USF COVID-19 Rapid Response Grant Program
Funded COVID-19 Rapid Response projects in the news
USF COVID-19 Rapid Response Grant Program – Round One
The USF COVID-19 Rapid Response Grant Program, administered through USF Research & Innovation, is offering at least two rounds of proposal submission for funding consideration. The first round — with submissions due April 13, and awards announced one week later, on April 20, 2020 — offered tenured/tenure-track and full-time research faculty members the opportunity to apply for up to $25,000 in funds to focus specifically on research that can be immediately initiated, completed within a short time frame (i.e., 3-6 months) and lead to the rapid submission of proposals for external funding. The Florida High Tech Corridor Council also provided matching funds to six of the projects that are based on intellectual property that may be patented and commercialized through licensing, startups and corporate partnerships.
Of the 128 proposals submitted by more than 400 faculty for the first round, 14 projects were funded — a conversion rate of 10.9 percent. An aggregate of nearly $3 Million in funds was requested by these proposals.
Read about the first 14 funded projects: USF Creates Pandemic Response Research Network™, Invests in Projects Addressing Coronavirus Outbreak.
Executive Summaries – Round One
Self-Contained Acoustic Isolation and Detection System (SCAIDS) for SARS-CoV-2 and its Antibodies
PI: Dr. Venkat Bhethanabotla, College of Engineering
Executive Summary: A dual delay-line surface acoustic wave (SAW) device, a sensing system including cell and associated electronics for point of need testing were designed, fabricated and tested for the detection of SARS-CoV-2 directly from a small sample of body fluid. Preliminary experiments to assess mutual affinity of gene sequences representing the COVID genome and its complement have been completed. Efficiency of the Rayleigh SAW waves in removing the non-specifically bound proteins and other material present in the analyte fluid was established. Further miniaturization of the sensing platform and completing the COVID detection experiments remains for future work.
Secure Mobile Contact Tracing App
PI: Dr. Jean-Francois Biasse, College of Arts & Sciences, Director of the Center for Cryptographic Research
Executive Summary: The PIs successfully described a secure and privacy preserving protocol that allows a central authority to learn information on the spread of the virus in real time in a community of users of the proposed mobile application. The PIs developed a prototype for the app on Android and iOS that is able to successfully leverage the Bluetooth signal of a user’s phone in order to detect proximity with another user, and quantify exposure to the virus. The PIs were able to conduct preliminary tests.
The PIs described a variant of their protocol which is an app to be used by COVID-positive people only. The app finds locations visited in the past 14 days and communicates with a central server that is tasked to identify possible hotspots. The PIs realized a proof-of-concept of this alternate design working on Android.
Alternative Processing of Civil and Criminal Justice System Matters for People with Behavioral Health Disorders
PI: Dr. Annette Christy, College of Behavioral and Community Sciences
Executive Summary: We interviewed 44 people using a structured interview protocol. Half were states attorneys, public defenders, judges and witnesses involved involuntary (Baker Act) hearings. Half were mental health professionals and public defenders involved in forensic assessment/hearings, such as for incompetence to proceed. Zoom was the most commonly used videoconference platform. In person was indicated to be better as it relates to confidentiality/privacy, rapport, validity of the assessment, ability to assess, and comfort of the defendant/examiner. Video conferencing was indicated to be better as it relates to security, cost/time efficiency, health of those involved, and allowed to more easily record. Suggestions for improving video conferencing included being able to hold them in secure rooms and having the placement of the camera so you can see the entire person. These findings and detailed comments are informing our writing in this area and will serve as useful pilot data to seek additional funding.
Rapid Development of Covid-19 Therapies and Evaluation of Side Effects
PI: Dr. Robert Frisina, Department of Medical Engineering
Executive Summary: Since the main symptom of Covid-19 is airway inflammation, human lung epithelia cells (HBEpC) were utilized in different paradigms. Western blots and confocal microscopy were used to identify changes in signaling proteins. An OriGene ELISA was used for determining the vitality of the virus under different conditions. Main findings so far: Remdesivir (Re) and hydroxychloroquine (HCQ) increased LC3II and p62 protein expression in HBEpC cells compared to nontreated cells, indicating autophagy flux was blocked (Fig. 1). We infected the HBEpC cells with lenti-mCherry-GFP-LC3 and compared the controls to the different doses of Re and HCQ, and found that both mCherry and GFP signals were decreased in Re and HCQ treatments compared to non-treatment control group. In addition, the fusion signals of GFP and mCherry (yellow labeling) are increased as GFP signals in treated cells, suggesting Re and HCQ inhibit virus proliferation at the point of autolysosome formation (Fig. 2). We collected the supernatants three days post-infection of lenti-mCherry-GFP-LC3, to assess viral production by the HIV p24 ELISA method. In both Re and HCQ treatment groups, viral concentrations had significantly decreased compared to the untreated controls (Fig. 3).
