Represents Grant table in the DB

GET /v1/grants?sort=other_investigators
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    "data": [
        {
            "type": "Grant",
            "id": "15133",
            "attributes": {
                "award_id": "2414965",
                "title": "Instrument-free yes/no quantitative analysis of molecular biomarkers",
                "funder": {
                    "id": 3,
                    "ror": "https://ror.org/021nxhr62",
                    "name": "National Science Foundation",
                    "approved": true
                },
                "funder_divisions": [
                    "Engineering (ENG)",
                    "Special Initiatives"
                ],
                "program_reference_codes": [],
                "program_officials": [
                    {
                        "id": 961,
                        "first_name": "Aleksandr",
                        "last_name": "Simonian",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "start_date": "2024-09-01",
                "end_date": null,
                "award_amount": 380074,
                "principal_investigator": {
                    "id": 31692,
                    "first_name": "Irina",
                    "last_name": "Nesterova",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": []
                },
                "other_investigators": [],
                "awardee_organization": {
                    "id": 574,
                    "ror": "https://ror.org/012wxa772",
                    "name": "Northern Illinois University",
                    "address": "",
                    "city": "",
                    "state": "IL",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "Contemplating on the recent pandemics, the general public came to realize and appreciate the vital role of do-it-yourself diagnostic devices for disease control and management.  Such devices report whether a unique pathogen-associate molecule (also known as a molecular biomarker) is found in a human.  To extend the benefit of accessible molecular diagnostics to a wider range of diseases and situations, it is critical to develop devices that not only report whether a specific molecular biomarker is present but also answer the question of how much of that biomarker is present (so called quantitative analysis).  The goal of this project is to develop a platform that enables an equipment-free and easy-to-interpret quantitative analysis of molecular biomarkers in do-it-yourself and point-of-care environments.  To ensure an easy interpretation, the platform will produce a yes/no answer that involves observing bubbles as a readout.  Observing bubbles does not require scientific training, an equipped lab, or color vision proficiency and, therefore, can be easily recognized by everyone ages 2 and up.  In addition to public health benefits, the proposed development will spark and sustain a STEM interest in middle- and high school student through their direct hands-on engagement in the project- related experimental work.<br/><br/>The goal of this project is to develop a platform for instrument-free easy-to-interpret quantitative analysis of molecular biomarkers.  The proposed platform will comprise two developments:  a yes/no output for quantitative measurement and a novel equipment-free signal readout.  The yes/no quantitative measurement will be enabled through stoichiometry.  The heart of the model is negative cooperativity-based target – probe binding.  The binding modality yields a well-defined structure exactly at the stoichiometric equivalence point.  Detection of the structure is a yes/no event for a quantitative result.  The new equipment-free readout will be based on bubbling produced in a gas-generating reaction.  As an easy to spot and interpret phenomena, bubbling perfectly matches the yes/no paradigm.  The gas-generating readout will be triggered via an activatable in the equivalence point catalytic system.  The project will produce a general methodology that is adaptable to a range of molecular targets including potential new agents (once their target binding is characterized to some extent).<br/><br/>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": [],
                "approved": true
            }
        },
        {
            "type": "Grant",
            "id": "15194",
            "attributes": {
                "award_id": "1R43OH012683-01",
                "title": "Voice Amplifier to Enhance Occupational Safety and Critical Care among Masked Providers",
                "funder": {
                    "id": 4,
                    "ror": "https://ror.org/01cwqze88",
                    "name": "National Institutes of Health",
                    "approved": true
                },
                "funder_divisions": [
                    "National Institute for Occupational Safety and Health (NIOSH)"
                ],
                "program_reference_codes": [],
                "program_officials": [
                    {
                        "id": 24462,
                        "first_name": "BRIDGETTE E",
                        "last_name": "GARRETT",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "start_date": "2024-09-01",
                "end_date": "2025-08-31",
                "award_amount": 357231,
                "principal_investigator": {
                    "id": 31774,
                    "first_name": "Matthew",
                    "last_name": "Hilden",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": []
                },
                "other_investigators": [],
                "awardee_organization": {
                    "id": 2518,
