Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1405&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=1442&sort=funder", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1406&sort=funder", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1404&sort=funder" }, "data": [ { "type": "Grant", "id": "11755", "attributes": { "award_id": "1R01DC020701-01A1", "title": "Determining the ototoxic potential of COVID-19 therapeutics using machine learning and in vivo approaches", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute on Deafness and Other Communication Disorders (NIDCD)" ], "program_reference_codes": [], "program_officials": [ { "id": 27630, "first_name": "Nancy", "last_name": "Freeman", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-06-07", "end_date": "2028-05-31", "award_amount": 400317, "principal_investigator": { "id": 27631, "first_name": "ALLISON B", "last_name": "COFFIN", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 306, "ror": "https://ror.org/05dk0ce17", "name": "Washington State University", "address": "", "city": "", "state": "WA", "zip": "", "country": "United States", "approved": true }, "abstract": "There are over 900 drugs and drug combinations currently in clinical trials for COVID-19. While this pace of drug development is necessary, it also comes with increased risk of producing therapies with significant side- effects. One likely side-effect of some COVID-19 drugs is hearing loss. The potential of drugs to cause hearing loss is typically unassessed during drug development or clinical testing. Our research will rapidly assess COVID-19 drugs for ototoxic potential, as per NOT-DC-20-008 to determine the “Potential ototoxicity from therapeutics or vaccination related to COVID-19.” Our goal is to promote the development of safe COVID-19 drugs with minimal side effects. Some drugs in clinical trials for COVID-19 are associated with hearing loss but the ototoxic potential for these drugs is based on individual case reports or in vitro experiments so the true ototoxic burden is largely unknown. We should not use patients as a testbed for a life-altering negative side- effect when there are rapid low-cost alternatives available. The objective of this proposal is to rapidly identify the ototoxic potential of COVID-19 therapeutics using both in silico and in vivo approaches. We will achieve this objective with three Specific Aims: 1) Predict ototoxic potential of COVID-19 therapies with Machine Learning (ML), 2) Determine the relative hair cell toxicity of COVID-19 therapies in the zebrafish lateral line, and 3) Determine the degree to which predicted ototoxins cause hearing loss in rats. Our innovative ML model correctly categorizes ototoxins vs. non-ototoxins with 87% accuracy. In this project we will employ our current model for immediate ototoxicity detection and further optimize the model for better predictive accuracy. In parallel with the ML model, we will screen COVID-19 therapeutics in the larval zebrafish lateral line, which is an excellent model for rapid ototoxicity screening. Prior work by our group and others demonstrates the validity of the lateral line as a platform for effective ototoxin discovery. Finally, we will validate predicted ototoxins from Aims 1 and 2 in rats using both physiological and morphological assays. Our research is significant because we will determine the ototoxic potential of new or repurposed therapeutics for COVID-19, which can inform efforts to 1) advance effective candidates that are not ototoxic, 2) modify successful yet ototoxic COVID-19 drugs and/or develop otoprotective co-therapies to preserve therapeutic efficacy while minimizing ototoxic side- effects, and 3) determine which patients require audiometric monitoring due to the drugs they receive. Our team includes experts in ototoxicity, medicinal chemistry, biostatistics, machine learning, and clinical expertise in large-scale human trials for COVID-19 therapies. Our research is highly likely to identify ototoxic COVID-19 drugs, facilitating development of safer pharmacotherapies to combat this deadly pandemic. Further, many drugs in clinical trials for COVID-19 are already approved for other indications. Our research will therefore provide important data about drugs in clinical use for non-COVID-related disease, adding additional value.", "keywords": [ "Adult", "Animals", "Auditory", "Azithromycin", "Biological Assay", "Biometry", "Blood", "COVID-19", "COVID-19 patient", "COVID-19 screening", "COVID-19 therapeutics", "COVID-19 treatment", "Case Study", "Categories", "Cause of Death", "Chemical Structure", "Clinical", "Clinical Trials", "Cochlea", "Computer Models", "Computers", "Data", "Data Set", "Databases", "Detection", "Development", "Disease", "Drug Combinations", "Drug usage", "FDA approved", "Goals", "Hair Cells", "Hearing Tests", "Human", "Human Resources", "Hydroxychloroquine", "Immune response", "Immune system", "In Vitro", "Individual", "Infection", "Intervention", "Ivermectin", "Labyrinth", "Life", "Link", "Machine Learning", "Methods", "Modeling", "Molecular", "Monitor", "Morphology", "Organ", "Patient Monitoring", "Patients", "Pharmaceutical Chemistry", "Pharmaceutical Preparations", "Pharmacologic Substance", "Pharmacotherapy", "Physiological", "Physiology", "Positioning Attribute", "Preclinical Testing", "Principal Component Analysis", "Public Health", "Publishing", "Rattus", "Reporting", "Research", "Risk", "Ritonavir", "Scientist", "Sensory", "Sensory Hair", "Stavudine", "Supporting Cell", "Synapses", "System", "Testing", "Therapeutic", "Therapeutic Uses", "Toxic effect", "Training", "Treatment Efficacy", "Vaccination", "Work", "Zebrafish", "anti-viral efficacy", "combat", "cost", "cytotoxic", "cytotoxicity", "drug candidate", "drug development", "experimental study", "feature selection", "hearing impairment", "in silico", "in vivo", "innovation", "lateral line", "machine learning model", "novel", "novel therapeutics", "older patient", "otoprotectant", "ototoxicity", "ototoxin", "pandemic disease", "pre-clinical", "preservation", "rapid detection", "research clinical testing", "response", "screening", "severe COVID-19", "side effect", "systemic inflammatory response" ], "approved": true } }, { "type": "Grant", "id": "11756", "attributes": { "award_id": "1R01DA058992-01", "title": "Discrimination and Racial Inequalities in Drug Use in U.S. Adults: Associations and Mechanisms", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute on Drug Abuse (NIDA)" ], "program_reference_codes": [], "program_officials": [ { "id": 10174, "first_name": "Sheba King", "last_name": "Dunston", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-06-15", "end_date": "2027-04-30", "award_amount": 385010, "principal_investigator": { "id": 27632, "first_name": "Hongying", "last_name": "Dai", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 