Medicine and Health Sciences Commons^™

Shining A Light On Marginal Food Insecurity In An Understudied Population Comment, Angela D. Liese

Faculty Publications

No abstract provided.

A Non-Invasive Interpretable Diagnosis Of Melanoma Skin Cancer Using Deep Learning And Ensemble Stacking Of Machine Learning Models, Iftiaz A. Alfi, Mahfuzur Rahman, Mohammad Shorfuzzaman, Amril Nazir

All Works

A skin lesion is a portion of skin that observes abnormal growth compared to other areas of the skin. The ISIC 2018 lesion dataset has seven classes. A miniature dataset version of it is also available with only two classes: malignant and benign. Malignant tumors are tumors that are cancerous, and benign tumors are non-cancerous. Malignant tumors have the ability to multiply and spread throughout the body at a much faster rate. The early detection of the cancerous skin lesion is crucial for the survival of the patient. Deep learning models and machine learning models play an essential role in …

Exploring And Evaluating The Impact Of Covid-19 On Mobility Changes In Singapore, Aldy Gunawan, Linh Chi Tran, Kar Way Tan, I-Lin Wang

Research Collection School Of Computing and Information Systems

This paper analyzes the changes in mobility trends due to the impact of the COVID-19 pandemic in Singapore in the six different sectors: Retail and Recreation, Grocery and Pharmacy, Parks, Transit Stations, Workplaces and Residential. The period of observation is from 15 February 2020 to 18 August 2021. The observed patterns obtained from the descriptive data analysis sheds light on the effectiveness of social distancing measures in Singapore as well as the level of compliance among the country’s residents. Correlation analysis is used to explore the relationship between different sectors during the pandemic period. The results reveal a strong sense …

A Deep Dive Into The Impact Of Covid-19 On Software Development, Paulo Anselmo Da Mota Silveira Neto, Umme Ayda Mannan, Eduardo Santana De Almeida, Nachiappan Nagappan, David Lo, Pavneet Singh Kochhar, Cuiyun Gao, Iftekhar Ahmed

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic is considered as the most crucial global health calamity of the century. It has impacted different business sectors around the world and software development is not an exception. This study investigates the impact of COVID-19 on software projects and software development professionals. We conducted a mining software repository study based on 100 GitHub projects developed in Java using ten different metrics. Next, we surveyed 279 software development professionals for better understanding the impact of COVID-19 on daily activities and wellbeing. We identified 12 observations related to productivity, code quality, and wellbeing. Our findings highlight that the impact …

Hyperparameter Optimization For Covid-19 Chest X-Ray Classification, Ibraheem Hamdi, Muhammad Ridzuan, Mohammad Yaqub

Computer Vision Faculty Publications

Despite the introduction of vaccines, Coronavirus disease (COVID-19) remains a worldwide dilemma, continuously developing new variants such as Delta and the recent Omicron. The current standard for testing is through polymerase chain reaction (PCR). However, PCRs can be expensive, slow, and/or inaccessible to many people. X-rays on the other hand have been readily used since the early 20th century and are relatively cheaper, quicker to obtain, and typically covered by health insurance. With a careful selection of model, hyperparameters, and augmentations, we show that it is possible to develop models with 83% accuracy in binary classification and 64% in multi-class …

Using A Stochastic Continuous-Time Markov Chain Model To Examine Alternative Timing And Duration Of The Covid-19 Lockdown In Kuwait: What Can Be Done Now?, Mustafa Al-Zoughool, Tamer Oraby, Harri Vainio, Janvier Gasana, Joseph C. Longenecker, Walid Al Ali, Mohammad Alseaidan, Susie Elsaadany, Michael G. Tyshenko

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Background

Kuwait had its first COVID-19 in late February, and until October 6, 2020 it recorded 108,268 cases and 632 deaths. Despite implementing one of the strictest control measures-including a three-week complete lockdown, there was no sign of a declining epidemic curve. The objective of the current analyses is to determine, hypothetically, the optimal timing and duration of a full lockdown in Kuwait that would result in controlling new infections and lead to a substantial reduction in case hospitalizations.

Methods

The analysis was conducted using a stochastic Continuous-Time Markov Chain (CTMC), eight state model that depicts the disease transmission and …

An Odd-Protocol For Agent-Based Model For The Spread Of Covid-19 In Ireland, Elizabeth Hunter, John D. Kelleher

Reports

No abstract provided.

