Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=4&sort=-keywords
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-keywords", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1397&sort=-keywords", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=5&sort=-keywords", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=3&sort=-keywords" }, "data": [ { "type": "Grant", "id": "6047", "attributes": { "award_id": "3U45ES006173-30S1", "title": "Promoting Health, Safety, and Recovery Training for COVID-19 Essential Workers and their Communities", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Environmental Health Sciences (NIEHS)" ], "program_reference_codes": [], "program_officials": [ { "id": 20625, "first_name": "Sharon", "last_name": "Beard", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "1992-09-01", "end_date": "2022-05-31", "award_amount": 143444, "principal_investigator": { "id": 20626, "first_name": "Kevin William", "last_name": "Riley", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 818, "ror": "", "name": "UNIVERSITY OF CALIFORNIA LOS ANGELES", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 818, "ror": "", "name": "UNIVERSITY OF CALIFORNIA LOS ANGELES", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "WRUC COVID Resource and Recovery Centers Project Summary/Abstract The overarching goal of this proposed initiative is establish a network of COVID Resource and Recovery Centers in the Western Region with the capacity to meet the critical needs of essential workers and communities disproportionately impacted by COVID-19. WRUC will achieve this goal through engagement with worker and community organizations that maintain trusted relationships with key target groups, many of whom have already pivoted their activities to respond to the COVID-19 crisis. The model we propose will extended much needed resources, training, and technical assistance to these organizations to maintain and expand these local efforts, while also promoting collaboration and exchange between participating network members.", "keywords": [ "COVID-19", "COVID-19 pandemic", "Collaborations", "Communicable Diseases", "Communities", "Disasters", "Disease Outbreaks", "Future", "Goals", "Health Promotion", "Modeling", "Recovery", "Resources", "Safety", "Training", "Trust", "community organizations", "coronavirus disease", "diversity and equity", "health equity", "member", "response" ], "approved": true } }, { "type": "Grant", "id": "6721", "attributes": { "award_id": "1R01AG071610-01A1", "title": "Effect of post-acute care pay for performance in skilled nursing facilities on outcomes and disparities", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute on Aging (NIA)" ], "program_reference_codes": [], "program_officials": [ { "id": 22477, "first_name": "Marcel", "last_name": "Salive", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-03-01", "end_date": "2025-11-30", "award_amount": 330148, "principal_investigator": { "id": 22478, "first_name": "Robert Edward", "last_name": "Burke", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 232, "ror": "https://ror.org/00b30xv10", "name": "University of Pennsylvania", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 232, "ror": "https://ror.org/00b30xv10", "name": "University of Pennsylvania", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Post-acute care (PAC) is increasingly common and costly. One in five Medicare beneficiaries receives care after hospitalization in a skilled nursing facility at a cost of more than $28 billion annually. Unfortunately, more than 1 in 4 Medicare beneficiaries are readmitted to the hospital within 30 days, and these readmissions are associated with increased mortality. The Skilled Nursing Facility Value-Based Purchasing program (SNF VBP) ties Medicare reimbursements to SNF to their 30-day all-cause hospital readmission rates. Determining the effect of SNF VBP on patient outcomes is crucial for patients, health systems, and policymakers, and will inform the development and implementation of similar programs in other post-acute care settings. Evaluating potential unintended consequences of this policy is especially important because SNFs face significant financial pressure, and SNFs that care for large proportions of patients who are especially vulnerable to adverse outcomes (e.g. frail, cognitively impaired, poor, or racial and ethnic minority populations) are most likely to be penalized under the program, potentially leading to increased disparities. The COVID-19 pandemic may have magnified the effects of SNF VBP, acting as a second “stress” on SNFs already stressed by SNF VBP. There is an urgent need to determine the effect of SNF VBP on patient outcomes