University of Maryland COVID-19 Research Expertise Listing

Don Milton
School of Public Health/MIAEH
https://sph.umd.edu/people/donald-milton
also https://catch.umd.edu/

The objective of this research study, “UMD COVID-19 Surveillance,” led by Donald Milton, MD, DrPH, Professor of Environmental Health and funded by research grants and contracts from the University of Maryland and one or more federal government sources including the U.S. Defense Advanced Research Projects Agency (DARPA) and the Biomedical Advanced Research and Development Authority (BARDA) of the Department of Health and Human Services, is to better understand the new coronavirus (SARS-CoV-2) that causes the Coronavirus Infectious Disease – 2019 (COVID-19) that emerged and was first identified in Wuhan, China, in 2019. The primary goal of this research is to identify how people who have been exposed and are in the early, often asymptomatic days of infection shed virus and transmit the virus and especially whether they shed virus from their lungs in exhaled breath, and whether surgical and homemade masks reduce shedding. This work will contribute to understanding the potential role of airborne transmission, masks as source control, and whether breath measurements and biometric signals can be used to improve early diagnosis of infection. It will also contribute to response to COVID-19 by collecting samples that can be used to understand the immune repose to the virus and to develop new treatments for the infection through the DARPA P3 program.

Brooke Liu
Arts and Humanities (ARHU)/Communication
https://www.comm.umd.edu/people/faculty/bfliu

I have researched and taught crisis communication for the past 20 years, including for infectious disease outbreaks, terrorist attacks, and natural disasters. My current UMD seed grant examines how members of university crisis management teams are responding to the pandemic, lessons they have learned, obstacles they have overcome, and challenges that they still face.

Long Doan
Behavioral and Social Sciences (BSOS)/Sociology
http://longdoan.net/
also http://groupslab.com/

"This project will examine the impacts of COVID-19 and states’ and local governments’ social distancing efforts on behavior, time spent with others, use of technology, and mental and physical wellbeing. The pandemic’s negative consequences to public health and the economy has received much attention in public and academic spheres. Yet, we know little about the social consequences of COVID-19. How the virus will affect social life as we know remains to be seen, but it is important to examine the impacts it has on daily life in real time. This is especially time sensitive as European nations and some states begin to ease social distancing restrictions. Regardless of the timing and extent of social distancing restrictions, what is clear is that as restrictions are placed, Americans have to adapt their daily routines to navigate their new realities. Social distancing restrictions may increase social isolation, lead to an increase in divorce, and have negative consequences on mental and physical health due to anxiety related to the disease.

To address this question, we leverage data from several hundred respondents’ daily time use before the pandemic to create a natural experiment that isolates the effects of the pandemic on changes in behavior. In addition, we will recruit a total of 2,000 respondents from online crowdsourcing panels like Prolific Academic and Mechanical Turk. We will then follow-up with all respondents after the pandemic subsides. Using this approach, we will have data on people’s social behaviors before, during, and after the pandemic. We will field a survey to collect relevant information respondents’ daily behavior and the context for those behaviors. The survey will collect data on sociodemographics, typical sleep, work, and exercise patterns as well as typical approaches to division of labor for housework and carework. In examining changes in behavior due to the pandemic, we can see if distinct clusters of social behaviors emerge and whether these types of behaviors relate to changes in mental health. We are particularly interested in exploring how the effects of COVID-19 varies by gender, sexuality, family structure (parental and marital status), race/ethnicity, and immigrant status–all key sociodemographic characteristics that affect time use and wellbeing. In doing so, we can provide evidence-based recommendations to address the social consequences of the unfolding pandemic."

Lei Zhang
A. James Clark School of Engineering (ENGR)/Maryland Transportation Institute
https://mti.umd.edu/
also https://data.covid.umd.edu/

An interactive COVID-19 impact analysis platform with a focus on mobility, economic, and health impact at: https://data.covid.umd.edu

Rick Blanton
A. James Clark School of Engineering (ENGR)/EIT / Strategic Operations

Using additive manufacturing to bridge the gap between front line medical professionals (hospitals & first responders) need for PPE and industry's ability to handle the increased demand.

Jonathan Dinman
Computer, Mathematical and Natural Sciences (CMNS)/Cell Biology and Molecular Genetics
https://cbmg.umd.edu/faculty/jonathand-dinman/

SARS-CoV-2, the causative agent of COVID-19, uses a molecular mechanism called Programmed -1 Ribosomal Frameshifting (-1 PRF) as a critical developmental switch. Altering -1 PRF has been shown to interfere with the replication of many viruses, including SARS-Co-V. We are using genetic and biochemical/biophysical tools to illuminate the SARS-CoV-2 frameshift signal. We are also developing assays to screen for small molecules that interact with, and alter the activity of this -1 PRF signal.

Ming Hu
Architecture, Planning, and Preservation (ARCH))/Architecture
https://www.arch.umd.edu/arch/faculty/ming-hu

Origami inspired mobile clinic

Nathan Fox
Education (EDUC)/HDQM
www.cdl.umd.edu

We are tracking the mental health of a sample of adolescents and their parents who we have followed since infancy and on whom we have pre-covid measures of mental health.