International Consensus On Lung Function Testing During Covid-19 Pandemic And Beyond, Aisling Mcgowan, Pierantonio Laveneziana, Sam Bayat, Nicole Beydon, P.W. Boros, Felip Burgos, Matjaž Fležar, Monika Franczuk, Maria-Alejandra Galarza, Adrian H. Kendrick, Enrico Lombardi, Jellien Makonga-Braaksma, Meredith C. Mccormack, Laurent Plantier, Sanja Stanojevic, Irene Steenbruggen, Bruce Thompson, Allan L. Coates, Jack Wanger, Donald W. Cockcroft, Bruce Culver, Karl Sylvester, Frans De Jongh

Articles

Coronavirus disease 2019 (COVID-19) has negatively affected the delivery of respiratory diagnostic services across the world due to the potential risk of disease transmission during lung function testing. Community prevalence, reoccurrence of COVID-19 surges and the emergence of different variants of SARS-CoV-2 have impeded attempts to restore services. Finding consensus on how to deliver safe lung function services for both patients attending and for staff performing the tests are of paramount importance. This international statement presents the consensus opinion of 23 experts in the field of lung function and respiratory physiology balanced with evidence from the reviewed literature. It describes …

Collected Papers (On Physics, Artificial Intelligence, Health Issues, Decision Making, Economics, Statistics), Volume Xi, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

This eleventh volume of Collected Papers includes 90 papers comprising 988 pages on Physics, Artificial Intelligence, Health Issues, Decision Making, Economics, Statistics, written between 2001-2022 by the author alone or in collaboration with 84 co-authors from 19 countries.

Collected Papers (On Neutrosophics, Plithogenics, Hypersoft Set, Hypergraphs, And Other Topics), Volume X, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

This tenth volume of Collected Papers includes 86 papers in English and Spanish languages comprising 972 pages, written between 2014-2022 by the author alone or in collaboration with 105 co-authors from 26 countries.

Studying Spread Patterns Of Covid-19 Based On Spatiotemporal Data, Beiyu Lin, Xiaowei Jia, Zhiqian Chen

Computer Science Faculty Publications and Presentations

The current COVID-19 epidemic have transformed every aspect of our lives, especially our behavior and routines. These changes have been drastically impacting the economy in each region, such as local restaurants and transportation systems. With massive amounts of ambient data being collected everywhere, we now can develop innovative algorithms to have a much greater understanding of epidemic spread patterns of COVID-19 based on spatiotemporal data. The findings will open up the possibility to design adaptive planning or scheduling systems that will help preventing the spread of COVID-19 and other infectious diseases.

In this tutorial, we will review the trending state-of-theart …

Exo-Sir: An Epidemiological Model To Analyze The Impact Of Exogenous Spread Of Infection, Nirmal Kumar Sivaraman, Manas Gaur, Shivansh Baijal, Sakthi Balan Muthiah, Amit Sheth

Publications

Epidemics like Covid-19 and Ebola have impacted people's lives significantly. The impact of mobility of people across the countries or states in the spread of epidemics has been significant. The spread of disease due to factors local to the population under consideration is termed the endogenous spread. The spread due to external factors like migration, mobility, etc. is called the exogenous spread. In this paper, we introduce the Exo-SIR model, an extension of the popular SIR model and a few variants of the model. The novelty in our model is that it captures both the exogenous and endogenous spread of …

Covid-19 Collaborative Modelling For Policy Response In The Philippines, Malaysia And Vietnam, Angus Hughes, Romain Ragonnet, Pavithra Jayasundara, Hoang-Anh Ngo, Elvira P. De Lara-Tuprio, Ma. Regina Justina Estuar, Timothy Robin Y. Teng, Law Kian Boon, Kalaiarasu M. Peariasamy, Zhuo-Lin Chong, Izzuna Mudla M. Ghazali, Greg J. Fox, Thu-Anh Nguyen, Linh-Vi Le, Milinda Abayawardana B. Eng, David Shipman, Emma S. Mcbryde, Michael T. Meehan, Jamie M. Caldwell, James M. Trauer

Mathematics Faculty Publications

Mathematical models that capture COVID-19 dynamics have supported public health responses and policy development since the beginning of the pandemic, yet there is limited discourse to describe features of an optimal modelling platform to support policy decisions or how modellers and policy makers have engaged with each other. Here, we outline how we used a modelling software platform to support public health decision making for the COVID-19 response in the Western Pacific Region (WPR) countries of the Philippines, Malaysia and Viet Nam. This perspective describes an approach to support evidence-based public health decisions and policy, which may help inform other …

The Online Ordering Behaviors Among Participants In The Oklahoma Women, Infants, And Children Program: A Cross-Sectional Analysis, Qi Zhang, Kayoung Park, Junzhou Zhang, Chuanyi Tang

