Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1419&sort=funder
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=funder", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1419&sort=funder", "next": null, "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1418&sort=funder" }, "data": [ { "type": "Grant", "id": "12232", "attributes": { "award_id": "1R35GM151145-01", "title": "Large-scale phylodynamics under non-neutral and non-treelike models of evolution", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of General Medical Sciences (NIGMS)" ], "program_reference_codes": [], "program_officials": [ { "id": 24539, "first_name": "Ronald", "last_name": "Adkins", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-08-01", "end_date": "2028-05-31", "award_amount": 374491, "principal_investigator": { "id": 28104, "first_name": "Jonathan G", "last_name": "Terhorst", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 770, "ror": "", "name": "UNIVERSITY OF MICHIGAN AT ANN ARBOR", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true }, "abstract": "Technological breakthroughs such as next-generation sequencing have recently led to the creation of immense “BioBanks” featuring genomic information collected from hundreds of thousands of people, and the ongoing pandemic has resulted in an even more extreme repository containing over 10 million SARS-CoV-2 genomes. Unfortunately, existing techniques for inferring evolutionary models can, in most cases, only analyze a tiny fraction of the information contained in these datasets. At a time when we should be able to use vast quantities of data to answer increasingly nuanced evolutionary questions, lack of adequate methods has limited our opportunities for discovery and hampered our ability to respond to the ongoing pandemic. The proposed research addresses this problem through the creation of novel statistical and computational methods designed to study targeted evolutionary hypotheses using BioBank- and pandemic-scale datasets. First, we will develop new phylodynamic methods for epidemiological inference using tens of thousands of sampled pathogen genomes. Apart from being more scalable, these methods will innovate over previous work by being more biologically realistic and making fewer simplifying assumptions about the data. In particular, we will study systems where multiple strains co-circulate and have differential fitness, and we will use this model to improve our understanding of the role that natural selection has played in shaping the pandemic. We will further extend this method to integrate non-genetic sources of information such as case count data, which will enable public health researchers to partition case counts into different variants and estimate variant-specific effective reproduction numbers. Second, we will develop improved methods for inferring phylogenetic networks, and use them to understand the role that recombination has played in the evolution of the coronavirus, as well as its role in confounding earlier studies that incorrectly assumed that SARS-CoV-2 evolution could be represented by a single tree. All of these advances will be implemented and released as easy to use open source software packages. In summary, this work represents advances in several areas of statistical genetics including phylodynamic modeling, genetic epidemiology, inference of natural selection and phylogenetic network analysis, and will provide empirical researchers with modern tools needed to propel the next generation of discoveries in these fields.", "keywords": [ "2019-nCoV", "Address", "Area", "Computer software", "Computing Methodologies", "Coronavirus", "Data", "Data Set", "Epidemiologic Methods", "Evolution", "Genetic", "Genetic Recombination", "Genome", "Genomics", "Learning", "Methods", "Modeling", "Modernization", "Natural Selections", "Pathway Analysis", "Persons", "Phylogenetic Analysis", "Play", "Public Health", "Reproduction", "Research", "Research Personnel", "Role", "SARS-CoV-2 genome", "Sampling", "Shapes", "Source", "Statistical Methods", "System", "Techniques", "Technology", "Time", "Trees", "Variant", "Work", "biobank", "combat", "design", "fitness", "genetic epidemiology", "improved", "innovation", "next generation", "next generation sequencing", "non-genetic", "novel", "open source", "pandemic disease", "pathogen genome", "repository", "tool" ], "approved": true } }, { "type": "Grant", "id": "12233", "attributes": { "award_id": "1R16GM149432-01", "title": "Impacts of Social Determinants of Health and COVID-19 Pandemic Factors on Suicide Risk among Youth", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of General Medical Sciences (NIGMS)" ], "program_reference_codes": [], "program_officials": [ { "id": 23750, "first_name": "Irina N", "last_name": "Krasnova", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-08-01", "end_date": "2027-07-31", "award_amount": 136367, "principal_investigator": { "id": 28105, "first_name": "MARTIE