate any possible trends as a result of remote learning brought on by the pandemic. By looking at data in seven different states across the country, there is a notable …

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Evidence-Based Study: The Effect Of The Covid-19 Pandemic On Post-Secondary Enrollment And Chosen Fields Of Study, Hannah Fields '25 Dec 2022

Evidence-Based Study: The Effect Of The Covid-19 Pandemic On Post-Secondary Enrollment And Chosen Fields Of Study, Hannah Fields '25

Student Research

The onset of the COVID-19 pandemic in the United States in March of 2020 derailed educational systems at all levels. Specifically, at the post-secondary level, the pandemic sent many students online or forced them to take a fifth year to complete their degrees. As a result, post-secondary enrollment rates are likely to have dropped to reflect these changing post-COVID views surrounding education. Additionally, changing viewpoints about the essentiality of certain jobs and roles changed the chosen fields of study of these same students. Data for this study was collected by way of a short-scale meta-analysis, and enrollment rates were split …

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Critically Observing The Challenges And Changes: An Analysis On Covid-19’S Impact With An Emphasis On Students In Higher Education, Landon Perkins Dec 2022

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 …

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Smartphone Usage Before And During Covid-19: A Comparative Study Based On Objective Recording Of Usage Data, Khansa Chemnad, Sameha Alshakhsi, Mohamed Basel Almourad, Majid Altuwairiqi, Keith Phalp, Raian Ali Dec 2022

Smartphone Usage Before And During Covid-19: A Comparative Study Based On Objective Recording Of Usage Data, Khansa Chemnad, Sameha Alshakhsi, Mohamed Basel Almourad, Majid Altuwairiqi, Keith Phalp, Raian Ali

All Works

Most studies that claimed changes in smartphone usage during COVID-19 were based on self-reported usage data, e.g., that collected through a questionnaire. These studies were also limited to reporting the overall smartphone usage, with no detailed investigation of distinct types of apps. The current study investigated smartphone usage before and during COVID-19. Our study used a dataset from a smartphone app that objectively logged users’ activities, including apps accessed and each app session start and end time. These were collected during two periods: pre-COVID-19 (161 individuals with 77 females) and during COVID-19 (251 individuals with 159 females). We report on …

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Estimating Sewage Flow Rate In Jefferson County, Kentucky, Using Machine Learning For Wastewater-Based Epidemiology Applications, Dhiraj Kanneganti, Lauren E. Reinersman, Rochelle H. Holm, Ted Smith Dec 2022

Estimating Sewage Flow Rate In Jefferson County, Kentucky, Using Machine Learning For Wastewater-Based Epidemiology Applications, Dhiraj Kanneganti, Lauren E. Reinersman, Rochelle H. Holm, Ted Smith

Faculty Scholarship

Direct measurement of the flow rate in sanitary sewer lines is not always feasible and is an important parameter for the normalization of data used in wastewater-based epidemiology applications. Machine learning to estimate past wastewater influent flow rates supporting public health applications has not been studied. The aim of this study was to assess wastewater treatment plant influent flow rates when compared with weather data and to retrospectively estimate flow rates in Louisville, Kentucky (USA), based on other data types using machine learning. A random forest model was trained using a range of variables, such as feces-related indicators, weather data …

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Association Between The Health Belief Model, Exercise, And Nutrition Behaviors During The Covid-19 Pandemic, Keagan Kiely, Bill Mase, Andrew R. Hansen, Jessica S. Schwind Nov 2022

Association Between The Health Belief Model, Exercise, And Nutrition Behaviors During The Covid-19 Pandemic, Keagan Kiely, Bill Mase, Andrew R. Hansen, Jessica S. Schwind

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

Introduction: The COVID-19 pandemic has affected our nation’s health further than the infection it causes. Physical activity levels and dietary intake have suffered while individuals grapple with the changes in behavior to reduce viral transmission. With unique nuances regarding the access to physical activity and nutrition during the pandemic, the constructs of Health Belief Model (HBM) may present themselves differently in nutrition and exercise behaviors compared to precautions implemented to reduce viral transmission studied in previous research. The purpose of this study was to investigate the extent of exercise and nutritional behavior change during the COVID-19 pandemic and explain the …

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Functional Data Analysis Of Covid-19, Nichole L. Fluke Nov 2022

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 1st, 2020 and goes through March 31st, 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 …

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A Comparative Analysis Of Anti-Vax Discourse On Twitter Before And After Covid-19 Onset, Tareq Nasralah, Ahmed El Noshokaty, Omar El-Gayar, Mohammad A. Al-Ramahi, Abdullah Wahbeh Nov 2022