Social closeness despite social distance: A study of strategies to fight loneliness during the COVID-19 pandemic
PI: Dr. Fallon R. Goodman, College of Arts and Sciences, Department of Psychology; Director, Emotion and Resilience Laboratory
Executive Summary: Results from our study of 310 adults with elevated depression and social anxiety symptoms offer new insights on loneliness. Even during a pandemic, participants socialized frequently; over the 14-day study, participants socialized at least once on most days, most of which were in-person conversations.
Different social experiences impacted loneliness. On days when participants socialized, they reported the highest loneliness when they felt closed off from others and the lowest loneliness when they felt authentic. Across all social experiences, the more time participants spent socializing, the less lonely they felt. This was especially true for participants high in depression/social anxiety—on very social days, these individuals reported the largest decreases in loneliness of all participants. Thus, although individuals high in depression/social anxiety were lonelier and socialized less often, socializing strongly impacted their loneliness—particularly when they felt open and true to themselves during social interactions.
A 2-in-1 Nanoaerosols Development to Mitigate COVID-19 Spread in Both Humans and PPEs
PI: Dr. Alya Limayem, Taneja College of Pharmacy
Executive Summary: Our preliminary data pertaining to the size, morphology and the aerodynamic flow of the prophylactic virucide, chitosan combined to Zinc oxide nanocomposite (CZNPs) in conjunction with typical excipients (i.e., mannitol and lactose) have demonstrated rudimentary microsphere formation of CZNPs.The synergistic CZNPs when combined to lactose alone has shown the largest microspherical size with a diameter of 2 μm, whereas CZNPs with mannitol and with both mannitol and lactose, measured approximately 0.7 μm and 1μm, respectively, falling within the required flowing range in order to reach the lung and act as an antiviral. Additionally, the effectiveness of CZNPs (200 ug/mL) without excipients was observed through TEM in a volume of 3 ul (1:1) including the BSL1, heat inactivated SARS-CoV-2 (1.16 x 10 E6 PFU/mL), denoting a significant disintegration of COVID-19 envelope alongside the protein spikes dispersal, showing elongated shapes compared to the control sample (CZNPs free), where all viral clusters remained intact.
Planning for Hurricane Shelter Operations during a Pandemic
PI: Dr. Jennifer Marshall, College of Public Health
Executive Summary: This project was conducted by researchers with expertise in public health, disaster management, psychology, and occupational safety. We established a network of over 300 federal, state and local leaders, staff, and experts from 22 states and a range of disciplines (disaster planning, mass care, disability, healthcare, community) to identify knowledge gaps. 265 of these stakeholders participated in online workshops to discuss six priority research topics: Vulnerable population and planning considerations; Health; Logistics; Public messaging/risk communication; Workforce; and Psychological adjustment. From these workshops, we identified areas of immediate need and created products to support them, including a Disaster Workforce Planning Quick Guide and Job Hazard Assessment Tool, a Disaster Workforce Survey to measure burnout and role strain, Just-in-Time Trainings on Special Needs Shelter Operations and Disaster Worker Self-Care, and bilingual (English and Spanish) hurricane preparedness materials tailored to pregnant women, families with infants and young children, and children with special healthcare needs.
SARS-CoVid-19 tissue-specific susceptibility in different ethnic backgrounds
PI: Dr. Thomas McDonald, Morsani College of Medicine, USF Health Heart Institute
Executive Summary: In this project, we have successfully differentiated iPSCs into cardiac myocytes (iCM), cardiac fibroblasts (iCF), endothelial cells (iEC) and macrophages (iMf). We examined cells from donors of both genders and from Caucasians and African-Americans. The next step was to determine whether these cell types expressed the receptor for SAR-CoV2 entry—ACE2. The parent stem cells expressed very little ACE2 but upon differentiation into iCM, iCF, or iEC, the cells upregulated ACE2 robustly (5-50-fold over iPSCs). Expression was gender, ethnicity and sex hormone-dependent. ACE2 was not expressed in iM. We also have incorporated the novel SARS-CoV2 spike protein mutation D614G that has emerged since April as the dominant strain infection USA and other countries into the SARS-CoV-2 spike pseudotyped VSV reporter virus. Our ongoing work now combines this reporter virus with our cell types to determine gender, cell-type, and ethnicity infection susceptibilities.
