Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1385&sort=-principal_investigator
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-principal_investigator", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1405&sort=-principal_investigator", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1386&sort=-principal_investigator", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1384&sort=-principal_investigator" }, "data": [ { "type": "Grant", "id": "500", "attributes": { "award_id": "1943777", "title": "CAREER: Enabling Immunomodulatory Treatment of Influenza Infection using Multiscale Modeling", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [], "program_officials": [ { "id": 1017, "first_name": "Stephanie", "last_name": "George", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-05-01", "end_date": "2025-04-30", "award_amount": 441696, "principal_investigator": { "id": 1018, "first_name": "Jason", "last_name": "Shoemaker", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 272, "ror": "https://ror.org/01an3r305", "name": "University of Pittsburgh", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 272, "ror": "https://ror.org/01an3r305", "name": "University of Pittsburgh", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Respiratory virus infections are a constant threat to public health. Influenza infection results in up to 700,000 hospitalizations and 56,000 deaths each year in the US. Extreme lung inflammation due to an excessive immune response is a major factor of severe disease outcomes in influenza virus and coronavirus infection (including SARS, MERS, and in emerging evidence, the COVID-19 virus.) The immune system is a complex, interactive, dynamic system that must optimally clear the virus infection while minimizing collateral damage to the lungs and other organs initiated by immune-regulated processes. Engineering-based mathematical modeling approaches are ideally suited to create computational simulations of the immune system that can be used to estimate the system’s response to virus infection. The overall goal of this research project is to construct realistic, predictive, physiologically accurate computational models of the natural immune response during influenza virus infection. The computational models will form the foundation for simulation-based research to identify the immunologic conditions that allow for excessive immune responses to occur. Simulations will also identify the best way to suppress immune activity, using chemical inhibition to reduce tissue inflammation while ensuring rapid clearance of the infection. As excessive inflammation is a common feature of many respiratory virus infections, the insights on immune regulation generated are expected to impact a variety of respiratory virus diseases. In parallel with this research effort, the research team will develop virtual reality (VR) games to better engage the public on matters associated with respiratory infection and immune responses. The VR games will be distributed to user smartphones for free to ensure strong public engagement. The VR games will also be used during workshops at local high schools to promote student engagement in engineering and immunology. The Investigator’s long-term CAREER vision is to engineer computational modeling-based solutions to regulate and improve immune system responses. Toward this vision, the objectives of this CAREER project are to identify the molecular/cellular mechanisms that drive lung inflammation during influenza infection and to evaluate immunomodulatory treatment in silico using multiscale computational modeling. Studies show that selectively inhibiting the immune system can significantly improve infection outcomes by reducing inflammation without compromising virus clearance. Immunomodulation has also been shown to offer greater protection than administration of antiviral medicines (e.g. oseltamivir), but no comprehensive guidelines for administering immunomodulatory treatments, such as anti-inflammatory corticosteroids, exist. Such immunomodulatory strategies are inherently an engineering optimization challenge: modifying immune responses to limit inflammation while ensuring virus clearance. The predictive models designed can be used to evaluate specific hypotheses on the mechanisms regulating inflammation during influenza virus infection. The research program is organized under three synergistic objectives. The FIRST Objective is to construct and use an ODE (Ordinary Differential Equations) model to identify the molecular drivers of inflammation in influenza-infected human lung epithelial cells. A model of epithelial intracellular signaling will be developed and used to uncover the molecular drivers of inflammatory protein production, evaluate trade-offs between inflammation and suppressing virus replication, and to identify possible virus-specific inflammatory regulation when comparing highly pathogenic (H5N1) and milder virus infections. Completion of this objective will provide evidence of the molecular mechanisms regulating lung epithelial inflammation in general and