Community & Environmental Health Faculty Publications

The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) is a nutrition assistance program in the United States (U.S.). Participants in the program redeem their prescribed food benefits in WIC-authorized grocery stores. Online ordering is an innovative method being pilot-tested in some stores to facilitate WIC participants' food benefit redemption, which has become especially important in the COVID-19 pandemic. The present research aimed to examine the online ordering (OO) behaviors among 726 WIC households who adopted WIC OO in a grocery chain, XYZ (anonymous) store, in Oklahoma (OK). These households represented approximately 5% of WIC households who redeemed …

Why Do Family Members Reject Ai In Health Care? Competing Effects Of Emotions, Eun Hee Park, Karl Werder, Lan Cao, Balasubramaniam Ramesh

Information Technology & Decision Sciences Faculty Publications

Artificial intelligence (AI) enables continuous monitoring of patients’ health, thus improving the quality of their health care. However, prior studies suggest that individuals resist such innovative technology. In contrast to prior studies that investigate individuals’ decisions for themselves, we focus on family members’ rejection of AI monitoring, as family members play a significant role in health care decisions. Our research investigates competing effects of emotions toward the rejection of AI monitoring for health care. Based on two scenario-based experiments, our study reveals that emotions play a decisive role in family members’ decision making on behalf of their parents. We find …

Characterizing Long Covid: Deep Phenotype Of A Complex Condition, Rachel R. Deer, Madeline A. Rock, Nicole Vasilevsky, Leigh Carmody, Halie Rando, Alfred J. Anzalone, Marc D. Basson, Tellen D. Bennett, Timothy Bergquist, Eilis A. Boudreau, Carolyn T. Bramante, James Brian Byrd, Tiffany J. Callahan, Lauren E. Chan, Haitao Chu, Christopher G. Chute, Ben D. Coleman, Hannah E. Davis, Joel Gagnier, Casey S. Greene, Ramakanth Kavuluru

Institute for Biomedical Informatics Faculty Publications

BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies.

METHODS: The Human Phenotype Ontology …

Evaluation Of The United States Covid-19 Vaccine Allocation Strategy, Md Rafiul Islam, Tamer Oraby, Audrey Mccombs, Mohammad Mihrab Chowdhury, Mohammad Al-Mamun, Michael G. Tyshenko, Claus Kadelkai

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Background: Anticipating an initial shortage of vaccines for COVID-19, the Centers for Disease Control (CDC) in the United States developed priority vaccine allocations for specific demographic groups in the population. This study evaluates the performance of the CDC vaccine allocation strategy with respect to multiple potentially competing vaccination goals (minimizing mortality, cases, infections, and years of life lost (YLL)), under the same framework as the CDC allocation: four priority vaccination groups and population demographics stratified by age, comorbidities, occupation and living condition (congested or non-congested).

Methods and findings: We developed a compartmental disease model that incorporates key elements of the …

Bisindolylmaleimide Ix: A Novel Anti-Sars-Cov2 Agent Targeting Viral Main Protease 3clpro Demonstrated By Virtual Screening Pipeline And In-Vitro Validation Assays, Yash Gupta, Dawid Maciorowski, Samantha E. Zak, Krysten A. Jones, Rahul S. Kathayat, Saara-Anne Azizi, Raman Mathur, Catherine M. Pearce, David J. Ilc, Hamza Husein, Andrew S. Herbert, Ajay Bharti, Brijesh Rathi, Ravi Durvasula, Daniel P. Becker, Bryan C. Dickinson, John M. Dye, Prakasha Kempaiah

Chemistry: Faculty Publications and Other Works

SARS-CoV-2, the virus that causes COVID-19 consists of several enzymes with essential functions within its proteome. Here, we focused on repurposing approved and investigational drugs/compounds. We targeted seven proteins with enzymatic activities known to be essential at different stages of the viral cycle including PLpro, 3CLpro, RdRP, Helicase, ExoN, NendoU, and 2′-O-MT. For virtual screening, energy minimization of a crystal structure of the modeled protein was carried out using the Protein Preparation Wizard (Schrodinger LLC 2020-1). Following active site selection based on data mining and COACH predictions, we performed a high-throughput virtual screen of drugs and investigational molecules (n = …

Understanding Covid-19 Dynamics And The Effects Of Interventions In The Philippines: A Mathematical Modelling Study, Jamie M. Caldwell, Elvira P. De Lara-Tuprio, Timothy Robin Y. Teng, Ma. Regina Justina E. Estuar, Raymond Francis R. Sarmiento, Milinda Abayawardana B. Eng, Robert Neil F. Leong, Richard T. Gray, James G. Wood, Linh-Vi Le, Emma S. Mcbryde, Romain Ragonnet, James M. Trauer

Mathematics Faculty Publications

Background

COVID-19 initially caused less severe outbreaks in many low- and middle-income countries (LMIC) compared with many high-income countries; possibly because of differing demographics; socioeconomics; surveillance; and policy responses. Here; we investigate the role of multiple factors on COVID-19 dynamics in the Philippines; a LMIC that has had a relatively severe COVID-19 outbreak.