27633, "first_name": "Adam Matthew", "last_name": "Leventhal", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 628, "ror": "https://ror.org/00thqtb16", "name": "University of Nebraska Medical Center", "address": "", "city": "", "state": "NE", "zip": "", "country": "United States", "approved": true }, "abstract": "Exposure to racial discrimination has long been identified as a key social determinant of substance use that stratifies by race/ethnicity. Starting in 2020, displays of racism and their impacts have intensified, and the recent volatile climate during the COVID-19 pandemic provides a unique opportunity to assess mechanisms that link discrimination and other social determinants of health with racial/ethnic disparities in drug use, but there has not been the requisite science on this topic as it deserves. Existing research on the discrimination-substance use association is plagued by both external validity (i.e., non-representative sampling with low generalizability to overall U.S.) and internal validity (i.e., low temporal precision from annual inter-survey intervals to detect prospective, potentially causal association). Additionally, there is little evidence to guide clinicians and policymakers on interventions that can disrupt discrimination’s impact on substance use in the modern social, economic, and public health context. This secondary analysis of the nationally-representative Understanding America Study (UAS, n~9,000 U.S. adults) aims to elucidate the nature and mechanisms of the association of discrimination with race/ethnicity inequalities in substance use. To chart the broad effects of the pandemic, this study will harmonize longitudinally bi-weekly (March 2020-July 2021) and monthly (August/September 2021- June 2022) survey waves with a total of 38 timepoints. Time-varying measures include 1) frequency of discrimination experience, racism, and COVID-19 related discrimination, and 2) substance use (past-week use of alcohol, cigarettes, e-cigarettes, cannabis, and other drugs, poly-substance use, and binge drinking) along with key public health (e.g., COVID-19 illness and vaccination), economic (e.g., economic insecurity, housing insecurity, and employment instability), and behavioral factors (e.g., resilience and coping strategies). We will combine person-level data (38 survey waves) with state-level geocoded data on hate crime incidence, statutory provisions, and other public health or economic context. Intensive longitudinal multi-level modeling will be conducted to partition between- and within-subject variance and address between-person confounds, thus overcoming the biases inherent in other annual-interval national substance use surveillance with low temporal precision and recall errors. Through three inter-related aims and theory-driven hypothesis testing, we will 1) examine whether within-person changes in discrimination are associated with substance use and if associations are moderated by race and ethnicity (Aim 1), 2) determine person- and environment-level factors that exacerbate or buffer against the association of discrimination with substance use (Aim 2), and 3) assess mechanisms that explain race/ethnicity differences in the association of discrimination with substance use (Aim 3). Findings from this study will provide timely evidence to guide clinicians and policymakers on interventions that can disrupt discrimination’s impact on substance use in the modern social, economic, and public health context.", "keywords": [ "Address", "Adult", "Alcohol consumption", "Alcohols", "Amplifiers", "Anxiety", "Asian population", "Behavioral", "Black Populations", "Buffers", "COVID-19", "COVID-19 pandemic", "COVID-19 vaccination", "Cannabis", "Characteristics", "Cigarette", "Climate", "Coping Behavior", "Coping Skills", "Coronavirus", "Crime", "Data", "Data Reporting", "Data Set", "Discrimination", "Disease", "Drug usage", "Economics", "Electronic cigarette", "Employment", "Employment Status", "Environment", "Ethnic Origin", "Event", "Exercise", "Exposure to", "Food", "Frequencies", "Friends", "Hispanic Populations", "Household", "Housing", "Incidence", "Internet", "Intervention", "Life", "Link", "Measures", "Mediating", "Mediation", "Mental Depression", "Methods", "Modernization", "Nature", "Not Hispanic or Latino", "Outcome", "Outcome Study", "Patient Self-Report", "Persons", "Pharmaceutical Preparations", "Police", "Policy Maker", "Probability", "Public Health", "Race", "Research", "Risk Factors", "Sampling", "Science", "Surveys", "Techniques", "Testing", "Time", "Unemployment", "United States", "Vaccination", "Volatilization", "Vulnerable Populations", "addiction", "anti-Asian", "anti-racism", "anxiety symptoms", "binge drinking", "data modeling", "depressive symptoms", "ethnic difference", "ethnic disparity", "ethnic minority", "ethnic minority population", "experience", "follow-up", "hate crimes", "health equity", "killings", "minority communities", "multi-racial", "multilevel analysis", "pandemic impact", "people of color", "perceived discrimination", "polysubstance use", "prospective", "racial difference", "racial discrimination", "racial disparity", "racial minority", "racial minority population", "racial population", "racism", "recruit", "resilience", "secondary analysis", "social", "social determinants", "social health determinants", "substance use", "theories" ], "approved": true } }, { "type": "Grant", "id": "11757", "attributes": { "award_id": "1R01CA269832-01A1", "title": "Promoting Equity of Cancer Screening and Follow-up for Lung Cancer", "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": [ { "id": 23464, "first_name": "SALLIE JAYNE", "last_name": "Weaver", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-06-09", "end_date": "2028-05-31", "award_amount": 718974, "principal_investigator": { "id": 27634, "first_name": "Chyke Abadama", "last_name": "Doubeni", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 778, "ror": "", "name": "OHIO STATE UNIVERSITY", "address": "", "city": "", "state": "OH", "zip": "", "country": "United States", "approved": true }, "abstract": "PROJECT SUMMARY/ABSTRACT: Lung cancer is highly lethal and accounts for nearly as many deaths as breast, cervical, colorectal, and prostate cancers combined, but most lung cancer cases are potentially preventable. About 80-90% of cases are smoking-related, and screening followed by high-quality treatment has been shown to reduce the risk of death in people at high-risk. Therefore, smoking cessation interventions plus screening are two complementary pillars that are recommended together by the US Preventive Services Task Force and other guidelines to reduce the lung cancer death rate. Unfortunately, uptake of lung cancer screening (LCS) remains low and although disparities in lung cancer deaths by socioeconomic factors, including rurality, are widely acknowledged, they remain understudied. Evidence