Project Grant 2527286
- The University of Connecticut received a $149,999 Project Grant award from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) to develop and use mathematical models and computational methods, including novel Math-Model Informed Neural Networks (MINN), to study climate-dependent mosquito-dengue biology. The project aims to (A) develop MINN models capturing emerging mathematics in mosquito-dengue biology, (B) analyze models and develop MINN-based methods...
- This National Science Foundation (NSF) Directorate for Mathematical and Physical Sciences (CFDA 47.049) Project Grant of $246,620 awarded to The University of Texas at San Antonio (UTSA) will fund the development of novel mathematical models for Wolbachia-based strategies to control mosquito-borne diseases like dengue fever, malaria, chikungunya, and Zika. The multi-stage models will account for the complex transmission dynamics, spatial and temporal heterogeneity, and Wolbachia's biological...
- This $130,064 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports collaborative research to develop new statistical algorithms for analyzing spatiotemporal data on vector-borne disease transmission, using dengue virus in Rio de Janeiro as a case study. The project aims to address methodological challenges in modeling complex, nonlinear, and partially-observed spatial-temporal systems, with the goal of...
- This National Science Foundation (NSF) Project Grant award, funded under the Social, Behavioral, and Economic Sciences program (CFDA 47.075), aims to investigate the role of human behavior in the dynamics of mosquito-borne diseases such as dengue and Zika. The $100,000 grant, awarded to North Carolina State University (NC State), will support a multidisciplinary research project to understand how individual decision-making around mosquito prevention behaviors impacts disease transmission. The...
- This Project Grant award from the National Science Foundation (CFDA 47.049 - Mathematical and Physical Sciences) will develop an early-warning system to forecast surges in disease-carrying mosquito populations in the United States. The $300,000 award, effective September 1, 2025 through August 31, 2028, will create modeling tools and ensembling approaches to generate 1- to 4-week ahead forecasts of the relative abundance of Aedes aegypti and Aedes albopictus mosquitoes. The forecasts will be...
- The National Science Foundation (NSF) awarded a 5-year, $977,779 Project Grant under the Biological Sciences (CFDA 47.074) program to the University of California, Santa Barbara (UCSB) to investigate how climate change and land use shifts may impact the synchronization between mosquito vectors and bird hosts, and the implications for West Nile Virus transmission. The research will leverage a combination of modeling, causal inference, citizen science, and field data collection to understand how...
- This $174,544 Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the University of North Carolina at Charlotte in developing a novel, integrated geospatial framework that applies advanced machine learning techniques to map disease transmission risk from mosquito-borne illnesses. The project will process high-resolution satellite imagery, population data, and other geospatial inputs to generate...
- The National Science Foundation (NSF) Division of Environmental Biology awarded a $283,164 Project Grant to the University of North Carolina at Greensboro (UNC-G) to develop physiology-based mechanistic models to forecast the responses of sand fly vector species to coarse-scale environmental changes like climate change, as well as fine-scale changes from land use modifications. The project aims to (1) determine the physiological parameters that influence the geographical spread and...
- This Project Grant award from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) supports research to accurately quantify recurring seasonal effects in ecological models. The $247,495 award to Texas Tech University System will develop mathematical approaches to represent the complex interactions between short-term and seasonal behaviors in ecosystems, with a focus on assessing the identifiability of model parameters and their ability to match real-world...
- The University of California, San Diego (UCSD) was awarded a $500,000 Project Grant from the National Science Foundation (NSF) Division of Integrative Organismal Systems under the Biological Sciences (CFDA 47.074) federal grant program. Through this three-year award beginning June 1, 2023, UCSD will investigate olfactory learning and neuromodulation in the Aedes aegypti mosquito vector. The research aims to elucidate the role of dopamine-mediated plasticity in early olfactory circuits and how...
This Project Grant award from the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) federal grant program provides $200,000.00 to San Diego State University Foundation to develop and use mathematical models and computational methods, including novel Math-Model Informed Neural Networks (MINN), to study the climate-dependent biology of mosquitoes and the transmission of dengue. The project aims to: (A) develop MINN models capturing emerging mathematics in mosquito-dengue biology, (B) analyze models and develop MINN-based methods to estimate epidemic thresholds, and (C) develop MINN-based user-friendly online platforms for public health policy evaluations and healthcare accessibility. The project will validate the novel models using data from collaborators in Nepal and incorporate an experimentally observed mosquito life cycle and dengue transmission. The outcomes will advance the fields of mathematical biology and quantitative biology while also having a broad, positive societal impact through improved management guidelines to mitigate the burden of dengue infection.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $200.0k | 7/29/25 |