Axel Krieger
A. James Clark School of Engineering (ENGR)/MechE, Fischell Institute for Biomedical Devices
https://mrelab.com/

1. Teleoperated In-ICU Robotics to Reduce Exposure of Critical Care Personnel
Critical care personnel often must enter contaminated area to make simple adjustments to equipment such as ventilators or infusion pumps. Each visit requires use of another set of PPE masks, gowns, etc. We are building low cost teleoperated robot systems with video camera and custom finger to push buttons or operate touch screen displays. Here is a video of a prototype robot that UMD student Misha Khrenov built to control an ICU ventilator touchscreen: https://youtu.be/bm_2c3z82NU

2. Patient Hood to Reduce Exposure of Critical Care Personnel
Critical care personnel are at risk of infection when interacting with COVID-19 patients. The risk is especially high during intubation and other airway manipulations. We are building a low-cost patient hood that provides access to the patient and provides a negative pressure environment using available suction ports. We are submitting an FDA emergency use authorization (EUA) so we can clinically test and distribute the hood.

3. Testing Booth Development to Reduce Exposure of Medical Personnel
Medical personnel is at risk of infection when interacting with COVID-19 patients during testing. Testing requires use of large amount of PPE. We are developing a positive pressure booth that protects medical personnel during testing for deployment with the Baltimore City Health Department. The rapidly deployable booth could especially be used to help combat health disparities. Here is a video of the prototype booth that students and Lidia Al-Zogbi, Jiawei Ge, and engineer Kevin Aroom built: https://youtu.be/RQ94WcnCi3A

Margaret Scull
Computer, Mathematical and Natural Sciences (CMNS)/Cell Biology and Molecular Genetics
https://cbmg.umd.edu/faculty/margaretscull/

Project 1 (Mutli-PI: Scull / DeStefano) aims to generate novel, high-affinity aptamers to block SARS-CoV-2 entry into cells and to develop an in vitro platform to assess the efficacy of candidate SARS-CoV-2 entry inhibitors using well-differentiated cultures of human airway epithelium and SARS-CoV-2 pseudoparticles.

Project 2 (Multi-PI: Scull / Rosenberg) aims to use well-differentiated cultures of human airway epithelium and novel transcriptomics methods to define the host response to SARS-CoV-2 at single cell resolution.

Gregg Duncan
A. James Clark School of Engineering (ENGR)/Bioengineering
http://duncan.umd.edu

While scientists have long collected and studied bioaerosols to learn more about their impact on human health, none of the collection media used today in bioaerosol sampling has been specifically designed for the isolation of viruses. To address this, the Duncan lab are working to develop a bio-inspired hydrogel filtration media that mimics how the body’s own mucus “catches” inhaled virus particles and other pathogens in efforts to prevent infection. To accomplish this, we will leverage our expertise in respiratory bioengineering and fabrication of biomimetic materials to create a virus-specific capture media. One of our group’s main objectives is to develop wearable bio-aerosol sampler devices that can efficiently capture airborne SARS-COV-2 particles. The team’s hope is that hospital staff and other frontline workers could wear the devices to determine if they have been exposed to the virus, even before they exhibit symptoms.

Don DeVoe
A. James Clark School of Engineering (ENGR)/Mechanical Engineering
http://mml.umd.edu

Microfluidic-enabled lab-on-a-stick: rapid RT-PCR diagnostics for broad-scale surveillance

Derek Paley
A. James Clark School of Engineering (ENGR)/Maryland Robotics Center
https://robotics.umd.edu/

The COVID-19 crisis has presented a need for rapid disinfection of hospitals, businesses, schools, and homes. Disinfecting robots have already been developed and deployed in environments, such as hospitals, to meet needs when dealing with contagious diseases. While these robots have been specifically designed for large scale environments, there are drawbacks because they primarily use UV light, which does not disinfect areas outside the line-of-sight, or merely apply disinfecting solutions to floors. Solutions are required for disinfection robots that are easily implemented and scalable with the capability of tracing the same space as through airborne transmission of the virus. Therefore, we propose the deployment of a new robotic misting technology already developed for an industrial cleaning robot by Brain Corporation, a world leader in Robotic Floor Care with previous experience on biomedical detection, that will automatically detect and disinfect COVID-19 in interior spaces. This effort will involve three phases: (1) measuring coverage effectiveness in a room using fluorescein, (2) measuring disinfecting effectiveness using a target seeded with COVID-19, and (3) detection capability and automated assessment of residual threat.

Jeffrey Herrmann
A. James Clark School of Engineering (ENGR)/Mechanical Engineering and Institute for Systems Research
https://user.eng.umd.edu/~jwh2/jwh2.html

We created mathematical and simulation models of mass dispensing and vaccination clinics (also known as points of dispensing or PODs). We also developed decision support tools to help emergency preparedness planners design clinics that have enough capacity to serve residents quickly while avoiding unnecessary congestion. This research originally was developed with mass dispensing and vaccination clinics in mind. However, the principles behind the models and support tools are useful for those setting up emergency clinics to combat the COVID-19 pandemic. They are offered free of charge. For more information, see the website at https://isr.umd.edu/research/clinic-planning

Alok Bhargava
Public Policy (SPP)/Center for Global Sustainability

Social and economic impacts of COVID-19

George Belov
Agriculture and Natural Resources (AGNR)/VetMed
https://vetmed.umd.edu/people/faculty/dr-george-belov

Development of a vectored vaccine against COVID-19

Yanjin Zhang
Agriculture and Natural Resources (AGNR)/VetMed
https://vetmed.umd.edu/people/faculty/dr-yanjin-zhang

Rapid diagnosis, antiviral drug, molecular pathogenesis, and vaccine development

Zhengguo Xiao
Agriculture and Natural Resources (AGNR)/ANSC
https://agnr.umd.edu/about/directory/zhengguo-xiao

Immunology, CD8 T cells, activation

Wendy Peer
Agriculture and Natural Resources (AGNR)/ENST
https://enst.umd.edu/people/faculty/wendy-ann-peer