shows that rural areas have higher lung cancer death rates than urban populations, likely related to risk factors and healthcare access. However, efforts to understand and address rural-urban disparities are hampered by low representation of rural populations in public data systems. The goal of this proposal is to elucidate factors that contribute to lung cancer disparities between rural and urban areas and provide contextual information for future interventions and policies. Our specific aims are to: (1) Characterize the delivery of evidence-based interventions (EBIs) for lung cancer prevention and early detection, comparing rural to urban areas, by assessing differences in use of smoking cessation interventions and LCS at multiple levels of influences; (2) Identify potentially modifiable care gaps across the LCS continuum, including risk assessment and timely treatment, by examining patients who died of lung cancer relative to patients who are alive by rural-urban status; and (3) Evaluate similarities and differences in the barriers and promoters to delivery of EBIs across the LCS continuum (smoking cessation, shared decision-making, screening, and treatment) in the rural and urban contexts. We will use a multidimensional health equity framework to apply a convergent, mixed methods approach for our studies. We will leverage the Rochester Epidemiology Project, a unique population-based data resource for a 27-county contiguous area in the Midwestern US, along with the Southern Community Cohort Study across 12 states in the Southeastern US, among a diverse population of 50- 80-year-old people. We will use Rural-Urban Commuting Area codes to define rurality and will assess both self- reported and area-level socioeconomic information. We will conduct semi-structured interviews with patients and clinical staff to gain perspectives on LCS barriers and promoters, including the potential role of smoking-related stigma. The proposed research has the potential for high impact by elucidating gaps on lung cancer prevention and early detection that will translate directly into strategies to address intransigent lung cancer disparities in our study population, and beyond. We will thus address priorities of the NCI and the President’s Cancer Panel to advance equity and address the potential COVID-19 impact on the delivery of LCS. Our transdisciplinary team has a track record of high-impact research and has the needed expertise to successfully complete this research.", "keywords": [ "Address", "Advisory Committees", "Area", "COVID-19", "COVID-19 impact", "COVID-19 pandemic", "Cancer Control", "Cancer Death Rates", "Cancer Etiology", "Caring", "Censuses", "Cessation of life", "Classification", "Clinic", "Clinical", "Code", "Cohort Studies", "Colorectal Cancer", "Communities", "Commuting", "Continuity of Patient Care", "County", "Data", "Databases", "Death Rate", "Dimensions", "Disparity", "Early Diagnosis", "Elderly", "Eligibility Determination", "Epidemiology", "Equity", "Evidence based intervention", "Federally Qualified Health Center", "Future", "Goals", "Guidelines", "Health Professional", "Health Services Accessibility", "Health care facility", "Health system", "Healthcare", "Individual", "Information Systems", "Intervention", "Interview", "Knowledge", "Malignant Neoplasms", "Malignant neoplasm of cervix uteri", "Malignant neoplasm of lung", "Malignant neoplasm of prostate", "Measures", "Methods", "Patient Care", "Patient Self-Report", "Patients", "Persons", "Policies", "Population Heterogeneity", "President&apos", "s Cancer Panel", "Preventive service", "Primary Care", "Process", "Race", "Recommendation", "Reporting", "Research", "Risk Assessment", "Risk Factors", "Risk Reduction", "Role", "Rural", "Rural Population", "Scientist", "Screening Result", "Screening for cancer", "Series", "Site", "Smoking", "Smoking Cessation Intervention", "Social Environment", "Socioeconomic Factors", "Socioeconomic Status", "Structure", "System", "Taxonomy", "Translating", "Travel", "United States National Institutes of Health", "Urban Population", "Variant", "Woman", "X-Ray Computed Tomography", "aged", "cancer care", "cancer diagnosis", "cancer health disparity", "cohort", "data resource", "disorder risk", "effective intervention", "epidemiology study", "follow-up", "health care availability", "health equity", "high risk", "improved", "improved outcome", "innovation", "lens", "low dose computed tomography", "lung cancer prevention", "lung cancer screening", "malignant breast neoplasm", "men", "mortality", "mortality risk", "novel", "novel coronavirus", "population based", "preventable death", "preventive intervention", "promoter", "resilience", "rural area", "rurality", "screening", "shared decision making", "smoking cessation", "smoking prevalence", "social", "social factors", "social stigma", "socioeconomic disadvantage", "socioeconomics", "study populat" ], "approved": true } }, { "type": "Grant", "id": "11758", "attributes": { "award_id": "1K01AI168452-01A1", "title": "Mentored Research (K01) Integrative Spatial Epidemiology Study of Wildlife Rabies Spillover", "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": 6054, "first_name": "Eun-Chung", "last_name": "Park", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-06-27", "end_date": "2028-05-31", "award_amount": 126372, "principal_investigator": { "id": 2935, "first_name": "Luis E", "last_name": "Escobar", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 244, "ror": "", "name": "Virginia Polytechnic Institute and State University", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 839, "ror": "", "name": "VIRGINIA POLYTECHNIC INST AND ST UNIV", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "Synopsis: This is a K01 application by Dr. Luis Escobar, researcher on zoonotic infectious diseases. Escobar’s project Integrative Spatial Epidemiology Study of Wildlife Rabies Spillover will combine spatial modeling with large epidemiological, genomic, and ecological data to investigate pathogen spillover from wildlife to humans and livestock. Candidate: PI Escobar, DVM/MSc/PhD, is a tenure-track Assistant Professor at Virginia Tech, with prior postdoctoral training at SUNY Upstate Medical University and the University of Minnesota and a strong record of scientific achievements. This application has three training objectives to strengthen Escobar’s research as an independent investigator: (1) Training in bioinformatics; (2) Integrate bioinformatics with spatial epidemiology; and (3) Gaining skills in laboratory management and research proposal development to transition to career independence. Mentors: Prof. X.J. Meng, with a solid history of NIH funding, outstanding expertise in bioinformatics, and at the applicant’s institution, will serve as Primary Mentor. Four additional mentors (Drs. Z. Tu, W. Hopkins, S. VandeWoude, A.T. Peterson) will