Cooperative Agreement U54CK000447

This $968,765 Project Grant awarded by the National Science Foundation's (NSF) Division of Mathematical Sciences (CFDA 47.049 - Mathematical and Physical Sciences) will develop a flexible modeling framework to simulate the impact of various testing-based infection control strategies for respiratory pathogens like SARS-CoV-2. The project aims to improve our ability to control existing respiratory diseases and enhance preparedness for future pandemics. Key deliverables include: Developing a...

This federal Project Grant award of $360,000 from the National Science Foundation's (NSF) Division of Mathematical Sciences and the CDC Coronavirus and Other Respiratory Viruses Division aims to improve policymaking processes for mitigating the transmission of respiratory pathogens, such as during the COVID-19 pandemic. The principal investigators will develop and study game theoretical mathematical models, simulation tools, and numerical approaches that can be adapted to specific public...

This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will provide $599,783 to develop novel computational approaches to identify effective intervention strategies against healthcare-associated infections (HAIs). The research aims to leverage electronic medical records data and machine learning algorithms to predict potential future infections and unobserved/asymptomatic cases, enabling real-time resource...

This National Science Foundation Project Grant of $200,000.00, awarded on November 15, 2022 with a completion date of October 31, 2026, will fund research at Columbia University to develop behavior-driven mathematical models and forecasting systems for respiratory disease transmission in urban settings. Funded jointly by NSF's Division of Mathematical Sciences and Division of Social and Economic Sciences under the Biological Sciences program (CFDA 47.074), this research aims to incorporate...

This federal Project Grant award from the National Science Foundation's (NSF) Division of Mathematical Sciences (CFDA 47.049) provides $1,344,200 to the University of Vermont to develop mathematical epidemiological models that better represent the complexities of human behavior and social processes in disease dynamics. The project will focus on understanding respiratory diseases like COVID-19 and the flu, aiming to improve the ability to predict and respond to infectious disease outbreaks. Key...

This $223,001 National Science Foundation project grant supports research to develop novel predictive models of epidemic spread dynamics and validate those models against COVID-19 data. The award is made under the NSF Engineering program (CFDA 47.041) to support fundamental engineering research. Specifically, researchers at the University of Cincinnati will work collaboratively to: develop new predictive dynamic models based on partial differential equations; study the interaction of...

This $201,299 National Science Foundation project grant supports research to develop novel predictive models of epidemic spread dynamics and validate those models using COVID-19 data. The funding will be used to conduct fundamental research advancing the scientific understanding of how uncertainties in human behavior and pathogen characteristics influence spatial and temporal stochastic epidemic dynamics. Specific aims of the research include developing new predictive dynamic models based on...

This $600,000 project grant awarded by the National Science Foundation (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program aims to enhance influenza forecasting through an integrated platform for user-generated temporal forecasts. The project takes a participatory modeling approach to guide the construction of a human judgment platform that generates temporal forecasts of infectious disease trajectories. The key goals are to: 1) identify the factors and decision-making...

This $133,182 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) supports the development of new point-process algorithms for modeling infectious disease threats over varying temporal and spatial scales. Specifically, the funding will be used to derive expectation maximization algorithms to infer probabilistic transmission networks for contact tracing and outbreak source detection. Multivariate Hawkes processes will be formulated to...

This $2 million project grant from the National Science Foundation's Division of Computing and Communication Foundations supports the development of predictive modeling tools to aid pandemic prevention and response efforts. Funded under the Computer and Information Science and Engineering program, the 18-month award to Boston Children's Hospital will plan a future center-scale effort to address gaps in understanding and modeling pandemic potential, impact of interventions, and factors...