and on disparities, especially given the magnifying effect of COVID-19. Our long-term goal is to drive the delivery of high-value care for all older adults leaving the hospital. SNF VBP is among the first pay-for-performance programs in post- acute care settings. In order to improve the development and success of these policies, it is crucial to understand how their design and implementation influences outcomes. Our central hypothesis, based on preliminary data, is that SNF VBP achieves its intended effects at SNFs that were already high-performing, but has unintended and negative effects at low-performing SNFs. Our specific aims are to: 1) Determine the impact of SNF VBP on intended outcomes prior to the COVID-19 pandemic; 2) Determine the effect of SNF VBP on disparities in outcomes in vulnerable populations; 3) Determine how financial penalties from SNF VBP impacted COVID-19 readiness and outcomes; and 4) Assess key aspects of organizational context among SNFs that improved performance in SNF VBP and explore how this impacted their response to COVID-19. Accomplishing these aims will improve the design of future VBP initiatives, and lead to higher-value care for the growing number of vulnerable older adults receiving SNF care.", "keywords": [ "COVID-19", "COVID-19 pandemic", "Caring", "Data", "Development", "Elderly", "Elements", "Face", "Fee-for-Service Plans", "Future", "Goals", "Health", "Health care facility", "Health system", "Home", "Hospitalization", "Hospitals", "Impaired cognition", "Incentives", "Individual", "Interview", "Lead", "Length of Stay", "Medicare", "Methods", "Outcome", "Patient-Focused Outcomes", "Patients", "Performance", "Policies", "Prevalence", "Process", "Readiness", "Schedule", "Shapes", "Skilled Nursing Facilities", "Stress", "Structure", "Testing", "Time", "Vulnerable Populations", "acute care", "adverse outcome", "base", "beneficiary", "care outcomes", "coronavirus disease", "cost", "design", "ethnic minority population", "evidence base", "hospital readmission", "improved", "improved outcome", "insight", "low socioeconomic status", "mortality", "patient population", "payment", "personal protective equipment", "pressure", "programs", "public health relevance", "racial and ethnic", "racial minority", "readmission rates", "response", "stressor", "success" ], "approved": true } }, { "type": "Grant", "id": "8090", "attributes": { "award_id": "75N92021C00001-P00004-9999-1", "title": "TO UPDATE THE PERFORMANCE WORK STATEMENT FOR RADX TECH PROJECT NO. 2643 - PATHOGENDX, INC. - PATHOGENDX COVID-19 MICROARRAY CLADE VARIANT DETECTION TE", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Biomedical Imaging and Bioengineering (NIBIB)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2021-02-22", "end_date": "2022-12-31", "award_amount": 590553, "principal_investigator": { "id": 23976, "first_name": "MILAN", "last_name": "PATEL", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1095, "ror": "", "name": "PATHOGENDX", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1095, "ror": "", "name": "PATHOGENDX", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true }, "abstract": "With PathogenDx's solution (DetectX-Rv), over the next four months, we will deliver a 25 fold increase in test capacity for the nation without increasing lab-real-estate footprint, without adding endless lines of testing systems that depreciate instantly, upholding the level of accurate testing needed, and a solution that can ‘flex’ to the demands of the market with the different sized SBS plates. What we propose is quadrupling test capacity twice on the same actual test substrate ~ optimizing the same SBS plate from 12 well array slides to 96 wells ultimately to a 384 well format in less than 4 months. Exercising this strategy will deliver 4.15M tests per month, and result in cost savings of 55% and 70% per test. As a comparison, to deploy the same capacity using qRT-PCR technology, it will cost RaDx five times as much in CapEx and three times more per test cost.", "keywords": [ "COVID-19", "Cost Savings", "Exercise", "Performance at work", "Quantitative Reverse Transcriptase PCR", "RADx", "RADx Tech", "Slide", "System", "Technology", "Testing", "Time", "Update", "cost", "variant detection" ], "approved": true } }, { "type": "Grant", "id": "8089", "attributes": { "award_id": "75N92021C00001-0-9999-1", "title": "TO UPDATE THE PERFORMANCE WORK STATEMENT FOR RADX TECH PROJECT NO. 2643 - PATHOGENDX, INC. - PATHOGENDX COVID-19 MICROARRAY CLADE VARIANT DETECTION TE", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Biomedical Imaging and Bioengineering (NIBIB)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2021-02-22", "end_date": "2022-02-21", "award_amount": 