provide complementary expertise and will assess Escobar’s progress towards career independence. Research: Emergent infectious diseases, such as Ebola, Nipah, and COVID-19, have been linked to pathogen spillover from bats to other species. A gap in knowledge exists in the fundamental ecology of pathogen spillover transmission (i.e., Where does it occur and why?), which limits understanding of previous epidemics and capacities to prevent disease emergence. This project will study pathogen spillover from bats to humans and livestock using rabies from the common vampire bat (Desmodus rotundus), a well-documented system of a virus that frequently spills from D. rotundus bats over to other species. While D. rotundus-rabies is restricted to Latin America, it is rapidly expanding towards the United States (US) for unknown reasons. The central hypothesis is that D. rotundus-rabies spillover does not occur randomly in the geography but follows specific biodiversity and habitat patterns, which can be used to predict where pathogen spillover will occur. Aim 1 will determine the role of habitat and virus lineage on rabies-spillover to humans and livestock across Latin America. Aim 2 will identify effect of biodiversity composition on rabies virus spillover transmission. Aim 3 will investigate genomic, geographic, and environmental factors shaping the spread of rabies virus. This hypothesis-driven project has conceptual and technological innovations and combines the expertise of PI Escobar and mentors to illuminate ecological drivers of rabies spillover. Findings will offer new mechanistic insights to explain and anticipate pathogen spillover. As such, this K01 application will facilitate Escobar’ s transition towards research independence and offers exciting discoveries on the ecology of spillover transmission, aligned with the NIH mission to seek fundamental knowledge about the nature of living systems to enhance human health.", "keywords": [ "Achievement", "Address", "Americas", "Animals", "Area", "Biodiversity", "Bioinformatics", "Biology", "COVID-19", "Cattle", "Characteristics", "Chiroptera", "Classification", "Climate", "Communicable Diseases", "Data", "Development", "Disease", "Doctor of Philosophy", "Domestic Animals", "Ebola", "Ecology", "Economics", "Environmental Risk Factor", "Epidemiology", "Evolution", "Expenditure", "Exposure to", "Funding", "Genetic Structures", "Genomics", "Geographic Distribution", "Geographic Factor", "Geographic Locations", "Geography", "Goals", "Habitats", "Health", "Human", "Incidence", "Individual", "Industry", "Infection", "Institution", "Knowledge", "Laboratories", "Latin America", "Link", "Livestock", "Machine Learning", "Mammals", "Measures", "Medical", "Mentors", "Methods", "Mexico", "Minnesota", "Mission", "Modeling", "Molecular Epidemiology", "Nature", "Organism", "Pattern", "Persons", "Phylogenetic Analysis", "Prevention", "Public Health", "Rabies", "Rabies virus", "Recording of previous events", "Report (document)", "Research", "Research Personnel", "Research Project Grants", "Research Proposals", "Risk", "Role", "Shapes", "Signal Transduction", "Solid", "System", "Temperature", "Testing", "Training", "United States", "United States National Institutes of Health", "Universities", "Vaccination", "Virginia", "Virus", "Zoonoses", "career", "disease diagnostic", "epidemiology study", "genomic data", "improved", "innovation", "insight", "machine learning model", "mortality", "multiple datasets", "novel", "pathogen", "pathogen spillover", "post-doctoral training", "prevent", "previous epidemic", "professor", "skills", "spatial epidemiology", "technological innovation", "tenure track", "transmission process", "viral transmission" ], "approved": true } }, { "type": "Grant", "id": "11759", "attributes": { "award_id": "1R21AI175905-01", "title": "Investigation of sarbecovirus exposure patterns and development of pan-SARS-CoV-2 neutralizing antibody responses in high-risk cohorts in Myanmar", "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": 6588, "first_name": "MICHAEL JOHN", "last_name": "Cooper", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-06-06", "end_date": "2025-05-31", "award_amount": 204874, "principal_investigator": { "id": 24369, "first_name": "Tierra Smiley", "last_name": "Evans", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 746, "ror": "", "name": "UNIVERSITY OF CALIFORNIA AT DAVIS", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern pose a global challenge to the effectiveness of existing and future vaccines. This project will address questions surrounding the immunological response to different sarbecovirus exposure patterns with implications for vaccine development by conducting longitudinal repeated surveillance of unique human populations, previously determined to be highly exposed to a diversity of SARS-CoV-2-related coronaviruses in Myanmar. There is a timely opportunity to follow these communities, particularly immediately following SARS-CoV-2 infection and/or vaccination to understand which previous sarbecovirus exposure patterns expand the likelihood of development of pan-sarbecovirus neutralizing antibodies. We will evaluate the impact of diverse patterns of natural and vaccination-based sarbecovirus exposure on development of pan- sarbecovirus neutralizing antibodies by following three specific human cohorts: (1) elephant loggers engaged in bushmeat hunting (including bats and pangolins) during the process of active deforestation of Myanmar’s remaining teak forests, (2) bat guano harvesting communities surrounding HpaAn cave systems in Kayin State and (3) a previously uninvestigated population engaged in religious activities within the Karst cave systems in the Northern Dawna range. Waxing and waning of specific antibody responses will be followed over time through use of pre-pandemic archived specimens from these populations and repeated prospective sampling. We will utilize a novel Luminex bead-based multi-plex sarbecovirus assay, capable of simultaneously detecting neutralizing antibodies against 21 different hACE2-binding sarbecoviruses. Exposure patterns to specific sarbecoviruses will be identified and viral characteristics evaluated for their contribution to the likelihood of developing pan-sarbecovirus antibody responses, including viral genetic and functional phenotypic similarity and host plasticity (breadth of host species a virus is known to infect). Patterns of prior natural sarbecovirus exposure coupled with natural SARS-COV-2 infection and / or vaccination will then be evaluated for contributions to broadly reactive antibody responses. Data generated through this project will inform on potential cross sarbecovirus clade vaccination strategies that could protect against both known and future emerging SARS-CoV-2 variants. We will also conduct an in-depth investigation of behavioral risk factors contributing