A plant-expressed saposin – ACE2-decoy fusion for SARS-CoV-2 Spike-glycoprotein binding Abstract: In the absence of effective and safe vaccines and for immunocompromised persons, therapies that limit viral infection and disease severity are essential. Current antivirals and other pharmaceuticals used off-label have shown limited efficacy. This proof-of-principle project will assess the potential value of a saposin-ACE2-decoy fusion that competitively binds the S-protein to block SARS-CoV-2 viral entry into cells. Here, the ACE2 – S binding motif will be fused to a plant saposin protein that is readily isolated in saposin/ sphingolipid nanodiscs. The long-term goal is to develop this as an effective therapeutic/ prophylactic. The S-protein has the S1-ACE2 binding domain and the S2 cell entry-enabling domain. The hypotheses tested here are 1) S1 nanonparticles bind to an ACE2 decoy without dissociation of S2, and 2) S2 nanoparticles bind the saposin domain linked to ACE2 decoy. The project will test the biologic in vitro to determine if in vivo testing is warranted. The proposed biologic is not a vaccine.

The relevant expertise of the PIs: ACE2 is an M family protease. The Peer lab has extensive expertise in M family proteases (Murphy et al., 2002; Peer et al., 2009; Hosein et al., 2010), including expression, purification, substrate specificity and site-directed mutagenesis. Dr. Peer has also worked on nanoparticles as co-PI on a USDA-NIFA funded project: Functionalized lipid nanoparticles for pathogen inactivation in cut leafy-greens and other minimally processed vegetables. The Spike protein is a glycoprotein. The Murphy lab is expert in membrane and glycoprotein biology focused on ATP-binding cassette subfamily B/ multi-drug resistant/ P-glycoproteins (MDR/PGP/ABCB) in sterol / sphingolipid domains (Geisler et al., 2005; Titapiwatanakun et al., 2009; Christie et al., 2011; Yang et al., 2013). The lab has pioneered the use of nanodiscs for membrane structure/function analysis in plants. The PIs have used the split-luciferase system to examine the transient interactions of chaperone and adaptor complex proteins that regulate cellular trafficking. Both Dr. Peer and Dr. Murphy are IBBR Associate Fellows with a long history of collaboration in adjoining labs on the 5th floor of Plant Sciences Building.

Eric Luedtke
School of Public Policy (SPP)

Local government adaptation to online meetings due to COVID lockdown and impacts on public participation

Catherine Worsnop
School of Public Policy (SPP)
https://spp.umd.edu/our-community/faculty-staff/catherine-z-worsnop

During the ongoing COVID-19 pandemic, a wider variety of cross-border measures (travel restrictions, visa bans, flight suspensions, border closures, etc) have been adopted by a higher number of countries than other major outbreaks of the recent past. Many of these measures go against World Health Organization (WHO) guidance and country commitments under WHO's International Health Regulations. This project undertakes a comprehensive accounting of what cross-border measures have been adopted during the COVID-19 pandemic and how this compares to past outbreaks; documents the range of public health, social, political, and economic impacts of these measures; examines the factors that influence government decisions to impose and relax such measures through a mixed methods approach; and finally, will create a decision tool to improve the evidence base for policy decisions around such measures during this and future outbreaks.

Ariel Bierbaum
Architecture, Planning, and Preservation (ARCH)/Urban Studies and Planning
https://www.arch.umd.edu/ursp/faculty/ariel-bierbaum

The purpose of our research is to capture educational leaders’ decision-making rationales and processes in response to COVID-19, specifically related to school operational status, delivery of technology-oriented instructional content, and social service provision to students, families, and the broader community. This project will offer new insights in the domain of school closures as a response to public health crises. By mapping rule configurations to on-the-ground impacts, we will be able to identify strategies and practices that are more or less successful in reducing/mitigating harm in future crises.

Our team of researchers from the University of Maryland Urban Studies and Planning Program and Department of Civil Engineering has extensive experience on issues of urban and rural cross-sector public policy and coordinated practice between school districts and other jurisdictions. We bring to bear comprehensive knowledge of state and local infrastructure policy and health and educational disparities. We have expertise in both qualitative and quantitative methods, enabling us to execute the mixed methods study. The PI is trained in urban and regional planning and a leading scholar on the nexus of planning and K-12 public education. The Co-PI is an expert in administering surveys during disaster and fast-moving events; her research team was the only group allowed to survey Camp Fire (CA, Nov. 2018) evacuees housed in Red Cross shelters immediately after evacuation.

Susan Moeller
Philip Merrill College of Journalism (JOUR)/Journalism + ICMPA
https://merrill.umd.edu/about-merrill/staff-faculty/susan-moeller/

Media, Life & Community during the COVID-19 Pandemic

Naeemul Hassan
Philip Merrill College of Journalism (JOUR)/Journalism
https://naeemulhassan.github.io/

Using Artificial Intelligence and Natural Language Processing to Bridge the Knowledge-Practice Gap in Risk and Healthcare Communication during COVID-19
Abstract

According to previous studies, there is a gap between how mass and social media are practicing crisis, risk, and healthcare communication and what scholars and expert practitioners advise based on supporting scientific evidence and risk communication best practices. We aim to explore state-of-the-art natural language processing models and artificial intelligence to assess how well COVID-19 news stories conform to best practices. If funded, our study can play a significant role in informing high-quality and accurate information to the general public during this COVID-19 pandemic and future disaster and emergency events.