                    "ror": "",
                    "name": "MINNESOTA HEALTHSOLUTIONS CORPORATION",
                    "address": "",
                    "city": "",
                    "state": "MN",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "The proposed project relates to the development of a technological intervention to improve speech intelligibility among healthcare workers who wear personal protective equipment for occupational safety while caring for patients with infectious diseases. Respiratory protective equipment such as filtering facepiece respirators, elastomeric half- and full-facepiece respirators and powered air-purifying respirators are routinely worn in the critical care unit as components of personal protective equipment for occupational safety when caring for patients with infectious diseases including COVID-19. Diminished speech intelligibility has been observed to be associated with certain types of respiratory protective equipment. Effective verbal exchanges are vital in critical care and significant reductions in speech intelligibility impact many complex tasks. The objective of this proposed scientifically rigorous phase I project is to specify, design, construct, test and evaluate a fully functional prototype system to improve speech intelligibility among healthcare workers wearing respiratory protective equipment. The system will be designed for use in a healthcare environment and be compatible with a wide variety of respiratory protective equipment.",
                "keywords": [],
                "approved": true
            }
        },
        {
            "type": "Grant",
            "id": "15202",
            "attributes": {
                "award_id": "1R56AI178166-01A1",
                "title": "Pathogenesis and Outcomes of SARS-CoV-2 In Utero Transmission - Immunologic and Virologic Evaluations",
                "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": 6243,
                        "first_name": "BROOKE ALLISON",
                        "last_name": "Bozick",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "start_date": "2024-09-01",
                "end_date": "2025-08-31",
                "award_amount": 664837,
                "principal_investigator": {
                    "id": 31785,
                    "first_name": "Andrea A.Z.",
                    "last_name": "Kovacs",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": []
                },
                "other_investigators": [],
                "awardee_organization": {
                    "id": 152,
                    "ror": "https://ror.org/03taz7m60",
                    "name": "University of Southern California",
                    "address": "",
                    "city": "",
                    "state": "CA",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "Importance: Despite effective vaccines, SARS-CoV-2 infection remains a major public health problem for pregnant women and their newborns as they have increased morbidity and mortality. Studies on estimated rates of in utero transmission are conflicting and reported on small numbers mostly limited to PCR testing at birth. Critical Gaps include limited diagnostics to identify in utero infection and lack of understanding of factors that impact MTCT and the pathogenesis of disease. From October 2021 through February 2023, we studied 1294 infant cord bloods for presence and level of SARS-CoV-2 antibodies. Overall, 89.9% had anti-RBD IgG, indicating maternal vaccination and/or previous infection and 55.1% had both anti-N and anti-RBD IgG, indicative of past infection. Fetal IgA and/or IgM antibodies to SARS-CoV-2 were found in 21.8% of 176/808 samples with anti-N, indicative of in utero transmission. The overall goal of this study is to identify newborns with in utero SARS-CoV-2 and prospectively follow infants to identify clinical and neurodevelopment outcomes.  Aim 1: Identify newborns with in utero SARS-CoV-2 infection using a multi-faceted approach and assess relationship with inflammation, placental infection and pathology, and immunity. Hypothesis 1: In utero infection will be associated with elevated soluble markers of inflammation in newborn cord blood and evidence of placental infection and dysfunction. Using cord blood we will screen 3,600 newborns for anti-N, S, and RBD IgG antibodies (Abs) and if anti-N+ we will assess for SARS-CoV-2 specific anti-IgM and anti-IgA abs. Maternal SARS-CoV-2 qPCR testing will be done at delivery, and if qPCR+, newborn qPCR will be performed at 24/48 hours. Variant type will be determined by ddPCR. Newborn meconium/stool samples will have qPCR testing. Soluble biomarkers of inflammation and immune activation will be determined. Finally, placentas will be evaluated for pathology and SARS-CoV-2 infection.  Aim 2. Longitudinally assess for immune activation, dysregulation, and function among a subset of infants with in utero infection and matched controls. Hypothesis 2: In utero infected infants will have abnormal markers of inflammation, immune activation, and dysregulation that if sustained will be associated with adverse clinical outcomes. In a subset of 100 infants with in utero SARS-CoV-2 and 50 uninfected controls we will determine levels of CD4 and CD8 T-cell activation and dysregulation and assess for SARS-CoV-2 specific antibodies and T cell response in mother-infant dyads at birth and longitudinally. We will then correlate with clinical and neurodevelopmental outcomes.  At the end of this project, we will have developed a comprehensive algorithm to screen and follow newborns with in-utero SARS-CoV-2 and will have determined if there are immunologic dysfunctions impacting clinical, developmental, neurologic, and other abnormalities that may require long-term follow-up, treatments and/or interventions.",