to zoonotic sarbecovirus spillover that will aid in mitigation strategies in this critically important ecological region for coronavirus emergence.", "keywords": [ "2019-nCoV", "Address", "Age", "Antibody Response", "Behavior", "Behavioral", "Binding", "Biological", "Biological Assay", "COVID-19 pandemic effects", "Characteristics", "Chiroptera", "Communities", "Coupled", "Data", "Deforestation", "Development", "Effectiveness", "Elephants", "Exposure to", "Frequencies", "Funding", "Future", "Harvest", "Human", "Immune response", "Immunization Programs", "Individual", "Infection", "Investigation", "Medical History", "Myanmar", "Pattern", "Phenotype", "Population", "Process", "Public Health", "Religion and Spirituality", "Risk Behaviors", "Risk Factors", "SARS coronavirus", "SARS-CoV-2 infection", "SARS-CoV-2 infection history", "SARS-CoV-2 variant", "Sampling", "Sarbecovirus", "Serum", "Specimen", "Surveys", "System", "Time", "USAID", "United States National Institutes of Health", "Vaccination", "Vaccines", "Viral", "Virus", "Waxes", "Work", "Zoonoses", "biological specimen archives", "cohort", "exposed human population", "forest", "high risk", "high risk behavior", "neutralizing antibody", "novel", "novel coronavirus", "post SARS-CoV-2 infection", "pre-pandemic", "prospective", "vaccination strategy", "vaccine development", "vaccine strategy", "variants of concern", "virus genetics" ], "approved": true } }, { "type": "Grant", "id": "11760", "attributes": { "award_id": "1R21AI178249-01", "title": "Investigation of Dpp9 in COVID19", "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": 26918, "first_name": "Michelle Marie", "last_name": "Arnold", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-06-09", "end_date": "2025-05-31", "award_amount": 244919, "principal_investigator": { "id": 27635, "first_name": "Richard A.", "last_name": "Flavell", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 452, "ror": "https://ror.org/03v76x132", "name": "Yale University", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true }, "abstract": "To better understand the determinants of severe COVID19, we have focused on the inflammasome regulatory protein DPP9. GWAS have implicated DPP9 in poor outcomes in COVID19 and in the development of idiopathic pulmonary fibrosis. DPP9 and closely related DPP8 serve as endogenous inhibitors of the viral inflammasome sensors NLRP1 and CARD8. This pathway is activated by diverse mechanisms of pathogen sensing which include detection of viral encoded proteases, bacterial E3 ubiquitin ligases and direct sensing of viral dsRNA. Our preliminary data indicate that this pathway is transcriptionally upregulated in human myeloid cells in response to SARS-CoV-2, a stimulus which activates the inflammasome. We have also discovered that mice which lack Dpp8 and Dpp9 have dysregulated T cell responses and develop more severe disease when challenged with SARS-CoV-2. Our ongoing work seeks to better understand 1) the immunological differences conferred by the COVID19 risk allele rs2109069 “A” located within a DPP9 intronic region, 2) the basis for T cell dysregulation in our novel mouse model and 3) how T cell dysfunction influences disease severity in response to SARS-CoV-2 infection.", "keywords": [ "2019-nCoV", "Biological Assay", "COVID-19", "COVID-19 risk", "COVID-19 severity", "COVID-19 susceptibility", "Cell Death", "Cells", "Cessation of life", "Data", "Dendritic Cells", "Dendritic cell activation", "Development", "Disease", "Disease Outcome", "Double-Stranded RNA", "Effectiveness", "Failure", "Functional disorder", "Future", "Genes", "Genetic", "Genetic Transcription", "Human", "Human Genetics", "Humoral Immunities", "Hyperactivity", "Immune", "Immune response", "Immunity", "Immunologics", "Individual", "Inflammasome", "Inflammatory", "Investigation", "K-18 conjugate", "Knowledge", "Lung", "Mediating", "Mus", "Myeloid Cells", "Outcome", "Pathway interactions", "Peptide Hydrolases", "Phenotype", "Physiology", "Population", "Respiratory distress", "Role", "SARS-CoV-2 infection", "Severity of illness", "Stimulus", "Susceptibility Gene", "T cell response", "T-Lymphocyte", "Testing", "Vaccination", "Vaccines", "Viral", "Virus", "Virus Inhibitors", "Work", "adaptive immune response", "comorbidity", "cytokine", "genetic regulatory protein", "genome wide association study", "global health", "idiopathic pulmonary fibrosis", "migration", "monocyte", "mouse model", "novel", "novel coronavirus", "novel vaccines", "pandemic coronavirus", "pathogen", "peripheral tolerance", "pharmacologic", "protein complex", "respiratory virus", "response", "risk variant", "sensor", "severe COVID-19", "ubiquitin-protein ligase", "viral detection" ], "approved": true } }, { "type": "Grant", "id": "11761", "attributes": { "award_id": "1I01HX003569-01A2", "title": "Disruption of Health Services: The Impact of COVID-19 on Veterans with SCI/D", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2023-06-01", "end_date": "2025-05-31", "award_amount": null, "principal_investigator": { "id": 27636, "first_name": "Andrea K", "last_name": "Finlay", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 27637, "first_name": "Marinella", "last_name": "Galea", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 1533, "ror": "", "name": "JAMES J PETERS VA MEDICAL CENTER", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Background: As of May 19, 2022, 3,427 of the 17,307 Veterans living with spinal cord injury and disorders (SCI/D) who have received services from the Veterans Health Administration (VHA) in fiscal year (FY) 2022 had a confirmed positive COVID-19 test, with 187 COVID-related deaths. Stay-at-home orders and social distancing guidelines during the pandemic have had numerous effects on this population including disrupting healthcare, increased mortality and morbidity as well as negative psychosocial effects. Veterans with SCI/D are a unique population within the VHA who are primarily served at 25 SCI/D Centers nationally. Veterans with SCI/D have higher rates of chronic physical conditions than other Veterans. Research on the pandemic impact on Veterans with SCI/D is scant but critical to study because these individuals utilize VHA health services as their primary source of health care and SCI/D support (e.g., wheelchair repair, home-based care, bowel and bladder care, assistive technology, etc.). To inform program planning and resource allocation, it is essential to know how the COVID-19 pandemic has impacted health service delivery, access to essential resources, and mortality and morbidity among Veterans with SCI/D. This explanatory mixed methods study will fill this gap in knowledge by examining patient-, community-, and system-level factors related to changes in health services care, physical and mental health outcomes in Veterans with SCI/D. Significance: Given the elevated risk of