Stanford Medicine scientists have launched dozens of research projects as part of the global response to COVID-19. Some aim to prevent, diagnose and treat the disease; others aim to understand how it spreads and how people’s immune systems respond to it.
Below is a curated selection, including summaries, of the projects.
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To improve our ability to determine who has COVID-19 and treat those infected.
Track COVID study
Yvonne Maldonado, MD
Researchers at Stanford, UC-San Francisco and the Chan Zuckerberg Biohub have begun a study to track changes in San Francisco Bay Area SARS-CoV-2 infection rates over a nine-month period. The participants will receive monthly diagnostic tests to identify current infection and serological tests to determine previous infection. Researchers are also sequencing the viral genomes from all participants who test positive to help understand how the virus has spread and whether co-infections with other viruses play a role in the illness. The study is being led by Maldonado at Stanford and George Rutherford, MD, at UC-San Francisco.
Building COVID-19 testing capacity both locally and nationally
Benjamin Pinsky, MD, PhD
Pinsky’s team is focused on building COVID-19 testing capacity, both locally and nationally. They are collaborating with other clinical laboratories to ensure these labs can meet the requirements of the Food and Drug Administration for COVID-19 clinical testing. The group is also working with various collaborators to develop and evaluate novel methods for the diagnosis of COVID-19, as well as methods to assess immune protection and to predict the severity of disease.
Maldonado, Altamirano, Govindarajan and Blomkalns are investigating three swab techniques used during COVID-19 testing: a self-collected nasal swab performed with the aid of an instruction sheet; a health care worker-collected nasal swab; and a health care worker-collected oropharyngeal swab. Should self-collected nasal swabs prove as effective as those collected by health care workers, patients may be able to safely and effectively collect specimens outside of health care settings.
Lung function in people infected with SARS-CoV-2
Carlos Milla, MD
Milla and his team are evaluating whether improvements they’ve made in a lung function test can more successfully and safely identify subjects at high risk of severe COVID-19 disease, even when disease is in its early, asymptomatic stage. Standard tests involve inhaling deeply and quickly exhaling as much air as possible. The Milla lab’s improvements allow subjects to simply breathe passively for a few seconds through a mouthpiece. This not only makes the test feasible for sick subjects but also minimizes the generation of aerosols.
Machine-learning-based evaluation for COVID-19
Niaz Banaei, MD
Banaei’s group is using machine learning to develop a web tool that uses non-SARS-CoV-2 test results (such as blood cell counts and other available tests) to rule out COVID-19 infection with high accuracy. The goal is to provide health care workers another, possibly faster, option for screening individuals for COVID-19.
Development of rapid at-home testing for COVID-19
William Greenleaf, PhD
Greenleaf is leading an effort to develop new methods of COVID-19 detection at the point of care to help get around current supply chain problems and allow for rapid screening. The kit in development is meant to function directly in sample swabs and, in principle, could be done at home or in decentralized clinics if users were taught proper swabbing techniques.
Snyder and his team will track biological parameters of individuals who are ill with COVID-19 or at risk for the disease using a smart watch. Their goal is to determine whether they can tell if the smart watch user is becoming ill based on measurements such as heart rate.
To better prevent and understand the transmission of the coronavirus.
Natural history of shedding and household transmission of COVID-19: Constructing patterns of viral spread and evolution
Yvonne Maldonado, MD
Maldonado’s team will combine genomic and epidemiologic data to address questions about the transmission and evolutionary dynamics of COVID-19. Her team plans to use whole-genome sequencing to understand how COVID-19 mutates during the early stages of infection, as well as generate a bio-repository of specimens and associated clinical and epidemiologic data for use in understanding the transmission of COVID-19.
Repurposing snorkel masks for personal protective equipment
Manu Prakash, PhD, and University of Utah collaborators
Prakash and his lab are repurposing full-face snorkel masks as reusable personal protective equipment for healthcare workers to help combat the shortage of personal protective equipment in hospitals. To ensure protection against airborne pathogens, the group is 3D-printing N95 filter attachments that are fitted to the snorkel masks. The prototypes are currently being tested in the three clinics currently.