P", "last_name": "Thompson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 426, "ror": "https://ror.org/051m4vc48", "name": "Appalachian State University", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true }, "abstract": "Suicide is a significant public health problem among youth. Data indicate suicidal behaviors were increasing among youth even before the COVID-19 pandemic began and have likely increased even more since its onset. This R16 proposed research seeks to address the urgent mental health crisis and respond to the recent advisories from the US Surgeon General that highlight the need for a better understanding of the impact of the pandemic on youth. We will meet this objective by pursuing the following specific aims: (1) Identifying the trajectory of suicide risk among youth across the pandemic period and testing if there have been differential changes based on demographics; (2) Determining how social determinants of health are related to suicide risk among youth; and (3) Characterizing the moderating and mediating roles of social determinants of health in the association between COVID-19 burden and suicide risk among youth. This research is innovative in several ways. First, it will apply a Social Determinants of Health framework and thus will widen the investigation of suicidal behavior risk factors beyond individual-level factors to include relevant social, economic, education, physical infrastructure, and healthcare risk factors, which have often been overlooked in COVID-19 mental health research with youth. Second, it will use real-time crisis response data to determine how suicide risk has changed over the course of the pandemic, an important asset given the reporting time lag involved with other data sources. Third, it will link data from large national databases (SDOH, Crisis Text Line, USAFacts) that each provides important and unique strengths (e.g., national, real-time, explores sexual orientation and race identity) to assess the direct, indirect, and interactive effects of social determinants of health and COVID-19 burden on suicidal behavior among youth. Our research team is particularly poised to undertake this investigation. The PI has extensive experience in suicide research, secondary data analysis, and mentoring students, and the Co-Investigators have experience using several of the proposed data sources and similar data analytic approaches as proposed. Further, Appalachian State University is an ideal institution to receive this award because Pell grants support 28% of its undergraduate students, it awards degrees in biomedical sciences, and has received only one NIH grant in the past two years.", "keywords": [ "Accident and Emergency department", "Address", "Age", "Appalachian Region", "Award", "COVID-19", "COVID-19 impact", "COVID-19 pandemic", "Cause of Death", "Communities", "Data", "Data Analyses", "Data Analytics", "Data Set", "Data Sources", "Databases", "Economics", "Education", "Environment", "Gender", "Grant", "Growth", "Health", "Healthcare", "Human Resources", "Individual", "Infrastructure", "Institution", "Investigation", "Lead", "Light", "Link", "Location", "Mediating", "Mental Health", "Modeling", "Persons", "Principal Component Analysis", "Public Health", "Publications", "Race", "Reporting", "Research", "Research Personnel", "Research Training", "Risk Factors", "Role", "Rural", "Rural Appalachia", "Science", "Sex Orientation", "Students", "Suicide", "Surgeon", "System", "Testing", "Text", "Time", "Training", "United States National Institutes of Health", "Universities", "Youth", "demographics", "digital mental health", "experience", "graduate student", "health disparity", "innovation", "multilevel analysis", "novel", "pandemic disease", "pandemic impact", "racial identity", "response", "sexual identity", "social", "social health determinants", "sociodemographic group", "student mentoring", "suicidal behavior", "suicidal risk", "suicide rate", "traumatic event", "undergraduate student" ], "approved": true } }, { "type": "Grant", "id": "12234", "attributes": { "award_id": "1R01AG083173-01", "title": "The Paycheck Protection Program and its Effects on Staffing Patterns and the Outcomes of Residents Living with Dementia", "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": 7229, "first_name": "Elena", "last_name": "Fazio", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-08-15", "end_date": "2028-04-30", "award_amount": 740150, "principal_investigator": { "id": 28106, "first_name": "Jason Raymond", "last_name": "Falvey", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 28107, "first_name": "Jasmine", "last_name": "Travers", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 167, "ror": "https://ror.org/0190ak572", "name": "New York University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": ". Nursing home staff shortages are well known to be an important factor impacting both the quality of care that nursing home residents receive, their health outcomes, and healthcare worker