chronic physical conditions and mortality for Veterans with SCI/D, it is imperative that VHA provides health services to address the needs of this population. This study responds to the VA SCI/D National Program Office priorities to support, promote, and maintain the health, independence, quality of life, and productivity of Veterans with SCI/D throughout their lives. Further, this project identifies challenges faced by Veterans with SCI/D during the COVID-19 pandemic and utilizes these results to inform health services for future emergency events and global disasters. Specific Aims: The project’s three aims are scientifically important and reflect extensive input from key Veteran and SCI/D stakeholders regarding how to improve the quality of SCI/D services: (1) Identify COVID-19 related disruptions and adaptations in health services utilization and mortality and morbidity among Veterans with SCI/D; (2) Qualitatively evaluate Veterans’ and providers’ perspectives on how health services utilization changed during the COVID-19 pandemic and the subsequent impact on mortality and morbidity; and (3) Examine Veterans experiences and decision-making during the COVID-19 pandemic. Methodology: Our study is guided by the International Classification of Functioning, Disability, and Health conceptual framework. In Aim 1, we will estimate incidence rate ratios of health services utilization, morbidity, and mortality in the year prior and years 1 and 2 after the start of the pandemic. We will also examine if there are differences between the time periods by Veteran, SCI/D and VHA, and community factors. Finally, we will conduct exploratory analyses of patterns of disrupted care (n=18,331 in FY20). Aim 2 will be to conduct focus groups with Veterans with SCI/D (n=4 groups with ~3-5 Veterans per group) and VHA providers who deliver healthcare services for these Veterans (n=2 groups with ~3-5 providers per group). For Aim 3, we will conduct a national survey with Veterans with SCI/D who use VHA health services (n=~6,100, which approximates 35% of the 17,307 currently living Veterans with SCI/D identified by the National SCI/D Registry). Next Steps/Implementation: Results will be of immediate value to the SCI/D National Program Office to identify health services needs for Veterans with SCI/D and will be used to develop measures for enhanced emergency preparedness for future disasters. This information will have broad and long-ranging impacts on the SCI/D System of Care, informing access improvement projects, telehealth service expansion, performance measures development, and VHA enrollment and health care projection modeling (20+ year timeframe).", "keywords": [ "Address", "Awareness", "Bladder", "Businesses", "COVID-19", "COVID-19 impact", "COVID-19 pandemic", "COVID-19 risk", "COVID-19 test", "Caregiver support", "Caregivers", "Caring", "Cessation of life", "Chronic", "Chronic Disease", "Classification", "Communities", "Complex", "Data", "Decision Making", "Development", "Disasters", "Disease", "Disease Management", "Economics", "Emergency Situation", "Emergency response", "Emotional", "Enrollment", "Evaluation", "Event", "Focus Groups", "Future", "Goals", "Guidelines", "Health", "Health Personnel", "Health Services", "Health Services Accessibility", "Health Services Administration", "Health Services Needs", "Healthcare", "Home", "Housing", "Hurricane", "Improve Access", "Incidence", "Individual", "International", "Intestines", "Knowledge", "Learning", "Measures", "Medical", "Mental Depression", "Mental Health", "Methodology", "Methods", "Modeling", "Morbidity - disease rate", "Natural Disasters", "Nature", "New York", "Newly Diagnosed", "Outcome", "Patients", "Pattern", "Performance", "Persons", "Policies", "Population", "Primary Care", "Productivity", "Provider", "Quality of life", "Readiness", "Registries", "Research", "Resource Allocation", "Resources", "Risk", "SARS-CoV-2 positive", "Self-Help Devices", "Services", "Site", "Social Distance", "Social isolation", "Source", "Spinal cord injury", "Stress", "Surveys", "System", "Systems Integration", "Time", "Transportation", "Treatment/Psychosocial Effects", "United States", "Variant", "Veterans", "Veterans Health Administration", "Vulnerable Populations", "Wheelchairs", "World Health Organization", "care delivery", "care systems", "community-level factor", "coronavirus disease", "decubitus ulcer", "disability", "experience", "food insecurity", "health care delivery", "health care service", "health service use", "high risk", "improved", "inpatient service", "medical specialties", "mortality", "mortality risk", "operation", "pandemic disease", "pandemic impact", "patient home care", "physical conditioning", "primary care practice", "programs", "psychosocial", "repaired", "research and development", "response", "stay-at-home order", "telehealth" ], "approved": true } }, { "type": "Grant", "id": "11762", "attributes": { "award_id": "1R43DA058470-01", "title": "Noncontact Remote Monitoring for the Detection of Opioid-Induced Respiratory Depression", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute on Drug Abuse (NIDA)" ], "program_reference_codes": [], "program_officials": [ { "id": 12311, "first_name": "LEONARDO MARIA", "last_name": "Angelone", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-06-15", "end_date": "2024-05-31", "award_amount": 325001, "principal_investigator": { "id": 27638, "first_name": "Behnood", "last_name": "Gholami", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2047, "ror": "", "name": "AUTONOMOUS HEALTHCARE, INC.", "address": "", "city": "", "state": "NJ", "zip": "", "country": "United States", "approved": true }, "abstract": "The US opioid crisis continues to have a catastrophic impact on human lives and the ongoing COVID-19 pandemic is compounding its effects. Based on the statistics published by the CDC, 91,799 drug overdose deaths occurred in the US in 2020, where the age-adjusted overdose deaths increased by 31% from 2019 to 2020. In addition, opioids, which cause respiratory depression, were involved in 75% of all drug overdose deaths in the US. We propose to build on our work in non-invasive monitoring of vital signs to develop an FDA- regulated medical device with a primary application in monitoring patients for opioid-induced respiratory depression. This includes at-home monitoring of patients with chronic pain being treated with high-dose opioid prescription medications or patients suffering from opioid use disorder (OUD) as well as monitoring subjects with OUD at supervised injection sites (also known as supervised consumption spaces). Our overall goal is to develop a non-contact multi-modal monitoring system for the detection of opioid-induced respiratory depression at home and in supervised injection sites. While radar is capable of penetrating through clothing and blankets to measure chest wall movements