Seed-Funded COVID-19 Projects

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On March 3, the Huck Institutes launched a rapid-response internal call-for-proposals across the university to address the emerging outbreak, with support from the Materials Research Institute, Social Sciences Institute, Institutes for Energy and the Environment, and the Institute for Computational and Data Science. 

Over the course of five weeks, units across Penn State stepped up to assist. To date, more than 135 faculty members in 48 research teams from across 10 colleges at Penn State have been granted $2.4 million in seed-funding to initiate their vitally important work. 

The projects span six core areas: Diagnostics and Detection, Therapeutics and Vaccines, Transmission-blocking Interventions, Social Sciences, Cohort Studies, and Predictive Modeling.

You can help support Penn State’s COVID-19 research initiatives. Learn more here.

Diagnostics and Detection

Timely and accurate determination of where the virus is and where it has been are critical to global efforts to prevent and treat infectious diseases, including COVID-19. These projects aim to advance the creation, testing, and distribution of innovative methods for rapid and accurate virus detection in patients, people who are not sick, and in the environment.  

PI: Weihua Guan (Electrical Engineering and Computer Science)

Collaborators: Yusheng Zhu

Guan and his team are developing integrated USB-stick-sized microfluidic devices for the quantitative detection of SARS-CoV-2 target nucleic acids in biological samples using loop-mediated isothermal amplification assays. If successful, they hope to be able to fully-integrate pre-analytical clinical sample processing, with target amplification, signal detection in a disposable device.

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PI: Yin-Ting Yeh (Physics)

Collaborators: Huaguang Lu, Joshua A. Robinson, Sharon Huang, Shengxi Huang, Elodie Ghedin, Mauricio Terrones

Yeh, Robinson, Huang, Lu, Huang, Ghedin, and Terrones are combining carbon-nanotube based virus enrichment platforms with 2D-metal enhanced Raman spectroscopy for rapid (in minutes) amplification- and label-free detection and characterization of SARS-CoV-2 with high sensitivity. They hope to accomplish this by leveraging their considerable expertise in application of novel materials for the detection, analysis, and separation of biologically important compounds, macromolecules including viruses.

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PI: Yong Wang (Biomedical Engineering)

Wang and his team seek to integrate magnetic bead-based mRNA-DNA recognition, enzyme-free DNA polymerization for the ultra-sensitive detection of SARS-CoV-2 RNA using a portable handheld fluorometer. If successful, the approach will enable the rapid and sensitive detection of SARS-CoV-2 without the use of enzymes, antibodies or complicated instrumentation.

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PI: Paul Cremer (Chemistry)

Cremer’s group is designing and building an inexpensive, real-time, microfluidic sensor to continuously monitor for SARS-CoV-2 in environmental settings. They plan to achieve this by combining receptor-based capture of viral targets in microfluidic flow cells with real-time-detection of fluorescent signals using inexpensive lasers.

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PI: Zhiwen Liu (Electrical Engineering)

Collaborators: Shengxi Huang

Raman spectroscopy, by probing “fingerprint-like” molecular vibrational response, is a proven tool for rapid detection of viruses such as influenza viruses and HIV. However, Raman signal is typically very weak due to the rather small Raman scattering cross-section. Liu and Huang will build a low-cost hand-held Raman sensor, by matched Raman sensing and amplification via the use of a Raman spectroscopic template.

PI: Steven Hicks (General Pediatrics)

Collaborators: Scott Halstead, Judie Ann Hawrylak

Given the projected strain on healthcare resources, it would be helpful to be able to predict which patients will require escalation of care before it becomes critically necessary. Hicks and colleagues propose that molecular characterization of the host response to SARS-CoV-2 will lead to identification of one or more salivary biomarkers that could inform prognosis in patients with COVID-19.

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Therapeutics and Vaccines

To prevent the contraction and mitigate the effects of the novel coronavirus, our research teams are investigating targeted treatments for patients who test positive for COVID-19 and exploring innovative approaches to vaccine development.

PI: Nikolay Dokholyan (Pharmacology)

Dokholyan’s team plans to design as well as structurally and biophysically characterize SARS-CoV-2 immunogens for evaluation as candidate vaccines. They plan to accomplish this by using state-of-the-art computational and protein engineering methods to design and identify SARS-CoV-2 vaccine candidate improved immunogenicity and cross-reactivity against other coronaviruses.