A Comparative Analysis Of Anti-Vax Discourse On Twitter Before And After Covid-19 Onset, Tareq Nasralah, Ahmed El Noshokaty, Omar El-Gayar, Mohammad A. Al-Ramahi, Abdullah Wahbeh

Computer Information Systems Faculty Publications

This study aimed to identify and assess the prevalence of vaccine-hesitancy-related topics on Twitter in the periods before and after the Coronavirus Disease 2019 (COVID-19) outbreak. Using a search query, 272,780 tweets associated with anti-vaccine topics and posted between 1 January 2011, and 15 January 2021, were collected. The tweets were classified into a list of 11 topics and analyzed for trends during the periods before and after the onset of COVID-19. Since the beginning of COVID-19, the percentage of anti-vaccine tweets has increased for two topics, “government and politics” and “conspiracy theories,” and decreased for “developmental disabilities.” Compared to …

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Advancing The Use Of Fecal Sludge For Timelier And Better-Quality Epidemiological Data In Low- And Middle-Income Countries For Pandemic Prevention, Petros Chigwechokha, Renée Street, Rochelle H. Holm Nov 2022

Advancing The Use Of Fecal Sludge For Timelier And Better-Quality Epidemiological Data In Low- And Middle-Income Countries For Pandemic Prevention, Petros Chigwechokha, Renée Street, Rochelle H. Holm

Faculty Scholarship

No abstract provided.

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A Data Driven Model To Promote Preparedness And Respond Intelligently To Pandemic Outbreaks, Safea Mohammed Al Senani Nov 2022

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 …

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Population Health Metrics During The Early Stages Of The Covid-19 Pandemic: Correlative Pilot Study, Marie A. Severson, David A. Cassada, Victor C. Huber, Daniel D. Snow, Lisa M. Mcfadden Oct 2022

Population Health Metrics During The Early Stages Of The Covid-19 Pandemic: Correlative Pilot Study, Marie A. Severson, David A. Cassada, Victor C. Huber, Daniel D. Snow, Lisa M. Mcfadden

Nebraska Water Center: Faculty Publications

Background: COVID-19 has caused nearly 1 million deaths in the United States, not to mention job losses, business and school closures, stay-at-home orders, and mask mandates. Many people have suffered increased anxiety and depression since the pandemic began. Not only have mental health symptoms become more prevalent, but alcohol consumption has also increased during this time. Helplines offer important insight into both physical and mental wellness of a population by offering immediate, anonymous, cheap, and accessible resources for health and substance use disorders (SUD) that was unobstructed by many of the mandates of the pandemic. Further, the pandemic also …

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Predicting The Level Of Respiratory Support In Covid-19 Patients Using Machine Learning, Hisham Abdeltawab, Fahmi Khalifa, Yaser Elnakieb, Ahmed Elnakib, Fatma Taher, Norah Saleh Alghamdi, Harpal Singh Sandhu, Ayman El-Baz Oct 2022

Predicting The Level Of Respiratory Support In Covid-19 Patients Using Machine Learning, Hisham Abdeltawab, Fahmi Khalifa, Yaser Elnakieb, Ahmed Elnakib, Fatma Taher, Norah Saleh Alghamdi, Harpal Singh Sandhu, Ayman El-Baz

All Works

In this paper, a machine learning-based system for the prediction of the required level of respiratory support in COVID-19 patients is proposed. The level of respiratory support is divided into three classes: class 0 which refers to minimal support, class 1 which refers to non-invasive support, and class 2 which refers to invasive support. A two-stage classification system is built. First, the classification between class 0 and others is performed. Then, the classification between class 1 and class 2 is performed. The system is built using a dataset collected retrospectively from 3491 patients admitted to tertiary care hospitals at the …

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Role Of Imaging And Ai In The Evaluation Of Covid-19 Infection: A Comprehensive Survey, Mayada Elgendy, Hossam Magdy Balaha, Mohamed Shehata, Ahmed Alksas, Mahitab Ghoneim, Fatma Sherif, Ali Mahmoud, Ahmed Elgarayhi, Fatma Taher, Mohammed Sallah, Mohammed Ghazal, Ayman El-Baz Sep 2022

Role Of Imaging And Ai In The Evaluation Of Covid-19 Infection: A Comprehensive Survey, Mayada Elgendy, Hossam Magdy Balaha, Mohamed Shehata, Ahmed Alksas, Mahitab Ghoneim, Fatma Sherif, Ali Mahmoud, Ahmed Elgarayhi, Fatma Taher, Mohammed Sallah, Mohammed Ghazal, Ayman El-Baz

