Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1383&sort=program_reference_codes
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=program_reference_codes", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1424&sort=program_reference_codes", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1384&sort=program_reference_codes", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1382&sort=program_reference_codes" }, "data": [ { "type": "Grant", "id": "1802", "attributes": { "award_id": "2032465", "title": "RAPID: Optimizing the Life-Cycle Impacts of COVID-19 Policy Interventions", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [ "096Z", "7914" ], "program_officials": [ { "id": 4757, "first_name": "Katharina", "last_name": "Dittmar", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-01", "end_date": "2022-05-31", "award_amount": 123238, "principal_investigator": { "id": 4760, "first_name": "Philip N", "last_name": "Brown", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 490, "ror": "", "name": "University of Colorado at Colorado Springs", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 4758, "first_name": "Lisa M", "last_name": "Hines", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 4759, "first_name": "Gia E", "last_name": "Barboza-Salerno", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 490, "ror": "", "name": "University of Colorado at Colorado Springs", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true }, "abstract": "As COVID-19 spreads throughout communities, government officials face a series of challenging decisions, each fraught with an array of difficult tradeoffs. Current efforts to stop the spread of the novel coronavirus by closing non-essential businesses have resulted in the loss of millions of jobs. In addition to the economic costs, lockdown measures have had other unintended consequences that are difficult to measure. Unquestionably, the suffering caused by COVID-19 will go far beyond clinical effects alone. However, if no measures are taken, the virus may spread rapidly, overwhelming local healthcare resources and causing substantial human loss. This raises the urgent question: How can leaders make public policy decisions regarding the COVID-19 pandemic in a scientific way that is locally appropriate and properly accounts for both near-term and longer-term costs of policy interventions? This project combines rigorous mathematical modeling, innovative approaches to data collection, and input from policymakers, to develop a decision aid framework that weighs the costs and benefits of various policy interventions at a local level and tailors interventions to the locale considering the effects of specific indicators such as urbanization, economic distress, and availability of regional healthcare. Additionally, graduate students will be trained in the context of this research. To develop a rigorous understanding of the tradeoffs involved in policy interventions geared at mitigating COVID-19, two complementary approaches will be applied. First, the benefits of policy interventions will be estimated using a new dynamical game-theoretic mathematical COVID-19 epidemic model which accounts for the interactions between social behavior, policy interventions, and disease contagion. Second, the costs of policy interventions will be estimated via geospatial data aggregation and analysis which identifies local vulnerability to unintended consequences of policy interventions and assesses the disparities of these impacts across racial and socioeconomic divides. This project will advance knowledge in two complementary directions. First, the project’s data collection and aggregation activities will create datasets which would be otherwise impossible to recreate if this historic opportunity were missed; these datasets will facilitate our understanding of the connection between the spread of COVID-19 and the emergence of social behavior, identify the long-term costs of infection, and are anticipated to be applicable to future pandemics as well. Second, the project’s game-theoretic epidemiological model captures the feedback interconnection between two dynamical systems (human behavior and disease spread, respectively). These systems and their abstractions have been well-studied in isolation, but their interconnection is not well understood. Mathematical models will be reviewed and revised based on feedback from policymakers in order to best tailor interventions to the locale considering the effects of specific indicators such as urbanization, economic distress, and availability of regional healthcare. This interdisciplinary project will significantly advance understanding of these inherent societal feedback effects in a data driven, real world context. This RAPID award is made by the Ecology and Evolution of Infectious Disease Program in the Division of Environmental Biology, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "1803", "attributes": { "award_id": "2029515", "title": "RAPID: Determination of health risks and Status from SARS-CoV-2 Presence in Urban Water cycle", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "7914" ], "program_officials": [ { "id": 4761, "first_name": "Mamadou", "last_name": "Diallo", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-05-15", "end_date": "2023-04-30", "award_amount": 123706, "principal_investigator": { "id": 4762, "first_name": "Ramesh", "last_name": "Goel", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 202, "ror": "https://ror.org/03r0ha626", "name": "University of Utah", "address": "", "city": "", "state": "UT", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 