Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1393&sort=abstract
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=abstract", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1424&sort=abstract", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1394&sort=abstract", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1392&sort=abstract" }, "data": [ { "type": "Grant", "id": "1103", "attributes": { "award_id": "2120530", "title": "Collaborative Research: Disruption and Resilience in Healthcare Routines Following Adverse Events", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)" ], "program_reference_codes": [], "program_officials": [ { "id": 2764, "first_name": "Patricia Van", "last_name": "Zandt", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-09-01", "end_date": "2024-08-31", "award_amount": 310161, "principal_investigator": { "id": 2766, "first_name": "Brian T", "last_name": "Pentland", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 521, "ror": "https://ror.org/05hs6h993", "name": "Michigan State University", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 2765, "first_name": "Ken", "last_name": "Frank", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 521, "ror": "https://ror.org/05hs6h993", "name": "Michigan State University", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true }, "abstract": "When routines are disrupted, people want to get back to normal. If the disruption is minor, like a flat tire, recovery is easy. If the disruption is major, recovery may be more difficult. For example, the shutdowns caused by the COVID pandemic forced doctors, nurses, and other clinical staff to find new ways to care for their patients. This research will use this example to study the effects of disruptions on healthcare routines. The expectation is that routines will “bounce back” from minor disruptions, but the effects of major disruptions are more difficult to predict. After major disruptions, some routines may return to normal, while others may not. The goal of this project is to discover basic mechanisms that influence stability and change in routines. To understand what makes some routines stronger than others, the effects of the COVID pandemic will be studied in four medical fields at the University of Rochester Medical Center: dermatology, orthopedics, oncology, and cardiology. Data from electronic health records will be used to study the effects of shutdowns and other kinds of disruptions, such as changes in software and billing codes. Tools from network science will be used to model routines as patterns of action. These methods will allow comparisons to be made between patterns of action before and after a disruption with great precision. The extent to which the strength of a routine depends on the structure of the action pattern itself will be examined. Data will be produced on outpatient clinical routines during the COVID-19 pandemic along with a variety of materials to communicate the findings with a broader audience. Ultimately, this research will lead to a better understanding of how institutional routines can be made more reliable and effective in the face of disasters large and small.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": "1104", "attributes": { "award_id": "2120014", "title": "Collaborative Research: Disruption and Resilience in Healthcare Routines Following Adverse Events", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)" ], "program_reference_codes": [], "program_officials": [ { "id": 2767, "first_name": "Patricia Van", "last_name": "Zandt", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-09-01", "end_date": "2024-08-31", "award_amount": 227839, "principal_investigator": { "id": 2768, "first_name": "Julie R", "last_name": "Wolf", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 464, "ror": "https://ror.org/022kthw22", "name": "University of Rochester", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 464, "ror": "https://ror.org/022kthw22", "name": "University of Rochester", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "When routines are disrupted, people want to get back to normal. If the disruption is minor, like a flat tire, recovery is easy. If the disruption is major, recovery may be more difficult. For example, the shutdowns caused by the COVID pandemic forced doctors, nurses, and other clinical staff to find new ways to care for their patients. This research will use this example to study the effects of disruptions on healthcare routines. The expectation is that routines will “bounce back” from minor disruptions, but the effects of major disruptions are more difficult to predict. After major disruptions, some routines may return to normal, while others may not. The goal of this project is to discover basic mechanisms that influence stability and change in routines. To understand what makes some routines stronger than others, the effects of the COVID pandemic will be studied in four medical fields at the University of Rochester Medical Center: dermatology, orthopedics, oncology, and cardiology. Data from electronic health records will be used to study the effects of shutdowns and other kinds of disruptions, such as changes in software and billing codes. Tools from network science will be used to model routines as patterns of action. These methods will allow comparisons to be made between patterns of action before and after a disruption with great precision. The extent to which the strength of a routine depends on the structure of the action pattern itself will be examined. Data will be produced on outpatient clinical routines during the COVID-19 pandemic along with a variety of materials to communicate the findings with a broader audience. Ultimately, this research will lead to a better understanding of how institutional routines can be made more reliable and effective in the face of disasters large and small.