Novel aerosol capture tools for understanding COVID-19 infectiousness
Jason Andrews, MD, SM
Andrews’ group is developing and validating tools to capture airborne biological particles and characterize infectiousness, with the goals of understanding predictors and determinants of infectiousness and potentially monitoring environments for presence of SARS-CoV-2.
Vaccination and Treatment
To improve our ability to prevent COVID-19 and treat those infected.
Nadeau and Ahuja are conducting a randomized, double-blind, placebo-controlled phase 2 trial to evaluate the safety and efficacy of the Ebola drug remdesivir in hospitalized adult patients diagnosed with COVID-19. The study is sponsored by the National Institutes of Health and is a multicenter trial that will be conducted at as many as 50 sites globally.
Subramanian and Grant have been conducting two multicenter, randomized, phase 3 clinical trials of an anti-viral medication, remdesivir. They are following patients to see how quickly they improve to the point of no longer needing oxygen or hospitalization. These trials, supported by Gilead Sciences, are being conducted at 100 centers worldwide. Stanford Medicine has been enrolling patients since March 14.
Camarillo and Van Wert have undertaken a project to design and build simplified, rapidly scalable, single-use ventilators to help address the broad shortage of ventilators nationwide. The team aims to create machines that hospitals can use to save lives when standard ventilators are unavailable. The Chan Zuckerberg Biohub is supporting this work.
Clinical trial of novel therapeutic for mild COVID-19 infection to prevent severe disease and reduce viral shedding
Upinder Singh, MD; Julie Parsonnet, MD; Jason Andrews, MD; Prasanna Jagannathan, MD; and other clinical collaborators
Singh’s team is conducting a trial of a novel therapeutic called Lambda, a broad-spectrum anti-viral compound that’s been given to more than 3,000 patients in clinical trials of hepatitis viruses, for efficacy in outpatients with mild COVID-19. In vitro and animal-model data suggest Lambda may also inhibit replication of respiratory viruses, such as the COVID-19 virus. The team plans to perform a phase 2 randomized controlled trial of Lambda among outpatients with mild COVID-19 to determine whether the drug reduces the duration of symptoms, viral shedding and the risk of hospitalization.
Defining the therapeutic potential of host-targeted approaches for combating COVID-19
Shirit Einav, MD
Einav’s lab is researching repurposed and novel anti-viral approaches targeting two cellular kinases that are an Achilles' heel of multiple unrelated RNA viruses. Their data show that a combination of two already-approved anti-cancer drugs that act against these kinases inhibits replication of multiple viruses in vitro and reduces mortality in mice infected with the dengue or Ebola viruses. The lab has also been developing more selective compounds that target these cellular kinases and have potent activity against multiple RNA viruses, including flaviviruses and coronaviruses, both in vitro and in human primary cells.
Specimen collection during COVID-19 clinical trials and lab biosafety enhancements
Catherine Blish, MD, PhD; with Aruna Subramanian, MD; Philip Grant, MD; Angela Rogers, MD; and other clinical collaborators
Subramanian and Grant are co-principal investigators of a Gilead-sponsored clinical trial that evaluates the safety and efficacy of using the Ebola drug remdesivir to treat patients with COVID-19. In parallel with these trials, Blish wants to collect specimens, such as blood and stool samples, and later expand collection to individuals outside of the trials. These bio-specimens will be crucial in understanding the biological underpinnings of this virus.
Glenn is preparing two potential COVID-19 drugs for clinical trials: a lipid kinase inhibitor that could be used to combat COVID-19 and other viruses, and a locked nucleic acid, similar to one that he has successfully developed to target every known strain of the flu and that could potentially be used during any flu pandemic. Both of these drugs could treat multiple viruses and strains, have high barriers to resistance, and, in some cases, could be used in nonviral applications.