The USF Rapid-Risk Assessment and Intervention for COVID-19
PI: Dr. Usha Menon, College of Nursing
Executive Summary: An interdisciplinary team of researchers from the University of South Florida and Moffitt Cancer Center conducted a survey and tailored intervention in a sample of 1039 US adults primarily located in the state of Florida. Participants were recruited from July to November 2020 via email, social media, and through Prodege, an industry leading market research provider. Targeted advertising was used to ensure the sample was representative of Florida’s population. A total of 578 participants chose to receive tailored messages on resources and risk mitigation via email or text message. Participants that opted-out of tailored messages had the opportunity to review a comprehensive list of resources on the project’s website, livingwellduringcovid.com. In addition, the study team has established a registry with a cohort of participants that can be contacted for follow-up and future studies; 286 participants agreed to join the registry. Preliminary analyses of survey data are underway.
A novel therapy for high-risk critically ill COVID-19 patients
PI: Dr. Subhra Mohapatra, Morsani College of Medicine
Executive Summary: This proposal focuses on repurposing an anti-diabetic FDA-approved drug, pioglitazone (PG) as an adjunct therapy to mesenchymal stem cell (MSC) therapy for treating COVID-19. Our previous research had led us to conceptualize that oral PG followed by MSC Rx will effectively treat high-risk and critically ill COVID-19 patients, wherein pretreatment with PG will reduce SARS-CoV-2 viral load and attenuate the viral-induced neuroinflammation and MSC will promote lungs and neuronal tissue regeneration. To this end, first we conducted significant molecular docking analyses which suggested that PG has the potential to bind to a number of SARS-COV-2 viral proteins including the Spike protein. Further analyses has suggested that the Leriglitazone (LG), an metabolic byproduct that crosses blood brain barrier can also bind to SARS-CoV-2 spike proteins. Second, we conducted in vitro studies of inhibition using a human coronavirus, NL63, which uses SARS-CoV-2 like mechanism to infect cells. Thus in a number neuronal cell lines and in Calu-3 lung cells we have demonstrated the inhibition of viral replication by PG and LG. These support our hypothesis of combining PG/LG with MSCs against severely ill patients.
Sniffing out COVID-19: A Novel Nanofilm Detector System
PI: Dr. Salvatore Morgera, College of Engineering
Executive Summary: Our research team successfully reached a milestone in the development of a novel gas sensor array test bed prototype having a mucus film that, in minutes, provides a rapid, accurate, sensitive, selective detection of exhaled breath VOCs, such as Hydrogen, CO, NO, Alcohol, and Acetone. These are breath biomarkers that are associated with some key symptoms of COVID-19. This prototype serves as the basis of a diagnostic screening device for detecting levels of VOCs specific to SARS-CoV-2. The electronic detection of the unique composition signature of COVID-19 from the exhaled breath of an individual serves as the motivation of our research. An extensive literature review of gas sensing technologies has been performed and submitted for publication alongside the development of the test bed prototype. As the prototype evolves to more accurately detect VOCs of COVID-19, the novel structural features are written into a draft patent application. A Standard Operating Procedure (SOP) has also been drafted.
Sterilization Mechanism of Corona Discharge for Masks and Environment to Combat COVID-19
PI: Dr. Ying Zhong, College of Engineering
Executive Summary: Corona discharge was investigated to efficiently disinfect masks and surfaces to address the shortage of PPEs and disinfectants during COVID-19 and future pandemics. Corona can simultaneously disinfect and recharge masks to guarantee their safe reuse by avoiding static charge loss caused filtration efficiency deterioration. The log reduction against E. coli was confirmed to reach 6, good enough for surgical applications. Log reduction against spores reached 3, indicating its high disinfection effectiveness against a wide range of challenging microorganisms. N95 masks were recharged effectively with static charges stable for up to several weeks. The filtration efficiency of N95 masks subject to extensive corona treatment cycles was still near 95%. The outstanding disinfection efficiency on solid surfaces including metals and polymers were confirmed. Portable and affordable disinfection devices are being developed for commercialization. With the support of PRRN, this project was further granted an NSF award (#2030033).
USF COVID-19 Rapid Response Grant Program – Round Two
For round two, the University of South Florida’s COVID-19 Rapid Response Grants program has invested in 14 faculty research projects to advance new medical interventions to detect and stop infections, develop innovations in personal protective equipment, and address fear and confusion in communities particularly vulnerable to the virus.