in specific virus infections. The SECOND Objective is to construct and use an ODE model to identify the immunologic conditions that drive enhanced inflammation in influenza-infected mouse lungs. The model will link lung epithelial signaling with immune cell infiltration. The model will be used to identify the mechanisms that drive enhanced inflammation at the tissue level and explore treatment options. Comparisons between infection with different viruses and between male (less severe) vs female (more severe) infection may reveal virus and cohort-specific inflammation regulation. Completion of this objective will identify the key molecular and cellular drivers of influenza-induced inflammation, provide a novel computational model of the lung immune system that enables comparisons between important infection cohorts, and potentially identify virus-specific or sex-specific immune regulation that is driving differential inflammation. The THIRD Objective is to construct and use an ABM (Agent Based Model) of the lung immune system to quantify the impact of cell heterogeneity on tissue-level inflammation. Interferon production is stochastic and may factor into variable infection outcomes. Using customized code, an ABM in which ODEs define how agents (epithelial cells) interact with their environment will be constructed and used to interrogate how epithelial cellular heterogeneity impacts tissue-level inflammation during influenza infection. Completion of this objective will identify the components of the immune system responsible for maintaining a tightly regulated inflammatory response, provide knowledge of how intra-subject inflammation may vary due to differences in immune regulation, produce new code for the simulation community, and produce a novel ABM of the lung immune system during influenza infection.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": "499", "attributes": { "award_id": "2030049", "title": "Collaborative Research: RAPID--Urban Air Quality during the Coronavirus (COVID-19) Shelter-In-Place Orders", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)" ], "program_reference_codes": [], "program_officials": [ { "id": 1015, "first_name": "Sylvia", "last_name": "Edgerton", "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": 101072, "principal_investigator": { "id": 1016, "first_name": "Kelley", "last_name": "Barsanti", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 153, "ror": "", "name": "University of California-Riverside", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 153, "ror": "", "name": "University of California-Riverside", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "In this RAPID project, a collaborative PI team intends to collect time sensitive atmospheric samples in the Los Angeles, CA, area, where historically high pollutant levels of ozone (O3) and fine particulate matter (PM2.5) have plagued public health. By taking advantage of significant reductions in atmospheric emissions associated with current COVID-19 shelter-in-place orders, a natural experiment has presented itself that allows for observations to be made under uniquely useful conditions. Results will help constrain predictive models of pollutant concentrations and guide regulatory agencies in best strategies to mitigate poor air quality.Gaseous and particulate samples will be collected during and after the lifting of COVID-19 by co-locating sampling devices on Caltech’s established roof-top sampling platform, where continuous monitoring of essential parameters, including NOx, O3, and PM2.5, is ongoing. Focus in this study is on the detailed chemical speciation of the important precursor group of compounds denoted as volatile to intermediate volatility organic compounds (I/VOCs) containing 1 to 15 carbon atoms (C1-C15). These compounds are emitted through a number of different sources, including from fossil fuel production and burning, use of chemical products, and biological productivity. Their ill-defined sources and reactivities have been attributed to an existing gap in knowledge that could describe higher-than-expected O3 levels in megacities where precursor emissions have seen a general decrease in past decades. Here, I/VOC sources and source markers will be determined during a period when transportation associated emissions to VOCs and NOx are low. State-of-the-art analyses of collected samples at PIs’ laboratories include two-dimensional gas chromatography (GC×GC) with time-of-flight mass spectrometry (TOFMS) and a multi-column/detector GC system with 5 different types of separation and detection combinations. Results will (i) provide new insight into the intricate mechanisms of O3 and PM2.5 production under uniquely low NOx conditions and a changing mix of VOCs, and (ii) help constrain predictive models of atmospheric chemistry and air quality.