outcomes. Staffing shortages are compounded by limited financial resources in nursing homes, especially for smaller nursing homes, which was further exacerbated by the COVID-19 pandemic. These staffing shortages disproportionately impact nursing home residents living with Alzheimer’s disease and related dementias (ADRD) as they require more time from staff compared to care for residents who do not have ADRD. As the number of Americans living with ADRD increases, the need for fully staffed nursing homes that can provide quality care for older adults living with ADRD is now more important than ever. During public health emergencies, direct funding to nursing homes has been proposed as an expedient way to prevent staffing losses and maintain safety standards for residents. One federal policy mechanism utilized by nursing homes during the COVID-19 pandemic was the Paycheck Protection Program (PPP). The PPP loan program offers a unique natural experiment by which to evaluate the effectiveness and efficacy of a program that directly funds small businesses and in the case of this project, nursing homes, to maintain safe staffing levels during public health emergencies. While PPP loans were effective overall at keeping workers on the payroll across all US small businesses, it is unclear if the effects of the program were equitable across nursing homes in socioeconomically deprived neighborhoods which prior work from our team showed have lower staffing rates. Using robust econometric methods and an exploratory sequential mixed methods approach, the proposed project will assess the effectiveness and equity of PPP funding by 1) examining changes in staffing patterns and resident outcomes among nursing homes that received the PPP loans compared to nursing homes that did not and evaluating whether changes in staffing patterns and outcomes were equitable for those with ADRD living in the most socioeconomically deprived facilities; 2) qualitatively exploring facility strategies, tools, and social contexts that promoted resilience to declines in staffing and ADRD resident outcomes after receipt of PPP, and 3) quantitatively assessing the extent to which resilience strategies, cultures, and behaviors identified in Aim 2 are reflected in administrative actions about staffing and care for residents with ADRD, and how actions differed by neighborhood context. The overall goal is to develop a framework by which to guide future nursing home responses to public health emergencies that will improve staff patterns and subsequent ADRD outcomes in the most socioeconomically deprived/lowest-resourced neighborhoods.", "keywords": [ "Address", "Alzheimer&apos", "s disease related dementia", "American", "Area", "Behavior", "Businesses", "COVID-19", "COVID-19 pandemic", "Caring", "Characteristics", "Clinical", "Data", "Dementia", "Development", "Diagnosis", "Disasters", "Disparity population", "Economic Factors", "Economics", "Effectiveness", "Elderly", "Eligibility Determination", "Emergency Situation", "Equity", "Event", "Excess Mortality", "Funding", "Future", "Goals", "Health", "Health Personnel", "Health Services Research", "Health care facility", "Home Nursing Care", "Hour", "Individual", "Infrastructure", "Intervention", "Interview", "Leadership", "Medicare", "Methods", "Natural experiment", "Neighborhoods", "Nurse Administrator", "Nursing Homes", "Nursing Staff", "Outcome", "Pattern", "Phase", "Policies", "Population", "Preparation", "Public Health", "Qualitative Research", "Quality of Care", "Reporting", "Resources", "Safety", "Shock", "Social Environment", "Structure", "Survey Methodology", "Surveys", "Time", "Work", "cohort", "community-level factor", "deprivation", "design", "econometrics", "economic disparity", "effectiveness evaluation", "experience", "federal policy", "health disparity", "improved", "improved outcome", "indexing", "mortality", "nursing care quality", "pandemic disease", "prevent", "programs", "promote resilience", "public health emergency", "resilience", "resilience factor", "response", "socioeconomics", "telehealth", "tool", "ventilation" ], "approved": true } }, { "type": "Grant", "id": "12235", "attributes": { "award_id": "1R13AI179176-01", "title": "11th Annual Meeting of International Cytokine & Interferon Society", "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": 23719, "first_name": "Susan F.", "last_name": "Cooper", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-08-15", "end_date": "2024-07-31", "award_amount": 5000, "principal_investigator": { "id": 28108, "first_name": "James K", "last_name": "Turkson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 766, "ror": "https://ror.org/02pammg90", "name": "Cedars-Sinai Medical Center", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "The purpose of this application is to request financial support for Cytokines 2023: 11th Annual Meeting of the International Cytokine & Interferon Society (ICIS), October,15-18, 2023, with llivestream and on-demand virtual access