A total of $344,855 has been invested in support this new round of research projects. USF is partnering with the Florida High Tech Corridor Council which has contributed $100,000 in support of five of the proposals with the potential for technology commercialization.
Faculty from nine colleges spanning USF Tampa, USF St. Petersburg and USF Sarasota-Manatee are part of this funding round designed to kick-start projects that would last six months to a year.
This round of funding brings the total investment from the USF COVID-19 Rapid Response Grant program to nearly $685,000.
Read about the 14 funded projects in round two: USF COVID-19 Rapid Response Research Effort Delivers Funding in Second Round of Pandemic Projects.
Executive Summaries – Round Two
Mathematics and Science Teaching and Learning of COVID-19 Public Health Issues in eLearning Environments
PI: Dr. Allan Feldman, College of Education
Executive Summary: We engaged eleven public middle school math and science teachers (eight in Cohort 1 and three in Cohort 2), recruited from five local schools, in participatory action research to develop methods and materials to deliver high quality, reform-based online instruction and to increase students’ knowledge of public health issues and their ability to serve as COVID-19 public health ambassadors to their communities. We studied the development and implementation of culturally-responsive pedagogical methods and curricular materials for the Covid-related lessons. Teachers engaged in summer professional development on the public health aspects of the pandemic, the use of various online technologies, and action research. Teachers developed their curriculum materials and engaged in action research on the implementation of their COVID-related lessons. Teachers’ research uncovered the effects of inequities in the educational system (often tied to economics, race/ethnicity, and language) and documented their experiences with students in the delivery of the COVID-related lessons.
Contact Tracing of Ships and Seaports in Florida
PI: Dr. Mark Luther, College of Marine Science
Executive Summary: Vessels arriving in Florida ports in early 2020, during the early phase of the pandemic had previously visited ports throughout the globe, including the Caribbean, South America, northern Europe, western and northern Africa, the Middle East, and east Asia. Time in port and time between ports were found to be sufficient for viral transmission and development, but not necessarily sufficiently long to act as quarantine. We can quantify the relative risk of case importation from specific ports based on number of trips and vessel type.
Wearable COVID Observational Device with Machine Learned Physiological Signatures
PI: Dr. Matthew Mullarkey, Muma College of Business
Executive Summary: Thus far, the project team has completed the recruitment and monitoring of 14 subjects. Each subject was ambulatory, COVID positive. The complete dataset is in the process of data management and initial analysis by the study data team. The analysis will ultimately be compared to the progression of the disease in the subject as recorded in the medical healthcare record. All subjects recovered from the disease and none were admitted to hospital.
Targeting Phosphatidylserine Exposure and Phospholipid Scramblase Activity to COVID-19 Infections
PI: Dr. Meera Nanjundan, College of Arts & Sciences, Department of Cell Biology, Microbiology and Molecular Biology
Executive Summary: Phospholipid scramblase reagents were optimized for expression analyses using relevant lung cell lines resulting in prominent detection of PLSCR1 and TMEM16F. Using HEK392T-ACE2, A549-ACE2, and HBEC-3KT cell lines, their growth conditions were optimized in 2D systems along with efforts to knockdown PLSCR1 using an shRNA approach. Towards preparation of pseudo-SARS-CoV-2, we generated lentiviruses following generation of plasmids towards SARS-Related Coronavirus 2, Wuhan-Hu-1 Spike-Pseudotyped and HEK293T packaging cell line. Lentiviral production was optimized based on the VSVG control in HEK293T-ACE2 and A549-ACE2 cell lines for which infectivity was monitored via optimized luciferase and fluorescence-based assays. Studies to investigate the efficacy of the scramblase inhibitor, R5421 (dose range 0.5uM to 100uM) identified reduction in viral infectivity with moderate effect on cellular viability. Studies remain ongoing to test the efficacy of Bavituximab (PS targeting agent) and assess PS externalization in response to these viruses within the 3D culture model for HBEC3KT cells.
Exploring Racial Disparities in the Treatment, Perceptions, and Tracking of COVID-19 Through Automated Stigma Detection and Sentiment Analysis of Social Media Data
PI: Dr. Tempestt Neal, College of Engineering
Executive Summary: This study investigates the discourse around COVID-19 in the African American community, facilitated by social media data. This research consists of three phases: data collection, data filtering, and text analysis. First, we collected over 5 million tweets using a deep neural network model to identify Twitter data relevant to COVID-19. To further extract tweets most likely composed by African American Twitter subscribers, we trained an image classification model on publicly available face datasets that are labeled by ethnicity. We then used this trained model to classify public profile images for data filtering. The final phase consists of applying Microsoft Azure’s Text Analytics cloud computing service for sentiment analysis and opinion mining to expose mental models surrounding COVID-19, and how public health initiatives, illness caused by COVID-19, stay-at-home orders, and other factors stemming from the pandemic have been perceived and/or communicated by those within this community.