Coronavirus antiviral research database
Robert Shafer, MD
Shafer’s team has created an online database of compounds with proven or potential anti-COVID-19 activity. The compounds include targeted anti-virals, repurposed drugs, investigational agents and other compounds that inhibit virus replication. The data come from published biochemical, cellular, small animal, nonhuman primate and human clinical studies. The goal of the database is to provide a uniform way to report experimental results, enabling comparisons between different compounds and allowing prioritization for further development.
Using artificial intelligence to predict drugs that may inhibit COVID-19
Russ Altman, MD, PhD, and other collaborators
Altman and his group have used artificial intelligence to computationally predict six drugs that could inhibit TMPRSS2, a protein that plays a key role in SARS-CoV-2 infections. Altman and his collaborators outside of Stanford Medicine plan to conduct experimental follow-up studies to explore the efficacy of two of the drugs in blocking SARS-CoV-2 from causing infection. While promising, the potential drugs are still part of a preliminary computational analysis and would be dangerous to use clinically at this time.
The Chang and Das labs are engaging participants of the online-gaming platform Eterna to understand how the RNA genome of SARS-CoV-2 virus might change during the pandemic. Eterna educates and enables its players to “be the virus,” simulating how it shifts its sequence over time to evade diagnostics, therapeutics and vaccines being developed to fight COVID-19. The project seeks to provide RNA-structure-informed predictions and analyses that are not available through other computational efforts, while engaging and educating millions of citizens worldwide through compelling puzzles.
To better understand how the coronavirus is spreading.
Stanford Medicine National Daily Health Survey for Coronavirus
Lawrence “Rusty” Hofmann, MD
Hofmann is leading an effort to track COVID-19 symptoms nationally using self-reported data from a daily, digital survey. The goal is to create a novel coronavirus heat map that can be used to target and inform national efforts and public health interventions. The creation of this data set is dependent on participation across Stanford Medicine and our broader communities.
Genomic surveillance to identify silent transmission clusters of COVID-19
Jason Andrews, MD, MS
Andrews’ team is developing and testing novel tools that utilize microbial whole-genome sequences to identify chains of transmission between individuals. Andrews proposes to work with local hospitals and the state and county health departments to perform whole-genome sequencing on all COVID-19-positive samples and apply these methods in real-time to characterize transmission chains and help guide public health investigations.
Linos and her team are developing a website with reliable public health information about COVID-19 and surveys about the social and behavioral impact of the evolving pandemic. They also plan to share survey results to directly inform public health practitioners, health care systems, clinicians and policymakers about the informational, social and health needs of community members in their regions.
Snyder and his group plan to track different variants and strains of COVID-19 and quantitatively determine which ones correlate with different phenotypes, such as levels of pathogenicity. His team also plans to study the false negative rate of COVID-19, seeking to better understand how many people receive a false negative test result during early stages of the disease.
COVID-19 and Stanford WELL for Life study to understand the effects of shelter-in-place on well-being
Ann Hsing, PhD
Hsing and the Stanford WELL for Life team are investigating the effect of COVID-19 and the shelter-in-place order on well-being. They are surveying existing Stanford WELL for Life participants (about 5,000) with the WELL questionnaire, which measures distress and multiple dimensions of well-being longitudinally at six time points over the next 12 months. This approach will enable the evaluation of the short- and long-term effects of COVID-19 quarantine and social distancing on emotions, social connectedness and physical health.
The Bhatt group and collaborators are investigating whether SARS-CoV-2 was circulating through oral-fecal cycles in the Bay Area community. The lab plans to screen stool samples collected through a biobank at Stanford for signs of SARS-CoV-2 from December 2019 through December 2020. Depending on sample availability, the team also plans to research whether a patient’s gut microbiome composition affects gastrointestinal symptoms of COVID-19, as well as other details about how the virus sheds.
Data Science and Modeling
To better predict medical, fiscal and resource-related outcomes of the COVID-19 pandemic.