All Works

Coronavirus disease 2019 (COVID-19) is a respiratory illness that started and rapidly became the pandemic of the century, as the number of people infected with it globally exceeded 253.4 million. Since the beginning of the pandemic of COVID-19, over two years have passed. During this hard period, several defies have been coped by the scientific society to know this novel disease, evaluate it, and treat affected patients. All these efforts are done to push back the spread of the virus. This article provides a comprehensive review to learn about the COVID-19 virus and its entry mechanism, its main repercussions on …

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Cov-Inception: Covid-19 Detection Tool Using Chest X-Ray, Aswini Thota, Ololade Awodipe, Rashmi Patel Sep 2022

Cov-Inception: Covid-19 Detection Tool Using Chest X-Ray, Aswini Thota, Ololade Awodipe, Rashmi Patel

SMU Data Science Review

Since the pandemic started, researchers have been trying to find a way to detect COVID-19 which is a cost-effective, fast, and reliable way to keep the economy viable and running. This research details how chest X-ray radiography can be utilized to detect the infection. This can be for implementation in Airports, Schools, and places of business. Currently, Chest imaging is not a first-line test for COVID-19 due to low diagnostic accuracy and confounding with other viral pneumonia. Different pre-trained algorithms were fine-tuned and applied to the images to train the model and the best model obtained was fine-tuned InceptionV3 model …

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Wastewater-Informed Public Health Intervention Playbook Sep 2022

Wastewater-Informed Public Health Intervention Playbook

Sustain Magazine

As the SARS-CoV-2 pandemic quickly spread from country to country and continent to continent in 2020, governments and scientists needed a way to track COVID-19 through populations in order to position public health interventions in the most impactful locations. Having a decision-based risk framework may help to guide policy creation that could minimize or prevent possible outbreaks and surges of infection within communities. The University of Louisville in partnership with Louisville’s Department of Public Health and Wellness tested this strategy in 2021 and 2022. This Wastewater-Informed Public Health Intervention Playbook describes the decisions and actions of that academic and public …

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Quantifying The Relationship Between Sub-Population Wastewater Samples And Community-Wide Sars-Cov-2 Seroprevalence, Ted Smith, Rochelle H. Holm, Rachel J. Keith, Alok R. Amraotkar, Chance R. Alvarado, Krzysztof Banecki, Boseung Choi, Ian Santisteban, Adrienne M. Bushau-Sprinkle, Kathleen T. Kitterman, Joshua Fuqua, Krystal T. Hamorsky, Kenneth E. Palmer, J. Michael Brick, Aruni Bhatnagar, Grzegorz A. Rempala Sep 2022

Quantifying The Relationship Between Sub-Population Wastewater Samples And Community-Wide Sars-Cov-2 Seroprevalence, Ted Smith, Rochelle H. Holm, Rachel J. Keith, Alok R. Amraotkar, Chance R. Alvarado, Krzysztof Banecki, Boseung Choi, Ian Santisteban, Adrienne M. Bushau-Sprinkle, Kathleen T. Kitterman, Joshua Fuqua, Krystal T. Hamorsky, Kenneth E. Palmer, J. Michael Brick, Aruni Bhatnagar, Grzegorz A. Rempala

Faculty Scholarship

Robust epidemiological models relating wastewater to community disease prevalence are lacking. Assessments of SARS-CoV-2 infection rates have relied primarily on convenience sampling, which does not provide reliable estimates of community disease prevalence due to inherent biases. This study conducted serial stratified randomized samplings to estimate the prevalence of SARS-CoV-2 antibodies in 3717 participants and obtained weekly samples of community wastewater for SARS-CoV-2 concentrations in Jefferson County, KY (USA) from August 2020 to February 2021. Using an expanded Susceptible-Infected-Recovered model, the longitudinal estimates of the disease prevalence were obtained and compared with the wastewater concentrations using regression analysis. The model analysis …

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Overview Of The Clef-2022 Checkthat! Lab Task 2 On Detecting Previously Fact-Checked Claims, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Shaden Shaar, Hamdy Mubarak, Nikolay Babulkov Sep 2022

Overview Of The Clef-2022 Checkthat! Lab Task 2 On Detecting Previously Fact-Checked Claims, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Shaden Shaar, Hamdy Mubarak, Nikolay Babulkov