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": "1467", "attributes": { "award_id": "2028724", "title": "RAPID: Collaborative Research: The Diffusion of State Policy Responses to the 2019 Novel Coronavirus", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)" ], "program_reference_codes": [ "096Z", "7914", "9178" ], "program_officials": [ { "id": 3812, "first_name": "Jan", "last_name": "Leighley", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-05-15", "end_date": "2022-04-30", "award_amount": 44904, "principal_investigator": { "id": 3813, "first_name": "Frederick J", "last_name": "Boehmke", "orcid": "https://orcid.org/0000-0003-3309-0885", "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": "['https://dataverse.harvard.edu/dataverse/sprc19/']", "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 220, "ror": "https://ror.org/036jqmy94", "name": "University of Iowa", "address": "", "city": "", "state": "IA", "zip": "", "country": "United States", "approved": true }, "abstract": "When the 2019 novel coronavirus arrived in the United States in February and March of 2020, state governments quickly began enacting policies intended to contain and mitigate its spread. Understanding the timing and sequence of these policy choices, and those policies’ eventual consequences, is critical for assessing how governments can be most effective during pandemics. This project collects data on state and local governments’ responses to COVID-19, including policies related to closing schools, canceling travel, banning public gatherings, closing restaurants and bars, delaying rent payments, and rules on medical licenses. This data allows researchers to examine the factors that influence states’ policy choices, whether those factors differ from the ways in which states enact policies during normal times, which policies are effective in slowing the spread and morbidity of the virus, and how states roll back policies in a manner that allows economic activity to resume while maintaining preparedness to avoid and mitigated waves of the virus. This project collects data on state government responses to COVID-19 by scraping government websites daily, focusing on sites dedicated to COVID-19 and those associated with the executive branch, state legislatures, and state departments of public health. It also collects data on the number of diagnosed cases, fatalities, recoveries in the states, and mobility data that tracks geographic movements from mobile phones. The policy recommendations or decisions recorded from state government pages include decisions related to closing schools, canceling travel, banning public gatherings (and their size), closing restaurants and bars, travel quarantines, postponing elections, safe shelter orders, limiting elective medical procedures, as well as when states modify these policies; additional data is collected from official state Twitter accounts. This data allows researchers to examine the factors that influence states’ policy choices, whether those factors differ from the ways in which states enact policies during normal times, which policies are effective in slowing the spread and morbidity of the virus, and how states roll back policies in a manner that allows economic activity to resume while maintaining preparedness to avoid and mitigate new waves of the virus. This project is jointly funded by the Accountable Institutions and Behavior Program and the Established Program to Stimulate Competitive Research (EPSCoR).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": "1468", "attributes": { "award_id": "2028674", "title": "RAPID: Collaborative Research: The Diffusion of State Policy Responses to the 2019 Novel Coronavirus", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)" ], "program_reference_codes": [ "096Z", "7914", "9178" ], "program_officials": [ { "id": 3814, "first_name": "Jan", "last_name": "Leighley", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-05-15", "end_date": "2021-04-30", "award_amount": 8730, "principal_investigator": { "id": 3815, "first_name": "Jeffrey J", "last_name": "Harden", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 171, "ror": "https://ror.org/00mkhxb43", "name": "University of Notre Dame", "address": "", "city": "", "state": "IN", "zip": "", "country": "United States", "approved": true }, "abstract": "When the 2019 novel coronavirus arrived in the United States in February and March of 2020, state governments quickly began enacting policies intended to contain and mitigate its spread. Understanding the timing and sequence of these policy choices, and those policies’ eventual consequences, is critical for assessing how governments can be most effective during pandemics. This project collects data on state and local governments’ responses to COVID-19, including policies related to closing schools, canceling travel, banning public gatherings, closing restaurants and bars, delaying rent payments, and rules on medical licenses. This data allows researchers to examine the factors that influence states’ policy choices, whether those factors differ from the ways in which states enact policies during normal times, which policies are effective in slowing the spread and morbidity of the virus, and how states roll back policies in a manner that allows economic activity to resume while maintaining preparedness to avoid and mitigated waves of the virus. This project collects data on state government responses to COVID-19 by scraping government websites daily, focusing on sites dedicated to COVID-19 and those associated with the executive branch, state legislatures, and state departments of public health. It also collects data on the number of diagnosed cases, fatalities, recoveries in the states, and mobility data that tracks geographic movements from mobile phones. The policy recommendations or