Shah and Maldonado are hoping to better anticipate the evolution of the COVID-19 pandemic. Existing predictions of the pandemic are uncertain due to many factors, such as a lack of plentiful and optimal data and the fact that models vary depending on the location. The scientists are creating a platform that combines diverse inputs to quantify the effects of the shelter-in-place order. The goal is to create more accurate, higher-resolution models about COVID-19 pandemic parameters.
Continuous symptom profiling of patients screened for SARS-CoV-2
Nigam Shah, PhD
Shah’s team is analyzing medical notes describing symptoms of patients screened and tested for SARS-CoV-2 at Stanford Medicine. They want to determine if combinations of symptoms are predictive of SARS-CoV-2 test results to assist screening in low-resource settings. They also hope to use information from the medical notes — such as symptoms, duration of disease, travel history and more — to anticipate which patients will require admission or eventual ICU care.
Enhancing the public health data ecosystem for COVID-19 prevention
Lorene Nelson, PhD
Nelson and her team are building an integrated geospatial data ecosystem for examining geographic clustering and unequal burden of COVID-19 by income, race/ethnicity, household crowding and other social determinants of health. They will begin with Santa Clara and Solano counties, but the system is scalable to all 58 California counties. This work will enable public health agencies to identify risk factors for SARS-CoV-2 infection and predict and prevent future outbreaks.
A group of faculty members at Stanford Health Policy, including Joshua Salomon and David Studdert, as well as graduate and medical students, are working with Fernando Alarid-Escudero and his group at the Center for Research and Teaching in Economics, in Mexico, to provide high-quality modeling of the epidemiology of COVID-19. Their work encompasses diverse populations and geographies, including California, Mexico and India. The model incorporates realistic demography and patterns of contacts and disease transmissions, as well as nonpharmaceutical interventions, such as social distancing.
Utilizing radiological imaging of COVID-19 patients for allocation of hospital resources
Matthew Lungren, MD, MPH
Lungren and his collaborators are using machine learning to analyze CT scans, X-rays and clinical data of COVID-positive patients to predict the risk of respiratory failure or the need for supportive treatment. Their goal is to help direct the allocation of hospital resources, including decision-making on admission and use of intensive care resources.
Analysis of COVID-19 CT scans and X-rays for classification and prediction of patient outcomes
Matthew Lungren, MD, MPH
Lungren and his collaborators are using imaging and clinical data to predict the risk of respiratory failure, mortality and length of hospital admission among patients with COVID-19. In addition, they aim to quantify CT scans of COVID 19 patients and auto-generate medical reports and correlate the scans to clinical outcomes, such as infection.
Hernandez-Boussard and Desai will use data that shows the time of hospital admission up to the time of mechanical ventilation to predict patient recovery, details of hospital discharge and survival at 24 hours, 7 days, and later. This model will include important factors for COVID-19 recovery and will be continuously updated in real-time as emerging data become available. In the event of resource scarcity, this effort has the potential to inform optimal resource allocation at Stanford Health care.
Hernandez-Boussard and Desai plan to use data from patients who tested positive for COVID-19 at Stanford Health Care to investigate how disease burden varies significantly in patients infected with the virus. Currently, the association of co-infections, symptomatology, comorbidities and other parameters on patient trajectories is unknown.
School closures help reduce peak hospital bed demand, but they can unintentionally cause health care worker absenteeism for those with children. Huynh and Chin are examining the economic feasibility of child care subsidies, as well as the policy effects of child care interventions on absenteeism at Stanford Health Care.
Carmichael and Asch are investigating the connection between unusual symptoms of COVID-19 and the frequency that those cases become ambulatory patients with severe respiratory failure or impending severe respiratory failure. Their objective is to describe clinical factors that may identify people with COVID-19 predisposed to severe respiratory failure outside the hospital.