8919208, "principal_investigator": { "id": 23976, "first_name": "MILAN", "last_name": "PATEL", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1095, "ror": "", "name": "PATHOGENDX", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1095, "ror": "", "name": "PATHOGENDX", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true }, "abstract": "With PathogenDx's solution (DetectX-Rv), over the next four months, we will deliver a 25 fold increase in test capacity for the nation without increasing lab-real-estate footprint, without adding endless lines of testing systems that depreciate instantly, upholding the level of accurate testing needed, and a solution that can ‘flex’ to the demands of the market with the different sized SBS plates. What we propose is quadrupling test capacity twice on the same actual test substrate ~ optimizing the same SBS plate from 12 well array slides to 96 wells ultimately to a 384 well format in less than 4 months. Exercising this strategy will deliver 4.15M tests per month, and result in cost savings of 55% and 70% per test. As a comparison, to deploy the same capacity using qRT-PCR technology, it will cost RaDx five times as much in CapEx and three times more per test cost.", "keywords": [ "COVID-19", "Cost Savings", "Exercise", "Performance at work", "Quantitative Reverse Transcriptase PCR", "RADx", "RADx Tech", "Slide", "System", "Technology", "Testing", "Time", "Update", "cost", "variant detection" ], "approved": true } }, { "type": "Grant", "id": "2193", "attributes": { "award_id": "2028999", "title": "RAPID: COVID Information Commons (CIC)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Office of the Director" ], "program_reference_codes": [ "096Z", "7914", "9102" ], "program_officials": [ { "id": 5935, "first_name": "Lara", "last_name": "Campbell", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-05-15", "end_date": "2022-10-31", "award_amount": 200000, "principal_investigator": { "id": 3099, "first_name": "Florence D", "last_name": "Hudson", "orcid": "https://orcid.org/0000-0003-0896-2127", "emails": "[email protected]", "private_emails": "", "keywords": "['Data science', 'analytics', 'health', 'COVID', 'coronavirus', 'cybersecurity', 'connected healthcare', 'Medical Internet of Things', 'IoT', 'TIPPSS', 'Trust', 'Identity', 'Privacy', 'Protection', 'Safety', 'Security', 'data science', 'STEM', 'researcher collaboration']", "approved": true, "websites": "['https://covidinfocommons.net', ' https://nebigdatahub.org/about/']", "desired_collaboration": "", "comments": "Slack, google group, discord, CIC websiteThank you!", "affiliations": [ { "id": 196, "ror": "https://ror.org/00hj8s172", "name": "Columbia University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 5936, "first_name": "Jeannette", "last_name": "Wing", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 196, "ror": "https://ror.org/00hj8s172", "name": "Columbia University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "This project will create a COVID Information Commons (CIC) website to facilitate knowledge sharing and collaboration across various COVID research efforts, especially focusing on all the NSF-funded COVID Rapid Response Research (RAPID) projects. The CIC will serve as a resource for researchers as well as decision-makers from government, academia, not-for-profit and industry to leverage each other's findings, and invest in and accelerate the most promising research to mitigate the broad societal impacts of the COVID-19 pandemic. It will also serve as a model for integrated knowledge sharing and collaboration on other public health challenges, in benefit to society. Projects will be able to enter and publish information about their efforts in ways that are most relevant and user-friendly for a variety of potential stakeholders from academia, industry, government, and non-profit sectors. Information will be organized in multiple ways, for example, by research topics areas and by geography. In addition to information from NSF COVID-19 RAPID projects, the COVID Information Commons will incorporate coronavirus-related information from NSF Open Knowledge Network projects, as well as from other NSF research projects in general. The COVID Information Commons will utilize information science methods to bring together information about the collection of COVID-19 RAPID projects funded by the National Science Foundation. A wide array of research efforts are underway to study the impacts of the pandemic in fields as far ranging as biophysics, social justice/inequity, behavioral science, public health, supply chains, and risk management. The CIC will semantically link information across projects to provide a more holistic