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=1397&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": "2082", "attributes": { "award_id": "2027094", "title": "RAPID: Evolution of Public Risk Perception and Mental Models Regarding 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", "9179" ], "program_officials": [ { "id": 5594, "first_name": "Robert", "last_name": "O'Connor", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-04-01", "end_date": "2022-03-31", "award_amount": 199717, "principal_investigator": { "id": 5597, "first_name": "Andrew", "last_name": "Parker", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 5595, "first_name": "Melissa L", "last_name": "Finucane", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 5596, "first_name": "Katherine G", "last_name": "Carman", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 515, "ror": "https://ror.org/00f2z7n96", "name": "RAND Corporation", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "In crises such as the emergence of COVID-19, the public is a critical response partner. Novel threats are concerning to the public, but often poorly understood, with misunderstanding leading to inappropriate reactions. Clarifying when and why misperceptions occur is important because resulting behavior can contribute to disease spread, supply shortages, and unnecessary health-care system burden. Central are individual mental models, intuitive theories made up of related beliefs or perceptions individuals have about a risk, which may or may not align with scientific consensus. Mental models form a foundation for how people conceive risk, structure decisions, and their risk-related behaviors. This project follows individuals’ risk perceptions, mental models, and risk behaviors over the course of the COVID-19 pandemic, capitalizing on a time-sensitive opportunity to push forward the science on public risk responses to crises, within a concrete public health context. The primary goal is to longitudinally track risk perceptions, mental models, and risk-related behaviors within individuals over the course of the COVID-19 pandemic. Secondary goals are to develop new methodological approaches to process and analyze large-sample mental models data and engage experts on our approach and needs for larger infrastructure. The project leverages existing data and planned survey data collection, building out a longitudinal assessment to be able to capture changes in risk perceptions, mental models, and behaviors. The surveys use freelisting, a simple free-association technique from anthropology, to gather a large-sample picture of people’s risk mental models. The research team employs automated lexical analysis tools to process the data and network analytic techniques to map out the mental models. The team uses regression analysis to examine relationships among mental models, risk perceptions, behavior, and their change over time.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": "1381", "attributes": { "award_id": "2030830", "title": "RAPID: Effective Recovery for Organizations from the COVID-19: Optimizing Strategic Responses", "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", "9179" ], "program_officials": [ { "id": 3561, "first_name": "Tara", "last_name": "Behrend", "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": 120925, "principal_investigator": { "id": 3563, "first_name": "Gwendolyn K", "last_name": "Lee", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 158, "ror": "https://ror.org/02y3ad647", "name": "University of Florida", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 3562, "first_name": "Mo", "last_name": "Wang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 158, "ror": "https://ror.org/02y3ad647", "name": "University of Florida", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true }, "abstract": "How do business organizations recover from a crisis? Studies of crises show that human communities differ significantly in their responses; a crisis presents individual organizations and communities of organizations with a common problem, yet solutions may be elusive. This project will advance basic knowledge about the effectiveness of organizational recovery in response to the COVID-19 pandemic and global economic crisis. The project will help organizations and managers to better understand the conditions under which organizations responding to a crisis of unprecedented magnitude may recover more effectively. Results will equip organizations and managers with knowledge and skills about how to choose strategic responses to crisis, by highlighting the insights derived from study conditions. In collaboration with the University of Florida Entrepreneurship and Innovation Center, the project will disseminate results to business and scientific communities by providing free-of-charge webinars that explain to managers and researchers the strategic responses that can help organizations, particularly small-and-medium sized enterprises, to more effectively recover from the current crisis. Project findings and activities will help to ensure the economic competitiveness of the United States and promote our nation's safety and security. When crises occur, business organizations need to move strategically to recover, but leaders and managers may be unclear as to which actions to take. The project will provide prescriptive theoretical directions for the development of processes and actions toward effective recovery from the COVID-19 pandemic and global economic crisis. The project will classify, explain, and evaluate organizations’ strategic responses to the current crisis for effective recovery and answer three research questions: First, among the multiple paths toward organizational recovery, which ones are more effective? Second, what organizational and environmental factors are most conducive to effective recovery? Third, would dynamic adaptation (e.g., switching resource allocation from the organization’s own rebuilding to community-based self-organizing efforts, and vice versa) be effective for recovery? Interview data will be used to inform, validate and improve a computational model designed to explain and evaluate the effectiveness of strategic responses of organizations. The project will use this model to compare a wide range of variation in responses, and probe the conditions under which certain responses could be more effective for organizational recovery. The project will produce: (1) a multi-level taxonomy of strategic responses to crisis for organizational recovery and (2) an explanation and evaluation of strategic responses to crisis for effective recovery. Using a mixed-method approach, the project will not only corroborate a computational model with interview data, but also use the model to extend understanding beyond case observations. Findings will inform theories of organization regarding business strategy, especially within the context of crises and extreme events.