resulting from respiration, it requires the guidance of depth imaging to target a person and the chest area. Our specific aims are: 1. Estimate tidal volume using a noncontact monitoring system. Our current technology is capable of detecting respiratory rate with a high degree of accuracy for stationary subjects. However, robust detection of respiratory depression involves monitoring of respiratory rate, pattern, and depth (i.e., tidal volume). As part of this specific aim, we will develop a framework to estimate tidal volume of a stationary subject using radar and depth information, where we estimate tidal volume from chest wall displacements. Furthermore, we will extract features to characterize respiratory pattern from the acquired radar signal. As a primary validation of this estimation framework, our system will be tested on 20 healthy volunteers. The outcome of the test will provide us with preliminary data regarding the accuracy of the radar and the depth-based tidal volume estimation as compared with the gold standard. 2. Develop and validate a framework for integrating data from sensors to detect respiratory depression. In this specific aim, we will develop a framework to use the respiratory rate, respiratory pattern, and tidal volume information from the radar and depth camera to determine if respiratory depression has occurred. This involves a two-step approach, where we extract respiratory features to characterize respiratory patterns to complement respiratory rate and tidal volume, and then use a machine learning model to detect the occurrence of respiratory depression. To help with design the right model, we will collect data using our radar and depth imaging system from anesthetized pigs going through opioid-induced respiratory depression.", "keywords": [ "Age", "Anesthesia procedures", "Area", "COVID-19 pandemic", "Chest", "Chest wall structure", "Clothing", "Complement", "Consumption", "Data", "Detection", "Devices", "Dose", "Drug Prescriptions", "Family suidae", "Goals", "Home", "Human", "Image", "Injections", "Involutional Depression", "Measures", "Medical Device", "Modeling", "Monitor", "Movement", "Opioid", "Outcome", "Patient Monitoring", "Patients", "Pattern", "Penetration", "Persons", "Pharmaceutical Preparations", "Phase", "Publishing", "Radar", "Respiration", "Sensitivity and Specificity", "Signal Transduction", "Site", "System", "Technology", "Testing", "Tidal Volume", "Validation", "Ventilatory Depression", "Work", "chronic pain patient", "data integration", "design", "detection platform", "healthy volunteer", "image guided", "imaging system", "machine learning framework", "machine learning model", "multimodality", "non-invasive monitor", "opioid epidemic", "opioid use disorder", "optical imaging", "overdose death", "prescription opioid", "privacy preservation", "prototype", "remote monitoring", "research clinical testing", "respiratory", "sensor", "statistics" ], "approved": true } }, { "type": "Grant", "id": "11763", "attributes": { "award_id": "1R21ES034438-01A1", "title": "Identifying Spatial and Environmental Correlates of Airborne Microplastics and Nanoplastics across Philadelphia", "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": 10732, "first_name": "Yuxia", "last_name": "Cui", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-06-15", "end_date": "2025-05-31", "award_amount": 424634, "principal_investigator": { "id": 27639, "first_name": "Inkyu", "last_name": "Han", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 1445, "ror": "", "name": "TEMPLE UNIV OF THE COMMONWEALTH", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Due to the massive production and careless disposal of plastic waste, plastic pollution and its potential health effects have drawn attention recently. The annual production of plastic materials was approximately 370 million tons in 2019 and is expected to increase continually. During the Coronavirus Disease 2019 (COVID-19) pandemic, the production of plastics in the world skyrocketed to 584 million tons in 2020 due to an unprecedented demand for single-use plastics. More than half of the plastic waste generated worldwide is thrown away into the environment without proper management. Of the various sizes of plastics, much attention has focused on the smaller sized plastics such as microplastics (1 µm to 5 mm) and nanoplastics (< 1 µm). Microplastics and nanoplastics (MANs) contain thousands of harmful chemicals (i.e., plasticizers, flame retardants, and other toxic organic chemicals), and MANs are easily absorbed into humans and other living organisms, potentially causing respiratory inflammation, systemic oxidative stress, and neurotoxic effects. Hence, their ubiquity in environments and the ease with which they can be absorbed has raised concerns about the potential impact of exposure to MANs on human health. Although ingestion of MANs was considered to be the primary route of exposure, recent reviews suggest that inhalation of MANs may be two to three orders of magnitude greater than ingestion of MANs. While the information on human exposure to inhalable MANs is a fundamental step in determining human health risk, there are several knowledge gaps for exposure assessment of airborne MANs. Exposure assessment of outdoor air MANs in the United States (U.S.) has not yet been conducted, yet people living in densely populated urban areas are likely at risk for significant exposure to airborne MANs. As the second poorest major city in the U.S. (23% poverty rate), many Philadelphians (especially people of color) without air conditioning units spend more time outside or with the windows open in warmer months, thereby increasing their exposure to outdoor air MANs. To date, the spatial variation of ambient air MANs in urban areas has not been assessed. Additionally, the specific composition of MANs, the distribution of these components, and their likely sources in urban environments are unknown. This study will address these gaps. Specifically, we aim to (1) collect ambient air MANs at 48 different sampling sites, quantify inhalable size of MANs and characterize their composition, (2) characterize the geographic distribution of airborne exposure to MANs (and their chemical composition) across Philadelphia, Pennsylvania, and (3) identify environmental correlates of higher MANs levels and explore seasonal differences. This proposed exploratory study is directly responsive to NIEHS strategic goals “Emerging Environmental Health Issues.” Airborne MANs are emerging pollutants and their related health effects are largely unknown locally and globally. Quantifying exposure to airborne MANs will provide necessary data for future health studies to determine the potential risks of airborne MANs to human health.", "keywords": [ "Address", "Air", "Air Conditioning", "Air Pollutants", "Air Pollution", "Attention", "Biological", "COVID-19 