202, "ror": "https://ror.org/03r0ha626", "name": "University of Utah", "address": "", "city": "", "state": "UT", "zip": "", "country": "United States", "approved": true }, "abstract": "COVID-19 has impacted human health on a global scale. Understanding the spread of COVID-19 is thus an urgent national need. This project addresses this need focusing on the urban wastewater treatment system. Wastewater generated by wash water and toilets is known to carry human pathogens. Thus, municipal wastewater represents an important pathway for human exposure to viruses like SARS-CoV2 (the coronavirus that causes COVID-19). The goal of this project is to determine if wastewater obtained from different municipal wastewater treatment plants and sewer lines harbors SARS-CoV2. A secondary goal is to use this information to understand the exposure risk to wastewater treatment plant workers and track community COVID-19 infections. This will be achieved by testing whether SARS-CoV2 (or its genetic material) is present in municipal wastewater. This information will be combined with data on other water quality parameters to establish correlations between SARS-CoV2 and wastewater quality. Results will help understand the risk of exposure to SARS-CoV2 in wastewater treatment plant operators. In addition, the results from this project have potential to be used as a rapid measure to track hotspots of COVID-19 in the community.COVID-19 caused by the coronavirus SARS-CoV2 has become a global pandemic, resulting in over a quarter million fatalities worldwide. Although SARS-CoV2 has some similarity to the virus SARS-CoV1 (a well-studied coronavirus responsible for a severe respiratory disease outbreak earlier this century), we still lack information needed to understand the survival and infectivity of this pathogen in municipal wastewater infrastructure. Municipal wastewater generated in kitchens and restrooms is known to carry human viral pathogens, thus representing a potential exposure pathway for humans. The goal of this project is to develop efficient techniques to extract and monitor SARS-CoV2 in wastewater. The secondary goal of this research is to understand human health risks associated with the presence of SARS-CoV2 in municipal wastewater influent and treated effluent. This will be achieved through three broad tasks to: (1) select biomarkers and develop methods for rapid and efficient extraction and analysis of SARS-CoV2 in wastewater; (2) sample wastewater treatment plants and distribution systems to determine spatial and temporal spread; and (3) develop a risk prediction model for exposure to SARS-CoV2. This project will generate data that can be used to develop health risk models for municipal wastewater treatment plant operators. Results generated from this project also hold promise to help epidemiologists and other health professionals to understand and predict COVID-19 outbreaks in the community. This project will expand the diversity of the Nation’s STEM workforce through the education and training of a female graduate student. Broader impacts to society include the potential development of early warning tools to detect the spread of human pathogens such as COVID-19.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": "1804", "attributes": { "award_id": "2029363", "title": "RAPID: Educational Interventions for Undergraduate Students and Informal Learners for Robust Learning of COVID-19 Knowledge", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Education and Human Resources (EHR)" ], "program_reference_codes": [ "096Z", "7914" ], "program_officials": [ { "id": 4763, "first_name": "Carleitta", "last_name": "Paige-Anderson", "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": 200000, "principal_investigator": { "id": 4767, "first_name": "Raphael D", "last_name": "Isokpehi", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 683, "ror": "https://ror.org/04e0j1059", "name": "Bethune-Cookman University", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 4764, "first_name": "Sarah E", "last_name": "Krejci", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 4765, "first_name": "Matilda O Johnson", "last_name": "Dr.", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 4766, "first_name": "Baraka", "last_name": "Mapp", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 683, "ror": "https://ror.org/04e0j1059", "name": "Bethune-Cookman University", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true }, "abstract": "The Historically Black Colleges and Universities - Undergraduate Program (HBCU-UP) supports RAPID projects when there is a severe urgency with regard to availability of, or access to, data, facilities or specialized equipment, including quick-response research on natural or anthropogenic disasters and similar unanticipated events, such as the COVID-19 pandemic. The project at Bethune Cookman University seeks to investigate the effects of two educational interventions on the robust learning measures of long-term retention or desire for future learning of COVID-19 knowledge. It will produce designers of effective, efficient, and engaging distance learning while equipping undergraduate students and informal learners with relevant skills and competencies to contribute transdisciplinary solutions to the current COVID-19 and future disease outbreaks. Undergraduate students are involved as researchers in this project.The goal of the project is to understand how to optimize the successful learning of knowledge content types such as procedures for data associated problem solving activities, especially in the circumstances of mandatory remote education. The abundance of data resources resulting from the