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": "1393", "attributes": { "award_id": "2032044", "title": "RAPID: Evaluating the potential for SARS-CoV-2 spillback infections of native North American wildlife", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [ "096Z", "7914", "9179" ], "program_officials": [ { "id": 3597, "first_name": "Joanna", "last_name": "Shisler", "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": 199791, "principal_investigator": { "id": 3601, "first_name": "Sonia M", "last_name": "Hernandez", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 160, "ror": "", "name": "University of Georgia Research Foundation Inc", "address": "", "city": "", "state": "GA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 3598, "first_name": "Michael J", "last_name": "Yabsley", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 3599, "first_name": "Daniel G", "last_name": "Mead", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 3600, "first_name": "Nicole M", "last_name": "Nemeth", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 160, "ror": "", "name": "University of Georgia Research Foundation Inc", "address": "", "city": "", "state": "GA", "zip": "", "country": "United States", "approved": true }, "abstract": "SARS-CoV-2 originated from a bat, likely passing through another animal before it infected people. The objective is to determine if two North American native wildlife species can be infected with SARS-CoV-2, the causative agent of COVID-19, which to date has not been evaluated. Skunks and raccoons are closely related to other species that are known to be susceptible with this virus, and are highly abundant in human environments, frequently consuming human refuse. Both species are also handled frequently in wildlife research and rehabilitation settings—creating situations where spillback of the virus from people to them is likely. Further, this study will investigate whether skunk-to-skunk and racoon-to-raccoon transmission is possible, needed to forecast what would happen if this virus spilled into our native wildlife; the worst case scenario is that these species become reservoirs of the virus for people. Skunks and raccoons will be inoculated with two doses of SARS-CoV-2 that represent doses they might encounter the environment, or when in close contact with people. Nasal and fecal samples will be collected after inoculation and tested using two detection methods. Blood will also be collected at intervals to determine if these species create antibodies against the virus. In addition to rapidly disseminating this information to wildlife management agencies, presenting and publishing the results, this work will train three graduate and two undergraduate students on animal husbandry, experimental infections, and various laboratory analyses.The objective of this study is to identify if two North American native wildlife species that represent a high likelihood of susceptibility and ecological opportunity—skunks and raccoons—are susceptible to infection with SARS-Cov-2. Current phylogenetic evidence indicates a spillover event from an animal host prompted the COVID-19 pandemic, thus, understanding susceptibility of animal species is paramount. Researchers will assess clinical outcome, duration and route of virus shedding, and seroconversion and pathology to understand the: 1) potential reservoir status of these common and abundant, peridomestic, mammalian wildlife species and, 2) likelihood of virus spillover from humans to these species. Results will guide proactive actions to manage contact between humans, domestic animals and wildlife—crucial to combat the ongoing COVID-19 pandemic. Animals will be acquired from a captive breeder and housed in BSL3 facility. Three pairs of each species will be intranasally inoculated with one of two doses of SARS-CoV-2 (103 and 105 plaque forming units). To determine direct contact transmission, at Day 1 post-inoculation, we will add one animal to each pair of inoculated animals. Post-inoculation, nasal and rectal swabs for qrtPCR and virus isolation and blood samples from both inoculated and direct contact animals will be collected up to 21 days. All animals will be monitored for clinical signs daily by a veterinarian and humanely euthanized, whereby a complete post-mortem examination will be conducted. This RAPID award is made by the Physiological and Structural Systems Cluster in the BIO Division of Integrative Organismal Systems, 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": "1420", "attributes": { "award_id": "2031626", "title": "RAPID: CLEARED: Culture of Living-biopsies for Emerging Airway-pathogens and REspiratory Disease", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [ "096Z", "7914", "9179" ], "program_officials": [ { "id": 3671, "first_name": "Joanna", "last_name": "Shisler", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-07-01", "end_date": "2021-06-30", "award_amount": 138793, "principal_investigator": { "id": 3675, "first_name": "Wallace G", "last_name": "Sawyer", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 158, "ror": "https://ror.org/02y3ad647", "name": "University of Florida", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 3672, "first_name": "Brent S", "last_name": "Sumerlin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 