decisions recorded from state government pages include decisions related to closing schools, canceling travel, banning public gatherings (and their size), closing restaurants and bars, travel quarantines, postponing elections, safe shelter orders, limiting elective medical procedures, as well as when states modify these policies; additional data is collected from official state Twitter accounts. This data allows researchers to examine the factors that influence states’ policy choices, whether those factors differ from the ways in which states enact policies during normal times, which policies are effective in slowing the spread and morbidity of the virus, and how states roll back policies in a manner that allows economic activity to resume while maintaining preparedness to avoid and mitigated waves of the virus. This project is jointly funded by the Accountable Institutions and Behavior Program and the Established Program to Stimulate Competitive Research (EPSCoR).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": "1486", "attributes": { "award_id": "2028675", "title": "RAPID: Collaborative Research: The Diffusion of State Policy Responses to the 2019 Novel Coronavirus", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)" ], "program_reference_codes": [ "096Z", "7914", "9178" ], "program_officials": [ { "id": 3863, "first_name": "Jan", "last_name": "Leighley", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-05-15", "end_date": "2022-04-30", "award_amount": 16417, "principal_investigator": { "id": 3864, "first_name": "Bruce A", "last_name": "Desmarais", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 219, "ror": "", "name": "Pennsylvania State Univ University Park", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "When the 2019 novel coronavirus arrived in the United States in February and March of 2020, state governments quickly began enacting policies intended to contain and mitigate its spread. Understanding the timing and sequence of these policy choices, and those policies’ eventual consequences, is critical for assessing how governments can be most effective during pandemics. This project collects data on state and local governments’ responses to COVID-19, including policies related to closing schools, canceling travel, banning public gatherings, closing restaurants and bars, delaying rent payments, and rules on medical licenses. This data allows researchers to examine the factors that influence states’ policy choices, whether those factors differ from the ways in which states enact policies during normal times, which policies are effective in slowing the spread and morbidity of the virus, and how states roll back policies in a manner that allows economic activity to resume while maintaining preparedness to avoid and mitigated waves of the virus. This project collects data on state government responses to COVID-19 by scraping government websites daily, focusing on sites dedicated to COVID-19 and those associated with the executive branch, state legislatures, and state departments of public health. It also collects data on the number of diagnosed cases, fatalities, recoveries in the states, and mobility data that tracks geographic movements from mobile phones. The policy recommendations or decisions recorded from state government pages include decisions related to closing schools, canceling travel, banning public gatherings (and their size), closing restaurants and bars, travel quarantines, postponing elections, safe shelter orders, limiting elective medical procedures, as well as when states modify these policies; additional data is collected from official state Twitter accounts. This data allows researchers to examine the factors that influence states’ policy choices, whether those factors differ from the ways in which states enact policies during normal times, which policies are effective in slowing the spread and morbidity of the virus, and how states roll back policies in a manner that allows economic activity to resume while maintaining preparedness to avoid and mitigated waves of the virus. This project is jointly funded by the Accountable Institutions and Behavior Program and the Established Program to Stimulate Competitive Research (EPSCoR).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": "9943", "attributes": { "award_id": "2200338", "title": "PIPP Phase I: Coupling Predictive Intelligence with Adaptive Response to Create Pandemic-Resilient Cities", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "PIPP-Pandemic Prevention" ], "program_reference_codes": [], "program_officials": [ { "id": 1030, "first_name": "Mitra", "last_name": "Basu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-09-01", "end_date": "2024-02-29", "award_amount": 1000000, "principal_investigator": { "id": 25706, "first_name": "Benjamin", "last_name": "Dalziel", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 4533, "first_name": "Tyler S", "last_name": "Radniecki", "orcid": "https://orcid.org/0000-0002-5295-3562", "emails": "[email protected]", "private_emails": "", "keywords": "['Wastewater microbiology']", "approved": true, "websites": "['https://cbee.oregonstate.edu/people/tyler-radniecki', 'https://arxiv.org', 'https://www.medrxiv.org', 'https://trace.oregonstate.edu/testing-results', 'https://public.tableau.com/profile/oregon.health.authority.covid.19#!