Mass and social media play a central role in delivering crisis, risk, and healthcare information to the general public. The U.S. has a national objective to increase public information that follows crisis and emergency risk communication best practices (U.S. Department of Health and Human Services, n.d.). However, our previous studies find that there is a gap between how mass media are practicing crisis, risk, and healthcare communication and what scholars and expert practitioners advise based on supporting scientific evidence and risk communication guidelines (Tinker, 2010; Parmer, 2016). In one study of U.S. media, on average, slightly less than two (1.86) of the seven best practices were included in each news story covering an emergency event. One of our ongoing preliminary studies finds that only four out of ten of the best practice guidelines (Moynihan, 2000) are satisfied in an average healthcare news story. This gap between scientific knowledge of how effective risk communication should be done and how it is practiced has never been so critical as in the COVID-19 pandemic. A recent poll by Gallup (Mccarthy, 2020) shows that news media had the worst approval rating (44%) in the US among other institutions (e.g. CDC had 80%) in covering COVID-19. The negative perception of media coverage along with the growing amount of misinformation has made it difficult for the public to stay informed about accurate risk and healthcare information and make informed decisions (Lederer, 2020). So, it is very urgent that the quality of public information during this pandemic improves.

There is a large and increasing amount of COVID-19 related risk and healthcare information on the internet. It is humanly impossible to ensure the quality and credibility of every piece of health information in this ‘infodemic’. The long-term goal of our project is to use AI and NLP methods to close a knowledge-practice gap and assist mass media content creators in preparing effective and high-quality health information that conforms to science-based criteria. Towards that goal, we envision a transformative approach to build a scalable solution and form a multidisciplinary research project at the intersection of computer science, journalism, and public health communication based on three connected research activities under this proposal:

RA1: Gather Data about COVID-19 News Stories: We will collect COVID-19 news from U.S. based mainstream news outlets including print, broadcast, and social media. Some of the major sources need a subscription to access their data. In addition to using our in-house news crawling software, we will leverage available university resources such as Nexis Uni and the library as much as we can to gather data. In case data from an important media, source is not accessible, we will subscribe. This will give us a comprehensive dataset of COVID-19 related healthcare news.

RA2: Data Modeling and Annotation: We already curated a health-expert annotated dataset of 1,800 healthcare news articles from https://www.healthnewsreview.org. Each of these news stories is annotated by expert healthcare communicators and academicians following existing literature and scientific evidence (Moynihan, 2000). Preliminary classification models trained on these data show promising results. As annotating data with experts is a costly endeavor, we plan to use less expensive but more scalable and faster annotation options through Amazon Mechanical Turk (AMT).

RA3: Design and Evaluate Classification Model: We plan to use artificial intelligence and natural language processing to design, develop, and evaluate an algorithm that can automatically identify, assess and explain to what extent a news article is conforming to the best crisis, risk, and healthcare communication practice guidelines. In addition to using the best practice guidelines as features, we will identify linguistic features such as the presence of factual information, claims, and supporting/opposing evidence and use them as features. These features will allow us to identify if a healthcare claim in a news story is properly attributed to a credible source or not. Moreover, we plan to leverage attention and transformer-based language models to highlight for writers- while they are writing- the specific portions in their stories that breach best practice guidelines. We will also use these models to explain to readers why a story is of high or low quality.

Risk Management and Evaluation: We will take multiple steps to evaluate each of our research activities. In RA1, before starting the full-scale AMT based annotation, we will run a pilot AMT annotation to check the quality of the annotators using statistical measures such as inter-rater agreements. We will take multiple cautionary steps such as using ground-truth data, training annotators, and deploy spam detectors to control the quality of the full-scale annotation. In RA2, we will evaluate our feature modeling by consulting with public health researchers (in UMD School of Public Health) and healthcare communication experts (in UMD Journalism College). In RA3, we will use standard metrics such as precision, recall, f-measures to evaluate the prediction models.

A corpus of COVID-19 healthcare news with annotations of how much they conform to scientific evidence based best-practice guidelines. An automated program to assess risk and healthcare news quality and explain how a news story can be made more effective. A prototype web based dashboard that shows high-quality healthcare information related to COVID-19.

The COVID-19 pandemic puts the need for accurate and trustworthy risk and healthcare communication in high relief. People must accurately be informed of, understand, and evaluate the science of virus transmission and prevention so they can confidently take action to protect themselves. This project provides the opportunity to test how an automated algorithm can help content creators write risk messages that follow best practices; how algorithms can filter low-quality information, and the public can identify high-quality risk and healthcare information. If funded, our study can play a significant role in informing high-quality and accurate information to the general public during this COVID-19 pandemic. The outcomes will advance knowledge in many domains including data science, crisis and emergency risk communication, information credibility, and healthcare communication.

The primary innovation in this proposal is developing the ability to automatically assess the quality of healthcare news in terms of conformity to the best practice guidelines. This will have a short-term significant impact on improving the COVID-19 media coverage and informing the public with accurate information. Long term, the data and findings from the research will put UMD in a leading position to pursue external grants from NSF (e.g., RAPID, Cyber-Human Systems, Information and Intelligent Systems) and NIH. Moreover, tackling online misinformation, a more general problem, is one of the top priorities around the globe. Our research outcomes will contribute to misformation-related research proposals with UMD’s unique capability (top tier Computer Science, Information Studies, Journalism, and Public Health school/colleges.)

While most of the current COVID-19 dashboards are about numbers of infected people in different regions, none of them are providing high-quality news about prevention, treatment, and healthcare. We will mock-up a web-based dashboard to disseminate high-quality healthcare news. The contents in the dashboard will be evaluated by our algorithm developed in RA3. In addition, we will disseminate our findings through scholarly venues of computer science, human-computer interaction, and public health domains. The annotated data will also be made available for research purposes through the UMD Digital Repository (DRUM) facility.