Natural Language Processing Faculty Publications

We describe the fourth edition of the CheckThat! Lab, part of the 2022 Conference and Labs of the Evaluation Forum (CLEF). The lab evaluates technology supporting three tasks related to factuality, and it covers seven languages such as Arabic, Bulgarian, Dutch, English, German, Spanish, and Turkish. Here, we present the task 2, which asks to detect previously fact-checked claims (in two languages). A total of six teams participated in this task, submitted a total of 37 runs, and most submissions managed to achieve sizable improvements over the baselines using transformer based models such as BERT, RoBERTa. In this paper, we …

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Overview Of The Clef-2022 Checkthat! Lab Task 1 On Identifying Relevant Claims In Tweets, Preslav Nakov, Alberto Barrón-Cedeño, Giovanni Da San Martino, Firoj Alam, Mucahid Kutlu, Wajdi Zaghouani, Mucahid Kutlu, Wajdi Zaghouani, Chengkai Li, Shaden Shaar, Hamdy Mubarak, Alex Nikolov Sep 2022

Overview Of The Clef-2022 Checkthat! Lab Task 1 On Identifying Relevant Claims In Tweets, Preslav Nakov, Alberto Barrón-Cedeño, Giovanni Da San Martino, Firoj Alam, Mucahid Kutlu, Wajdi Zaghouani, Mucahid Kutlu, Wajdi Zaghouani, Chengkai Li, Shaden Shaar, Hamdy Mubarak, Alex Nikolov

Natural Language Processing Faculty Publications

We present an overview of CheckThat! lab 2022 Task 1, part of the 2022 Conference and Labs of the Evaluation Forum (CLEF). Task 1 asked to predict which posts in a Twitter stream are worth fact-checking, focusing on COVID-19 and politics in six languages: Arabic, Bulgarian, Dutch, English, Spanish, and Turkish. A total of 19 teams participated and most submissions managed to achieve sizable improvements over the baselines using Transformer-based models such as BERT and GPT-3. Across the four subtasks, approaches that targetted multiple languages (be it individually or in conjunction, in general obtained the best performance. We describe the …

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Analyzing The Impact Of Covid-19 Control Policies On Campus Occupancy And Mobility Via Wifi Sensing, Camellia Zakaria, Amee Trivedi, Emmanuel Cecchet, Michael Chee, Prashant Shenoy, Rajesh Krishna Balan Sep 2022

Analyzing The Impact Of Covid-19 Control Policies On Campus Occupancy And Mobility Via Wifi Sensing, Camellia Zakaria, Amee Trivedi, Emmanuel Cecchet, Michael Chee, Prashant Shenoy, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Mobile sensing has played a key role in providing digital solutions to aid with COVID-19 containment policies, primarily to automate contact tracing and social distancing measures. As more and more countries reopen from lockdowns, there remains a pressing need to minimize crowd movements and interactions, particularly in enclosed spaces. Many COVID-19 technology solutions leverage positioning systems, generally using Bluetooth and GPS, and can theoretically be adapted to monitor safety compliance within dedicated environments. However, they may not be the ideal modalities for indoor positioning. This article conjectures that analyzing user occupancy and mobility via deployed WiFi infrastructure can help institutions …

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Respiratory Pattern Analysis For Covid-19 Digital Screening Using Ai Techniques, Annita Tahsin Priyoti Aug 2022

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 …

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Sel-Covidnet: An Intelligent Application For The Diagnosis Of Covid-19 From Chest X-Rays And Ct-Scans, Ahmad Al Smadi, Ahed Abugabah, Ahmad Mohammad Al-Smadi, Sultan Almotairi Aug 2022

Sel-Covidnet: An Intelligent Application For The Diagnosis Of Covid-19 From Chest X-Rays And Ct-Scans, Ahmad Al Smadi, Ahed Abugabah, Ahmad Mohammad Al-Smadi, Sultan Almotairi

All Works

COVID-19 detection from medical imaging is a difficult challenge that has piqued the interest of experts worldwide. Chest X-rays and computed tomography (CT) scanning are the essential imaging modalities for diagnosing COVID-19. All researchers focus their efforts on developing viable methods and rapid treatment procedures for this pandemic. Fast and accurate automated detection approaches have been devised to alleviate the need for medical professionals. Deep Learning (DL) technologies have successfully recognized COVID-19 situations. This paper proposes a developed set of nine deep learning models for diagnosing COVID-19 based on transfer learning and implementation in a novel architecture (SEL-COVIDNET). In which …

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Statistical Analysis Methods Applied To Early Outpatient Covid-19 Treatment Case Series Data, Eleftherios Gkioulekas, Peter A. Mccullough, Vladimir Zelenko Aug 2022