/vizhome/O…']", "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 154, "ror": "https://ror.org/00ysfqy60", "name": "Oregon State University", "address": "", "city": "", "state": "OR", "zip": "", "country": "United States", "approved": true } ] }, { "id": 25703, "first_name": "Jeffrey W", "last_name": "Bethel", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 25704, "first_name": "Justin", "last_name": "Sanders", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 25705, "first_name": "Katherine R", "last_name": "McLaughlin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 154, "ror": "https://ror.org/00ysfqy60", "name": "Oregon State University", "address": "", "city": "", "state": "OR", "zip": "", "country": "United States", "approved": true }, "abstract": "When the first cases of COVID-19 appeared in cities across the United States, it triggered a process of exponential spread that could not be reversed using available technologies, interventions, and solutions. As climate change accelerates the emergence of pathogens with pandemic potential, cities and urban areas will provide the media and conduits that collect and transmit novel pathogens. Recent advances in pathogen sensing/surveillance and epidemiological forecasting along with the early success in the use of non-pharmaceutical interventions to reduce the spread of COVID-19 suggest that feedback loops between predictive intelligence and adaptive response could enable cities to efficiently attenuate pandemic threats if the feedback is sufficiently localized and rapid. The overarching goal of this project is to lay the foundation for the establishment of a Center that will combine and integrate mathematical/computational modelling with engineering, public health, and public engagement to explore the design and prototyping of city-scale feedback loops that could proactively attenuate the rates of transmission of pathogens with pandemic potential. The proposed PIPP Phase I Center development activities will include targeted research projects, workshops, and workforce development including the mentoring of four graduate students and the establishment of a graduate student rotation program at Oregon State University that will provide cross-training in transdisciplinary pandemic science and enable the development and facilitation of bi-directional trainings and exchanges on pandemic dynamics between scientists, engineers, and public health professionals and stakeholders.\n\nThis PIPP Phase I project will lay the foundation for a Center that addresses the “Grand Challenge” of transforming cities from pandemic amplifiers to attenuators. To advance this goal, the project team proposes to design, build, and evaluate feedback loops between predictive intelligence and adaptive response that could attenuate pandemic threats in cities and urban areas by leveraging the networks of interacting components in urban systems. The specific objectives of the research are to: 1) Build and scale up community-academic partnerships with public health professionals and community leaders to advance pandemic predictive intelligence and adaptive response in cities and urban areas; 2) Develop mathematical and computational models that could simulate the process of stepping back across epidemic tipping points in urban systems; and 3) Design and prototype feedback loops that could predict and attenuate the transmission of infectious diseases in cities and urban areas. The successful completion of the proposed research has the potential for transformative impact through the establishment of community-academic partnerships to develop and validate disease contagion prediction-response systems and evaluate their effectiveness and adoptability. \n\nThis award is supported by the cross-directorate Predictive Intelligence for Pandemic Prevention Phase I (PIPP) program, which is jointly funded by the Directorates for Biological Sciences (BIO), Computer Information Science and Engineering (CISE), Engineering (ENG), and Social, Behavioral and Economic Sciences (SBE).\n\nThis 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": "5109", "attributes": { "award_id": "0969400", "title": "Pierre Auger Project - Observatory's Operating Costs", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "Particle Astrophysics/Cosmic P" ], "program_reference_codes": [], "program_officials": [ { "id": 18211, "first_name": "Jean", "last_name": "Allen", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2010-08-15", "end_date": "2017-01-31", "award_amount": 968451, "principal_investigator": { "id": 18213, "first_name": "James", "last_name": "Cronin", "orcid": null, "emails": "[email protected]", "private_emails": null, "keywords": "[]", "approved": true, "websites": "[]", "desired_collaboration": "", "comments": "", "affiliations": [ { "id": 1368, "ror": "", "name": "Universities Research Association Inc", "address": "", "city": "", "state": "DC", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 18212, "first_name": "Paul", "last_name": "Mantsch", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 1368, "ror": "", "name": "Universities Research Association Inc", "address": "", "city": "", "state": "DC", "zip": "", "country": "United States", "approved": true }, "abstract": "When the Pierre Auger Project was proposed in 1998 the stated scientific objective was \"to discover and understand the source or sources of cosmic rays with energies exceeding 10**19 eV.\" A unique partnership of 17 countries has come together to pursue this science. The Pierre Auger Observatory (PAO), completed in June 2008, has accumulated data since January of 2004, and has already yielded results that are the first crucial steps toward those scientific goals. \n\nThe growing Auger data set will address vital questions in astrophysics and particle physics. The PAO will continue to map the southern sky to strengthen the correlation of the highest energy events with extragalactic sources. A continuously enriched sample of hybrid events with measured longitudinal development will improve our understanding of the cosmic ray composition and features of particle interactions from LHC energies to those well beyond. Resolving the puzzle of apparent excess of muons will benefit from increasing statistics. A precise spectrum measurement in the ankle region with the help of the AMIGA in-fill and the HEAT high elevation telescopes will help determine the transition from galactic to extragalactic sources. Based on hints in the data the search for galactic sources of neutrons and photons may well be fruitful. Finally a search for EeV neutrinos will continue to be of great interest.