COVID-19 pandemic presents unique conditions suitable to design and develop educational technology interventions for learning procedures to solve data challenges in areas of data flow, data curation, and data analytics. The research is guided by the Knowledge-Learning-Instruction theoretical framework for producing robust student learning. Two online educational technology interventions will be developed and investigated among cohorts of designers of learning experiences on generating knowledge from complex data resources on COVID-19 pandemic, and among informal learners of the genomics and environmental survival of coronaviruses. An “in vivo” experimentation approach will be implemented that combines causal principles and real online instructional events with or without an ecological control group. The transactions and artifacts of learning events will be analyzed to detect features that predict robust learning and the performance of complex cognitive activities. Post-educational intervention assessments will capture academic and professional success measures including satisfaction with the learning process, self-confidence to work effectively with complex datasets, desire to pursue data careers, and involvement in developing data-driven solutions to COVID-19 pandemic. This RAPID award is made by the Historically Black Colleges and Universities - Undergraduate Program in the Division of Human Resource Development, Directorate of Education and Human Resources, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "1807", "attributes": { "award_id": "2028370", "title": "RAPID: How People Learn Rapidly: COVID-19 as a Crisis of Socioscientific Understanding and Educational Equity", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Education and Human Resources (EHR)" ], "program_reference_codes": [ "096Z", "7914" ], "program_officials": [ { "id": 4773, "first_name": "Jolene", "last_name": "Jesse", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-05-01", "end_date": "2022-04-30", "award_amount": 199744, "principal_investigator": { "id": 4776, "first_name": "Angela Calabrese", "last_name": "Barton", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 4774, "first_name": "Leslie R", "last_name": "Herrenkohl", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 4775, "first_name": "Elizabeth A", "last_name": "Davis", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 169, "ror": "", "name": "Regents of the University of Michigan - Ann Arbor", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true }, "abstract": "The primary objective of this study is to document how people learn the science of the COVID-19 pandemic in real time, how they activate this scientific knowledge towards informed decision making, and how these processes change over time. This study is intended to produce additional insights on how such learning is shaped by equity concerns and contextual factors. For example, researchers will document how the ways in which people learn the science of COVID-19 are mediated by the sources of information they have access to and leverage, as well as what supports them in doing so. The research will further document how people leverage their understandings of COVID-19, alongside other forms of knowledge and concerns in their decision-making. This study may serve a crucial role in aiding the public understanding of where structural points of informational failure might occur. It may also reveal where and how the public engages or resists community action strategies to mitigate spread and suffering through when, how and why they gather, share, and make sense of scientific data. This RAPID was submitted in response to the NSF Dear Colleague letter related to the COVID-19 pandemic. This award is made by the AISL and ECR programs in the Division of Research on Learning, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act. This research will draw upon a conceptual framework of consequential learning and a methodological framework of narrative inquiry. Sixty participants in Lansing, Michigan and Seattle, Washington will participate over the course of one year in cyclical interviews, focus group conversations and experience sampling approaches. Documents and resources named and used by the participants in their learning will be collected and analyzed. Attention will be paid to science learning in the following areas as the primary focus: a) the science of SARS-CoV-2 and the relationship between virus and disease, b) viral transmission, and c) origination, replication and spread. A key focus will also be how people use scientific data and evidence-based explanations when developing understandings and making decisions with respect to the pandemic. This research is urgent and timely because the COVID-19 pandemic is projected to occur in multiple waves over approximately 18 months. Insights may produce basic understanding about rapid science learning, policy strategies, school-based practices and resources for use within current and future waves. Socioscientific crises differentially impact people, with effects felt more significantly by vulnerable people. Thus, this study will address the urgent call for investigation into factors and experiences of low-income individuals and families who are trying to educate themselves on continually changing data during an international health crisis.