view across distinct efforts, including efforts such as the COVID projects in the NSF Open Knowledge Network. The resulting, concise, curated, integrated resource will provide insight into NSF-funded COVID RAPID projects and facilitate collaborations among such efforts. These objectives will be achieved using information science approaches to 1) compile a comprehensive list of NSF COVID RAPID awards, along with relevant details for each project, 2) link to any publicly available data sets and data feeds, 3) organize the information and data feeds, for example, by categories of research areas and/or geography, using a meta-data schema developed for the resource and existing taxonomy and semantic frameworks; 4) design and develop a web portal to allow project teams to publish their data, or links to the data, and present project information in ways that are most relevant and user friendly for researchers in academia, industry, and government; 5) integrate the schema.org COVID-19 annotated data to enable more effective identification, retrieval, and integration of relevant data. A Minimum Viable Product for the website will be developed first, working with stakeholders in the community to prioritize features and add new functionality. In addition to the Information Commons, the project will also assess the effort and feasibility of implementing a data and model commons—to share datasets as well as data-driven models, such as machine learning models related to COVID-19.This RAPID award is made by the Convergence Accelerator program in the Office of Integrative Activities with funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [ "COVID-19", "coronavirus", "researcher collaboration", "SARS-CoV-2", "Future pandemic prevention", "long COVID research", "COVID research and recovery" ], "approved": true } }, { "type": "Grant", "id": "9233", "attributes": { "award_id": "75N91020C00036-0-9999-1", "title": "DIGITAL HEALTH SOLUTIONS FOR COVID-19: DIGITAL HEALTH PASS AND SMARTER CONTACT TRACING SOLUTIONS", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Cancer Institute (NCI)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2020-09-14", "end_date": "2020-11-13", "award_amount": 792019, "principal_investigator": { "id": 24971, "first_name": "RON", "last_name": "GOETZEL", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1810, "ror": "", "name": "INTERNATIONAL BUSINESS MACHINES CORP", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1810, "ror": "", "name": "INTERNATIONAL BUSINESS MACHINES CORP", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "The goal of this project it to develop both a contact tracing and secure data exchange tools. The contact tracing solution securely combines data from a variety of sources (including manual self-report data, mobile device surveys, wearable devices, electronic health records) to enable tracing of contacts with individuals that have tested positive for COVID-19. The data exchange solution is a secure mechanism that empowers users to control the data they share in the course of their return to normal activities, including the ability to provide a verifiable health status claim. These tools are to be used by employers, government agencies, and others to evaluate the risk of allowing individuals to return to normal activities and also the ability to trace user contact with individuals diagnosed with or suspected of having contracted COVID-19. Data collected under this project will be deidentified and securely transmitted to an NIH data hub.", "keywords": [ "COVID-19", "Contact Tracing", "Contracts", "Data", "Data Reporting", "Diagnosis", "Electronic Health Record", "Goals", "Government Agencies", "Health", "Health Status", "Individual", "Manuals", "Patient Self-Report", "Risk", "Secure", "Source", "Surveys", "Testing", "United States National Institutes of Health", "data exchange", "data hub", "data sharing", "digital", "handheld mobile device", "tool", "wearable device" ], "approved": true } }, { "type": "Grant", "id": "9234", "attributes": { "award_id": "75N91020C00036-P00001-9999-1", "title": "DIGITAL HEALTH SOLUTIONS FOR COVID-19: DIGITAL HEALTH PASS AND SMARTER CONTACT TRACING SOLUTIONS", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Cancer Institute (NCI)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2020-09-14", "end_date": "2021-09-13", "award_amount": 4135490, "principal_investigator": { "id": 24971, "first_name": "RON", "last_name": "GOETZEL", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1810, "ror": "", "name": "INTERNATIONAL BUSINESS MACHINES CORP", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1810, "ror": "", "name": "INTERNATIONAL BUSINESS MACHINES