Chang and Lu and their collaborators are collecting clinical questions related to COVID-19 that can be addressed through observational electronic health record data. The group is investigating connections between the disease and low levels of lymphocytes, lower cholesterol and abnormal chest X-rays. If you would like to submit a question, please do so here. A list of questions that have been submitted can be found here. Student submissions can be found here. For questions, please contact firstname.lastname@example.org.
COVID-19 imaging utilization per patient admission
Matthew Lungren, MD, MPH
Lungren and his team are building a dashboard for real-time visualization of COVID-19 radiological imaging at Stanford Hospital. The tool will aid the hospital’s resource planning by forecasting the impact of incoming patients on bed use and by predicting expected radiological image use. The team will create a web-based dashboard that will be implemented at Stanford Hospital for better radiological resource management.
To better understand immune responses to the coronavirus.
Kuo, Amieva and Blish are recreating the SARS-CoV-2 infection in three-dimensional human mini-organs, or “organoids.” SARS-CoV-2 is the virus that causes COVID-19. Kuo and Amieva are investigating details behind how the virus infects human lung and intestinal tissues through organoid models, and Blish is studying the response of individual cells infected with SARS-CoV-2.
Systems biological “multi-omics” analysis of immunity to COVID-19 infection
Bali Pulendran, PhD
Pulendran is investigating the interaction between the human immune system and the SARS-CoV-2 virus through systems-biological methods. His group will use a “multi-omics” approach to probe the host immune system response to SARS-CoV-2 during asymptomatic and symptomatic phases of infection. Their goal is to determine why some people get more severe symptoms than others and to identify biomarkers that predict disease severity in vulnerable populations. His group will also study the immune mechanisms by which vaccines confer protection against SARS-CoV-2.
Deep omics profiling to determine the genomic factors at play in disease severity
Euan Ashley, MB ChB, DPhill; Victoria Parikh, MD; Matthew Wheeler, MD; Carlos Bustamante, PhD; and Manuel Rivas, DPhil
Ashley, Parikh and their team are sequencing genomic information from SARS-CoV-2 and human hosts to better understand the diversity of host responses to the virus. Their work aims to better elucidate genomic details underlying COVID-19 disease severity. To do so, the team will collect de-identified omic and clinical data for 1,000 Stanford patients who tested positive for COVID-19-, including hospitalized patients and patients who were in the intensive care unit.
The Snyder group will collect biological samples from individuals ill with COVID-19 and those most at risk for the disease, observing and assessing levels of certain molecules involved in several biological pathways, including metabolism and immune function. The team will use this information to create “omics” profiles to look for potential molecular signatures of COVID-19 infection, as well as signs that an individual might have a strong adverse reaction to the virus.
Chang, Pinksy Boyd and Satpathy are collaborating with the company 10x Genomics to study the immune response to the coronavirus through single-cell genomics and clinical assays. The team will track immune responses in about 100 patients with COVID-19, performing in-depth molecular analyses of cells and blood samples.
Role of antibodies in SARS-CoV-2 infection and COVID-19 disease
Taia Wang, MD, PhD
Wang and her group are studying molecules that correlate with immunity against COVID-19. Their studies focus on defining a protective antibody response, and they will investigate whether antibodies have a role in determining the severity of COVID-19. The overarching goal of this work is to guide the development of vaccines and monoclonal antibody therapeutics against SARS-CoV-2.
Nolan and his team are applying multiplexed technologies to achieve in-depth profiling of immune responses to SARS-CoV-2 in nonclinical and clinical studies. Their goal is to identify immune markers associated with outcomes for COVID-19 and understand the arrangement of immune cells relative to lung tissue cells during infection.
Kin and Streett are exploring how people with inflammatory bowel diseases, including people with Crohn's disease and ulcerative colitis whose treatment frequently involves chronic immunosuppressive therapies, are affected by the COVID-19 outbreak. The study aims to understand the primary concerns that patients with inflammatory bowel diseases have about their illnesses and treatments as they relate to the COVID-19 epidemic so that physicians and the health care team can effectively engage them in shared decision-making.