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": "1808", "attributes": { "award_id": "2037331", "title": "RAPID: Societal Trust and Health amidst COVID-19, and an Evaluation Framework for the Societal Experts Action Network (SEAN)", "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" ], "program_officials": [ { "id": 4777, "first_name": "Lee", "last_name": "Walker", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-07-15", "end_date": "2022-06-30", "award_amount": 199933, "principal_investigator": { "id": 4781, "first_name": "Elizabeth", "last_name": "Suhay", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 509, "ror": "https://ror.org/052w4zt36", "name": "American University", "address": "", "city": "", "state": "DC", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 4778, "first_name": "Dave E", "last_name": "Marcotte", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 4779, "first_name": "Aparna", "last_name": "Soni", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 4780, "first_name": "Claudia L", "last_name": "Persico", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 509, "ror": "https://ror.org/052w4zt36", "name": "American University", "address": "", "city": "", "state": "DC", "zip": "", "country": "United States", "approved": true }, "abstract": "Too often, decision-makers in government and business have been unable to extract actionable information from scientific studies. As a result, the potential public benefit from that knowledge is blunted. The Societal Experts Action Network (SEAN) is a unique effort to bridge that gap and improve transmission of actionable insights from the social, behavioral, and economic (SBE) sciences to decision-makers who can benefit from the knowledge. SEAN is part of the National Academies of Sciences, Engineering, and Medicine (NASEM) focus on COVID-19. In coordination with the NASEM Standing Committee on Emerging Infectious Diseases and 21st Century Health Threats, SEAN provides SBE data and recommendations on social, behavioral, and economic (SBE) matters to decision-makers and the public. One of SEAN’s key goals is to rapidly gather and communicate actionable scientific evidence to public officials and other leaders who are managing the pandemic and working toward recovery.This project will 1) utilize survey data gathered under SEAN’s auspices to examine societal trust and its relationships to health outcomes, and 2) create a framework for an evaluative assessment of SEAN. It will create original scientific evidence using COVID-19-related survey data and will provide an evaluation of the effectiveness and impact of SEAN’s COVID-19-related communication activities. The first part of this project will analyze survey data associated with the SEAN COVID-19 survey archive to understand the critical role that trust in authorities (medical, scientific, government, media) plays in critical health behaviors by members of the public. COVID-19 represents a grave threat to America’s public health and the well-being of its populace. It is predicted that government officials at the federal, state and local levels who are trusted by members of society to inform them about COVID-19 play a large role in the lay public’s behavioral responses to the disease and, ultimately, their positive health outcomes. In the second part of this project, the research team will work with SEAN leadership, to plan a thorough, external evaluation of SEAN.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": "1812", "attributes": { "award_id": "2028534", "title": "RAPID: Collaborative Research: Understanding At-Risk Adolescents' and Parents' Daily Experiences During COVID-19", "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" ], "program_officials": [ { "id": 4789, "first_name": "Naomi", "last_name": "Hall-Byers", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-05-01", "end_date": "2023-04-30", "award_amount": 98435, "principal_investigator": { "id": 4790, "first_name": "April", "last_name": "Thomas", "orcid": "https://orcid.org/0000-0000-2529-9660", "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": "['https://www.adolescentlab.com/']", "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 446, "ror": "", "name": "University of Texas at El Paso", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 446, "ror": "", "name": "University of Texas at El Paso", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "While the COVID-19 pandemic has far-reaching effects on communities and individuals, its impact on at-risk youth may be particularly pervasive and distinct. This RAPID project will study how at-risk adolescents and their parents experience COVID-19 in the initial time period following the novel coronavirus pandemic. The research will compare adolescents’ sleep, social skills, social relationship quality, stress, mood, substance use, mental health symptoms, physical health, psychosocial development, externalizing behavior, and delinquency across the COVID-19 outbreak. The project also will examine whether juvenile incarceration exacerbates the potential impact of COVID-19 on youth outcomes. The project will engage in a longitudinal study of at-risk (justice-involved, low-SES) adolescents to address how adolescent-parent dyads respond to and are affected by the COVID-19 pandemic. This research will use multiple methods, including self-report, collateral report, official records from the partnering department of probation, electronic daily diary reports, and actigraph technology, to assess changes in adolescents’ and parents’ functioning on a variety of outcomes in response to the COVID-19 pandemic. The findings will evince physical and mental health risks in response to the pandemic among at-risk youth. As well, the research will provide best practices for juvenile detention facilities and departments of probation in times of crises to ensure that youth continue to receive important rehabilitative services while maintaining the health and safety of youth, legal actors, and community members. Results will contribute to the limited existing knowledge base on the needs, risks, and potential protective factors of a vulnerable group of youth during a global state of emergency.