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PI: Joyce Jose (Biochemistry & Molecular Biology)

Jose and her team seek to identify small molecule inhibitors by targeting the SARS-CoV-2 3C-like serine protease (3CLpro) for the identification of viral inhibitors in tissue culture models. In addition, Jose seeks to generate reverse genetic systems and virus like particles that consist of the SARS-CoV-2 spike, envelope, membrane, and nucleocapsid proteins for the generation and evaluation of vaccine and antiviral candidates.

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PI: Scott Halstead (Pediatric Critical Care)

Collaborators: Deb Kelly, Gail Matters, James H. Adair

Treating COVID-19 patients with acute respiratory distress syndrome (ARDS) is particularly difficult as the disease can present with symptoms of both hyperinflammation or hypoinflammation. Dr. Halstead’s research is designed to optimize the delivery of the immune cytokine GM-CSF directly to the lungs to test its effectiveness in clinical trials for COVID-19 patients. Effective, deep lung medication achieved via this approach is designed to ease the disease burden during treatment by jumpstarting immune cells to combat secondary bacterial infections and inflammation.

PI: Susan Hafenstein (Biochemistry & Molecular Biology)

Collaborators: Colin Parrish

Data on the COVID-19 and related viruses indicate that interactions between the viral S protein and the ACE2 receptor variants in different hosts are important for binding and infection. Dr. Hafenstein’s research will examine the structures of the S glycoproteins from different coronaviruses, their interactions with the ACE2 receptors from different hosts, as well as their interactions with different antibodies. They will analyze complex and variable structures at high resolution to define their functional interactions using structure-based protein engineering to model evolutionary variation of the viruses as they spread and move between hosts.

PI: Scott Medina (Biomedical Engineering)

Collaborators: Angela Pannier

DNA based vaccines have not been widely adopted due to their rapid degradation by tissue nucleases, limited uptake into host cells, and poor expression efficiency. Medina and colleagues propose to developed a biomimetic, gel-like nanoparticle aerosol - or ‘aerogel’ – designed to comprehensively addresses these barriers for a SARS-2 vaccine.

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PI: Pia Abel-zur Wiesch (Biology)

Collaborators: Jessica Conway

Currently, the most promising anti-viral drug for COVID-19 is remdesivir. However, optimal dosing regimens have yet to be identified. Abel-zur Wiesch and Conway will use PK and PD modelling to rationally identify optimal dosing regimens (for instance, is high infrequent or constant dosing preferable; when should dosing start and stop?). To do so, they will merge models of viral dynamics with conventional PK models to generate superior PD understanding.

PI: Jean-Paul Armache (Biochemistry & Molecular Biology)

In SARS-CoV-2, a highly conserved non-structural ribosome-binding protein is thought to be responsible for inhibiting host protein synthesis. It may also be responsible for activating pathways leading to the cytokine storm causing severe illness in patients. Armache aims to generate high-resolution structures of the protein complexes; The structures will show the available interacting surfaces, as well as modes of interactions and dynamics, and thus lead to the identification of viable drug candidates.

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PI: Scott Lindner (Biochemistry & Molecular Biology) and Troy Sutton (Veterinary & Biomedical Sciences)

Lindner will engineer nanocage vaccines with scaffolded Spike protein variants, in the presence/absence of a proteinaceous intranasal adjuvants. Sutton will test this vaccine candidate in ferrets infected with SARS-CoV-2.

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PI: Yong Wang (Biomedical Engineering)

Collaborators: Troy Sutton

This project will develop a delivery mechanism to increase lung residency duration of mesenchymal stem cells that suppress cytokine storms induced by SARS-CoV-2. Better controlling cytokine storms may alleviate the most deadly and medically burdensome feature of the disease.