Methods

We applied an age-structured compartmental model that incorporated time-varying mobility; testing; and personal protective behaviors (through a “Minimum Health Standards” policy; MHS) to represent the first wave of the Philippines COVID-19 epidemic nationally and for three highly affected regions (Calabarzon; Central Visayas; and the National Capital …

Decoding Clinical Biomarker Space Of Covid-19: Exploring Matrix Factorization-Based Feature Selection Methods, Farshad Saberi-Movahed, Mahyar Mohammadifard, Adel Mehrpooya, Mohammad Rezaei-Ravari, Kamal Berahmand, Mehrdad Rostami, Saeed Karami, Mohammad Najafzadeh, Davood Hajinezhad, Mina Jamshidi, Farshid Abedi, Mahtab Mohammadifard, Elnaz Farbod, Farinaz Safavi, Mohammadreza Dorvash, Shahrzad Vahedi, Mahdi Eftekhari, Farid Saberi-Movahed, Iman Tavassoly

Publications and Research

One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients’ characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 …

Covid-19 And The Impact On Rural And Black Church Congregants: Results Of The C-M-C Project, Lovoria B. Williams, Anita F. Fernander, Tofial Azam, Maria L. Gomez, Junghee Kang, Cassidy L. Moody, Hannah Bowman, Nancy E. Schoenberg

Nursing Faculty Publications

The COVID-19 pandemic has had devastating effects on Black and rural populations with a mortality rate among Blacks three times that of Whites and both rural and Black populations experiencing limited access to COVID-19 resources. The primary purpose of this study was to explore the health, financial, and psychological impact of COVID-19 among rural White Appalachian and Black nonrural central Kentucky church congregants. Secondarily we sought to examine the association between sociodemographics and behaviors, attitudes, and beliefs regarding COVID-19 and intent to vaccinate. We used a cross sectional survey design developed with the constructs of the Health Belief and Theory …

Covid-19 Impact On Radiology Students’ Distance Learning (Summer 2021), Mary Lee, Jason Chan, Cheryann Jackson-Holmes, Renzo Marmolejo, Zoya Vinokur

Publications and Research

The Radiological Technology students have adjusted from the urgent distance learning that was enacted in the Spring of 2020, to the hybrid distance learning that is currently in place. This hybrid distance learning is the same way the incoming class of radiological technology students were taught. Both cohorts of students were tracked over the year by online anonymous surveys. We wanted to know how students were adapting to distance learning, if their focus and motivation varied over the course of the year due to changing pandemic conditions. For the students that were working, what impact did it have on their …

Tocilizumab And Covid-19: A Meta-Analysis Of 2120 Patients With Severe Disease And Implications For Clinical Trial Methodologies, Azza Sarfraz, Zouina Sarfraz, Muzna Sarfraz, Hinna Aftab, Zainab Pervaiz

Department of Paediatrics and Child Health

Background/aim: Since the outbreak of the COVID-19, numerous therapies to counteract this severe disease have emerged. The benefits of Tocilizumab for severely infected COVID-19 patients and the methodologies of ongoing clinical trials are explored.
Materials and methods: A systematic search adhering to PRISMA guidelines was conducted in PubMed, Cochrane Central, medRxiv, and bioRxiv using the following keywords: “Tocilizumab,” “Actemra,” “COVID-19.” An additional subsearch was conducted on Clinicaltrials.gov to locate ongoing tocilizumab trials.
Results: A total of 13 studies were included in the meta-analysis comprising 2120 patients. The treatment group had lower mortality compared to the control group (OR = 0.42, …

Adapting An Agent-Based Model Of Infectious Disease Spread In An Irish County To Covid-19, Elizabeth Hunter, John D. Kelleher

Articles

The dynamics that lead to the spread of an infectious disease through a population can be characterized as a complex system. One way to model such a system, in order to improve preparedness, and learn more about how an infectious disease, such as COVID-19, might spread through a population, is agent-based epidemiological modelling. When a pandemic is caused by an emerging disease, it takes time to develop a completely new model that captures the complexity of the system. In this paper, we discuss adapting an existing agent-based model for the spread of measles in Ireland to simulate the spread of …