                "keywords": [],
                "approved": true
            }
        },
        {
            "type": "Grant",
            "id": "15178",
            "attributes": {
                "award_id": "1F31AI179125-01A1",
                "title": "Defining factors affecting natural killer cells' antibody-dependent responses in COVID-19",
                "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": "2024-09-01",
                "end_date": "2027-08-31",
                "award_amount": 42293,
                "principal_investigator": {
                    "id": 31761,
                    "first_name": "Leslie",
                    "last_name": "Chan",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": []
                },
                "other_investigators": [],
                "awardee_organization": {
                    "id": 266,
                    "ror": "https://ror.org/00f54p054",
                    "name": "Stanford University",
                    "address": "",
                    "city": "",
                    "state": "CA",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "SARS-CoV-2, the causative agent of COVID-19, has become an extended public health challenge due to the emergence of variants that results in reduced protection by vaccination and prior infection. As innate immune cells that recognize and lyse infected or stressed cells, natural killer (NK) cells are uniquely poised to respond to SARS-CoV-2 variants capable of escaping antigen-specific immune responses. NK cells can potently target virus-infected cells via antibody-dependent responses even if the host antibodies have poor neutralizing activity. While the ability of NK cells to mediate antibody-dependent responses could significantly influence disease pathogenesis, the factors affecting NK cells’ antibody-dependent responses are understudied. My proposed research seeks to resolve these critical gaps in our knowledge of the immune response to SARS-CoV-2. I hypothesize that SARS-CoV-2 infection, immunosuppressant treatment, and acquisition of surface molecules from infected cells impair the antibody-dependent responses of NK cells. To test this hypothesis, I will 1) identify how COVID-19 vaccination and infection influence the ability of memory-like NK cells to perform antibody-dependent responses; 2) elucidate how immunosuppressant drugs interact with COVID-19 cytokines to affect NK cells’ antibody-dependent responses; and 3) define mechanisms by which trogocytosis, the acquisition of surface molecules, from SARS-CoV-2-infected cells impairs NK cells’ antibody-dependent responses. In Aim 1, I will compare NK cells’ antibody-dependent responses across different COVID-19 patient groups and build upon my training in immune cells’ surface proteomics analysis to evaluate intracellular signaling activity. In Aim 2, I will co-culture NK cells with SARS-CoV-2-infected cells to elucidate the impact of immunosuppressant drugs on NK cells’ antibody-dependent response. In Aim 3, I will gain training in dissecting NK cells’ ligand interactions and NK cell engineering to define mechanisms by which trogocytosis can impair NK cells’ functions. My BSL3 certification and training to work with SARS-CoV-2, combined with my experiences in evaluating NK cells’ functions, uniquely qualify me to carry out this proposed research. This research plan will provide me with robust training in assessing NK cell responses to virus-infected cells through the establishment of co-culture systems. Notably, my proposed research on trogocytosis is a particularly novel research area and gives me the opportunity to creatively pursue an understudied topic of interest by identifying the tools appropriate for this research. This work will be the first to determine the mechanisms by which NK cells’ antibody-dependent responses are regulated in infection, with therapeutic implications for COVID-19 and other infectious diseases.",
                "keywords": [],
                "approved": true
            }
        },
        {
            "type": "Grant",
            "id": "15110",
            "attributes": {
                "award_id": "2405915",
                "title": "US-Israel Collab: A structural and multiepistemic approach to modeling Brucella transmission along complex networks in Bedouin communities",
                "funder": {
                    "id": 3,
                    "ror": "https://ror.org/021nxhr62",
                    "name": "National Science Foundation",
                    "approved": true
                },
                "funder_divisions": [
                    "Biological Sciences (BIO)",
                    "Ecology of Infectious Diseases"
                ],
                "program_reference_codes": [],
                "program_officials": [
                    {
                        "id": 599,
                        "first_name": "Samuel",
                        "last_name": "Scheiner",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "start_date": "2024-09-01",
                "end_date": null,
                "award_amount": 3000000,
                "principal_investigator": {
                    "id": 31655,
                    "first_name": "Julianne",
                    "last_name": "Meisner",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": []
                },
                "other_investigators": [],
                "awardee_organization": {
                    "id": 159,
                    "ror": "https://ror.org/00cvxb145",