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PI: Dr. David Rabago (Family and Community Medicine)

Collaborators: Dr. Robert Lennon, Dr. Lauren Jodi Van Scoy, Dr. Judy Howrylak, Dr. Jason Croad, Dr. Anne Darby, and Erin McGinley

A randomized controlled trial assessing adjunctive osteopathic manipulation therapy (OMT) in elderly patients with pneumonia reported that those who received OMT had significant reductions in the length of stay, duration of antibiotics, rates of respiratory failure and death. PI Rabago and colleagues will assess whether OMT is effective as an adjunctive therapy for Covid-19 patients with respiratory distress, the most common cause of death from the novel coronavirus (SARS-CoV-2).

PI: Joseph Reese (Biochemistry & Molecular Biology)

Collaborators: Troy Sutton, Scott Lindner, Joyce Jose

summary: The ability to carry out reverse genetics on many large RNA viruses, including SARS-CoV-2 , is severely hampered by the size of their genomes and instability in traditional cloning hosts such as E. coli. People have generally turned to using model viruses or replicons, which are not exact matches to the pathogenic forms. Budding yeast is a powerful genetic system that can quick genome assembly of large, difficult to clone DNAs. This project will establish a system to assemble SARS-CoV-2 genomes to be used to conduct reverse genetics on the virus to study the function of the virus and help design new treatments such as vaccines.

Transmission-Blocking Interventions

In order to slow the spread of COVID-19, communities must take steps to reduce and prevent disease transmission. While some transmission-blocking techniques are well known—such as frequent handwashing or physical distancing—other potentially effective strategies have not been tested or disseminated.

PI: Troy Sutton (Veterinary & Biomedical Sciences)

Dr. Sutton’s research will develop a much-needed animal model to understand transmission and develop countermeasures against the COVID-19 virus. Dr. Sutton has previously worked with MERS coronavirus (MERS-CoV) and on the animal models of coronaviruses including a rabbit model of MERS-CoV. This research will evaluate the ferret as a model of COVID-19 transmission and vaccine-mediated protection. Results from this proposal will provide key knowledge for development of a COVID-19 vaccine.

PI: Craig Meyers (Microbiology & Immunology)

Collaborators: David Goldenberg, Rena Kass, Samina Alam

Spread of COVID-19 is primarily through respiratory droplets that either are directly inhaled or contaminate surfaces to be later transferred to hands and then faces of uninfected individuals. To reduce the spread of COVID-19, Dr. Meyer’s research team will determine the efficacy of the use of disinfectants and pharyngeal rinses to inactivate and/or hinder transmission. Once identified, disinfectants or rinses with efficacy in vitro will be tested for efficacy in a ferret model for COVID-19 infection.

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PI: William Bahnfleth (Architectural Engineering), Suresh Kuchipudi (Veterinary & Biomedical Sciences)

Collaborators: James Freihaut, Donghyun Rim, Richard Mistrick

This project will characterize the ability of optical radiation at 254 nm and 365 nm (safer to humans) to disinfect and reduce transmission of coronaviruses. Results will be used in simulations that draw on both literature review and experimental findings.

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PI: Howie Weiss (Biology), Miriam Freedman (Chemistry)

This project will develop capabilities to reliably quantify SARS-CoV-2 aerosol advection and deposition in built environments. This will be accomplished by investigating strategies to efficiently detect, sample, and count released nanoparticles.

PI: Tak Sing Wong (Mechanical Engineering)

Collaborators: Pak Kin Wong

This proposal will establish an effective hand sanitization technology using a surfactant-stabilized self-healing liquid film. This technology not only can serve as a rapid and effective disease control measure for hospitals and public areas in the developed world, but also will benefit ~4 billion people that are under severe water scarcity globally.

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Social Sciences

Beyond immediate health impacts, our research teams are studying how the COVID-19 pandemic has shaped healthcare messaging, public policy, mental health, and more, and in turn how COVID-related messaging and public policy can be improved. These projects address the broader impacts of this crisis and aim to deliver valuable recommendations across the public sectors.

PI: Robert Lennon (Family and Community Medicine)

Collaborators: Aleksandra Zgierska, Bethany Snyder, Courtney Lennon, David Rabago, Emily Wasserman, Erin McGinley, Lauren Jodi van Scoy, Mack Ruffin IV, Vernon Chinchilli

Effective communication is a critical component of managing pandemic outbreaks. Dr. Lennon’s research will understand how best to relay effective messages and the impact of current information campaigns on educating the public and healthcare workers on what they should or should not do to help contain the spread of COVID-19. This project seeks to fill this knowledge gap by identifying, analyzing, and remediating COVID-19 misunderstandings as the first step in addressing communication shortfalls, improving compliance with recommendations, and thus minimizing further public risk, unnecessary economic burdens, and morbidity, mortality, resulting from the ongoing COVID-19 outbreak. This work is of urgent importance because public misunderstanding can drive policy decisions that increase patient risk to infectious disease outbreaks.