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": "498", "attributes": { "award_id": "2030112", "title": "Collaborative Research: RAPID--Urban Air Quality during the Coronavirus (COVID-19) Shelter-In-Place Orders", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)" ], "program_reference_codes": [], "program_officials": [ { "id": 1013, "first_name": "Sylvia", "last_name": "Edgerton", "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": 94495, "principal_investigator": { "id": 1014, "first_name": "Donald R", "last_name": "Blake", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 177, "ror": "", "name": "University of California-Irvine", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 177, "ror": "", "name": "University of California-Irvine", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "In this RAPID project, a collaborative PI team intends to collect time sensitive atmospheric samples in the Los Angeles, CA, area, where historically high pollutant levels of ozone (O3) and fine particulate matter (PM2.5) have plagued public health. By taking advantage of significant reductions in atmospheric emissions associated with current COVID-19 shelter-in-place orders, a natural experiment has presented itself that allows for observations to be made under uniquely useful conditions. Results will help constrain predictive models of pollutant concentrations and guide regulatory agencies in best strategies to mitigate poor air quality.Gaseous and particulate samples will be collected during and after the lifting of COVID-19 by co-locating sampling devices on Caltech’s established roof-top sampling platform, where continuous monitoring of essential parameters, including NOx, O3, and PM2.5, is ongoing. Focus in this study is on the detailed chemical speciation of the important precursor group of compounds denoted as volatile to intermediate volatility organic compounds (I/VOCs) containing 1 to 15 carbon atoms (C1-C15). These compounds are emitted through a number of different sources, including from fossil fuel production and burning, use of chemical products, and biological productivity. Their ill-defined sources and reactivities have been attributed to an existing gap in knowledge that could describe higher-than-expected O3 levels in megacities where precursor emissions have seen a general decrease in past decades. Here, I/VOC sources and source markers will be determined during a period when transportation associated emissions to VOCs and NOx are low. State-of-the-art analyses of collected samples at PIs’ laboratories include two-dimensional gas chromatography (GC×GC) with time-of-flight mass spectrometry (TOFMS) and a multi-column/detector GC system with 5 different types of separation and detection combinations. Results will (i) provide new insight into the intricate mechanisms of O3 and PM2.5 production under uniquely low NOx conditions and a changing mix of VOCs, and (ii) help constrain predictive models of atmospheric chemistry and air quality.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": "497", "attributes": { "award_id": "1816064", "title": "Ecology of MERS-CoV in camels, humans, and wildlife in Ethiopia", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [], "program_officials": [ { "id": 1010, "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": "2018-09-01", "end_date": "2020-05-31", "award_amount": 178326, "principal_investigator": { "id": 1012, "first_name": "Amira", "last_name": "Roess", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 174, "ror": "https://ror.org/00y4zzh67", "name": "George Washington University", "address": "", "city": "", "state": "DC", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 1011, "first_name": "Sally", "last_name": "Lahm", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 174, "ror": "https://ror.org/00y4zzh67", "name": "George Washington University", "address": "", "city": "", "state": "DC", "zip": "", "country": "United States", "approved": true }, "abstract": "Zoonotic diseases are diseases that exist in animals and can be transmitted to humans. Zoonoses currently account for approximately 75 percent of all emerging infections worldwide. However, the factors that trigger zoonotic disease emergence and spread remain poorly understood, in part because they involve multiple species, complex inter-species and intra-species relationships, and many interacting environmental, behavioral, social, and economic factors. Middle Eastern Respiratory Syndrome-Coronavirus (MERS-CoV) presents a case in point. MERS-CoV was first identified in human beings in 2012 and has killed 36 percent of those infected, but little is known about what has led to its emergence. For example, several human cases have been traced to contact with camels imported from Africa; studies also have detected MERS-CoV in African wildlife; and while camels are a known reservoir host for MERS-CoV, it is not known if there are additional reservoirs or intermediate hosts, or how frequently and under what conditions MERS-CoV spillover occurs. This project will investigate the natural ecology of MERS-CoV in relation to broader social, economic, and environmental changes; its potential wildlife reservoirs in close contact with camels; and the potential for spillover to humans who consume, herd, and trade camels and camel products. This work is of direct