Isolated and Safe? Analysis of the Mental Health Impacts of COVID19 on Detained Youth
PI: Dr. Joan Reid, USFSP College of Arts & Sciences, Department of Society, Culture & Language
Executive Summary: We examined the psychological stressors associated with COVID-19 on 557 justice-involved youth in Florida. From this research, we presented findings of violence and correlates of violence in justice-involved youth at the 2021 American Society of Criminology conference in Chicago. We contributed findings of multivariate analyses to the Crime and Delinquency special issue on COVID-19’s impact on crime and delinquency with findings suggesting increased psychological stressors in justice-involved youth with the onset of COVID-19 stay-at-home measures. Additionally, we organized the special issue for the Crime and Delinquency journal relating to various impacts of COVID-19 on crime.
Economic Recovery Markers from Satellite Imagery to help with City-scale Decisions during COVID-19 Recovery
PI: Dr. Sudeep Sarkar, College of Engineering
Executive Summary: A transdisciplinary team from USF’s Institute for Artificial Intelligence (AI+X), the UC Berkeley, and satellite company Maxar Technologies, developed a new artificial intelligence-enabled algorithm that uses satellite imagery to document and analyze the effects of travel bans and shutdown orders on the local economy quickly and economically, from a single source.
The project developed city-scale economic trend forecasts based on satellite images taken at regular intervals that could be augmented with information from other sources such as community mobility data, flight tracker data, and railway tracking data. The team applied the new technology to Tampa’s 2020 shutdown and found that the early months of the pandemic weren’t as problematic for local destinations like shopping mall — where occupancy was initially low, but then quickly rebounded — or locations in the downtown, where parking lot occupancy was the same as before the pandemic. Meanwhile, other destinations saw an impact as more people worked from home and didn’t venture out for lunches or after-work socialization.
The team won a top prize from the European Space Agency in a COVID-19 monitoring challenge and the solution was integrated into the agency’s data monitoring dashboard.
Real-Time Monitoring of COVID-19 Progress Using Magnetic Sensing and Machine Learning
PI: Dr. Manh-Huong Phan, College of Arts & Sciences, Department of Physics
Executive Summary: We have developed a novel, non-invasive, and contactless respiratory monitor based on ultrasensitive magnetic sensor technology that can precisely detect a patient’s abnormal breathings in real-time. The breathing monitor can identify COVID-19 infections faster than existing tests and requires no contact between the patient and a medical professional, which is an improvement over existing COVID-19 detection technologies. It can also track COVID-19 progress at multiple stages (early, intermediate, sever). Combining this technology with music, we have developed a new, innovative magnetic music therapy method that can help COVID-19 patients or patients with chronic pulmonary diseases to slow breathing and invite a relaxed physiology. This device can also be used to help those who suffer from anxiety or insomnia. Our research achievements include 2 US patents (pending), 4 journal papers (2 published, 2 in preparation), 2 theses (1 MS, 1 BS-honor), and 8 conference presentations (2 invited talks).
Dispersion Modeling of Respiratory Aerosols and COVID-19 Infection Risk Analysis in Airport Terminals
PI: Dr. Andres Tejada-Martinez, College of Engineering
Executive Summary: A computational fluid dynamics (CFD) model was developed to predict the dispersion of respiratory aerosol emissions in ventilated enclosed spaces. CFD has high computational requirements and given the relatively small dimensions of hospital isolation rooms as well the stress brought onto the healthcare community by COVID-19, the model has been initially used to predict aerosol dispersion in these hospital settings. The CFD model was also used to develop a less computationally intensive approach, namely the well-known box or compartment models of indoor air quality.
Physical experiments of the dispersion of aerosols emitted from a breathing and speaking mannequin simulator with and without protective face mask were also performed. Aerosol size distributions and concentrations were measured by an optical particle sizer. Aerosol velocities and distances traveled were measured via a high-resolution camera. In the future, this data will be used to validate and improve the CFD and compartment models developed.