3673, "first_name": "Stephen", "last_name": "Eikenberry", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 3674, "first_name": "Matthew", "last_name": "Schaller", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 158, "ror": "https://ror.org/02y3ad647", "name": "University of Florida", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true }, "abstract": "The ongoing COVID-19 pandemic has highlighted the lack of human cell culture models available for studying this virus, and the devastating consequences of this shortcoming as it relates to human health and disease. The proposed project, known as “CLEARED” for Culture of Living-biopsies for Emerging Airway-pathogens and REspiratory Disease, combines cutting-edge technologies in 3D-printing, soft tissue engineering, artificial-intelligence-enhanced imaging, human lung biology, and virology to understand the spread of COVID-19 in lungs. This will increase the knowledge of SARS-CoV-2 biology and transmission. The researchers have developed the technology to grow portions of lung into living 3D-printed tissue structures that resembles the architecture found in the lung in a liquid-like-solid matrix. Thus, this system more closely resemble the environment in living humans versus standard cell culture. After infecting these samples with SARS-CoV-2 virus, advanced imaging of these “living biopsies” will be used to study virus spread from cell to cell, and the efficacy of therapeutic treatments. Outcomes of the proposed research include: (i) Validating a standard model system using human lung biopsies and known diagnostics in response to SARS-CoV-OC43 infection; (ii) Determining how the disease develops and spreads in biopsies infected with different human and bat coronavirus strains. It is expected that this system will allow scientists to better understand virus transmission and prevention. This project also supports the training of three graduate students, leading to an increase in future workers to drive the bioeconomy.The proposing team hypothesizes that controlled perfusion of SARS-CoV-2 in 3D culture models of human respiratory microtissue explants can recapitulate early stages of SARS-CoV-2 infection and COVID-19 disease. To test this hypothesis, PIs will establish a 3D model of viral infection using living microtissue explants of human bronchus and peripheral lung, quantify the early responses to viral infection using a novel 3D tissue culture platform, and determine the spatiotemporal pathogenesis of different human and bat coronaviruses strains. Preliminary data show that SARS-CoV-2 indeed infects the micro-tissues of bronchus and peripheral lung. This is a transdisciplinary team of investigators from Astronomy, Chemistry, Medicine, Engineering, Virology and lung biology. The proposed work is organized by two tasks. Task 1 will validate a standard model system using human lung biopsies and known host-response to SARS-CoV-2 infection. Readouts will include viral titer, cytokine production and spatiotemporal imaging of viral replication in response to coronavirus infection. Task 2 will determine the spatiotemporal pathogenesis of human lung biopsies infected with different human coronavirus strains (HCoV-OC43, HCoV-NL63, SARS-CoV-2) and one bat strain (btCoV-HKU3). The heterogenous nature of biopsies will alter the viral titer and cytokine production of biopsies compared to measurements in cell lines, and will provide superior information about progression and virus spread through tissues than standard cell culture technology. This RAPID award is made by the Physiological and Structural Systems Cluster in the BIO Division of Integrative Organismal Systems, 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": "1427", "attributes": { "award_id": "2028683", "title": "RAPID: Evaluating the Impact of COVID-19 on Labor Market, Social, and Mental Health Outcomes", "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", "9179" ], "program_officials": [ { "id": 3692, "first_name": "Cheryl", "last_name": "Eavey", "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": 200000, "principal_investigator": { "id": 3697, "first_name": "Daniel M", "last_name": "Bennett", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 152, "ror": "https://ror.org/03taz7m60", "name": "University of Southern California", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 3693, "first_name": "Elizabeth A", "last_name": "Stuart", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 3694, "first_name": "Wandi Bruine de", "last_name": "Bruin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 3695, "first_name": "Frauke", "last_name": "Kreuter", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 3696, "first_name": "Johannes", "last_name": "Thrul", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "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": "This research project will advance understanding of the economic, social, and mental health toll of the COVID-19 pandemic. The pandemic is quickly eroding the social and economic platform the world is built upon. Quality data must be gathered quickly in order to understand the impact of the pandemic on human life. This project will collect robust data on people's experiences in the U.S. during the pandemic, including data collected quickly via social media platforms. The project also will develop methodology to facilitate the effective use of different data sources. Because experiences both within the U.S. and across countries vary widely, the investigators will collaborate with researchers in five countries outside the U.S. By implementing the same measures of experienced outcomes in similar surveys across the globe, a unique comparison is possible about the effectiveness of the policies that have been implemented across countries. The project results will provide insights for academics, practitioners, and policy makers who are seeking to understand and inform policies to curb the pandemic and its consequences. Data collected by this project, links to other data, and project findings will be made available through dashboards for policy makers, researchers, and the interested public. The investigators will