                    "name": "University of Washington",
                    "address": "",
                    "city": "",
                    "state": "WA",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "Zoonotic diseases are diseases that animals give to humans. SARS-CoV-2, the cause of COVD-19, is a zoonotic disease, and the COVID-19 pandemic has highlighted the importance of both zoonotic diseases, and mutual trust between public health institutions and the public whose health they are intended to safeguard. To effectively control zoonoses, we need a better understanding of exactly how they are transmitted, and how trust—and its absence—influences that transmission. Brucellosis is a zoonosis caused by a bacteria that is present worldwide, including the US. The most serious form is caused by the bacteria Brucella melitensis, which is spread by sheep and goats when a person drinks or eats milk or cheese that hasn’t been pasteurized, or when people assist a sheep or goat who is giving birth. In animals, the disease causes pregnancy losses and reduced milk production. In humans, the disease also causes pregnancy losses, as well as fever, headaches, back pain, physical weakness, and fatigue that can last for months or even years. In some cases, severe neurological and heart effects can also be seen. The project leverages the strong US-Israel research collaboration to advance the knowledge of the more-than-bio-physical drivers of interspecies disease transmission, focusing on Brucella melitensis but generalizable to other zoonotic diseases. <br/><br/>This project works with Bedouin communities in southern Israel, where Brucella burden is among the highest in the world, second only to Syria pre-war and likely worsening since. These communities exhibit extremely high levels of institutional distrust and experience ongoing urbanization. This provides a model setting for examining how distrust, urbanization, and zoonoses—a triad being replicated throughout the world—collectively impact humans, animals, and livelihoods. The research tests the hypothesis that institutional distrust and population displacement to urban centers increase the density of human-animal contact networks, facilitating the transmission of brucellosis. Objective 1 aims to measure human-animal contact networks among six Bedouin communities in southern Israel using qualitative data, quantitative data, and experience-based knowledge.  These data support Objective 2 to model synthetic human-animal networks and develop a new method for generating Brucella genomes, applied to samples collected from humans, livestock, and environments. Subsequent tasks for Objective 3 include fitting and validating an epidemic network model using these synthetic networks and Brucella genomes and applying this model to test the research hypothesis by exploring counterfactual scenarios defined by distrust and urbanization, developed through participatory methods. These methods and insights afford broad applicability beyond this empirical setting, to other Brucella systems and zoonotic diseases throughout the world.<br/><br/>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": [],
                "approved": true
            }
        },
        {
            "type": "Grant",
            "id": "15210",
            "attributes": {
                "award_id": "1G08LM014406-01",
                "title": "Long COVID Health Literacy Project: Bringing Health Information to Patients and Providers with Health Disparities in Rural Northern New England",
                "funder": {
                    "id": 4,
                    "ror": "https://ror.org/01cwqze88",
                    "name": "National Institutes of Health",
                    "approved": true
                },
                "funder_divisions": [
                    "National Library of Medicine (NLM)"
                ],
                "program_reference_codes": [],
                "program_officials": [
                    {
                        "id": 31790,
                        "first_name": "CRISTAN",
                        "last_name": "SMITH",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "start_date": "2024-09-01",
                "end_date": "2027-07-10",
                "award_amount": 150000,
                "principal_investigator": {
                    "id": 31791,
                    "first_name": "Jeffrey",
                    "last_name": "Parsonnet",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": []
                },
                "other_investigators": [],
                "awardee_organization": {
                    "id": 2072,
                    "ror": "",
                    "name": "DARTMOUTH-HITCHCOCK CLINIC",
                    "address": "",
                    "city": "",
                    "state": "NH",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "The purpose of this project is to address health disparities in the care of patients with post-acute COVID syndrome (PACS) due to the rural nature of northern New England and its shortage of medical services. We will develop useful, understandable and relatable information for patients and providers, in partnership with rural and biomedical libraries. The foundation for our project is the Dartmouth-Hitchcock PACS Clinic, an established, comprehensive clinic serving patients in Vermont and New Hampshire.  