To better understand the way the virus affects the cardiovascular system.
Wu and Nguyen are researching cardiovascular complications of COVID-19. The scientists are addressing the relationship between SARS-CoV-2 infection in heart muscle and vascular cells and the consequences of taking common drugs for high blood pressure. Their research employs muscle and vascular cells derived from human induced pluripotent stem cells to determine how these blood pressure drugs affect the virus’ ability to enter cells.
To better enable the workforce to achieve its goals during the COVID-19 pandemic.
Bondy, Nelson and Goodman have launched a national survey that aims to assess how the COVID-19 pandemic is affecting the population physically, socially, emotionally and financially. The team’s survey is hosted by an app, called Apollo, that’s designed to screen patients at drive-through COVID-19 testing sites.
Caregiver survey COVID-19
Ranak Trivedi, PhD
Trivedi and her team are conducting an anonymous online survey to better understand the experiences of informal caregivers during the COVID-19 pandemic. Informal caregivers are family members or friends who provide significant help to people with mental or physical health conditions. Trivedi aims to use the results of the survey to guide advocacy efforts in support of informal caregivers. A link to the approximately 20-minute survey, which can be taken from anywhere in the world, is available at https://is.gd/stanfordcaregiverstudy.
Optimized remote work during the COVID-19 pandemic
Pablo Paredes, PhD
Paredes and collaborators are creating digital tools to support and maintain productivity levels while managing stress associated with the COVID-19 pandemic, social distancing and long-term telecommuting. The researchers propose a collection of tools, dubbed “Home Sweet Office,” that can support personal productivity by managing procrastination caused by online behaviors, such as overuse of social media, and provide stress-management tactics and emotion-regulation interventions.
Adamson and her lab are studying the global impact of psychological stress during the COVID-19 crisis. They are using an eight- to 10-minute survey to help evaluate individual stress levels caused by factors related to remote work, homeschooling and dependent care.
Impact of COVID-19 pandemic on sleep and mental health
Andrea Goldstein-Piekarski, PhD
Goldstein-Piekarski and the Computational Psychiatry and Neuroimaging Sleep Lab (CoPsyN Sleep Lab) are conducting a survey-based study examining the short- and long-term impacts of the COVID-19 pandemic and the shelter-in-place orders on sleep, mood and quality of life. The data collected in this study will also help identify factors that predict the development of chronic sleep problems and other negative mental health outcomes arising from stressful life events.
A variety of other research projects related to the COVID-19 pandemic.
Cholankeril, Podboy and Ahmed aim to characterize the gastrointestinal symptoms associated with SARS-CoV-2 infection. Nearly one-third of patients in their study had gastrointestinal symptoms while infected with SARS-CoV-2. The team also saw mild elevations in liver enzymes in some patients, which may correlate with a need for a higher level of care. The group is continuing to investigate if gastrointestinal symptoms and liver enzyme abnormalities at presentation could be associated with increased severity of illness, requiring an escalation of care or higher rate of health care utilization.
The scientists published a research letter that reports on how often patients infected with the coronavirus in Northern California are co-infected with other respiratory pathogens. Results of their analysis suggest higher rates of co-infection than previously reported, with no significant difference in rates of SARS-CoV-2 infection in patients with and without other pathogens. The study indicates that the presence of a non–SARS-CoV-2 pathogen does not provide reassurance that a patient isn’t also infected with SARS-CoV-2.
The list isn’t comprehensive and instead represents a portion of Stanford Medicine research on COVID-19. This page is frequently updated.
If you are a Stanford Medicine scientist and would like to see your research included here, please send a note to: email@example.com
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At this time, many new projects and collaborations are being launched to address the pandemic. The Stanford Institute for Human-Centered Artificial Intelligence has created a webpage for COVID-19 research collaborations and other opportunities, such as research positions, internships and funding. If you would like to submit an opening please use the following form and they will post it on their website.