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": "1815", "attributes": { "award_id": "2029186", "title": "RAPID: SEAN COVID-19 Survey Archive", "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" ], "program_officials": [ { "id": 4795, "first_name": "Nancy", "last_name": "Lutz", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-08-01", "end_date": "2022-07-31", "award_amount": 548570, "principal_investigator": { "id": 4796, "first_name": "James M", "last_name": "Poterba", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 407, "ror": "", "name": "National Bureau of Economic Research Inc", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 407, "ror": "", "name": "National Bureau of Economic Research Inc", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "In this project, U.S. and international surveys on COVID-19 are compiled, these materials are made publicly available, and weekly summaries of key research findings are disseminated. U.S. social science research critically informs government and scientific responses to the COVID-19 pandemic. Accurate measurement of the public’s attitudes and behaviors in the crisis, including its impact on physical and emotional health, economic well-being, and daily activities, is essential in decision making, implementation and assessment. This project addresses key challenges in advancing this basic knowledge by assembling available survey data from myriad sources; assessing which data are of the necessary quality for use; making these data and associated research materials available to decisionmakers, researchers, and the American public in a highly functional single-source location; summarizing and communicating key findings on an ongoing basis to ensure that important survey findings on COVID-19 are available to the widest possible audience; and doing this all in a highly accelerated time frame. This resource supports decisionmakers concerning public health and social and economic conditions; assists researchers in their efforts to investigate, analyze and replicate existing studies; and serves the public good by providing open access to COVID-19 social, behavioral, and economic research.This project uses publicly and professionally available sources to compile U.S. and international surveys on COVID-19 and deploys rapid methodological assessments to identify probability-based studies among them. Producers or sponsors of such surveys are asked to share their topline data reports, scripted questionnaires, datasets, banner books of crosstabulated data, analytical reports and any related analyses and documentation. All available materials are posted to the open-access Societal Action Experts Network (SEAN) COVID-19 website, making use of the PARC knowledge management platform for survey research. Users can full-text search to retrieve individual survey questions and results, individual scripted questions, and all associated materials. Weekly summaries of key research findings released in the previous week are produced, linking back to data sources. These summaries are disseminated to a 1,000+-member email distribution list, the listservs of the American Association for Public Opinion Research and the World Association for Public Opinion Research, SEAN stakeholders, and visitors to the SEAN archive site who sign up for weekly notifications.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": "1818", "attributes": { "award_id": "2030140", "title": "RAPID: Collaborative Research: Modeling and Learning-based Design of Social Distancing Policies for COVID-19", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "7914" ], "program_officials": [ { "id": 4803, "first_name": "Lawrence", "last_name": "Goldberg", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-15", "end_date": "2022-05-31", "award_amount": 100000, "principal_investigator": { "id": 4804, "first_name": "Cynthia", "last_name": "Chen", "orcid": "https://orcid.org/0000-0002-1110-8610", "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": "['https://sites.uw.edu/thinklab']", "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": "Human contacts underlie the spread of any infectious diseases including COVID-19. For COVID-19, the widely implemented social distancing policies are designed precisely to drastically reduce individual travels and the resulting contacts. In a number of States, these policies have effectively reduced the peak number of infections. These policies have also come with huge costs on the society, economy and people’s lives: US economy has largely come to a halt and the number of unemployment claims has now exceeded the worst of the 2008-2009 financial crisis. This rapid COVID-19 application will develop a novel meta-population level model simulating the spread of COVID-19 and utilize reinforcement learning to explore optimal congregation restriction policies for social distancing. The technical approach will develop an SIQR (Susceptible, Infected, Quarantined, and Recovered) model integrated with reinforcement learning for continuous monitoring and policy adjustment. The SIQR model is built on the classic literature of the SIR (susceptible, infectious and recovered) and SEIR (susceptible, exposed, infectious, and recovered) models and enhances their capability to capture the unique quarantine features for COVID-19. The key focus of the proposed project is on the connection of the SIQR model to reinforcement learning to realize a control loop that provides optimal policy in spite of sparse and noisy observations. This is an important contribution to this emerging, interdisciplinary science of infectious disease modeling and control. The results of this project will have both immediate importance for designing the response to COVID-19 and also contribute to the broader development of an interdisciplinary education and research program involving infectious disease modeling, reinforcement learning and machine learning of big data.