The rural nature of northern New England poses a challenge to delivery of comprehensive care to PACS patients. Most parts of VT and NH are characterized as being “small town/isolated rural” or “large rural town.” The debilitating nature of PACS threatens job security, financial stability, and the ability to function normally, and there is limited access to primary care, physical therapy, occupational therapy, and mental health services that can accept and are familiar with the complex nature of PACS. Furthermore, the Area Deprivation Index (ADI), based on a measure created by HRSA, shows that at least half of the two states have ADI scores of >50, indicating that they are “disadvantaged” in relation to national standards. A large percentage of the 1300 patients referred to our PACS clinic report difficulties in accessing reliable information about managing their condition and finding locally based services. Affordable, high-speed internet service is often limited in rural settings, and many rely on local libraries to meet those needs. Above all, patients express a sense of isolation, both physical and emotional. Our experience has taught us that bridging that sense of isolation is often the greatest service we can provide.  Our goal is to “reach more people in more ways through enhanced engagement pathways.” Our aims are:   To improve the care of patients with PACS in rural VT and NH by disseminating useful, usable, and  understandable information to this health-disparity population.   To promote a better understanding of PACS for patients and providers by means of new, appropriately  targeted resources. We will create an online archive of “digital stories” that highlight lived experiences  of patients with PACS and create an independent website and monthly newsletter with content about  PACS that is responsive to the emerging science and meets the needs of our patients and providers.   To raise awareness about PACS in rural communities and promote community access to information  about PACS and post-COVID care.  We will partner with rural libraries, which are often a primary hub of information-sharing in rural communities, to assist in deploying computer and information technology that is otherwise unavailable or difficult to use for many of our patients. We will tailor information to meet the needs of our population. Our efforts should be generalizable to other rural communities in the US.",
                "keywords": [],
                "approved": true
            }
        },
        {
            "type": "Grant",
            "id": "15218",
            "attributes": {
                "award_id": "3U01CA260584-02S3",
                "title": "SARS-CoV-2 Serological Antibody Testing for Disease Surveillance and Clinical Use",
                "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": 23642,
                        "first_name": "Vaurice",
                        "last_name": "Starks",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "start_date": "2024-09-01",
                "end_date": "2024-11-30",
                "award_amount": 302796,
                "principal_investigator": {
                    "id": 25068,
                    "first_name": "Jacek",
                    "last_name": "Skarbinski",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": [
                        {
                            "id": 769,
                            "ror": "",
                            "name": "KAISER FOUNDATION RESEARCH INSTITUTE",
                            "address": "",
                            "city": "",
                            "state": "CA",
                            "zip": "",
                            "country": "United States",
                            "approved": true
                        }
                    ]
                },
                "other_investigators": [],
                "awardee_organization": {
                    "id": 769,
                    "ror": "",
                    "name": "KAISER FOUNDATION RESEARCH INSTITUTE",
                    "address": "",
                    "city": "",
                    "state": "CA",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "Serologic testing for presence of SARS-CoV-2 antibodies is a critical tool for understanding the epidemiology and designing control strategies for the COVID-19 pandemic. Our understanding of the epidemiology of this pandemic is primarily derived from real-time data on the number of polymerase chain reaction (PCR)-positive COVID-19 patients in outpatient and inpatient settings, and thus misses patients with asymptomatic infection or who have not had SARS-CoV-2 PCR testing. Serologic testing for SARS-CoV-2 antibodies can identify persons who have been exposed and infected with SARS-CoV-2 at any time and might be a correlate of protective immunity. This project aims to advance our understanding of SARS-CoV-2 serological testing at the individual and population-level. To achieve this we will develop and implement a large-scale, population- based, flexible platform to assess SARS-CoV-2 sero-prevalence, sero-incidence, risk of sero-conversion and longevity of antibody response in a large, integrated health system with linked rich demographic, behavioral and clinical data. For Aim 1 we will establish a community cohort of Kaiser Permanente Northern California (KPNC) members; a random sample of community dwelling persons, age 7 years and older, will be invited to participate in ongoing surveillance of antibody development to assess population-level sero-prevalence and sero-incidence. For Aim 2, we will enroll a cohort of persons who are positive for SARS-CoV-2 PCR or antibodies and will follow them prospectively with repeat SARS-CoV-2 antibody testing for immune surveillance and to determine longevity of antibody response. For Aim 3, we will establish a data-only cohort of all persons who have been diagnosed with COVID-19 disease, or had SARS-CoV-2 PCR or antibody testing; As of July 15, 