The research team is collaborating with the College of Healthcare Information Management Executives (CHIME), which built the technology infrastructure for the survey and is distributing the survey link globally. CHIME has members in 56 countries and 11 international chapters as well as ties with numerous organizations in the U.S. and overseas.

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PI: J. Taylor Scott (Prevention Research Center)

Collaborators: Cagla Giray, Daniel Max Crowley, Elizabeth Long

This project will utilize an already-established Research-to-Policy Collaboration (RPC) established by Drs. Taylor Scott and Crowley that consists of a team of RPC fellows in Washington, DC and major research sites across the country in collaboration with Penn State’s Office of Government and Community Relations. This project will build on the infrastructure of the RPC to respond to legislators’ needs for research related to social and behavioral policy responses to the coronavirus.

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PI: Amit Sharma (Hospitality Management)

Collaborators: Breffni Noone, Seoki Lee, Heyao Yu, Dr. Donna Quadri-Felitti

Dr. Sharma and his team will develop and disseminate rapid response strategies for restaurants and the food service industry to manage and minimize the negative economic impact of the COVID-19 pandemic. Specifically, the project will focus on the development of profit optimization strategies under demand and price constraints; identification of strategies to reengineer and enhance business processes in the context of surplus labor; and the creation of messaging targeted at alleviating customers’ concerns about food safety, dining in restaurants, and food deliveries.

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PI: Armen Kemanian (Plant Science)

Collaborators: Alexander Hristov, Heather Karsten, John Frazier Tooker, Erica A. H. Smithwick, Douglas H. Wrenn, Constantino Lagoa, Lorne Leonard, Francesco Di Gioia

Dr. Kemanian and his team will assess the impact of Covid-19 on Pennsylvania’s agriculture and the food supply chain, and deploy tools for assessing risks in the food system that require preemptive or remedial action. Furthermore, this team will provide quantitative assessments of emerging risks and plausible interventions and coalesce a multidisciplinary and multi-institutional team to assess Covid-19-like challenges in the future.

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PI: Jennifer Kraschnewski (General Internal Medicine)

Collaborators: Deepa Sekhar, William Calo

Drs. Kraschnewski, Sekhar, and Calo will evaluate the impact of Project ECHO on adherence to CDC recommendations and key implementation outcomes for healthcare providers during the COVID-19 outbreak in Pennsylvania. Project ECHO is a telehealth approach that has been used to disseminate medical knowledge to community providers to improve adherence to evidence-based care in chronic disease management. This approach will be evaluated to determine best practices during an infectious disease outbreak.

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PI: Christopher Daryl Cameron (Psychology)

Collaborators: Daniel Lim, Janet Swim

Drs. Cameron, Lim and Swim will examines how motivated choices to empathize relate to willingness to engage in social distancing and pandemic-relevant prosocial behaviors such as self-isolation, and moral judgments about violations of distancing recommendations. The team will also examine factors that influence an empathetic response to Covid-19 victims.

PI: Christian Connell (Human Development & Family Studies)

Collaborators: Michael Strambler

Drs. Connell and Strambler will conduct survey-based research to examine the relation of COVID-19 related stressors (e.g., direct exposure, impact of school and work closures, social distancing) on parents' levels of stress associated with parenting responsibilities or economic strain, as well as the effects on parents' discipline practices or care of their children that could adversely impact child safety and wellbeing. This information will provide critical insight into how best to support vulnerable children and their families during public health crises.

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PI: Jessica Ericson (Pediatric Infectious Disease)

Collaborators: Oluwamuyiwa Adebayo, Catharine Paules, Patrick Gavigan

Dr. Ericson and her team will evaluate the knowledge and belief in the validity of public health messaging related to COVID-19, as well as the desire and ability to respond to public health messaging among individuals presenting for COVID-19 evaluation and testing at Hershey Medical Center.