Dr. Hassan, a computer scientist by training, is an expert in computational journalism. His research areas are related to data mining, natural language processing, and social media analysis. His recent research projects involve automated fact-checking (Hassan, 2017), credible health information (Dhoju, 2019), and misinformation detection (Rony, 2017). He has built computational technologies (e.g., BaitBuster, ClaimBuster) that have been used by professional journalists to automate fact-checking and identify misinformation.
Dr. Baur is an internationally-recognized expert in health communication and health literacy. She is the Endowed Chair and Director of the UMD Horowitz Center for Health Literacy. Her research relates to making health information understandable to different audiences, explaining health risks in actionable formats, and using digital technologies to deliver health information. While at the U.S. Centers for Disease Control and Prevention (CDC), she designed the study and led the team for the Healthy People 2020 crisis and emergency risk communication objective that forms a core part of the proposed COVID-19 project.

Sarah Oates
Philip Merrill College of Journalism/ Journalism
https://merrill.umd.edu/about-merrill/staff-faculty/sarah-oates/

Measuring how COVID-19 disinformation spreads in social and traditional media by using human analysis combined with artificial intelligence.

Wolfgang Losert
Computer, Mathematical and Natural Sciences (CMNS)/IPST
https://ireap.umd.edu/losertlab/

CT scan image analysis

Jonathan Dinman
Computer, Mathematical and Natural Sciences (CMNS)/Cell Biology and Molecular Genetics
https://cbmg.umd.edu/faculty/jonathand-dinman/

SARS-CoV-2, the virus that causes COVID-19, uses a molecular mechanism called Programmed -1 Ribosomal Frameshifting (-1 PRF) as a "switch" to transition from expression of "early" genes (involved in host cell takeover and immune suppression) to "middle" genes (involved in genome replication and subgenomic mRNA expression). We previously showed using many viruses (a yeast virus, HIV-1, a deadly Alphavirus, and the original SARS-CoV) that altering the efficiency of -1 PRF significantly impacts virus replication and disease severity. These findings identify -1 PRF as a target for therapeutic intervention. We are currently finishing the molecular genetics characterization of the SARS-CoV-2 -1 PRF signal. Our next steps will be to 1) characterize this element at the biophysical level, 2) use our cell based reporter system to collaborate with other groups in high throughput screens to identify anti-frameshifting small molecules, and 3) use molecular genetics approaches to characterize the effects of -1 PRF signal mutations on SARS-CoV-2 replication and pathology using a recombinant viral system and mouse model.

Jen Golbeck
Information Studies (INFO)
http://www.cs.umd.edu/~golbeck

Data analytics, working on facebook project with survey methodology

Doug Lombardi
Education (EDUC) / Human Development and Quantitative Methodology
https://sciencelearning.umd.edu/

The World Health Organization recently declared an outbreak of a novel (new) coronavirus disease, commonly called COVID-19. In light of the serious threat to public health posed by this recent outbreak, my lab is developing ways to facilitate learning and teaching about virus transmission and prevention. We specifically hope to design effective instructional strategies to support teachers and their students to engage in reasoned evaluation of information sources and knowledge claims, particularly related to misinformation and problematic claims surrounding providence and transmission of viruses. We also want to investigate instructional scaffolds that will help students develop ways they might take action to mitigate the threats posed by misinformation and problematic claims about virus transmission in their communities. Our fundamental research question is: What are the features of instructional scaffolds that support students to develop critical-analytic thinking, evidence-based reasoning, and core disciplinary knowledge about virus transmission and prevention, and that facilitate problem solving abilities to equitably protect public health?

Cixin Wang
Education (EDUC)/Counseling, Higher Education, & Special Education
https://education.umd.edu/research-college/labs/bullying-prevention-and-mental-health-promotion-lab

Influences of the Coronavirus (COVID-19) Outbreak on Racial Discrimination, Identity Development and Socialization among Chinese American families.

The current 2019-nCoV outbreak has created a unique, urgent, and time-limited context to examine intensified discrimination targeting racial minority Chinese families in America, overlaying an enduring context of chronic and systemic racism. Using mixed-method and interdisciplinary approaches, we will study multiple forms of racial/ethnic discrimination and their subsequent impact on the identity development and adjustment of Chinese American parents and children, and parents’ reactive racial/ethnic socialization practices in three age groups (4-7 years old, 8-11 years old, and 12-15 year old) at the early stages of the outbreak and 6 months later. Protective factors for adjustment in parents and children will also be identified. In addition, we will analyze large scale texts of outbreak-related social media (Twitter) posts to account for how public opinion, social anxiety , and discriminatory attitudes evolve with the peaking and fading of this epidemic and provide objective indicators of the larger public social discourse climate across the year.

Gregg Vanderheiden
Information Studies (INFO)/Trace R&D Center
http://trace.umd.edu

Developing an operating system extension that will make it easier for elders and others who have trouble using computers to be able to use them for communication, information, food, medical, community connections and other things that they might ordinarily do through other means but can't due to COVID-19.

Kenneth Rubin
Education (EDUC)/HDQM

The COVID-19 crisis is having an enormous economic, physical, and psychological effect on families. And it is likely that these effects vary from family-to-family, from one venue within North America to another, and from one country to another. To examine the effects of the pandemic on family, parent, and child functioning, we propose to recruit 125-150 families in each of 11 cross-national and international sites. Focal children in these families will range in age between 4-and 5 years. Parents of preschoolers will be assessed in a baseline set of questionnaires measuring COVID-related stress, parental well-being, daily stressors, the availability of social support, parenting behaviors, and children’s emotional and behavioral regulation. In order to examine the ongoing processes of risk and resilience, follow-up data will be collected on these constructs monthly for six consecutive months.