\n\nThis award will provide partial funding for the continuing operation of the PAO in Argentina. Collaborating countries fund the operations of the Observatory in proportion to the number of senior authors they have on Auger science publications. The US portion of these operating costs is being shared equally by the National Science Foundation and the US Department of Energy.\n\nThe study of the highest energy cosmic rays, the most energetic particles in nature, will have broader impacts on the understanding of particle physics at the highest energies as well as astrophysics. The PAO has been a highly successful venue for the training of students and postdocs. The centerpiece of outreach to Malargüe, Argentina, and other nearby communities, the Auger Visitor Center attracts increasing numbers of visitors, typically 6000 each year with the total now exceeding 45,000 since 2001. The Auger collaboration has sponsored two science fairs and has given numerous lectures in the local communities and schools. The daily public release of about 1% of reconstructed events is being used for school projects in many locations.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "9881", "attributes": { "award_id": "5U01OH012264-02", "title": "Longitudinal Follow-Up of 9/11 Directly Exposed Children in their Age of Transition: Independence, Occupation and Morbidity", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [ { "id": 24208, "first_name": "JAMES", "last_name": "YIIN", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-07-01", "end_date": "2026-06-30", "award_amount": 599961, "principal_investigator": { "id": 22857, "first_name": "Christina W.", "last_name": "Hoven", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 812, "ror": "", "name": "NEW YORK STATE PSYCHIATRIC INSTITUTE", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 812, "ror": "", "name": "NEW YORK STATE PSYCHIATRIC INSTITUTE", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "When the World Trade Center was attacked on September 11, 2001, approximately 25,000 children were living or attending school in lower Manhattan, tens of thousands of other children were in the path of the plume. As we approach the 20th anniversary, it becomes clear that while we have thoroughly studied those exposed on 9/11 as adults, we did not adequately study those children, whose development was interrupted by 9/11. Those children are now in their early to mid-adulthood and many will carry the effects of 9/11 for a lifetime. There is, thus, a clear imperative to thoroughly understand the enduring impact of that exposure on all aspects of their lives now and going forward. Fortunately, our team, The Global Psychiatric Epidemiology Group at Columbia University, was funded by NIOSH to recruit a representative sample (N=xx) of 9/11 directly exposed youth who were ages 0-17 on 9/11, as well as an unexposed control group. We have followed them through two waves of in-depth physical and psychological assessments. This cohort now constitutes the best available opportunity to understand the intricacies of the impact of 9/11 on adults who were exposed as children. In this study we propose to study the impact of childhood trauma on the central challenges, roles and relationships of entering and occupying adulthood, in addition to continuing the study’s collection of vital longitudinal information. We have this important opportunity now to compare those exposed with controls, which will enable us to examine how trauma affects intimacy and family formation, education and career consolidation, moral development and civic engagement, and the challenge of parenting, with a traumatic history. It represents a unique opportunity to add to our understanding about the nature of their unfolding adulthood, psychologically and physically. We will conduct another wave of in-depth assessments of psychological and physical health including pulmonary health and related parameters, and we will collect and biobank blood for a second time to allow for the future examination of inflammatory and epigenetic biologicals. As the long-term consequences of 9/11 direct exposure now inevitably includes these individuals’ experience with COVID-19, so this study will also evaluate the effects of an additional mass trauma on these emerging adults. In sum, this study will encourage new ways of thinking about trauma, development from childhood to mid-life, health promotion, and even parenting support of those traumatized as children.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "8474", "attributes": { "award_id": "1U01OH012264-01", "title": "Longitudinal Follow-Up of 9/11 Directly Exposed Children in their Age of Transition: Independence, Occupation and Morbidity", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [ { "id": 24208, "first_name": "JAMES", "last_name": "YIIN", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-07-01", "end_date": "2026-06-30", "award_amount": 593680, "principal_investigator": { "id": 22857, "first_name": "Christina W.", "last_name": "Hoven", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 812, "ror": "", "name": "NEW YORK STATE PSYCHIATRIC INSTITUTE", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 812, "ror": "", "name": "NEW YORK STATE PSYCHIATRIC INSTITUTE", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "When the World Trade Center was attacked on September 11, 2001, approximately 25,000 children were living or attending school in lower Manhattan, tens of thousands of other children were in the path of the plume. As we approach the 20th anniversary, it becomes clear that