2020, there are about 290,000 such persons in KPNC and the number increases daily as we test ~10,000 persons per day. In this cohort, we will assess risk of SARS-CoV-2 re-infection and will have the opportunity to examine interactions with a personal history of cancer or cancer treatment and other clinical factors or comorbid conditions, to determine if these conditions influence the likelihood of development of COVID-19 or reinfection. For Aim 4, we will establish mechanisms for collaboration with other scientists in the Serological Sciences Network, including mechanisms for additional sample collection. This series of linked studies embedded in a large, integrated health system with a large number of COVID-19 patients and high SARS- CoV-2 testing capacity will enhance our understanding of the utility of commercially available, large-scale SARS-CoV-2 antibody testing for population-level and individual-level disease control.",
                "keywords": [],
                "approved": true
            }
        },
        {
            "type": "Grant",
            "id": "15125",
            "attributes": {
                "award_id": "2404834",
                "title": "Conference: MEE Hubs: A hybrid conference in microbial ecology and evolution",
                "funder": {
                    "id": 3,
                    "ror": "https://ror.org/021nxhr62",
                    "name": "National Science Foundation",
                    "approved": true
                },
                "funder_divisions": [
                    "Biological Sciences (BIO)",
                    "Evolutionary Processes"
                ],
                "program_reference_codes": [],
                "program_officials": [
                    {
                        "id": 6330,
                        "first_name": "Paco",
                        "last_name": "Moore",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "start_date": "2024-09-01",
                "end_date": null,
                "award_amount": 120910,
                "principal_investigator": {
                    "id": 31683,
                    "first_name": "Maria",
                    "last_name": "Rebolleda-Gomez",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": []
                },
                "other_investigators": [],
                "awardee_organization": {
                    "id": 177,
                    "ror": "",
                    "name": "University of California-Irvine",
                    "address": "",
                    "city": "",
                    "state": "CA",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "Recent years have seen an increased integration of ecology and evolution in the understanding of microbial populations and communities. For instance application and development of population genetic models allows investigation of the evolution of microbes in the host, and the ways in which spatial dynamics can shape evolutionary change. Increased integration physiological theories with ecology also increases predictability of microbial community assembly and function. These current advances make it clear that it is important to foster interdisciplinary interactions in understanding microbiomes. Conferences can play a central role in this type of fostering. However, travel costs, both monetary and environmental, are a barrier to increased conference participation. This conference will integrate microbiology, evolutionary ecology, physics, and mathematics, driving innovation in fundamental and applied questions. This conference will explore a novel mechanism for conferences that will allow the benefits of in person meetings while retaining the global networking available through virtual meetings. The project will develop a more sustainable model of conferences in the future and will promote the organizing similar conferences in other fields. Decreased cost will foster increased participation of a scientifically and demographically diverse set of participants. <br/>Virtual conferences as a result of the pandemic have provided an alternative to in person conferences that is more sustainable and accessible, but lack important aspects of in person encounters with colleagues. As a solution this conference will explore a hub-based conference model in microbial ecology and evolution. This entire conference will consist of six hubs meeting on the same day and interacting across four countries (USA, Mexico, UK, Switzerland). Each of the hubs will highlighting cutting-edge microbial ecology and evolution from a highly interdisciplinary perspective. This funding will support 3 USA based hubs, including awards to promote travel of students from historically underrepresented minorities in STEM.<br/><br/>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": [],
                "approved": true
            }
        },
        {
            "type": "Grant",
            "id": "15805",
            "attributes": {
                "award_id": "1K01DA062904-01",
                "title": "Clinician cannabis use-related preconceptions perpetuating low quality of prenatal care for women who use cannabis during pregnancy",
                "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": 32896,
                        "first_name": "SARAH",
                        "last_name": "VIDAL",
                        "orcid": "",
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "start_date": "2025-07-15",
                "end_date": "2030-06-30",
                "award_amount": 196236,
                "principal_investigator": {
                    "id": 32897,
                    "first_name": "Rachel Carmen",
                    "last_name": "Ceasar",