Susan Winter
Information Studies (INFO)/CASCI

We are investigating how to better address the information needs of independent businesses during regular operations and during the COVID-19 emergency. We focus on different kinds of information and the role of business support organizations (including public libraries) as sources of useful information.

Jing Liu
Education (EDUC)/TLPL (new hire staring Fall 2020)
https://www.annenberginstitute.org/people/jing-liu

With 55 million students in the United States out of school due to the COVID-19 pandemic, education systems are scrambling to meet the needs of schools and families, including planning how best to approach instruction in the fall given students may be farther behind than in a typical year. Yet, education leaders have little data on how much learning has been impacted by school closures. While the COVID-19 learning interruptions are unprecedented in modern times, existing research on the impacts of missing school (due to absenteeism, regular summer breaks, and school closures) on learning can nonetheless inform projections of potential learning loss due to the pandemic. In this study, we produce a series of projections of COVID-19-related learning loss and its potential effect on test scores in the 2020-21 school year based on (a) estimates from prior literature and (b) analyses of typical summer learning patterns of five million students. Under these projections, students are likely to return in fall 2020 with approximately 63-68% of the learning gains in reading relative to a typical school year and with 37-50% of the learning gains in math. However, we estimate that losing ground during the COVID-19 school closures would not be universal, with the top third of students potentially making gains in reading. Thus, in preparing for fall 2020, educators will likely need to consider ways to support students who are academically behind and further differentiate instruction.

Paul Gold
Education (EDUC)/Counseling, Higher Education, Special Education
https://education.umd.edu/directory/paul-gold

Tracking SARS-CoV-2 / COVID-19 Trends by Time, Region, Covariates (co-morbidities, demographics, public policy [e.g., mitigation strategies, testing, contact tracing])

Ruthanna Gordon
Applied Research Laboratory for Intelligence and Security (ARLIS)

We are studying the origins, patterns of sharing, and impacts of misinformation related to the COVID-19 pandemic. We are particularly interested in characterizing ongoing misleading narratives, and examining information spread in multilingual communities.

Adele Robinson
Public Policy (SPP)
www.spp.umd.ed/pizzigati

Sun Young Lee
Arts and Humanities (ARHU))/Communication
https://www.comm.umd.edu/people/faculty/SunLee

The project examines how companies are responding to the pandemic as part of their corporate social responsibility (CSR) activities and the effects of these CSR activities on mitigating the outbreak’s impact on their stakeholders and on U.S. society at large. The researcher has expertise in CSR strategies and CSR communication. Her previous projects include examining the effects of CSR in a crisis context and the effects of various CSR strategies on the public’s memory, perceptions of the messages, and behavioral engagement—specifically, social media engagement and prosocial outcomes

Ronald Yaros
Philip Merrill College of Journalism (JOUR)
https://merrill.umd.edu/about-merrill/staff-faculty/ron-yaros/

Measuring the Public’s Information Sources, Knowledge, Risk Assessment and Trust in Government following the first U.S. death from the coronavirus.
This national longitudinal survey study, which began February 29, 2020 will continue through the summer to measure the public sentiments, actions, and trust in government as the eCOVID-19 health crisis evolves in the U.S. Variables measured with a diverse national sample of 750 participants every two weeks include the public’s perceived risk factors of COVID-19, changes in precautionary actions taken as the number of cases changes, sources for information about the virus, interpretation of the latest CDC statements and if/how these factors affect the public’s level of trust in government agencies and White House officials.

Arefeh Nasri
Architecture, Planning, and Preservation (ARCH)/National Center for Smart Growth
http://www.umdsmartgrowth.org/people/arefeh-a-nasri/

We have designed a survey to investigate the influence of the pandemic and stay-at-home orders nationwide on the way people travel to meet their essential needs, do their routine daily exercises, and get to work—if employed in an essential service sector. Monitoring and analysis of the changes in travel behavior and the level of physical activity would help for a more efficient planning and management in the future.

J. Carson Smith
School of Public Health (SPH)/Kinesiology
https://e4bh.com/

"Manuscript in preparation for submission for publication in American Journal of Geriatric Psychiatry. IRB Protocol, Mood and Activity during the COVID-19 Pandemic Mood and Activity During the COVID-19 Pandemic
We examined whether the amount and intensity of physical activity affect depression and anxiety symptoms in older adults living in the United States and Canada who are under the current social distancing guidelines (SDG) for the COVID-19 pandemic. Older adults over the age of 50 complete an online Qualtrics survey. The survey contained questions pertaining to a participant’s basic demographic information, their current health status, the impact of the current SDG on their subjective state of physical and social isolation, the amount and intensity of physical activity they perform, changes to their sleep schedules, and information about their depression and anxiety symptoms. We expect that older adults performing greater levels of physical activity and less sedentary behavior will experience less anxiety and depression like symptoms during the current period of adherence to COVID-19 related SDG. Understanding how physical activity may alleviate the negative mental health impacts of social distancing and isolation due to the COVID-19 pandemic will provide initial evidence for ways that older adults can try to best cope during these challenging times.

