Collaborative Seed Grants
GIDI supports a seed funding program for cross-Grounds collaborative research projects. The purpose of this program is to bring diverse investigators together to tackle important questions and perform transformative, interdisciplinary work that will differentiate the UVA research enterprise. Proposals involve investigative teams from a variety of disciplines, from different Schools across Grounds. Evidence of prior collaboration is not required, and the creation of new partnerships is encouraged.
Seed Grant Awardees
The goal of the GIDI iGrant Program is to support innovative, impactful research conducted by individuals. Consistent with GIDI's mission, these projects will promote trans-disciplinary research and extend GIDI's national and international footprint in infectious disease research.
Characterization of SARS-CoV-2 N protein nuclear trafficking and its effect on cellular gene expression and screening for ACE2 inhibitors
- Marie-Louise Hammarskjold, Ph.D., Professor, Microbiology, Immunology and Cancer Biology
- David Rekosh, Ph.D., Professor, Microbiology, Immunology, and Cancer
- Ken Hsu, Ph.D., Associate Professor, Chemistry
A broadly applicable platform for reconstitution and high-resolution live-cell imaging of defined microbiome-host interfaces in physiologically relevant environments
- Andreas Gahlman, Ph.D., Assistant Professor, Chemistry, Molecular Physiology and Biological Physics
- Jim Nataro, MD, Ph.D., MBA, Professor, Pediatrics
- Graham Casey, Ph.D., Professor, Public Health Sciences
Advanced tissue culture models of the effects of pregnancy, lactation, infection, and inflammation on the maternal gut epithelium
- Sean Moore, MD, Professor, Division of Pediatric Gastroenterology
- Mark DeBoer, MD, Ph.D., Professor, Division of Pediatric Endocrinology
- Rebecca Pompano, Ph.D., Associate Professor, Chemistry
How can we best mitigate the effects of intimate partner violence under long-term shelter-in-place orders?
- Kathryn Laughon, Ph.D., RN, Associate Professor, School of Nursing
- Sarah Eaton, RN, Ph.D. student, Graduate Research Assistant, School of Nursing
Engineering the molecular architectures of antimicrobial peptide-polymer conjugates to balance potency, stability, and cytocompatibility
- Rachel Letteri, Ph.D., Assistant Professor, Chemical Engineering
- Molly Hughes, Ph.D., MD, Professor, Division of Infectious Diseases
- Matthew Crawford, Ph.D., Department of Medicine, SOM
- Anna Cliffe, Ph.D., Assistant Professor, Microbiology, Immunology and Cancer Biology
- Christopher Deppman, Ph.D., Professor, Biology
- William Petri, MD, Professor, Infectious Disease and Internal Health
- Linda Columbus, Ph.D., Professor, Chemistry
- Alison Criss, Ph.D., Professor, Microbiology, Immunology and Cancer Biology
- Peter Kasson, Ph.D., Associate Professor, Molecular Physiology and Biological Physics and Biomedical Engineering
- Anil Vullikanti, Ph.D., Professor of Computer Science
- Costi Sifri, MD, Professor and Director, Hospital Epidemiology
- Achla Marathe, Ph.D., Professor of Network Systems Science and Advanced Computing
Hospital-acquired infections (HAIs) of Clostridioides difficile and multidrug-resistant organisms such as carbapenem-resistant Enterobacteriaceae pose a significant burden to modern healthcare systems. Our goal is to develop an in-silico modeling framework for prediction of incidence rates and patient risk to healthcare-associated pathogens and evaluate interventions to control their spread. We will develop an agent-based modeling framework for pathogen transmission using high-dimensional clinical and network data and will harness it using machine learning to predict patients at risk of colonization and infection. We will also examine the socio-economic factors involved in HAI transmission through infection control measures across hospitals. The financial support by GIDI will bring together a multi-disciplinary team of researchers that includes Drs. Anil Vullikanti and Achla Marathe and infectious disease clinicians Drs. Costi Sifri and Gregory Madden to develop training sets and detailed simulations that will be the cornerstone of this project. The team hopes to explore multiple extramural funding opportunities to NSF and NIH to continue this work.
- Mami Taniuchi, Ph.D., Associate Professor of Medicine
The risk of adverse health outcomes, including enteric infections and diarrhea, due to exposure to contaminated drinking water sources among low-income households situated in economically distressed rural counties in rural Appalachia likely represents a greater threat to public health than is currently recognized. Our small-scale cohort and ethnographic study will help build a multidisciplinary understanding of water access, contamination, risk of enteric disease, and key sociocultural determinants to address the challenges associated with limited water access in this region. The work will generate key preliminary data. The GIDI Collaborative Seed grant will support the pilot fieldwork, specifically funding training opportunities, the inclusion of novel laboratory methods, and the ethnographic component.
- Christopher Moore, MD, Associate Professor of Infectious Diseases and International Health
- Joseph Moorman, MD, Professor of Cardiovascular Medicine
- N. Rich Nguyen, Ph.D., Assistant Professor of Engineering
Sepsis is a life-threatening organ dysfunction due to a dysregulated response to infection and is the leading cause of global mortality. Bloodstream infections (BSIs) are a frequent cause of sepsis. Symptoms of BSI are nonspecific, and published guidelines do not provide clear indications for obtaining blood cultures. This leads to a low diagnostic yield, with low true positive rate, and false positives lead to unnecessary antibiotic use, increased cost, and length of hospital stay. Using large physiological data from UVA ICUs, we identified 15 features associated with BSI.