record podcasts and webinars to broadly disseminate the results. Graduate students will be trained in the conduct of collaborative multi-site research.This project will leverage data collected as part of an ongoing tracking study of American households in the Understanding America Study. Survey data also will be collected via Facebook and Instagram. Research questions to be addressed by the data include: Which policies have helped to reduce anxiety and depression during this pandemic? Which individuals are at greatest risk for economic losses during the pandemic and what measures have helped them the most? How do these economic losses influence willingness to engage in social distancing, and which policies have helped people to stay at home in the face of economic losses? The project also will develop new survey weighting approaches to make use of the simultaneous collection of data with different sampling frames, sampling schemes, and modes. The availability of multiple data sources will allow for the assessment of measurement properties of mental health scales items in need of adaptations to rapidly changing environments. Methods will be developed for causal inference from data combined from different sources to assess the effects of different policy interventions by local areas, states, and countries.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": "1442", "attributes": { "award_id": "2029890", "title": "RAPID: Impact of the Covid-19 Pandemic on Crime and Corrections Populations", "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", "9179" ], "program_officials": [ { "id": 3741, "first_name": "Reginald", "last_name": "Sheehan", "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": 37428, "principal_investigator": { "id": 3743, "first_name": "Daniel S", "last_name": "Nagin", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 243, "ror": "", "name": "Carnegie-Mellon University", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 3742, "first_name": "Amelia M", "last_name": "Haviland", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 31234, "first_name": "Mikaela Rose", "last_name": "Meyer", "orcid": null, "emails": "[email protected]", "private_emails": null, "keywords": "[]", "approved": true, "websites": "[]", "desired_collaboration": "", "comments": "", "affiliations": [ { "id": 243, "ror": "", "name": "Carnegie-Mellon University", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true } ] } ], "awardee_organization": { "id": 243, "ror": "", "name": "Carnegie-Mellon University", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Anecdotal news accounts make clear that the COVID-19 pandemic is having profound impacts on crime and on jail and prison populations in the United States. The short-term reductions in most crimes are consistent with various opportunity-based theories of crime with fewer people on the streets and visiting places like bars. The reports of increased domestic violence align with opportunity-based theories and in addition strain-based theories. Over the longer term, however, the reported crime reduction trends may reverse themselves as people become more economically impacted. Impacts of restricted admissions and accelerated releases from local jails and prisons on crime and on infection rates, within these facilities during this pandemic, are also unknown and of policy interest. Analyses will be conducted at the level of county and city for crime and jail population impacts and at the level of the state for prison population impacts. To estimate these effects we aim to do difference-in-difference type analyses. The main objectives of this project are to provide a rapid analysis of these impacts on crime and corrections populations to be completed prior to a possible future resurgence of the pandemic, and to share with policymakers rigorous analyses that will assist in informing their decisions in dealing with the 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": "1452", "attributes": { "award_id": "2029258", "title": "RAPID: Examining Media Dependencies, Risk Perceptions, and Depressive Symptomatology during the 2020 COVID Pandemic", "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", "9179" ], "program_officials": [ { "id": 3770, "first_name": "Robert", "last_name": "O'Connor", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-15", "end_date": "2021-05-31", "award_amount": 66453, "principal_investigator": { "id": 3771, "first_name": "Kenneth", "last_name": "Lachlan", "orcid": "https://orcid.org/0000-0002-7856-2797", "emails": "[email protected]", "private_emails": "", "keywords": "['Risk communication']", "approved": true, "websites": "['https://comm.uconn.edu/person/kenneth-lachlan/']", "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 257, "ror": "https://ror.org/02der9h97", "name": "University of Connecticut", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 257, "ror": "https://ror.org/02der9h97", "name": "University of Connecticut", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true }, "abstract": "The COVID-19 pandemic presents a unique opportunity to examine risk perceptions and responses on both a national and regional scale. When faced with a major health crisis, individuals are likely to be motivated to seek information in order to alleviate anxiety and gather information about how to protect themselves. While these dependencies are well documented, less is known about the extent to which media dependency translates into desired behavior, and the extent to which other effects associated with these dependencies may help or hinder this translation. Particularly troubling is prior research supporting the notion that depressive symptomology may lead to inaction, and that reliance on different news sources may lead to variability in the perception of risk. The current study extends previous research by investigating the extent to which risk perception and motivation to take protective action are tied to specific source preferences, and the degree to which individual processing characteristics and related responses influence these relationships. The research also aims to investigate the argument