Michael Hanmer
Behavioral and Social Sciences (BSOS)/GVPT and CDCE
https://gvpt.umd.edu/facultyprofile/hanmer/michael

Public opinion on government response, health, public policies for business and individuals, elections

James Butler III
School of Public Health (SPH)/Behavioral and Community Health
https://sph.umd.edu/department/bch/bio/18791

COVID-19: paying attention to cigarette smoking and housing challenges and solutions. Certain populations (e.g., African Americans) who live in public housing often do not have access to vital features and services. These are areas where virus-related risks may be higher. Also, as these individuals have a higher smoking prevalence, it remains to be examined whether or not the virus exacerbates smoking and the risk of becoming COVID-19 positive due to smoking in their homes or outside in close proximity with others. I have spent over 20 years engaging public housing residents in community engaged smoking cessation research.

Jessica Fish
School of Public Health (SPH)/Family Science
https://sph.umd.edu/people/jessica-fishalso https://sph.umd.edu/laboratory-resources/sexual-orientation-gender-identity-and-health-sogi-health-lab

We propose to examine the impacts of COVID-19 and states’ and local governments’ social distancing efforts on behavior, time spent with others, use of technology, and mental and physical wellbeing. The pandemic’s negative consequences to public health and the economy has received much attention in public and academic spheres. Yet, we know little about the social consequences of COVID-19. To address this underexamined area, we leverage data from several hundred respondents’ daily time use before the pandemic to create a natural experiment that isolates the effects of the pandemic on changes in behavior. In addition, we will recruit additional respondents and follow-up with all respondents after the pandemic subsides. Using this approach, we will have data on people’s social behaviors before, during, and after the pandemic. We will field a survey to collect relevant information respondents’ daily behavior and the context for those behaviors. The survey will collect data on sociodemographics, typical sleep, work, and exercise patterns as well as typical approaches to division of labor for housework and carework. In examining changes in behavior due to the pandemic, we can see if distinct clusters of social behaviors emerge and whether these types of behaviors relate to changes in mental health. We are particularly interested in exploring how the effects of COVID-19 varies by gender, sexuality, family structure (parental and marital status), race/ethnicity, and immigrant status–all key sociodemographic characteristics that affect time use and wellbeing. In doing so, we can provide evidence-based recommendations to address the social consequences of the unfolding pandemic.

Nathan Dietz
School of Public Health (SPH)/Do Good Institute

It's not directly COVID-19 related, but on May 20, we are publishing a research brief about the surge in civic activity (performing volunteer work, giving to charity, working with neighbors on a community problem, and attending public meetings where community affairs are discussed) following crises. We are using data from the Current Population Survey to study the rise in civic engagement in New York following the 9/11 attacks, in New Orleans during Hurricane Katrina, and in both places (as well as nationwide) during the Great Recession. Following all three events, the surge in activity dissipated and returned to pre-crisis levels, which suggests that the charitable sector needs to work to maintain the increased interest in pro-civic activities caused by a crisis.

Jessica Fish
School of Public Health (SPH)/Family Science
https://sph.umd.edu/laboratory-resources/sexual-orientation-gender-identity-and-health-sogi-health-lab

Using data from internet chat-based support groups for LGBTQ youth, we are investigating how the COVID-19 pandemic is impacting the social life and mental health of LGBTQ youth.

John Salerno
School of Public Health (SPH)/Behavioral and Community Health, University of Maryland Prevention Research Center
https://sph.umd.edu/people/john-salerno

Online survey examining mental health, pandemic stress, and adverse experiences among LGBTQ College Students in the U.S.

Lyle Isaacs
Computer, Mathematical and Natural Sciences (CMNS)/Chemistry and Biochemistry
http://www.chem.umd.edu/faculty-staff-directory/facultydirectory/lyle-isaacs

Compound testing

Gary LaFree
Behavioral and Social Sciences (BSOS)/CCJS
https://ccjs.umd.edu/

We are working on examining impact of COVID 19 on crime rates in Baltimore.

Gary LaFree
Behavioral and Social Sciences (BSOS)/CCJS/START
https://ccjs.umd.edu/

We are planning to examine the world-wide impact of COVID 19 on terrorism attacks and fatalities.

Volker Briken
Computer, Mathematical and Natural Sciences (CMNS)/CBMG

The Briken and Scull labs will study the effect of SARS-CoV-2 infection on the host immune response in the context of co-infection with the human lung pathogen Mycobacterium tuberculosis.

Rob Sprinkle
School of Public Policy (SPP)

Robin Puett
School of Public Health (SPH)/MIEH

Various projects examining chronic health conditions and COVID19-related risk as well as behavioral interventions aimed at stress resilience among this subpopulation

James Yorke
Computer, Mathematical and Natural Sciences (CMNS)/IPST, Physics, Math

I have worked with models of several communicable viral human diseases.

Samantha Chiu
Behavioral and Social Sciences (BSOS)/Joint Program in Survey Methodology
https://jpsm.umd.edu/

Worldwide (130+ countries/55+ languages) COVID19 Symptoms Study with Facebook: The aim of this project is to implement a survey where people will be able to report symptoms as part of the effort to estimate the impact of COVID-19. The contributions will utilize the Facebook social media platform to recruit participants to provide information which will address issues on the lack of testing capacity, lack of data to identify hot-spots of COVID-19 and trace contacts, lack of data to guide policy decisions and to allocate resources. This project will advance the understanding of the effects of COVID-19 on economic and mental health outcomes of the US and Worldwide general population to guide efforts for economic and psychological response

Samantha Chiu
Behavioral and Social Sciences (BSOS)/Joint Program in Survey Methodology
https://jpsm.umd.edu/

Evaluating the Impact of COVID-19 on Labor Market, Social, and Mental Health Outcomes: The primary objective of this project is to understand the short and long-term economic, social and mental health toll of COVID-19, and to collect robust data during the outbreak and its progression to track the impact of this global pandemic. Data collection for this project (1) extends a baseline study within the COVID-19 context from the Understanding America Study (UAS), (2) contributes to an international study with similar questions in Denmark, Netherlands, Switzerland, and Germany and Australia, and (3) furthers methodological component to include a mode of data collection on Facebook. This project will advance the understanding of the effects of COVID-19 on economic and mental health outcomes of the US general population to guide efforts for economic and psychological response.