importance to national security with respect to disease threats; MERS-CoV is currently on the World Health Organization's priority shortlist of diseases in urgent need of accelerated research. To understand when and under what conditions MERS-CoV emerges and spreads from animals to humans, the researchers ask, (1) How do social, cultural and behavioral characteristics of camel economics shape virus ecologies? (2) Which intra- and inter-species interactions increase MERS-CoV emergence and transmission? and (3) What climatic and environmental variables are associated with transmission? Researchers will conduct field studies of wild and domestic (camel) reservoirs, collecting roughly 800 samples from targeted wildlife (ungulates and eulipotyphlads) over two years at four locations. They will carry out socio-behavioral studies across the camel value chain and follow individual camels longitudinally to determine when the same individuals seroconvert to MERS-CoV positive status. They will conduct laboratory analyses and do viral sequencing. The researchers will integrate the data into mathematical models using the 'Method of Plausible Parameter Sets' (MPPS), which will determine which mechanistic scenarios are consistent with observed patterns of MERS-CoV in camels and humans. This broadly inclusive approach expands upon traditional studies of zoonotic disease emergence. The transmission models will be applicable to other zoonotic diseases linked to livestock production and will help to identify interventions to reduce disease emergence and transmission.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": "496", "attributes": { "award_id": "1716698", "title": "CNH-L: Dynamics of Zoonotic Systems: Human-Bat-Pathogen Interactions", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [], "program_officials": [ { "id": 1004, "first_name": "Elizabeth", "last_name": "Blood", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2017-09-01", "end_date": "2022-08-31", "award_amount": 1650000, "principal_investigator": { "id": 1009, "first_name": "Raina K", "last_name": "Plowright", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 1005, "first_name": "Elizabeth A", "last_name": "Shanahan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 1006, "first_name": "Olivier Restif", "last_name": "Dr", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 1007, "first_name": "Liam P", "last_name": "McGuire", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 1008, "first_name": "Nita", "last_name": "Bharti", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 259, "ror": "https://ror.org/02w0trx84", "name": "Montana State University", "address": "", "city": "", "state": "MT", "zip": "", "country": "United States", "approved": true }, "abstract": "Increases in the frequency of human-wildlife interaction have led to the emergence of new zoonoses, which are infectious diseases that are transmitted from animals to humans. Zoonoses are a major threat to biosecurity and public health. Bats are home to some of the highest-profile emerging zoonoses, including Ebola, Marburg, Nipah, and Hendra viruses, and severe acute respiratory syndrome coronavirus (SARS). Transmission from bats to humans often occurs when bats abandon natural habitats to take advantage of resources associated with human settlements. This project will investigate how habitat loss causes bat migration into populated developed areas, which leads to increased bat-human encounters and increased disease transmission. The research will focus on Hendra virus, a bat borne pathogen in Australia, to study the interactions among changing landscapes, loss of natural habitats, humans, bats, and pathogens. A surge of bat movement into towns and cities in eastern Australia has led to increased negative bat-human interactions, and increased mortality of horses and humans from Hendra virus. An ultimate goal of the research is to identify and mitigate the specific interacting factors responsible for increased disease incidence and poor health outcomes. The research team includes investigators at ten academic institutions and a non-profit organization. The project will train U.S. students and postdoctoral researchers, improve science communication and policies that protect wildlife and human health, and will build greater research capacity among national and international collaborators. Methods and results will be generalizable to numerous countries in which similar zoonotic events occur, but that have limited resources for biological surveillance, disease prevention, and responding to outbreaks.This project will address the hypotheses that the root cause of negative bat-human interactions is the loss of habitat needed to sustain bats' nomadic feeding ecology, and that some management decisions (e.g., destruction of roost sites, not vaccinating horses) may exacerbate conflict, spillover, and habitat loss. The research integrates theory and field data spanning ecology, physiology, epidemiology, political science, anthropology, veterinary medicine, behavioral ecology, and mathematical modeling. Data will be