that depressive symptomatology may lead to inaction under such circumstances. Further, the research team explores specific protective actions and perceptions of risk while the threat is imminent, as opposed to relying on recall. The findings contribute to our knowledge base by filling a significant gap in the social science literature on emergency response by evaluating the links between trait processing, source preferences, depressive symptomatology, and protective actions. The new knowledge is beneficial to emergency managers for message design and placement.An online survey gathers data from a nationally representative sample of 5,000 respondents to assess the key variables of interest. Participants are asked about the relative importance of varying news outlets, sources of first alerts, time spent seeking information, risk perception (including magnitude and probability), specific protective behaviors advocated by the Center for Disease Control, and depressive symptomatology. Questions also measure emotional well-being, level of involvement in the information gathered, trait need for cognition, and ruminative coping tendencies. Prior findings concerning the role of rumination in information seeking are reexamined for replication and extended to investigate the subsequent role of this processing style in both depressive symptomatology and protective actions, such as social distancing. Source preferences are reduced into clusters using Exploratory Factor Analysis and examined in terms of the impact of specific source preference clusters on risk perception and protective action.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": "1454", "attributes": { "award_id": "2029790", "title": "RAPID: Developing Social Differentiation-respecting Disease Transmission Models", "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", "9179" ], "program_officials": [ { "id": 3774, "first_name": "Joseph", "last_name": "Whitmeyer", "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": 174891, "principal_investigator": { "id": 3777, "first_name": "James W", "last_name": "Moody", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 246, "ror": "https://ror.org/00py81415", "name": "Duke University", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 3775, "first_name": "Lisa A", "last_name": "Keister", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 3776, "first_name": "Dana K", "last_name": "Pasquale", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 246, "ror": "https://ror.org/00py81415", "name": "Duke University", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true }, "abstract": "In this project, transmission models that account for differences in social networks and exposure opportunities are developed to gain insight into the unequal spread of COVID-19 across populations. Some areas have experienced slow to no spread of COVID-19 while other settings have been overwhelmed. Within high-volume locations, some neighborhoods have been at much greater risk than others. To account for this uneven spread, these models incorporate population differences related to social density and sociodemographic characteristics—features that shape disease exposure and ability to social distance. These models augment general understanding of how social situation affects both disease risk and the cost of disease mitigation efforts, which will allow decisionmakers to evaluate the relative costs of different health-preserving interventions and, potentially, optimize interventions that minimize economic harm while maximizing physical safety.This project aims to have accurate, flexible and scalable models for disease transmission that can account for observed social differentiation in disease spread. Simulation models are employed to meet this goal, drawing on best estimates from the COVID-19 pandemic for disease-specific infection parameters and rates of transitioning into hospitalization, death, or recovery. Modeling occurs on two levels: Agent-Based Models (ABMs) and small-area cell-based simulation models. ABMs are constructed from social network data and allow for maximum flexibility, being tunable to different types of populations, ranging from rural communities in developing nations to dense urban centers. Small-area (census block group) cell-based simulation models, which translate network structure to interaction probabilities based on demographic and economic similarity profiles, include population differentiation but scale to the national level. These two modeling strategies complement each other and can be used to evaluate different mitigation strategies for both health effectiveness (lives saved) and economic hardship.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": "1464", "attributes": { "award_id": "2029963", "title": "RAPID: Assessing the Social Consequences of 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", "9179" ], "program_officials": [ { "id": 3801, "first_name": "Melanie", "last_name": "Hughes", "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": 110399, "principal_investigator": { "id": 3804, "first_name": "Long", "last_name": "Doan", "orcid": "https://orcid.org/0000-0001-9875-1037", "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 297, "ror": "https://ror.org/047s2c258", "name": "University of Maryland, College Park", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 3802, "first_name": "Jessica", "last_name": "Fish", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 3803, "first_name": "Liana", "last_name": "Sayer", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 297, "ror": "https://ror.org/047s2c258", "name": "University of Maryland, College Park", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "This project examines the impacts of COVID-19 and states’ and local governments’ social distancing directives on behavior, time spent with others, use of technology, and mental and physical wellbeing. The objective of the project is to investigate these daily life impacts in real time and to analyze how these impacts are affected by sociodemographic characteristics that affect time use and well-being. Data are leveraged from