We will use the data captured in the ICUs of multiple hospitals to develop stronger predictive models of BSI using deep learning. Our hypothesis is that our algorithms will lead to significantly better predictions of BSI than current methods. This GIDI award will bring together a robust team of clinical and computer science experts to determine predictive models of BSI by using big data and deep learning. The data generated from this grant will allow us to apply for independent funding to support this work through prospective validation and clinical trials.
- Henning Mortveit, Ph.D., Associate Professor of Engineering Systems and Environment
- Peter Beling, Ph.D., Professor and Associate Chair for Research of Engineering Systems and Environment
Policy makers that prepare responses to emergency situations need to have an understanding of the populations’ values, preferences and decision-making processes to implement effective interventions. Understanding the role of human behavior in epidemic outcomes has long been recognized as important, and is seen in the case of the COVID-19 pandemic. We will use a combination of data fusion techniques, large-scale agent-based simulation models, and inverse reinforcement learning to construct a framework that allows them to learn behaviors and responses to interventions so they can reshape responses and preferences to accomplish shared goals, including saving lives and maintaining a sustainable economy. This GIDI seed grant will allow us to generate a framework that will answer these questions. In the pilot work, synthetic populations will be used to prepare a calibrated, analytics and simulation platform; in follow-up work, surveys and sources such as social media data will be used to fine-tune models.
- Peter Kasson, MD/Ph.D., Associate Professor of Molecular Physiology and of Biomedical Engineering
- William Petri, MD/Ph.D., Vice Chair for Research, Department of Medicine, University of Virginia, Professor of Medicine, Microbiology, Immunology and Cancer Biology, and Pathology
SARS-CoV-2 infects humans via mucosal surfaces to cause COVID-19. Most vaccines in development, however, primarily target systemic immunity. Early successes in SARS-CoV-2 vaccine development suggest that these vaccines might protect against clinical disease but not transmission. In order to make a second-generation vaccine that protects against transmission as well as disease, we will leverage experience from studying other mucosal pathogens. We will design a mucosal-targeted vaccine candidate to protect against SARS-CoV-2 and future related viruses. By doing so, we hope to contribute to preventing not only COVID-19 disease in vaccinated individuals but also help interrupt transmission to others.
Increasing Access to Cervical Cancer Prevention through Innovative Technology in Rural Nicaragua: Culturally Tailored mHealth Approaches to Increase Impact
- Emma McKim Mitchell, PhD, MSN, RN
- Rebecca Dillingham, MD, MPH
- This project was awarded Undergraduate Research Award Supplement
Caused by high risk strains of Human Papillomavirus (HPV), cervical cancer is almost entirely preventable, yet significant morbidity and mortality persist in LMICs. Based on a long-term collaboration centered on access to care and cultural considerations for women's health on the Caribbean Coast of Nicaragua, we propose a novel combination of expertise on HPV screening and treatment (Mitchell), and an app/communication intervention (Dillingham) in order to: expand HPV DNA testing as primary screening in a culturally appropriate way to the Caribbean Coast of Nicaragua; implement telecolposcopy for women needing follow-up to decrease time to results communication and lost-to-follow-up rates; develop an app/communication intervention to decrease lost-to-follow-up rates and improve patient navigation; and to analyze the National cervical cancer registry in partnership with Movicancer.
- Bryan Lewis, PhD, MPH, Biocomplexity Institute & Initiative, UVA
- David Leblang PhD, Batten, CLAS
- Srini Venkatramanan, Research Scientist, Biocomplexity Institute & Initiative, UVA
Human mobility drives both spread and impact of infectious diseases, this is especially acute during complex humanitarian emergencies that displace people from their homes. We seek to undertake the development of a novel simulation framework that will bring together both migration attractors as well as repellers while simulating the spread of disease. We propose two case studies that will use this framework to estimate spread of disease across national borders and evaluate potential policy options.
- Nathan Swami (SEAS)
- Jason Papin (SOM)
- Steven Zeichner (SOM)
Translating Discovery to Therapy: Customization and Delivery of Multifunctional Chemokine-derived Peptides for Treating Wound Infections caused by Multidrug-resistant Bacterial Pathogens
- Molly Hughes (SOM)
- Shayn Peirce-Cottler (SOM)
- Donald Griffin (SEAS)
- Bob Nakamoto (SOM)
Personalized Medicine for Clostridium Difficile Infection with Real-time Diagnosis of Microbiome and Antibiotic Resistance Profiles
- Martin Wu (CLAS)
- Ann Hays (SOM)
- Cirle Warren (SOM)
- Sook Hoang (SOM)
- Farzad Hassanzadeh (SEAS)
- Jason Papin (SOM)
- Peter Kasson (SOM)
- Daniel Engel (SOM)
- Rebecca Pompano (CLAS)
- Young Hahn (SOM)
- John Lukens (SOM)