collected on land-use change and the physiology, energetics, and movement of bats; mechanistic models will be used to examine how the relations among these variables influence bats' use of urban areas. The researchers will conduct field and modeling studies on the dynamics of bat viruses to help predict future instances of virus spillover. They will additionally use narratives, collaboratively produced by researchers and local communities, to conduct experiments on risk perceptions and decisions about bat nuisance, virus spillover, and vaccination. Ultimately, the project will lead to an evidence-based program for reversing the negative human-wildlife interactions that lead to epidemics and loss of wildlife. It will also lead to a framework for public education and engagement that is endorsed by local communities and is embedded in ecological restoration initiatives.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "495", "attributes": { "award_id": "1614133", "title": "EAPSI:Rapid, Smartphone-based Paper Assay Fabrication for Sensitive and Specific Detection of Middle East Respiratory Syndrome Coronavirus (MERS-CoV)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Office Of The Director" ], "program_reference_codes": [], "program_officials": [ { "id": 1002, "first_name": "Anne", "last_name": "Emig", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2016-06-01", "end_date": "2017-05-31", "award_amount": 5400, "principal_investigator": { "id": 1003, "first_name": "Soohee", "last_name": "Cho", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 271, "ror": "", "name": "Cho Soohee", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 271, "ror": "", "name": "Cho Soohee", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true }, "abstract": "In summer 2015, the Middle East respiratory syndrome coronavirus (MERS-CoV) outbreak compromised South Korea, spreading rapidly due to high-density population and humid environment. Patients are quarantined while monitored by lab-based methods, which are laborious, expensive, and requires days for cross-validated results. A rapid diagnostic tool that detects MERS-CoV with high sensitivity and specificity is crucial for preventing further outbreaks. This project aims to fabricate rapid assays that can detect MERS-CoV Spike protein. Spike protein has gained recognition as a high research priority target and serves as a positive mimic for the virus. Smartphone-based analysis enables point-of-care (POC) diagnostics without requiring laboratory expertise and resources. This collaborative project will be performed with Dr. Seungjoo Haam at Yonsei University, South Korea. Dr. Haam has conducted extensive research on fabricating light-sensitive nanostructures that are target-specific, which is critical for efficient detection of MERS-CoV.This project includes fabrication of a rapid, POC microfluidic paper analytical device (µPAD) for sensitive and specific detection of Spike protein. µPADs have gained momentum as an advantageous lab-on-a-chip that makes disease diagnostics cost-effective, are operable by non-experts, and with rapid assay time within 30 s. The PI has expertise in µPAD fabrication and antibody-conjugation on submicron particles for pathogen detection from bio-complex matrices by measuring optical signal change from smartphone-based analysis. However, the optical signal change can be greatly enhanced by the use of Spike protein antibody conjugated to gold nanorods (GNRs), which are light-sensitive and respectively exhibits near-infrared absorbance for a long period upon irradiation. The synergistic product of PI?s µPADs and the collaborator?s GNRs may result in a highly effective lab-on-a-chip system, that enables rapid, POC detection of Spike protein with improved sensitivity and specificity that is unbound to clinical or poor-resource settings. Future work may include detection of other respiratory diseases, such as H1N1 influenza. This award under the East Asia and Pacific Summer Institutes program supports summer research by a U.S. graduate student and is jointly funded by NSF and the National Research Foundation of Korea.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "494", "attributes": { "award_id": "1555141", "title": "CAREER: Big Computation and the Management of Emerging Infectious Diseases", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)" ], "program_reference_codes": [], "program_officials": [ { "id": 1000, "first_name": "Gabor", "last_name": "Szekely", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2016-06-01", "end_date": "2021-06-30", "award_amount": 257477, "principal_investigator": { "id": 1001, "first_name": "Eric B", "last_name": "Laber", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 245, "ror": "https://ror.org/04tj63d06", "name": "North Carolina State University", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 245, "ror": "https://ror.org/04tj63d06", "name": "North Carolina State University", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true }, "abstract": "Emerging infectious diseases (EIDs) account for more than 25% of