PI: Matthew Johnson (Center for Science and the Schools)

Collaborators: Anthony Schmitt, Eugene L. Lengerich, Amber Cesare, Tiffany Lewis

Johnson’s interdisciplinary team seeks to develop a freely available, widely disseminated asynchronous online resource throughout the state of Pennsylvania that addresses two important needs: 1) a lack of public understanding of pandemics, how scientists study the spread of disease, how recommendations for policies are derived through this work, and how communities can act locally to mitigate some of the challenges, and; 2) the need for high-quality online learning materials that can be used by K-12 teachers and their students, homeschooling parents and their children, and interested citizens.

PI: Satish Mahadevan Srinivasan (Engineering - Great Valley)

Collaborators: Raghvinder Sangwan, Ashkan Negahban

Through analysis of social media data from different countries, Srinivasan’s team intends to develop an online tool that informs the public with their findings for the following research questions: How effective, as a policy, are social distancing measures in flattening the disease curve in these countries? What type of emotions and sentiments are being expressed by affected individuals or communities over the social distancing measures implemented by their respective countries? What are some tradeoffs that result from social isolation and what are their impact on people’s socio-economic, mental, and emotional wellbeing in affected communities? Is there a right approach to social distancing that provides a good balance among the various tradeoffs?

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PI: John Moran (Health Policy & Administration), Joel Segel (Health Policy & Administration)

Collaborators: Dennis Scanlon, Joel Segel, Kevin Black, Bill Bird, Gregory Stoner

During an outbreak like COVID-19, medical services are likely to be highly constrained and treatment for other diseases may be delayed. Dr. Moran and colleagues will examine the scheduling of non-elective surgeries and preventive care visits, and the filling of prescriptions as proxies for acute and chronic disease care in a large (>40,000) Pennsylvanian patient cohort.

Cohort Studies

To understand the links between risk factors and the contraction and severity of COVID-19, scientists must study the experiences of particular populations. These projects aim to identify the social factors influencing the experience of COVID-19 and predict health outcomes.

PI: Suresh Kuchipudi (Veterinary & Biomedical Sciences), David Kennedy (Biology)

This study will test for the SARS-CoV-2 virus in retrospective and prospective swab samples collected from students that visited/visit the student health center with respiratory symptoms during December 2019 until February 2020, and new samples collected in March and April. Results will provide unprecedented insight into incidence of SARS-CoV-2 infection in the US since December 2019 and incidence among PSU students.

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PI: Kristin Sznajder (Public Health Sciences)

Collaborators: Jaimey Pauli, Jaimie Maines, Kristen Kjerulff, Ping Du, Wenke Hwang, Carrie Daymont, Jeffrey Kaiser, Cynthia Chuang

Sznajder and colleagues will determine the reproductive and neonatal morbidity associated with COVID-19 in pregnancy. They will develop a registry of pregnant women diagnosed with COVID-19. They will use that cohort to study comorbidities, pregnancy and childbirth complications, fetal anomalies, and neonatal morbidity and mortality.

PI: Aleksandra Zgierska (Family and Community Medicine)

Collaborators: Robert Lennon, Rina Eiden, Jenae Neiderhiser, Danielle Symons Downs, Timothy Deimling, Lauren Jodi Van Scoy, Erin McGinley

To determine and improve maternal pregnancy and child health outcomes of COVID-19, this project will assess and identify the immediate needs of pregnant patients in rural Pennsylvania and rapidly connect the most vulnerable patients to their needed resources.

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PI: Mark Feinberg (Prevention Research Center)

Collaborators: Gregory Fosco, Michelle Hostetler, Emily Hotez, Jacqueline Mogle, Samantha Tornello

Dr. Feinberg and his team will evaluate the impact of social distancing on family conflict and adult and child health, and determine if and how family conflict and health influence sustained social distancing practices. The team will also examine if fluctuations in family conflict and parent/child mental health over time influence implementation of social distancing practices and who are the most vulnerable to the negative impacts of social distancing.

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Predictive Modeling & Computational Data Sciences

By studying the mechanisms by which the novel coronavirus spreads, we can help  predict future growth patterns and develop strategies and recommendations for public health interventions.