Motivating At-Risk Populations’ Return to Healthcare Facilities and Services Through Emotive Messaging
PI: Dr. Kimberly Walker, College of Arts & Sciences, Zimmerman School of Advertising and Mass Communications
Executive Summary: The team successfully engaged BayCare Health Systems as an external partner to provide test advertising media as well as access to their patient marketing research pool. Additional media were downloaded from the internet. This was the first time that we were using the iMotions on-line data collection platform, and it required some modifications causing a late start in data collection. The research instrument (Qualtrics) was created, tested, and fielded once IRB approval was granted. In addition to the BayCare patient pool, we recruited participants through USF Health. The survey was in the field from June 3rd to June 30th during which time 738 people opened the survey link to complete the full iMotions survey through the BayCare patient pool; 3,638 people opened the survey link to complete the full iMotions survey through USF Health recruitment; and 443 people opened the survey link to complete the survey without iMotions. A total of 75 participants completed the survey with the full iMotions suite through BayCare and 32 participants completed the survey with the full iMotions suite through USF Health. We sent a second round of the survey without iMotions to compare responses between June 15th and June 30th, during which time an additional 303 were added. We are actively analyzing the data now and will soon prepare a report to partners followed by a journal manuscript. Learnings from this research will inform BayCare’s messaging to the public as well as our future research using neurophysiological measures to evaluate health communications.
USF COVID-19 Rapid Response Grant Program – Round Three
The University of South Florida is providing seed funding to 14 new research projects designed to address the medical, technological and societal issues of COVID-19. This brings the total of institutional resources invested into pandemic research to more than $1 million.
This third round of funding is unique because researchers were challenged to forge partnerships with community organizations and corporations, so that their projects could more rapidly be put to real-world use. USF Research & Innovation is investing nearly $320,000 in the projects, with the Florida High Tech Corridor Council contributing $100,000 in support of five projects.
“Each of these projects tackles a specific shortcoming in the world’s ability to respond to the COVID-19 pandemic and works to find a creative, innovative or inventive solution that can move from lab to market quickly,” said Dr. Paul Sanberg, USF’s senior vice president for research, innovation & knowledge enterprise.
Since April, USF researchers have embarked on 42 separate COVID-19 projects supported through the Rapid Response Research Grant Program. More than 450 USF scientists, engineers, inventors and innovators from multiple disciplines and across all three campuses are working through the USF Pandemic Response Research Network to create a cohesive, transdisciplinary approach to addressing the pandemic from medical, social, environmental and economic angles.
In all, the effort has represented an extraordinary joining of institutional, community and private sector resources to combat the COVID-19 outbreak and future pandemics. In addition to the more than $1 million invested, university researchers and 26 separate external partners have contributed another $436,000 in both in-kind support and research dollars.
Read about the 14 funded projects in round three: USF supports COVID-19 research partnerships with new seed grants.
Executive Summaries – Round Three
COVID-19 Animal Model Resource Development for Microbiome & Intervention Studies
PI(s): Dr. Christian Brechot and Dr. Shyam S Mohapatra, Morsani College of Medicine
Executive Summary: The major goal of our project was to consolidate efforts to develop COVID-19 pre-clinical cellular and animal models at USF to assist in studies relating to validation of new interventions against COVID-19 infection. The support of this project has led to the development of three specific resources will be developed for collaborative research: i) establishing a colony of human ACE2 transgenic C57BL6 mouse for USF investigators involved in COVID-19 research; ii) developing a COVID-19 lethal model using human ACE2 transgenic C57BL6 mouse (with breeding pairs obtained from Jackson Lab); and iii) a SARS-CoV-2 adapted mouse model, MA10 model produced using reverse genetics approach. These models will be used to examine the detailed microbiota changes in COVID-19 infected individuals, develop COVID-19 vaccines and for cancer immunotherapy studies in collaboration with a prospective industry partner who is interested in collaborating and applying for federal support with the USF faculty within a year.
Relationships Between Air Quality, Health Outcomes, and Socioeconomic Impacts of the COVID-19 Pandemic in Florida
PI: Dr. Yasin Elshorbany, School of Geosciences, College of Arts & Sciences
Executive Summary: We have investigated the changes in air quality during the Pandemic and applied interdisciplinary approaches to study its socioeconomic impacts. Our results indicate that the reduction of traffic was effective in improving air quality in regions where traffic is the main pollution source, such as in New York City and FL, while was not effective in reducing pollution events where other pollution sources dominate, such as in IL, TX and CA. Regarding the societal impacts, we found that respiratory conditions, living in proximity to industrial areas, and financial impacts from the COVID-19 lockdowns influenced people’s concerns about air quality. People with respiratory issues were more familiar and concerned with the Air Quality Index than healthy individuals. We have also investigated the impacts on underrepresented and financially disfavored groups, who are found to be more impacted due to different factors investigated in the study.