global disease burden and more than 32% of global deaths. Current EIDs like Middle East Respiratory Syndrome Coronavirus (MERS) and antibiotic-resistant superbugs have the potential to make devastating impacts on public health. The methodologies under development in this project can be used to translate real-time data on EIDs into recommendations about where, when, and to whom to apply interventions so as to minimize negative impacts of the disease while reducing overall resource consumption. Furthermore, these recommendations are designed to be immediately interpretable in a subject matter context, thereby empowering decision makers to incorporate information from complex and heterogeneous data streams into disease management. Application of these methodologies has the potential to reduce mortality and morbidity at lower cost than existing management plans. Furthermore, models underpinning intervention recommendations will generate new knowledge about EID dynamics. This research project aims to make fundamental contributions to online sequential decision making and to create a new statistical framework for data-driven management of EIDs. We conceptualize the EID as spreading across a finite set of locations, which might be physical locations in space or nodes in a network. An allocation strategy formalizes management of an EID and is represented by a sequence of functions, one per intervention decision, that map up-to-date information on an EID to a subset of locations recommended for treatment. An optimal allocation strategy maximizes some mean utility function over the duration of the EID. Construction of an optimal allocation strategy from data on an EID is challenging because: (i) the number of allocations is exponential in the number of locations; (ii) estimation and management must occur simultaneously; (iii) spatial proximity induces causal interference; and (iv) an allocation strategy must be interpretable to subject matter experts. We integrate ideas from statistics, computer science, optimization, and disease ecology to overcome these challenges. We combine simulation-optimization with policy-search algorithms to construct an online estimator of the optimal allocation strategy; this strategy trades off exploring allocation choices that improve estimates of disease dynamics with exploiting current estimated dynamics to immediately slow spread of the EID. We show that the treatment allocation problem can be recast as an infinite-dimensional bandit problem. We leverage this connection to derive estimation algorithms that scale to very large allocation problems and are amenable to theoretical study. We combine our policy-search and bandit-based estimators with a novel class of allocation strategies that can be expressed as a sequence of if-then statements that are immediately interpretable to subject-matter experts and can be readily adjusted based on expert judgment. We derive a non-parametric lower bound on the approximation error of an estimated allocation strategy within this class; this bound is used to perform goodness-of-fit tests for the estimated optimal allocation strategy.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "493", "attributes": { "award_id": "1517719", "title": "Collaborative Research: Modeling Immune Dynamics of RNA Viruses In Reservoir and Nonreservoir Species", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)" ], "program_reference_codes": [], "program_officials": [ { "id": 997, "first_name": "Junping", "last_name": "Wang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2015-09-15", "end_date": "2020-08-31", "award_amount": 349803, "principal_investigator": { "id": 999, "first_name": "Linda J", "last_name": "Allen", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 270, "ror": "https://ror.org/0405mnx93", "name": "Texas Tech University", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 998, "first_name": "Adao", "last_name": "Trindade", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 270, "ror": "https://ror.org/0405mnx93", "name": "Texas Tech University", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "Over 50% of all human infectious diseases are zoonotic or originate through the cross-species transmission of viruses from wildlife to humans. Included among these are hantaviruses, which pose a significant threat to public health worldwide and are classified as emerging infectious diseases. Hantaviruses are transmitted to humans through contact with infected rodent excrement. Although hantaviruses cause little morbidity or mortality in their rodent reservoir, they establish a persistent infection that spills over into sympatric or human hosts. Spillover infection in nonreservoir rodents results in an asymptomatic acute infection without any apparent proinflammatory response or disease, whereas spillover in humans results in severe pathology (hantavirus cardiopulmonary syndrome) with mortality reaching 40-50%. Very little is known regarding the differences in the innate/adaptive immune response to hantavirus infection that characterize these three distinct responses: persistence, viral clearance, or severe pathology. The primary goals of this research are to formulate and to test new mathematical models based on carefully designed in vitro experiments for hantavirus infection and to identify key immune components at crucial time points that differentiate between natural versus nonnatural reservoirs (rodents and humans). This knowledge is essential for designing interventions and therapeutics for treatment of hantaviruses and other similar zoonotic viruses for which treatment is not currently available.The in vitro experiments are designed to clearly distinguish the pathways during hantavirus infection in natural reservoir (rodents) versus spillover into nonreservoir hosts (rodents and humans). Three different hantaviruses, endemic in North America, will be used to infect endothelial and immune cells: Sin Nombre virus, Black Creek Canal virus, and Prospect Hill virus in two different types of host cells, deer mice and human. Dependent on the combination of host and hantaviral species, three different outcomes can be observed in either reservoir or nonreservoir hosts: (i) persistence of infection with no disease, (ii) acute infection with viral clearance, and (iii) severe pathology and disease. In the lungs, endothelial cells and macrophages are the primary target cells of hantavirus. Based on the experimental outcomes, deterministic and stochastic mathematical models will be formulated and statistically validated for the dynamics of these and other cells important in the early phase of the immune response. Methods from ordinary and stochastic differential equations, Markov chains and branching processes will be used to model the virus-cell-immune dynamics that includes activation of proinflammatory and anti-inflammatory cytokines. Mathematical and statistical methods will be developed to identify thresholds that determine specific immunological pathways. In the broader context, this research will have educational and scientific impacts through cross-disciplinary training of students and a postdoc in mathematics and biology, through outreach and professional activities, and through development of new mathematical models and statistical methods. The mathematical models, methods, and data will be shared with other scientific groups to investigate questions and hypotheses regarding other zoonotic viruses important to public health such as avian influenza, Hendra, Ebola, and SARS Coronavirus.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "492", "attributes": { "award_id": "1516011", "title": "Collaborative Research: Modeling Immune Dynamics of RNA Viruses In Reservoir and Nonreservoir Species", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)" ], "program_reference_codes": [], "program_officials": [ { "id": 994, "first_name": "Junping", "last_name": "Wang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2015-09-15", "end_date": "2019-08-31", "award_amount": 349879, "principal_investigator": { "id": 996, "first_name": "Michele M", "last_name": "Kosiewicz", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 269, "ror": "", "name": "University of Louisville Research Foundation Inc", "address": "", "city": "", "state": "KY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 995, "first_name": "Colleen", "last_name": "Jonsson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 269, "ror": "", "name": "University of Louisville Research Foundation Inc", "address": "", "city": "", "state": "KY", "zip": "", "country": "United States", "approved": true }, "abstract": "Over 50% of all human infectious diseases are zoonotic or originate through the cross-species transmission of viruses from wildlife to humans. Included among these are hantaviruses, which pose a significant threat to public health worldwide and are classified as emerging infectious diseases. Hantaviruses are transmitted to humans through contact with infected rodent excrement. Although hantaviruses cause little morbidity or mortality in their rodent reservoir, they establish a persistent infection that spills over into sympatric or human hosts. Spillover infection in nonreservoir rodents results in an asymptomatic acute infection without any apparent proinflammatory response or disease, whereas spillover in humans results in severe pathology (hantavirus cardiopulmonary syndrome) with mortality reaching 40-50%. Very little is known regarding the differences in the innate/adaptive immune response to hantavirus infection that characterize these three distinct responses: persistence, viral clearance, or severe pathology. The primary goals of this research are to formulate and to test new mathematical models based on carefully designed in vitro experiments for hantavirus infection and to identify key immune components at crucial time points that differentiate between natural versus nonnatural reservoirs (rodents and humans). This knowledge is essential for designing interventions and therapeutics for treatment of hantaviruses and other similar zoonotic viruses for which treatment is not currently available.The in vitro experiments are