several hundred respondents’ daily time use before the pandemic along with data collected during and after the pandemic to create a natural experiment that isolates the effects of the pandemic on changes in behavior. Among the products of this research are evidence-based recommendations to address the social consequences of the pandemic.This project collects data for the second and third waves of a three-wave panel study, the second wave during the pandemic with shelter-at-home and lockdown orders in place and the third wave after the pandemic has subsided and orders have been relaxed. Data for these two waves consist of survey responses and 24-hour time diaries collected from 2,000 respondents from online crowdsourcing platforms. This sample includes a smaller sample from whom data were collected before the pandemic. Data are collected on sociodemographics, typical sleep, work, and exercise patterns, and arrangements for housework and carework to investigate effects on time use and wellbeing.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": "1473", "attributes": { "award_id": "2031287", "title": "RAPID: Analyzing forced habit change from COVID-19 using large-scale data", "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", "9179" ], "program_officials": [ { "id": 3826, "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": "2020-09-01", "end_date": "2022-08-31", "award_amount": 174313, "principal_investigator": { "id": 3830, "first_name": "Colin F", "last_name": "Camerer", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 211, "ror": "https://ror.org/05dxps055", "name": "California Institute of Technology", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 3827, "first_name": "Matthew S", "last_name": "Shum", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 3828, "first_name": "Yi", "last_name": "Xin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 3829, "first_name": "Lawrence", "last_name": "Jin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 211, "ror": "https://ror.org/05dxps055", "name": "California Institute of Technology", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "During the COVID-19 pandemic, people were forced to try new routine at school, work, and home — “forced exploration”. That is, habits used to guide how we work, conduct our daily routine, exercise, eat, go to school, and interact with friends and neighbors, Habits are formed to make the same routines effortless, to save time and mental effort, when routine choices work well. However, while the mental savings from habits are a benefit, when people are choosing habitually, they may not be exploring other options which could be even better— that is the hidden cost of habit. Forced exploration can actually be beneficial if it shows people better ways of school, work, and social interaction. This kind of exploration is like going to your favorite restaurant and finding out they have run out of your favorite dish — now you have to try something new, which you would not have explored without the disruption. This wave of forced exploration raises important questions: What new habits are formed that will persist— what will be the “new normal”? Consider, for example, wearing a face-mask outside of the house. This is exactly the kind of “muscle memory” behavior that usually habitizes— it can be triggered while stepping out of your car, or entering a store, and quickly becomes automatic and effortless. Whether a lot of other people are wearing masks or not can also be a trigger that prompts habit (in either direction).The same question arises across the board: Will people go back to movie theaters (or stay home with streaming)? Will restaurants fully reopen or will home delivery take over? Will knowledge firms switch to more remote “tele-work”? Will schools find better mixtures of home learning and in-school activity? This project will analyze two different kinds of big data to test whether or not this kind of forced exploration really does result in new habits.In social sciences, habits are usually modelled mathematically using a simple equation in which the more an activity has been done in the past, the more it is done in the future. This is called a \"reduced form\" approach because it reduces a biologically complicated mechanism to something much simpler. It is a good starting point but cannot answer questions such as \"What if past behavior is disrupted?” This research project uses a new approach to habits based on animal learning and human cognitive neuroscience. The starting point is that habits have developed to save effort ⎯— both physical and mental. The “neural autopilot” framework proposed here predicts that individuals develop habits for actions which, after repeated decisions, have proven to be reliably rewarding. Such habitual behavior drains fewer physical and mental resources. At the same time, when people are habitized⎯- about exercise, eating, or work — they ignore new goods and activities they would prefer if they actually tried them. While the neural autopilot approach has been tested in many lab studies of animal and human habituation, it has never been systematically explored using a large amount of data about how people actually behave in everyday life. An ideal test of this model is in a field setting where choice sets are artificially truncated, so people resort to new choices; and that is exactly what happened during the ongoing lockdowns. This project will use data from Weibo chat data and Fitbit fitness and sleep tracking. These large sets of data contain fine-grained measurements of behavior. Using this data, we will develop and test a statistical neural autopilot model, to recover values for the model’s main parameters. The parameters are numbers that measure, for each person, how fast habits are formed and the threshold to break out of a habit and explore something that might be better. The estimated parameter values will be used to make predictions about which habits acquired during the pandemic will persist, and which behavior will revert to pre-pandemic patterns.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": 1397, "count": 13961 } } }