through October 29, 2023. This Annual Meeting helps bridge the gap between the scientists performing basic research on molecular and cellular mechanisms of immune cell activation and function with those working to develop this knowledge into novel therapies. The 11th edition comes at a time when cytokine biology, cytokine biomarkers and cytokine therapeutics are revolutionizing modern medicine, providing novel treatments for a wide variety of diseases ranging from lethal inflammatory, autoimmune and allergic diseases, to viral infections and cancer. This year’s theme is “Cytokines and interferons in the precision medicine era”, focusing on the latest developments on cytokine biology in relation to immune regulation, host damage and disease, and the latest progress on cytokines/cytokine inhibitors as novel therapeutics in the clinic. A variety of topics will be covered by leaders in the field in the plenary and parallel sessions such as innate immunity and host defense, adaptive immunity, cytokines in T and B cell responses to vaccination, in Long COVID, HIV and novel targeted therapies from cancer immunotherapy to novel therapeutics in autoimmunity. Since a major goal of the meeting is to promote interactions between scientists and clinicians working in basic, translational or applied research, ample opportunity will be given to poster networking sessions to present the latest advances elated to cytokine research, biomarkers and therapeutics. Greater understanding of mechanisms of disease and novel concepts for therapy have and will continue to emerge from interdisciplinary gatherings where advances can be presented and discussed by established and trainee scientists. The meeting will focus on cytokines in personalized medicine and will provide an opportunity for updates on the development of novel therapeutic interventions in these fields and help spur international collaborations among the meeting participants. Although meeting participants will have primary interests in infectious diseases, cancer and immune-mediated diseases, the program integrates speakers on the periphery of Cytokine and Interferon research to help bridge these disciplines. This interdisciplinary environment is particularly interesting for early career researchers who are not only focused on their own field of research but are beginning to think about the wider implications of their work. Our goal is to increase attendance of early career investigators and trainees and also to achieve higher representation of underrepresented minorities at all levels of career development. Online presentations will consist of livestreamed video presentations for all speakers who give their permission to be recorded, to benefit virtual attendees as well as in-person attendees to access content from parallel sessions or missed presentations. ICIS Meetings Committee and Council have decided that included virtual access even without travel restrictions, makes the Annual Meeting more inclusive and sustainable.", "keywords": [ "Allergic Disease", "Amaze", "Applications Grants", "Applied Research", "Arthritis", "Authorization documentation", "Autoimmune Diseases", "Autoimmunity", "Award", "B-Lymphocytes", "Basic Science", "Biological Markers", "Biology", "Biotechnology", "Budgets", "COVID-19", "COVID-19 impact", "Chronic Disease", "Clinic", "Clinical Research", "Collaborations", "Communicable Diseases", "Country", "Cytokine Network Pathway", "Data", "Development", "Diabetes Mellitus", "Discipline", "Disease", "Event", "Feedback", "Financial Support", "Future", "Goals", "Government", "Greece", "HIV", "Hawaii", "Health", "Host Defense", "Human", "Hybrids", "Immune", "Infection", "Inflammation", "Inflammatory", "Institution", "Interferons", "International", "Intuition", "Kidney Diseases", "Knowledge", "Lightning", "Lobbying", "Long COVID", "Love", "Malignant Neoplasms", "Mediating", "Modern Medicine", "Molecular", "Natural Immunity", "Parents", "Participant", "Persons", "Pharmacologic Substance", "Proteins", "Qualifying", "Reporting", "Research", "Research Personnel", "Rheumatoid Arthritis", "Role", "Scientist", "Societies", "Students", "T-Lymphocyte", "Therapeutic", "Time", "Translational Research", "Travel", "Underrepresented Minority", "Update", "Vaccination", "Viral Cancer", "Virus Diseases", "Work", "adaptive immunity", "cancer immunotherapy", "career", "career development", "collaborative environment", "cost", "cytokine", "design", "digital platform", "exhibitions", "flexibility", "fundamental research", "immune activation", "immunoregulation", "inhibitor", "interest", "live stream", "meetings", "multidisciplinary", "new therapeutic target", "novel", "novel therapeutic intervention", "novel therapeutics", "personalized medicine", "posters", "precision medicine", "programs", "response", "symposium", "targeted cancer therapy", "therapeutic target", "virtual", "virtual platform" ], "approved": true } } ], "meta": { "pagination": { "page": 1419, "pages": 1419, "count": 14184 } } }