CORP", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "The goal of this project it to develop both a contact tracing and secure data exchange tools. The contact tracing solution securely combines data from a variety of sources (including manual self-report data, mobile device surveys, wearable devices, electronic health records) to enable tracing of contacts with individuals that have tested positive for COVID-19. The data exchange solution is a secure mechanism that empowers users to control the data they share in the course of their return to normal activities, including the ability to provide a verifiable health status claim. These tools are to be used by employers, government agencies, and others to evaluate the risk of allowing individuals to return to normal activities and also the ability to trace user contact with individuals diagnosed with or suspected of having contracted COVID-19. Data collected under this project will be deidentified and securely transmitted to an NIH data hub.", "keywords": [ "COVID-19", "Contact Tracing", "Contracts", "Data", "Data Reporting", "Diagnosis", "Electronic Health Record", "Goals", "Government Agencies", "Health Status", "Individual", "Manuals", "Patient Self-Report", "Risk", "SARS-CoV-2 positive", "Secure", "Source", "Surveys", "Testing", "United States National Institutes of Health", "data exchange", "data hub", "data sharing", "digital health", "handheld mobile device", "tool", "wearable device" ], "approved": true } }, { "type": "Grant", "id": "9149", "attributes": { "award_id": "75N92020F00202-P00002-0-1", "title": "PROJECT MANAGEMENT SUPPORT FOR COMMUNITY ENGAGEMENT ON TRANS-NIH THERAPEUTICS AND VACCINE TRIALS", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Heart Lung and Blood Institute (NHLBI)", "NIH Office of the Director" ], "program_reference_codes": [], "program_officials": [], "start_date": "2020-07-29", "end_date": "2021-01-28", "award_amount": 4297649, "principal_investigator": { "id": 24920, "first_name": "DANIEL", "last_name": "SHINGLEDECKER", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1803, "ror": "", "name": "DELOITTE CONSULTING, LLP", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1803, "ror": "", "name": "DELOITTE CONSULTING, LLP", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "Project Management support in setting up community engagement programs focused on populations most impacted by COVID-19 for Trans-NIH therapeutics and vaccine trials.", "keywords": [ "COVID-19", "Communication", "Communities", "Complex", "Development", "Population", "Structure", "Therapeutic Trials", "United States National Institutes of Health", "community engagement", "meetings", "outreach", "programs", "tool", "vaccine trial" ], "approved": true } }, { "type": "Grant", "id": "9483", "attributes": { "award_id": "316201200036W-P00009-27200001-4", "title": "COVID 19 Supplement: The Immunology Databse and Analysis Portal (ImmPort)", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Allergy and Infectious Diseases (NIAID)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2019-09-30", "end_date": "2021-09-29", "award_amount": 286956, "principal_investigator": { "id": 25195, "first_name": "JEANETTE", "last_name": "FRANK", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": null, "abstract": "To develop a COVID-19 Data Compendium which will greatly support the COVID-19 research community by enabling secondary data reuse, large-scale meta-analysis, and interoperability across other COVID-19 data repositories.", "keywords": [ "COVID-19", "Collaborations", "Communities", "Data", "Data Set", "Immunology", "Meta-Analysis", "Metadata", "Research", "Resources", "Retrieval", "Visualization", "coronavirus disease", "data acquisition", "data and analysis portal", "data harmonization", "data modeling", "data repository", "data resource", "data reuse", "data standards", "interoperability" ], "approved": true } }, { "type": "Grant", "id": "7016", "attributes": { "award_id": "3U19AI089992-09S2", "title": "Core for COVID-19 Cohort IMPACC", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Allergy and Infectious Diseases (NIAID)" ], "program_reference_codes": [], "program_officials": [ { "id": 6484, "first_name": "Gang", "last_name": "Dong", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-05-14", "end_date": "2021-11-30", "award_amount": 940621, "principal_investigator": { "id": 22804, "first_name": "Charles S", "last_name": "Dela Cruz", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 452, "ror": "https://ror.org/03v76x132", "name": "Yale University", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 10421, "first_name": "David A.", "last_name": "Hafler", 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