pandemic", "Chemicals", "Cities", "Communities", "DNA Damage", "Data", "Disease", "Dose", "Dust", "Endocrine Disruptors", "Environment", "Environmental Health", "Environmental Risk Factor", "Exposure to", "Flame Retardants", "Food", "Food Container", "Future", "Geographic Distribution", "Goals", "Health", "Heterogeneity", "Human", "In Vitro", "Industrialization", "Inflammation", "Ingestion", "Inhalation", "Inhalation Exposure", "Knowledge", "Location", "Lung", "Meteorology", "Monitor", "National Institute of Environmental Health Sciences", "Organic Chemicals", "Organism", "Oxidative Stress", "Pennsylvania", "Persons", "Philadelphia", "Plasticizers", "Plastics", "Pollution", "Population Density", "Poverty", "Production", "Public Health", "Pulmonary alveolar structure", "Risk", "Risk Factors", "Role", "Route", "Sampling", "Seasons", "Site", "Soil", "Source", "Study models", "Sunlight", "Time", "Toxicology", "United States", "Variant", "Water", "absorption", "airway inflammation", "anthropogenesis", "burden of illness", "cell injury", "cytokine", "epidemiology study", "exposed human population", "exposure route", "face mask", "fine particles", "in vivo", "neurotoxic", "people of color", "pollutant", "spatiotemporal", "urban area", "urban setting", "wasting" ], "approved": true } }, { "type": "Grant", "id": "11764", "attributes": { "award_id": "1R01MD018180-01", "title": "Evaluating Medicaid Postpartum Coverage Extensions through an Equity Lens", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute on Minority Health and Health Disparities (NIMHD)" ], "program_reference_codes": [], "program_officials": [ { "id": 23654, "first_name": "YEWANDE A", "last_name": "Oladeinde", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-06-04", "end_date": "2027-12-31", "award_amount": 745197, "principal_investigator": { "id": 27640, "first_name": "Teresa", "last_name": "Janevic", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 27641, "first_name": "Ellerie", "last_name": "Weber", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 625, "ror": "https://ror.org/04a9tmd77", "name": "Icahn School of Medicine at Mount Sinai", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Recent policy debates to extend Medicaid postpartum are fueled by the US maternal health crisis: The US maternal mortality rate is the highest among high-income countries and includes stark racial inequities. Black people have more than 3X risk of dying from pregnancy related causes than White people. Racial and ethnic disparities for maternal morbidity are equally glaring. Immigrants, too, face higher rates of maternal morbidity and perinatal complications. Sustained, continuous access to perinatal health care is critical to maternal health and health equity, yet ~45% of birthing people with Medicaid and CHIP lose coverage after 60 days. Postpartum Medicaid extensions are key features of recent policy attempts to address the deplorably high Black maternal mortality and morbidity rates. However, structural racism shaping US institutions means such policies could either mitigate or exacerbate inequities. Policymakers need evidence about the impact of postpartum Medicaid access on maternal health equity to guide design and implementation. Since March 2020, the Families First Coronavirus Response Act (FFCRA) has conferred a de-facto Medicaid postpartum coverage extension nationwide, but it is due to expire imminently. Meanwhile, 27 states have already adopted or are seeking to pass legislation to extend postpartum Medicaid coverage, but their policy approaches vary in legal basis, eligibility criteria, length of coverage, and immigrant exclusions. Moreover, states vary in their existing Medicaid eligibility policies prior to the pandemic, which has profoundly shaped who has remained eligible during the pandemic with uncertain eligibility post-pandemic. Our overarching objective is to evaluate the impact of postpartum Medicaid policy on maternal health equity. We propose using an adaptive concurrent mixed-methods design to measure national changes in postpartum Medicaid enrollment while exploiting differences in two states' policies to examine health care utilization in greater depth. We focus on two large, diverse states: Texas (TX) has expanded Medicaid to six months postpartum through a demonstration waiver, while New York (NY) is using the American Rescue Plan Act to expand Medicaid 12 months postpartum. Using national American Community Survey (ACS) and Medicaid claims data from TX and NY, our quantitative aims will apply interrupted time series (ITS) and difference-in-difference (DID) approaches. In our qualitative aim, we will interview postpartum women, healthcare providers, community-based organizations, and policymakers on the efficacy of postpartum Medicaid extension implementation, which will inform the analysis approach and enrich our findings. Our proposal not only fills gaps in targeted research on the impact of postpartum Medicaid access on maternal health equity, but also shifts the paradigm to focus on the role of structural racism in the design and implementation of policy and its influence on pregnant people's access to postpartum benefits. Our findings will be a key resource for policymakers on equitable design and implementation of postpartum Medicaid extension.", "keywords": [ "Address", "Adopted", "Adoption", "American", "Birth", "Black Populations", "Black race", "Communities", "Community Surveys", "Contraceptive methods", "Coronavirus", "Country", "Data", "Diabetes Mellitus", "Dimensions", "Eligibility Determination", "Enrollment", "Environment", "Equity", "Exclusion", "Exclusion Criteria", "Face", "Family", "Goals", "Health Personnel", "Health Policy", "Healthcare", "Hypertension", "Immigrant", "Income", "Inequity", "Institution", "Insurance", "Interruption", "Interview", "Laws", "Legal", "Length", "Maternal Health", "Maternal Mortality", "Maternal health equity", "Measures", "Medicaid", "Medicaid eligibility", "Mental Health", "Methods", "Modeling", "Neighborhoods", "New York", "Outcome", "Perinatal", "Persons", "Policies", "Policy Maker", "Postpartum Period", "Postpartum Women", "Pregnancy", "Provider", "Recommendation", "Reduce health disparities", "Research Priority", "Resources", "Risk", "Role", "Series", "Shapes", "Statutes and Laws", "Structural Racism", "Targeted Research", "Texas", "Time", "Variant", "Visit", "design", "ethnic disparity", "follow-up", "health care service utilization", "health equity", "improved", "insight", "lens", "maternal morbidity", "pandemic disease", "perinatal complications", "perinatal health", "post implementation", "post-pandemic", "postpartum health", "pragmatic implementation", "pre-pandemic", "pregnant", "primary outcome", "programs", "racial disparity", "response", "waiver" ], "approved": true } } ], "meta": { "pagination": { "page": 1405, "pages": 1442, "count": 14420 } } }