A Comparison Of Prospective Space-Time Scan Statistics And Spatiotemporal Event Sequence Based Clustering For Covid-19 Surveillance, Fuyu Xu, Kate Beard

Teaching, Learning & Research Documents

The outbreak of the COVID-19 disease was first reported in Wuhan, China, in December 2019. Cases in the United States began appearing in late January. On March 11, the World Health Organization (WHO) declared a pandemic. By mid-March COVID-19 cases were spreading across the US with several hotspots appearing by April. Health officials point to the importance of surveillance of COVID-19 to better inform decision makers at various levels and efficiently manage distribution of human and technical resources to areas of need. The prospective space-time scan statistic has been used to help identify emerging COVID-19 disease clusters, but results from …

Covid-19_Umaine News_Wvii Talks With Lieberthal About Disease Superspreader Prediction, University Of Maine Division Of Marketing And Communications

Division of Marketing & Communications

Screenshot of UMaine in the News regarding WVII (Channel 7) speaking with Brandon Lieberthal, a University of Maine research associate in the School of Biology and Ecology, about the development of a mathematical model that can be used to identify potential superspreader locations and to predict the efficacy of mitigation strategies.

Knowledge And Anxiety About Covid-19 In The State Of Qatar, And The Middle East And North Africa Region—A Cross Sectional Study, Sathyanarayanan Doraiswamy, Sohaila Cheema, Maisonneuve Patrick, Amit Abraham, Ingmar Weber, Jisun An, Albert B. Lowenfels, Ravinder Mamtani

Research Collection School Of Computing and Information Systems

While the coronavirus disease 2019 (COVID-19) pandemic wreaked havoc across the globe, we have witnessed substantial mis- and disinformation regarding various aspects of the disease. We conducted a cross-sectional study using a self-administered questionnaire for the general public (recruited via social media) and healthcare workers (recruited via email) from the State of Qatar, and the Middle East and North Africa region to understand the knowledge of and anxiety levels around COVID-19 (April–June 2020) during the early stage of the pandemic. The final dataset used for the analysis comprised of 1658 questionnaires (53.0% of 3129 received questionnaires; 1337 [80.6%] from the …

Spatially Refined Time-Varying Reproduction Numbers Of Covid-19 By Health District In Georgia, Usa, March–December 2020, Chigozie A. Ogwara, Arshpreet Kaur Mallhi, Xinyi Hua, Kamalich Muniz-Rodriguez, Jessica S. Schwind, Xiaolu Zhou, Jeffery A. Jones, Joanne Chopak-Foss, Gerardo Chowell, Isaac Chun-Hai Fung

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

This study quantifies the transmission potential of SARS-CoV-2 across public health districts in Georgia, USA, and tests if per capita cumulative case count varies across counties. To estimate the time-varying reproduction number, Rt of SARS-CoV-2 in Georgia and its 18 public health districts, we apply the R package ‘EpiEstim’ to the time series of historical daily incidence of confirmed cases, 2 March–15 December 2020. The epidemic curve is shifted backward by nine days to account for the incubation period and delay to testing. Linear regression is performed between log10-transformed per capita cumulative case count and log10-transformed population size. We observe …

Social Distancing And Testing As Optimal Strategies Against The Spread Of Covid-19 In The Rio Grande Valley Of Texas, Kristina P. Vatcheva, Josef A. Sifuentes, Tamer Oraby, Jose Campo Maldonado, Timothy Huber, Cristina Villalobos

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

At the beginning of August 2020, the Rio Grande Valley (RGV) of Texas experienced a rapid increase of coronavirus disease 2019 (abbreviated as COVID-19) cases and deaths. This study aims to determine the optimal levels of effective social distancing and testing to slow the virus spread at the outset of the pandemic. We use an age-stratified eight compartment epidemiological model to depict COVID-19 transmission in the community and within households. With a simulated 120-day outbreak period data we obtain a post 180-days period optimal control strategy solution. Our results show that easing social distancing between adults by the end of …

Covid-19_Umaine News_Education Week Talks With Ferrini-Mundy About Stem Teaching During The Pandemic, University Of Maine Division Of Marketing And Communications

Division of Marketing & Communications

Screenshot of UMaine in the News regarding Education Week report on a symposium at the American Educational Research Association's virtual annual meeting featuring Joan Ferrini-Mundy, University of Maine System vice chancellor for research and innovation and president of the University of Maine.