Spatial-Temporal Prediction Models for COVID-19
PI: Dr. Ming Ji, College of Nursing
Executive Summary: Our STPMCOVID team has exceeded the original planned goals. We have accomplished the following:
1. Developed a pipeline (in R) for pull, transform, predict and visualize daily COVID number of cases (URL: https://github.com/SpatialTemporalModel/STPM-COVID/tree/main/Rscripts )
2. Submitted our prediction model to the CDC COVID Forecast Hub who accepted our model (USF-STPM) (URL: covid19-forecast-hub/data-processed at 1f875718a5dac1366aff679a19e82277f62751a3 · reichlab/covid19-forecast-hub · GitHub )
3. After our model has accepted, our team became one of the members of the CDC COVID Forecast Hub and has been attending their weekly meeting on COVID predictions in the US.
4. We participated in the USF Codeathon in 2021 and investigated a variety of spatio-temporal prediction modeling approaches (spatio-temporal random forecast, convolutional neural network and point-process based spatio-temporal prediction models) in addition to STPMCOVID models. We stored our preliminary results in the github account (URL: https://github.com/SpatialTemporalModel/STPM-COVID)
5. We submitted a grant proposal for the CSTE (Council of State and Territorial Epidemiologists)’s RFP on Influenza Forecast).
Bending the Mental Distress Curve Among COVID-19 Responders: A Pilot Feasibility Study
PI: Dr. Kristin Kosyluk and Dr. Jerome Galea, College of Behavioral and Community Sciences
Executive Summary: We successfully developed a prototype resource navigator chatbot capable of screening COVID-19 first responders for distress and facilitating appropriate mental health resources based on their distress level and personal preferences. The chatbot was piloted it among N=20 COVID-19 first responders for feasibility and acceptability. We are presently completing data analysis and have 3 manuscripts under preparation:
1. Results from a national survey on the acceptability of a chatbot for mental health resource navigation
2. Development, feasibility, and acceptability of a chatbot mental health resource navigator among COVID-19 first responders
3. Using Conjoint Analysis to determine the feature preferences of a chatbot mental health resource navigator
We expect these manuscripts to be submitted by Q3 2022.
Exploring the Gut Microbiome in SARS-CoV-2 Infection Across Pregnancy
PI: Dr. Tara Randis, Morsani College of Medicine, and Dr. Maureen Groer, College of Nursing
Executive Summary: The accomplishment of aims 1 and 2 were largely due to the ability to study women enrolled in a NIH funded study of pregnancy. There were many unfortunate factors that contributed to our inability to complete aim 3. We found a high prevalence of seropositivity in this unvaccinated sample of pregnant Hispanic women. Our study showed that no differences in taxonomic levels in gut microbiome measured by the Illumina MiSeq in women who were SARS-CoV-2 IgG positive and asymptomatic or minimally symptomatic. Deeper sequencing with shotgun metagenomics would allow us to discover if there were signature species that differed by serostatus. We did find lower Il-10 plasma levels in seropositive women, which may be important as IL-10 is a major immunoregulatory cytokine. We also found relationships with particular microbes and IL-17 and IL-10, but this was independent of serostatus.
Impact of COVID-19 on The Management of Type 2 Diabetes Among Older Individuals: Food Insecurity, Decreased Physical Activity, and Social Isolation
PI: Dr. Nancy Romero-Daza, Department of Anthropology, College of Arts and Sciences
Executive Summary: While the COVID-19 pandemic posed challenges in participant recruitment and retention, the results from this pilot project suggest online diabetes self-management education and food vouchers is feasible and acceptable to adults over 50 with T2D. The experimental group (education plus food) reported a modest improvement in diabetes self-management and dietary quality when compared with the control group (education only). The majority of participants (63%) reported that COVID-19 had a moderate or extreme impact on their daily lives (social support, loneliness, physical activity, and management of diabetes). Limitations of this project include limited participant recruitment and high attrition, the lack of HbA1C data, and the many challenges posed by COVID-19 for the clinic staff and research team during the project.