                    "orcid": "",
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": []
                },
                "other_investigators": [],
                "awardee_organization": {
                    "id": 2622,
                    "ror": "",
                    "name": "UNIVERSITY OF SOUTHERN CALIFORNIA",
                    "address": "",
                    "city": "",
                    "state": "CA",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "Cannabis is the most used illicit substance during pregnancy. Rates of self-medicating with cannabis escalated during the COVID-19 pandemic. The scientific objective of this proposal is to investigate the mechanisms contributing to preconceptions about those who use cannabis, especially during pregnancy. The central hypothesis is that preconceptions about those who use cannabis result in negative interactions between patients and clinicians that reduce the quality of healthcare and result in poor outcomes. This innovative project will be the first to: (a) leverage natural language processing/artificial intelligence (NLP/AI) techniques to investigate preconceptions about cannabis use in clinical notes, and (b) investigate associations between cannabis use and prenatal care quality. Research aims will: (Aim 1) Investigate preconceptions about those who use cannabis during pregnancy using a mixed methods approach that integrates NLP/AI and qualitative interviews; (Aim 2) Investigate associations between cannabis use and prenatal care quality among different population groups, such as differences in socioeconomic status and education levels; and (Aim 3) Develop, adapt, and test the feasibility and usability of a clinician training on quality health care practices for those who use cannabis during  pregnancy using a multistage modified Delphi process, survey, and qualitative focus groups. This research is complemented by a training plan that builds upon Dr. Rachel Carmen Ceasar’s background in mixed qualitative-quantitative methods and substance use research. The training plan includes using NLP/AI approaches, advanced survey methods in reproductive epidemiology, and implementation science. Together, this research and training will prepare Dr. Ceasar to advance as an independent investigator conducting research on health and substance use among those who are pregnant across the lifespan. The proposed project will improve clinicians’ care of those who use cannabis during pregnancy, providing evidence to inform the development of interventions designed to reduce cannabis-use-related notions in prenatal care.",
                "keywords": [
                    "Adverse effects",
                    "American College of Obstetricians and Gynecologists",
                    "Artificial Intelligence",
                    "Belief",
                    "COVID-19 pandemic",
                    "California",
                    "Cannabis",
                    "Caring",
                    "Child Welfare",
                    "Clinical",
                    "Clinical Treatment",
                    "Consensus",
                    "Cross-Sectional Studies",
                    "Data",
                    "Detection",
                    "Education",
                    "Educational Status",
                    "Family",
                    "Focus Groups",
                    "Fright",
                    "Future",
                    "Goals",
                    "Guidelines",
                    "Gynecologic",
                    "Health",
                    "Health Benefit",
                    "Health Care",
                    "Income",
                    "Infant",
                    "Interview",
                    "Knowledge",
                    "Language",
                    "Legal",
                    "Link",
                    "Los Angeles",
                    "Medical",
                    "Medical center",
                    "Mentored Research Scientist Development Award",
                    "Mentors",
                    "Methods",
                    "Modeling",
                    "Moods",
                    "Mothers",
                    "Natural Language Processing",
                    "Nausea",
                    "Outcome",
                    "Output",
                    "Pain",
                    "Patient Outcomes Assessments",
                    "Patients",
                    "Persons",
                    "Policies",
                    "Policy Maker",
                    "Population",
                    "Population Group",
                    "Pregnancy",
                    "Pregnancy Outcome",
                    "Pregnant Women",
                    "Prenatal care",
                    "Prevalence",
                    "Process",
                    "Quality of Care",
                    "Questionnaires",
                    "Recommendation",
                    "Reporting",
                    "Research",
                    "Research Personnel",
                    "Rice",
                    "Risk",
                    "Socioeconomic Status",
                    "Supervision",
                    "Survey Methodology",
                    "Surveys",
                    "Techniques",
                    "Testing",
                    "Time",
                    "Training",
                    "Woman",
                    "authority",
                    "cannabis cessation",
                    "comparative",
                    "efficacy evaluation",
                    "evidence base",
                    "experience",
                    "feasibility testing",
                    "follow-up",