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": "1819", "attributes": { "award_id": "2030018", "title": "RAPID: Collaborative Research: Modeling and Learning-based Design of Social Distancing Policies for COVID-19", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "7914" ], "program_officials": [ { "id": 4805, "first_name": "Lawrence", "last_name": "Goldberg", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-15", "end_date": "2022-05-31", "award_amount": 100000, "principal_investigator": { "id": 4806, "first_name": "Vijay", "last_name": "Gupta", "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": "Human contacts underlie the spread of any infectious diseases including COVID-19. For COVID-19, the widely implemented social distancing policies are designed precisely to drastically reduce individual travels and the resulting contacts. In a number of States, these policies have effectively reduced the peak number of infections. These policies have also come with huge costs on the society, economy and people’s lives: US economy has largely come to a halt and the number of unemployment claims has now exceeded the worst of the 2008-2009 financial crisis. This rapid COVID-19 application will develop a novel meta-population level model simulating the spread of COVID-19 and utilize reinforcement learning to explore optimal congregation restriction policies for social distancing. The technical approach will develop an SIQR (Susceptible, Infected, Quarantined, and Recovered) model integrated with reinforcement learning for continuous monitoring and policy adjustment. The SIQR model is built on the classic literature of the SIR (susceptible, infectious and recovered) and SEIR (susceptible, exposed, infectious, and recovered) models and enhances their capability to capture the unique quarantine features for COVID-19. The key focus of the proposed project is on the connection of the SIQR model to reinforcement learning to realize a control loop that provides optimal policy in spite of sparse and noisy observations. This is an important contribution to this emerging, interdisciplinary science of infectious disease modeling and control. The results of this project will have both immediate importance for designing the response to COVID-19 and also contribute to the broader development of an interdisciplinary education and research program involving infectious disease modeling, reinforcement learning and machine learning of big data.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": "1823", "attributes": { "award_id": "2028576", "title": "RAPID: Collaborative Research: Understanding At-Risk Adolescents' and Parents' Daily Experiences During COVID-19", "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" ], "program_officials": [ { "id": 4814, "first_name": "Naomi", "last_name": "Hall-Byers", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-05-01", "end_date": "2021-04-30", "award_amount": 15907, "principal_investigator": { "id": 4815, "first_name": "Caitlin", "last_name": "Cavanagh", "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": [], "awardee_organization": { "id": 521, "ror": "https://ror.org/05hs6h993", "name": "Michigan State University", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true }, "abstract": "While the COVID-19 pandemic has far-reaching effects on communities and individuals, its impact on at-risk youth may be particularly pervasive and distinct. This RAPID project will study how at-risk adolescents and their parents experience COVID-19 in the initial time period following the novel coronavirus pandemic. The research will compare adolescents’ sleep, social skills, social relationship quality, stress, mood, substance use, mental health symptoms, physical health, psychosocial development, externalizing behavior, and delinquency across the COVID-19 outbreak. The project also will examine whether juvenile incarceration exacerbates the potential impact of COVID-19 on youth outcomes. The project will engage in a longitudinal study of at-risk (justice-involved, low-SES) adolescents to address how adolescent-parent dyads respond to and are affected by the COVID-19 pandemic. This research will use multiple methods, including self-report, collateral report, official records from the partnering department of probation, electronic daily diary reports, and actigraph technology, to assess changes in adolescents’ and parents’ functioning on a variety of outcomes in response to the COVID-19 pandemic. The findings will evince physical and mental health risks in response to the pandemic among at-risk youth. As well, the research will provide best practices for juvenile detention facilities and departments of probation in times of crises to ensure that youth continue to receive important rehabilitative services while maintaining the health and safety of youth, legal actors, and community members. Results will contribute to the limited existing knowledge base on the needs, risks, and potential protective factors of a vulnerable group of youth during a global state of emergency.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": 1383, "pages": 1424, "count": 14236 } } }