Optimizing the Allocation of COVID-19 Testing & Vaccine Resources in Florida
PI: Dr. Ran Tao, School of Geosciences
Executive Summary: In this study, we developed a spatial optimization model to choose the best locations for vaccination sites. The model is a modified two-step Maximal Covering Location Problem (MCLP). It aims at maximizing the number of residents who can conveniently access to the sites and mitigating inequity issues by prioritizing disadvantaged population groups who live in geographic areas identified through CDC’s Social Vulnerability Index (SVI). We conducted our study using the case of Hillsborough County, Florida. We found that by reserving up to 30% of total vaccines for the highly vulnerable communities, our model can optimize location choices for vaccination sites to provide effective coverage of residents at large while prioritizing disadvantaged groups of people. A series of sensitivity analyses have been performed to evaluate the impact of parameters such as site capacity and distance threshold. The model has the potential to guide the future allocation of critical medical resources in the U.S. and other countries.
Developing a data-driven agent-based model accounting for social heterogeneity and mobility at the census tract level to simulate local COVID-19 transmission dynamics
PI: Dr. Thomas Unnasch, College of Public Health
Executive Summary: We have developed an agent-based city scale digital twin platform called CitySEIRCast for supporting the analysis and simulation of COVID-19 transmission across the populations of Hillsborough County, FL. CitySEIRCast incorporates GIS data to create a virtual environment of Hillsborough, which is combined with synthetic populations of the county and epidemiological disease transmission parameters, to model pandemic spread at various spatial resolutions across the county. It forecasts the spread of infection over time, identifies spatial hot spots and important risk groups, and estimates the number of infected individuals arriving at hospitals, as well as deaths from the virus. It further allows explorations of the impacts of newly emergent variants, and the effects of different public health interventions, including various social measures and vaccinations, for curbing disease transmission to support the management of the spread of contagion. The platform is built using agile software development principles, so that threats from other infectious diseases can also be addressed.
Pulmonary Rehabilitation for Discharged Hospitalized Patients with Covid-19
PI: Dr. Constance Visovsky, RN, FAAN Professor, Director, College of Nursing
Executive Summary: In a sample of 20 individuals with long-term dyspnea (shortness of breath) following Covid-19 infection, we used a quasi-experimental design in a 12-week intervention consisting of external muscle strength training (EMST) plus pursed lip breathing to improve pulmonary function (thoracic expansion, peak expiratory flow), functional performance (6-minute walk test) and respiratory symptoms (COPD Assessment Test). This intervention resulted in statistically significant improvement in the 6-minute walk test (p=.024) and a decrease in respiratory symptoms (p=.000). There was a clinical change in the thoracic lung measurements from baseline to 12 weeks, but it did not achieve statistical significance (p=.176). There was no statistically significant difference in the average peak expiratory flow measures when compared over the 3 timepoints. The lack of statistical significance in thoracic expansion and peak expiatory flow are likely due to the small sample size.
Funded COVID-19 Rapid Response projects in the news …
You can read more about our research, including projects receiving external funding, on our PRRN news page. For example:
USF psychology professor wins NSF grant to study remote work in response to COVID-19
April 29, 2020
The National Science Foundation has awarded a USF psychology professor grant funding to study the rapid transition to remote work, driven by the COVID-19 pandemic. Distinguished University Professor Tammy Allen is gathering data to examine adjustment to remote work with the intention of developing guidelines for future telecommuting in normal and in emergency situations. READ MORE
USF Engineers Awarded NSF Grant to Fight COVID-19 using big data
May 20, 2020
A team of researchers from the University of South Florida College of Engineering is developing a digital tool to give government agencies, researchers and health professionals unparalleled insight into COVID-19. READ MORE
USF College of Public Health receives grant to study hurricane shelter operations during COVID-19 pandemic
May 22, 2020
How do we safeguard against the spread of COVID-19 if people are forced to evacuate to community shelters during a hurricane? That’s one of the questions a research team led by Dr. Jennifer Marshall, a USF College of Public Health (COPH) associate professor, and her co-principal investigator Elizabeth Dunn, an instructor in the COPH, will address as the hurricane season comes barreling toward us. The team has been awarded a $25,000 USF COVID-19 Rapid Response Research Grant. READ MORE
Developing a wearable device to detect COVID-19 progression in at-risk patients
June 12, 2020
A new study from researchers at the University of South Florida is shedding light on the human body’s physiological response to COVID-19, insight scientists say could help them develop an early warning system for those most at risk of severe infection. The wearable device, which is being provided by Shimmer Research, Inc., a private company partnering with USF for the study, will track a variety of markers, including skin temperature, thoracic bioimpedance, oxygen saturation (SpO2) and more. The study, funded through a USF COVID-19 Rapid Response Grant, brings together a transdisciplinary team of researchers from across the university. READ MORE