Andrew Fellows
Information Studies (INFO)/Campus Community Connection

Ongoing engagement with local governments responding to COVID-19

Sandra Quinn
Public Health (SPH)/Department of Family Science and Center for Health Equity
https://sph.umd.edu/department/fmsc/bio/18882

We are examining the narratives on COVID-19 present in the twitter accounts of known anti-vaccine groups and individuals.

Tess Wood
Arts and Humanities (ARHU)/Language Science Center
https://languagescience.umd.edu/users/ewood1

Investigating the impact of language choice on the spread of COVID-related health information spread (and particularly misinformation) on social media for speakers in multilingual communities.

Yueming (Lucy) Qiu
School of Public Policy (SPP)
https://sites.google.com/site/yueminglucyqiu/home

The aim of this project is to advance national health and welfare through investigating the impact of the coronavirus pandemic on electricity demand.

Brian Pierce
Computer, Mathematical and Natural Sciences (CMNS)/Department of Cell Biology and Molecular Genetics, Institute for Bioscience and Biotechnology Research
https://piercelab.ibbr.umd.edu

"My laboratory is performing computational structural biology research on SARS-CoV-2, with a focus on the spike glycoprotein, which is targeted by neutralizing antibodies and is the subject of vaccine design efforts. Our work includes structure-based design of monoclonal antibodies, structure-based design of the spike glycoprotein, and modeling of spike dynamics and the impact of glycosylation and viral variants. To facilitate this research, and to provide a resource for the research community, we developed an online database, named CoV3D: https://cov3d.ibbr.umd.edu

CoV3D contains experimentally determined structures of the spike glycoprotein and its interactions with receptors and antibodies, and also contains structures of other coronavirus proteins, updated on a weekly basis. It also includes browser-based molecular viewers and downloadable files. "

Naeemul Hassan
Philip Merrill College of Journalism (JOUR)/Journalism
naeemulhassan.info

Wendy Peer
Agriculture and Natural Resources (AGNR)/ENST, IBBR, ABC
https://agnr.umd.edu/about/directory/wendy-peer
also http://www.wendyannpeer.com/

Development of a therapeutic based on the mechanisms of Spike recognition and entry into cells. Relevant expertise: M family protease characterization and synthetic biology (hACE2 is an M family protease). P-glycoprotein and membrane biology (Spike is a glycoprotein that fuses with the membrane). Synthetic biology. Natural products chemistry.

Yancey Orr
Behavioral and Social Sciences (BSOS)/The Department of Anthropology
https://anth.umd.edu/facultyprofile/orr/yancey

Cultural perceptions of zoonotic disease. Religious perspectives on animals, disease and hygiene. Links between environmental and social health. Diseases in Southeast Asia and North America.

Jessica Vitak
Information Studies (INFO)
https://pearl.umd.edu

Technological tools to monitor the spread of COVID-19 may play an important role in reducing risk, but they also raise privacy concerns. I can offer insights into the risks associated with data collection related to COVID-19 and offer recommendations for those looking into collecting/analyzing this data. I have two articles (one in press and one in preparation) that consider the risks associated with using contact tracing apps and some of the barriers that might prevent widespread adoption.

Toby Egan
Public Policy (SPP)/School of Public Policy AND Robert H. Smith School of Business--Management and Organization
https://spp.umd.edu/our-community/faculty-staff/toby-egan

Since February, a cross-sector research team of emergency department physicians, medical consulting firm leaders, and university researchers worked with 18 (now over 100) US hospitals to design, develop and implement a COVID-19 mitigation strategy aimed at reducing nosocomial and community spread. I am co-author on the following article published July 30, 2020 in the "Journal of Microbiology, Immunology and Infection".
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7390767/.
I am now the leading the launch of two comparative international studies with physicians and university researchers/leaders in two of the 'model countries' for COVID-19 mitigation--South Korea and Taiwan. Our findings thus far and desired focus moving forward is to not only refine our understanding of 'best practices' for hospital mitigation of COVID-19, but to extend comparative International findings to (1) public policy; (2) leadership/public administration; and (3) implementation of mitigation practices in other facilities or community settings.

Jeffery Klauda
A. James Clark School of Engineering (ENGR)/Chemical and Biomolecular Engineering
https://user.eng.umd.edu/~jbklauda/

Our lab has focused on using our computational tools to understand the virus mechanism of infection and ways to potentially inhibit viral replication and develop antibodies. We have a NSF-supported project (https://nsf.gov/awardsearch/showAward?AWD_ID=2029900&HistoricalAwards=false) in collaboration with Dr. Bryan Berger at UVA studying two accessory proteins (ORF7a and ORF7b) and their importance to viral infection. The goal here is understand how these protein dimerize and how inhibiting dimer formation might be a pathway to develop a therapy. We have also done research in collaboration with NIH on ACE2 binding to the spike protein of SARS-CoV-2 and how natural mutations influence this interaction. This work also has focused on the glycosylation of the spike protein and what regions are ideal for developing antibodies for vaccines.