Statistical Analysis Methods Applied To Early Outpatient Covid-19 Treatment Case Series Data, Eleftherios Gkioulekas, Peter A. Mccullough, Vladimir Zelenko

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

When confronted with a public health emergency, significant innovative treatment protocols can sometimes be discovered by medical doctors at the front lines based on repurposed medications. We propose a statistical framework for analyzing the case series of patients treated with such new protocols, that enables a comparison with our prior knowledge of expected outcomes, in the absence of treatment. The goal of the proposed methodology is not to provide a precise measurement of treatment efficacy, but to establish the existence of treatment efficacy, in order to facilitate the binary decision of whether the treatment protocol should be adopted on an …

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Absence Of Visitors During Lockdown Reveals Natural Variation In Carbon Dioxide Level In The Glowworm Cave, Waitomo, New Zealand, David J. Merritt, Chris Hendy Dr, Shannon Corkill Ms Aug 2022

Absence Of Visitors During Lockdown Reveals Natural Variation In Carbon Dioxide Level In The Glowworm Cave, Waitomo, New Zealand, David J. Merritt, Chris Hendy Dr, Shannon Corkill Ms

International Journal of Speleology

Waitomo Glowworm Cave is a highly visited cave where the highlight is viewing the bioluminescence display of a large colony of glowworms. Anthropogenic carbon dioxide build-up in the cave is prevented by management of chimney-effect ventilation aided by a network of microclimate sensors. A cave door prevents ventilationunder drying conditions and promotes it when necessary to clear CO2 and when inflowing air has high relative humidity. A COVID-19-related nationwide “lockdown” in New Zealand from March 2020 resulted in neither staff nor visitors being present in the cave for 60 days, and provided an opportunity to assess the natural microclimate …

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Asian Hate Speech Detection On Twitter During Covid-19, Amir Toliyat, Sarah Ita Levitan, Zeng Peng, Ronak Etemadpour Aug 2022

Asian Hate Speech Detection On Twitter During Covid-19, Amir Toliyat, Sarah Ita Levitan, Zeng Peng, Ronak Etemadpour

Publications and Research

Coronavirus disease 2019 (COVID-19) started in Wuhan, China, in late 2019, and after being utterly contagious in Asian countries, it rapidly spread to other countries. This disease caused governments worldwide to declare a public health crisis with severe measures taken to reduce the speed of the spread of the disease. This pandemic affected the lives of millions of people. Many citizens that lost their loved ones and jobs experienced a wide range of emotions, such as disbelief, shock, concerns about health, fear about food supplies, anxiety, and panic. All of the aforementioned phenomena led to the spread of racism and …

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Machine Learning Model Comparison And Arma Simulation Of Exhaled Breath Signals Classifying Covid-19 Patients, Aaron Christopher Segura Aug 2022

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 …

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Relationships Between Covid-19 Infection Rates, Healthcare Access, Socioeconomic Status, And Cultural Diversity, Marghece P. J. Barnes Aug 2022

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 …

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A Climate Resilience Research Renewal Agenda: Learning Lessons From The Covid-19 Pandemic For Urban Climate Resilience, Mark Pelling, Winston T. L. Chow, Eric Chu, Richard Dawson, David Dodman, Arabella Fraser, Bronwyn Hayward, Luna Khirfan, Timon Mcphearson, Anjal Prakash, Gina Ziervogel Aug 2022

A Climate Resilience Research Renewal Agenda: Learning Lessons From The Covid-19 Pandemic For Urban Climate Resilience, Mark Pelling, Winston T. L. Chow, Eric Chu, Richard Dawson, David Dodman, Arabella Fraser, Bronwyn Hayward, Luna Khirfan, Timon Mcphearson, Anjal Prakash, Gina Ziervogel

Research Collection School of Social Sciences

Learning lessons from the COVID-19 pandemic opens an opportunity for enhanced research and action on inclusive urban resilience to climate change. Lessons and their implications are used to describe a climate resilience research renewal agenda. Three key lessons are identified. The first lesson is generic, that climate change risk coexists and interacts with other risks through overlapping social processes, conditions and decision-making contexts. Two further lessons are urban specific: that networks of connectivity bring risk as well as resilience and that overcrowding is a key indicator of the multiple determinants of vulnerability to both COVID-19 and climate change impacts. From …

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Regression Analysis Of Resilience And Covid-19 In Idaho Counties, Ishrat Zaman Aug 2022

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. …

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Social Media Analytics With Applications In Disaster Management And Covid-19 Events, Md Yasin Kabir Aug 2022

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 …

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