PI: Katriona Shea (Biology)

Collaborators: Emily Howerton

This project will identify uncertainties that limit the ability of policy-makers to respond most effectively to the SARS-CoV-2 pandemic. This will in turn allow prioritization of information gathering/surveillance/research and help to prioritize management strategies.

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PI: Le Bao (Statistics)

Dr. Bao will attempt to develop a unified global model for early detection of outbreaks using data from travelers. Specifically, he will use data on traveler infections and travel population sizes to estimate key epidemic parameters including the number of infected individuals, the doubling time of the epidemic, and the basic reproduction number, R0.

PI: Ping Du (Medicine)

Collaborators: Qiushi Chen

Dr. Du and colleagues will develop models to fully assess the potential impacts of a range of control measures, implemented in response to COVID-19. They will run simulations using data on sociodemographic characteristics, health systems, disease transmission and natural history of COVID-19, and the effects of a variety of epidemic control measures implemented during previous major epidemic outbreaks. Their findings will inform real world health responses and practices in the Commonwealth of Pennsylvania in preparation for future successive waves of the disease.

PI: Nita Bharti (Biology)

Collaborators: Anthony Robinson

Reported cases of disease are delayed indicators of underlying behavior, including movement, contact rates, transmission dynamics, and real disease incidence. We will measure changes in movement and contact patterns within and between locations to assess their impact on the COVID-19 outbreak in settlements where the relaxation of early behavioral interventions presents an immediate risk of a subsequent wave of transmission. Monitoring movement indicators to guide preventative efforts is more effective than relying on epidemic data to inform reactive interventions.

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PI: Ottar Bjornstad (Entomology)

Bjornstad and team plan to construct and parameterize age-structured compartmentalized covid-19 disease dynamic models develop a ShinyApp for scenario analyses and assessing the utility of various interventions in different populations during the epidemic phase through the establishment of the predicted long-term seasonal endemism of SARS-Cov-2.

PI: Ashkan Negahban (Engineering - Great Valley)

Collaborators: Ottar Bjornstad, Mohamad Darayi, Robin Qiu

Negahban and collaborators propose to mine individual-level trip data from a major subway system, perform network analyses and simulations, and enable the development and prioritization of optimal interventional strategies for subway stations and transportation hubs to reduce SARS-Cov-2 spread and enhance disease control.

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PI: Prasenjit Mitra (Faculty Teaching)

Collaborators: Clyde Giles

Mitra and Giles seek to develop deep learning algorithms and tools to systematically scan all covid-19 related research literature and develop annotated datasets that provide scientists and policy makers alike an up-to-date view of state-of-the science based on the best-known evidence, identify hidden associations, and key knowledge gaps.

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PI: Michael Norton (Center for Neural Engineering)

Collaborators: Steven Schiff, Helen Greatrex, Steven Greybush

Norton and team seek to inform decision-making to combat the spread of COVID-19 and assess optimal intervention strategies in real-time. They plan to accomplish this by developing and parameterizing optimal control and data assimilation frameworks and computational disease dynamic models.

PI: Swaroop Ghosh (Electrical Engineering)

Ghosh proposes to develop quantum machine learning modules and training models and methodology to speed up the process of COVID-19 related drug development through in silico discovery and assessment of candidate compounds and structures.

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PI: Kenneth Huang (Faculty Teaching)

Collaborator: Lee Giles

This project will recruit non-expert crowd workers to annotate COVID-19 publications to allow non-experts to query biomedical terms. Annotations will include region/time, biomedical named entities, and qualitative aspects (background, purpose, mechanism, findings) for COVID-19 publications. The resulting annotations will be released publicly via Github or PubAnnotation.

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PI: Robert Fraleigh

Collaborators: Chris Griffin, Brady Bickel, Kurt Vandegrift

COVIDExplorer is a web-application developed by Dr. Fraleigh and team that uses automated machine learning and interactive visualizations to help researchers find the most relevant and urgent documents for key scientific questions. The expansion of this project will include: 1) automating the ingestion of COVID-19 publications 2) scaling the backend infrastructure to accommodate the evolving literature landscape and 3) collaborating with Penn State CIDD to optimize the tool for virologists and epidemiologists.