Project Grant 2240409

Award Date 8/1/23
Completion Date 7/31/27
Dollars Obligated $330K
Federal Grant Program
47.041
Assistance Type
Project Grant
Place of Performance
Atlanta, GA 30332, USA
Similar Awards
This Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $670,000 to The Pennsylvania State University (Penn State) to develop a data-driven early warning system framework for detecting and responding to emerging epidemics of illicit substance use. The project aims to (1) create predictive models to identify high-risk communities and emerging threats, (2) uncover causal factors driving these substance use patterns, (3) optimize intervention...
This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $244,008 to The Research Foundation for the State University of New York (SUNY) to develop novel analytical methods and decision support models to help county policymakers in West Virginia more effectively combat the opioid crisis. The project aims to assess the effectiveness of interventions that disrupt opioid supply chains, including both supply-side interdiction strategies and...
The National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems awarded a $399,541 Project Grant to the Trustees of Dartmouth College to develop a high-throughput, label-free, and portable sensor that can quantitatively detect multiple illicit drugs including opioids, cocaine, psychostimulants, and methadone in liquid samples such as biofluids. The project aims to create a silver or gold nanoparticle-decorated zinc oxide nanorod coated silica nanofiber matrix...
This federal Project Grant award from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program provides $649,585 to Auburn University to develop an integrated and miniaturized opioid sensor system. The project aims to address the opioid crisis through innovative, cost-efficient, and portable opioid biosensors that can enable real-time, accurate detection and monitoring. The interdisciplinary team is working to deliver solutions for law...
This Project Grant award from the National Science Foundation (NSF) under the Engineering program (CFDA 47.041) supports a collaborative research project titled "Disrupting West Virginia's Opioid Crisis: A Multi-Disciplinary Approach through Interdiction and Harm Reduction". The $238,666 award to the Regents of the University of Minnesota aims to develop novel analytical methods and decision support models to help county policymakers in West Virginia effectively allocate resources to...
This Project Grant award in the amount of $311,024 was provided by the National Science Foundation (NSF) under the Engineering (CFDA 47.041) program. The grant supports a collaborative research project led by West Virginia University Research Corporation to develop novel analytical methods and decision support models to help county policymakers in West Virginia effectively allocate resources to combat the opioid crisis. The project aims to map and compare county-level budgetary approaches to...
This Project Grant award of $114,000 from the National Science Foundation's (NSF) Division of Mathematical Sciences (CFDA 47.049 - Mathematical and Physical Sciences) supports research to integrate wastewater surveillance and human behavior data to enhance epidemiological modeling and outbreak response. The key objectives are to: 1) Develop an early-warning system using wastewater and digital/social behavior data; 2) Create a socio-immuno-epidemiological framework to examine pharmaceutical...
The National Science Foundation awarded a $150,000 Project Grant to the University of Notre Dame du Lac to develop a holistic framework for detecting online opioid trafficking activities. Funded under the Computer and Information Science and Engineering program (CFDA 47.070), this two-year award will support the design of a heterogeneous temporal graph and graph transformer model with meta-learning capabilities. The framework aims to comprehensively model and analyze dynamic multi-modal data...
This National Science Foundation project grant award of $1,000,000 supports the establishment of the Center for Ecosystems Data Integration and Pandemic Early Warning Systems in Western New York. Funded under the NSF Engineering Directorate's Predictive Intelligence for Pandemic Prevention Phase I program, the award will support the development of an integrated early warning system to monitor and track emerging pathogens through wastewater surveillance and clinical sampling analysis....
This $250,000 Project Grant award from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) supports the development of algorithms for real-time dynamic risk identification and monitoring of streaming data, particularly in the domains of electronic medical records, mobile health, and supply chain. The key objectives are to create a unified framework for dynamic risk detection that can be incorporated into...

This Project Grant award from the National Science Foundation (NSF) Engineering (CFDA 47.041) program provides $330,000.00 to Georgia Tech Research Corporation to develop an Early Warning System (EWS) for emerging epidemics of illicit substances. The objective is to create a data-driven analytical framework to support early identification of new threats, such as the growing veterinary tranquilizer epidemic, by monitoring and analyzing multimodal data to understand causal factors and develop effective response strategies. The project takes a holistic, multidisciplinary approach, involving experts in operations research, criminal justice, and public health policy, to advance fundamental knowledge of illicit drug use patterns and support multi-pronged interventions. This four-year project will produce predictive and prescriptive models, uncover causal pathways, optimize dynamic interventions, and deliver a decision support tool as a proof-of-concept EWS framework. The work aims to provide transformative learning and help prepare graduate students to tackle complex societal challenges.

Generated 6/18/24, 2:12 AM