                    "health care delivery",
                    "health care quality",
                    "implementation science",
                    "improved",
                    "indexing",
                    "innovation",
                    "large language model",
                    "life span",
                    "low socioeconomic status",
                    "marijuana use",
                    "marijuana use in pregnancy",
                    "neurodevelopment",
                    "open source",
                    "preconception",
                    "prenatal",
                    "provider behavior",
                    "reproductive epidemiology",
                    "substance use",
                    "therapy design",
                    "therapy development",
                    "usability"
                ],
                "approved": true
            }
        },
        {
            "type": "Grant",
            "id": "15186",
            "attributes": {
                "award_id": "1R01HS030083-01",
                "title": "Reducing Uninsurance by Addressing Administrative Burdens in the Health Insurance Marketplaces",
                "funder": {
                    "id": 4,
                    "ror": "https://ror.org/01cwqze88",
                    "name": "National Institutes of Health",
                    "approved": true
                },
                "funder_divisions": [
                    "Agency for Healthcare Research and Quality (AHRQ)"
                ],
                "program_reference_codes": [],
                "program_officials": [
                    {
                        "id": 24040,
                        "first_name": "Fred",
                        "last_name": "Hellinger",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "start_date": "2024-09-01",
                "end_date": "2029-06-30",
                "award_amount": 376307,
                "principal_investigator": {
                    "id": 31767,
                    "first_name": "Coleman",
                    "last_name": "Drake",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": []
                },
                "other_investigators": [],
                "awardee_organization": {
                    "id": 848,
                    "ror": "",
                    "name": "UNIVERSITY OF PITTSBURGH AT PITTSBURGH",
                    "address": "",
                    "city": "",
                    "state": "PA",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "Over 27 million Americans remain uninsured in 2022, and millions more have lost Medicaid coverage with the end of the Public Health Emergency in 2023. Over 40% of uninsured persons were eligible for large subsidies to obtain coverage through the Health Insurance Marketplaces created by the Affordable Care Act. Health in- surance is critical to providing access to care and improving health outcomes. While the American Rescue Plan Act greatly reduced affordability barriers to Marketplace coverage, other key barriers to coverage remain un- addressed. Administrative burdens—the compliance, learning, and psychological costs people face when inter- acting with government services—have a large effect on health insurance coverage take-up. Despite the Market- places’ critical role in providing health insurance coverage to Americans during the COVID-19 pandemic, lim- ited research exists on the effects of administrative burdens on Marketplace enrollment. This proposal’s objec- tive is to assess how different types of administrative burdens impact Marketplace enrollment. The applicants will use state-of-the-art research methods from economics, public administration, and anthropology to address three specific aims: (1) determine if eliminating premium payment-related compliance costs affects reenroll- ment in Marketplace coverage; (2) determine whether reducing the burden of information costs through adver- tising affects Marketplace coverage take-up; and (3) create a person-centered understanding of how compli- ance, information, and psychological costs erect barriers to Marketplace coverage. Aims 1 and 2 will use Mar- ketplace enrollment data and causal inference approaches; Aim 3 will use semi-structured interviews in three diverse states, Arizona, Connecticut, and North Carolina, to study administrative burdens. This mixed methods research addresses a critical need for evidence on cost-effective policies that can reduce the number of unin- sured, who disproportionately consist of AHRQ priority populations, including racial and ethnic minorities and rural and low-income populations. In so doing, this proposal is directly responsive to AHRQ’s interest in re- search on health insurance coverage, access and affordability, and its special emphasis notice on health services research to advance health equity. It also is responsive to the President’s executive order on reducing adminis- trative burdens. Results will provide state and federal policymakers with easily implementable approaches to reducing the uninsured rate by making the process of Marketplace enrollment less burdensome. This proposal is particularly timely with the end of the Public Health Emergency, which will require millions of former Medi- caid enrollees to successfully navigate Marketplace administrative burdens to remain insured. The applicants will directly disseminate findings to Marketplace policymakers and administrators to facilitate translation of the proposed research into policies that reduce the number of uninsured.",
                "keywords": [],
                "approved": true
            }
        }
    ],
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