designed to clearly distinguish the pathways during hantavirus infection in natural reservoir (rodents) versus spillover into nonreservoir hosts (rodents and humans). Three different hantaviruses, endemic in North America, will be used to infect endothelial and immune cells: Sin Nombre virus, Black Creek Canal virus, and Prospect Hill virus in two different types of host cells, deer mice and human. Dependent on the combination of host and hantaviral species, three different outcomes can be observed in either reservoir or nonreservoir hosts: (i) persistence of infection with no disease, (ii) acute infection with viral clearance, and (iii) severe pathology and disease. In the lungs, endothelial cells and macrophages are the primary target cells of hantavirus. Based on the experimental outcomes, deterministic and stochastic mathematical models will be formulated and statistically validated for the dynamics of these and other cells important in the early phase of the immune response. Methods from ordinary and stochastic differential equations, Markov chains and branching processes will be used to model the virus-cell-immune dynamics that includes activation of proinflammatory and anti-inflammatory cytokines. Mathematical and statistical methods will be developed to identify thresholds that determine specific immunological pathways. In the broader context, this research will have educational and scientific impacts through cross-disciplinary training of students and a postdoc in mathematics and biology, through outreach and professional activities, and through development of new mathematical models and statistical methods. The mathematical models, methods, and data will be shared with other scientific groups to investigate questions and hypotheses regarding other zoonotic viruses important to public health such as avian influenza, Hendra, Ebola, and SARS Coronavirus.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "491", "attributes": { "award_id": "1521918", "title": "RAPID: On-site Disinfection and Survival of Ebola and Other Viruses in Human Fecal Wastes and Sewage", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Unknown" ], "program_reference_codes": [], "program_officials": [ { "id": 992, "first_name": "Karl", "last_name": "Rockne", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2015-02-01", "end_date": "2018-01-31", "award_amount": 144418, "principal_investigator": { "id": 993, "first_name": "Mark D", "last_name": "Sobsey", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 166, "ror": "https://ror.org/0130frc33", "name": "University of North Carolina at Chapel Hill", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 166, "ror": "https://ror.org/0130frc33", "name": "University of North Carolina at Chapel Hill", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true }, "abstract": "1521918SobseyRAPID: On-site Disinfection and Survival of Ebola and Other Viruses in Human Fecal Wastes and SewageThere is a critical and urgent need for quantitative data on the survival and rapid, onsite chemical disinfection of Ebola virus and surrogate/indicator viruses in feces and raw sewage, as no such data currently exist. Data on both survival and chemical disinfection of Ebola virus and surrogates/indicators for it will provide quantitative information to assess the risks posed by Ebola virus in fecal waste and raw sewage and to determine if the risks can be reduced effectively by on-site, rapid chemical disinfection. No previous studies have ever compared systematically the range of chemical disinfectants to be used here for inactivation of Ebola or other surrogate/indicator viruses. The project will provide critical and timely quantitative information on the survival and rapid on-site chemical disinfection of a mutant Ebola virus and several candidate indicator/surrogate viruses in feces and raw sewage.The objectives of this study are to: (1) do batch laboratory-scale experiments to quantify and characterize the rate and extent of inactivation of the infectivity of a mutant Ebola virus strain as well as surrogate/indicator viruses, both enveloped and non-enveloped) in feces and raw sewage at two temperatures (37C and a room temperature of ~23C) under both aerobic and anaerobic conditions, and, (2) to determine the rate and extent of inactivation of the infectivity of these viruses in feces and raw sewage by batch disinfection with different doses of the following disinfectants: free chlorine, 2 quaternary ammonium compounds, peracetic acid, lime (calcium hydroxide), a phenolic compound and an anionic detergent. The mutant Ebola virus strain that is not infectious for humans or animals but grows and can be assayed for infectivity in a genetically modified cell line will be used along with the following surrogate/indicator viruses: an animal coronavirus (Transmissible Gastroenteritis Virus of Swine), an avian influenza virus strain, an enveloped bacteriophage (Phi6) and 2 non-enveloped bacteriophages of E. coli (MS2 and PhiX-174).", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 1385, "pages": 1405, "count": 14046 } } }