while we have thoroughly studied those exposed on 9/11 as adults, we did not adequately study those children, whose development was interrupted by 9/11. Those children are now in their early to mid-adulthood and many will carry the effects of 9/11 for a lifetime. There is, thus, a clear imperative to thoroughly understand the enduring impact of that exposure on all aspects of their lives now and going forward. Fortunately, our team, The Global Psychiatric Epidemiology Group at Columbia University, was funded by NIOSH to recruit a representative sample (N=xx) of 9/11 directly exposed youth who were ages 0-17 on 9/11, as well as an unexposed control group. We have followed them through two waves of in-depth physical and psychological assessments. This cohort now constitutes the best available opportunity to understand the intricacies of the impact of 9/11 on adults who were exposed as children. In this study we propose to study the impact of childhood trauma on the central challenges, roles and relationships of entering and occupying adulthood, in addition to continuing the study’s collection of vital longitudinal information. We have this important opportunity now to compare those exposed with controls, which will enable us to examine how trauma affects intimacy and family formation, education and career consolidation, moral development and civic engagement, and the challenge of parenting, with a traumatic history. It represents a unique opportunity to add to our understanding about the nature of their unfolding adulthood, psychologically and physically. We will conduct another wave of in-depth assessments of psychological and physical health including pulmonary health and related parameters, and we will collect and biobank blood for a second time to allow for the future examination of inflammatory and epigenetic biologicals. As the long-term consequences of 9/11 direct exposure now inevitably includes these individuals’ experience with COVID-19, so this study will also evaluate the effects of an additional mass trauma on these emerging adults. In sum, this study will encourage new ways of thinking about trauma, development from childhood to mid-life, health promotion, and even parenting support of those traumatized as children.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "978", "attributes": { "award_id": "2043796", "title": "OPUS: Understanding How Climate Change Will Alter the Ability of Pathogens to Control Gypsy Moth Populations, and the Consequences for Forest Economics", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [], "program_officials": [ { "id": 2372, "first_name": "Diana", "last_name": "Pilson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-07-01", "end_date": "2023-06-30", "award_amount": 328466, "principal_investigator": { "id": 2374, "first_name": "Gregory", "last_name": "Dwyer", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 289, "ror": "https://ror.org/024mw5h28", "name": "University of Chicago", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 2373, "first_name": "Eyal", "last_name": "Frank", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 289, "ror": "https://ror.org/024mw5h28", "name": "University of Chicago", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "When they think of infectious diseases, most people think of diseases like covid-19 or HIV that have big negative effects on people and the economy. Few are aware that infectious diseases also keep pest insects in check, by killing insects before they can destroy forests. The gypsy moth is a classic example. Gypsy moth populations are held in check by a fungus disease that can kill more than 90% of gypsy moth caterpillars in a single spring. Since the fungus disease was introduced in 1989, gypsy moth defoliation has been very low, reducing the costs of gypsy moth attacks by millions of dollars every year. The fungus needs cool, moist conditions, however, and so the hotter, drier conditions that climate change is bringing to the US may lead to a gypsy moth comeback. Before the fungus was introduced, a virus disease killed many gypsy moths, but whether the virus can control gypsy moths in the future is unknown. This project asks, what will be the economic costs of a gypsy comeback, and can a virus comeback reduce these costs? Results will be presented to forest managers for input and refinement, and will be used to inform management decisions. Additionally, a graduate student and a technician will be trained in population and economic modeling.To answer these questions, the researchers will use a combination of ecological field experiments, infectious disease modeling, and economic modeling. They will use field experiments to estimate key parameters of their disease model, notably the severity of competition between the virus and the fungus, and how this competition depends on weather. The researchers will then extend their disease model to describe long-term virus-fungus competition, and the extent to which the virus can replace the fungus as climate change leads to hotter and drier climates. To understand the economic consequences of virus-fungus competition, the researchers will first parameterize regression models that quantify the economic costs of gypsy moth defoliation. They will then insert the predictions of climate change models into their virus-fungus competition models to predict how climate change will affect gypsy moth defoliation. The final step will be to quantify the costs of climate change on gypsy moths by inserting the model predictions of defoliation levels into the economic models. This work will provide a rare quantification of the effects of climate change on a species interaction, and of the economic costs of such effects.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 } } ], "meta": { "pagination": { "page": 1393, "pages": 1424, "count": 14236 } } }