Project Grant R43AI167462
- This federal Project Grant award from the National Institute of Allergy and Infectious Diseases (NIAID), under the Allergy and Infectious Diseases Research CFDA program, aims to establish a framework for understanding and predicting viral dynamics at the community level. The $568,909 project will integrate wastewater surveillance, computational modeling, and genomic sequencing to address two key challenges: translating wastewater data into precise epidemiological insights, and leveraging this...
- This $100,000 Project Grant award from the National Science Foundation (NSF) Social, Behavioral, and Economic Sciences (SBE) program (CFDA 47.075) aims to integrate wastewater surveillance and human behavior data to enhance epidemiological modeling and outbreak detection. The principal investigators at Lawrence Technological University will pursue three main objectives: (1) developing an early-warning system using wastewater and digital/social behavior data, (2) creating a...
- This Project Grant award from the National Science Foundation (NSF) Directorate for Mathematical and Physical Sciences (CFDA 47.049) provides $249,313 to Lawrence Technological University to enhance dynamic population-level epidemiological models by incorporating wastewater surveillance data. The project aims to improve the estimation of true disease prevalence, enhance forecasting of future COVID-19 cases, and monitor the emergence and evolution of viral variants. Key activities include...
- This $649,896 federal Project Grant awarded by the U.S. Department of Agriculture's (USDA) National Institute of Food and Agriculture (NIFA) under the Agriculture and Food Research Initiative (AFRI) program supports the development and testing of an mRNA vaccine cocktail against influenza A viruses (IAV) in livestock. The project aims to create a universal influenza vaccine that can provide broad protection against diverse IAV strains, including highly pathogenic avian influenza (HPAI) H5N1...
- The University of Missouri System, under a $650,000 project grant from the USDA National Institute of Food and Agriculture (NIFA) Agriculture and Food Research Initiative (AFRI) program, is developing safe and effective live attenuated swine influenza vaccines using Newcastle disease virus (NDV) as the vector. The project aims to address the challenges with current swine influenza vaccines, which often fail to provide cross-protection against diverse virus strains. The key products and...
- This Cooperative Agreement award of $1,352,292 from the National Institute of Allergy and Infectious Diseases (NIAID), under the Allergy and Infectious Diseases Research program (CFDA 93.855), supports a research project to develop a high-resolution profiling and computational modeling framework for studying influenza virus-immune dynamics during natural infection. The project aims to address critical knowledge gaps in understanding the human immune response to influenza viruses, with the goal...
- 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 Project Grant award from the National Institute of Allergy and Infectious Diseases (NIAID), under the Allergy and Infectious Diseases Research federal grant program (CFDA 93.855), provides $147,486.00 to Emory University to develop novel methods for assessing the pandemic potential of influenza A viruses. The project aims to accomplish this through two approaches: 1) using data from animal transmission studies to estimate key epidemiological parameters like the basic reproduction number and...
- The National Institute of Allergy and Infectious Diseases (NIAID) awarded a $416,625 Project Grant under the Allergy and Infectious Diseases Research program (CFDA 93.855) to the University of Nevada, Las Vegas (UNLV) for the "Genomic Surveillance of Mpox Through the Development of a Wastewater Intelligence Model and Data Analytics Platform" project. The goal of this high-risk, high-reward proposal is to leverage UNLV's previous successful approaches in wastewater surveillance for...
- This $200,000 Project Grant from the National Science Foundation Division of Environmental Biology supports research investigating the uptake, persistence, and impact of behavioral interventions on respiratory viruses. Funded under the Biological Sciences program (CFDA 47.074), the Pennsylvania State University will model the dynamics of COVID-19 and influenza transmission considering behavioral changes mandated by public health interventions as well as voluntary individual behaviors....
IMPROVING INFLUENZA VACCINES THROUGH WASTEWATER-BASED MACRO-SCALE STRAIN SURVEILLANCE - ABSTRACT INFLUENZA INFECTS 9 TO 45 MILLION PEOPLE IN THE UNITED STATES EACH YEAR AND RESULTS IN 300,000 TO 500,000 DEATHS WORLDWIDE. VACCINATION IS THE FOUNDATION OF THE GLOBAL RESPONSE TO CONTROL AND REDUCE THE SPREAD OF INFLUENZA; HOWEVER, SEASONAL INFLUENZA VACCINE EFFICACY RANGED FROM NON-STATISTICALLY SIGNIFICANT TO 60% BETWEEN 2011 AND 2019.VACCINE EFFICACY IS LARGELY CONTINGENT UPON PROPERLY MATCHING STRAINS IN CIRCULATION TO THE STAINS SELECTED FOR INCLUSION IN THE SEASONAL VACCINE. HISTORY PROVIDES EXAMPLES OF MISMATCHES THAT RENDERED VACCINE INEFFECTIVE, THUS HIGHLIGHTING THE NEED TO REVISIT THE STRAIN SELECTION PARADIGM. IN DEPTH VIRAL SURVEILLANCE AND GENOMIC CHARACTERIZATION OF CIRCULATING STRAINS AND THE MONITORING OF VIRAL SPREAD DYNAMICS ACROSS GEOGRAPHIC AREAS THROUGHOUT THE YEAR ARE PARAMOUNT TO SELECT STRAINS WITH THE HIGHEST PROBABILITY OF CIRCULATION. HOWEVER, WITH THE CURRENT INFLUENZA SURVEILLANCE NETWORK, < 0.2% OF ALL INFLUENZA CASES IN THE UNITED STATES UNDERGO GENOMIC CHARACTERIZATION, MAKING IT HIGHLY POSSIBLE THAT A CIRCULATING STRAIN WOULD NOT BE CHARACTERIZED. ADDITIONALLY, THERE ARE SEVERAL INHERENT CHALLENGES WITHIN THE CURRENT SWAB-BASED SURVEILLANCE APPROACH THAT COULD BIAS THE DATA COMING OUT OF THIS PROGRAM AND THUS RESULT IN THE INCORRECT SELECTION OF VIRUSES FOR INCLUSION IN THE YEARLY VACCINE. TO IMPROVE VACCINE-STRAIN SELECTION, WE PROPOSE A MACRO-SCALE INFLUENZA AND SARS- COV-2 SURVEILLANCE APPROACH THROUGH MONITORING COMMUNITY WASTEWATER. NEARLY ALL COMMUNITY MEMBERS UNINTENTIONALLY PROVIDE THEIR WASTEWATER TREATMENT FACILITIES WITH REGULAR FECAL SAMPLES, AND BOTH SARS-COV-2 AND INFLUENZA HAVE BEEN SHOWN TO BE SHED IN HUMAN FECES. GT MOLECULAR ALREADY DEVELOPED AND DEPLOYED A STATE-OF-THE-ART VIRAL QUANTIFICATION METHODOLOGY FOR SARS-COV-2 IN WASTEWATER MONITORING USED BY OVER 100 COMMUNITIES AROUND THE COUNTRY. IN THE PROPOSED WORK, WE WILL EXPAND OUR WASTEWATER MONITORING CAPABILITIES TO INCLUDE (I) MONITORING INFLUENZA PREVALENCE, IN ADDITION TO SARS-COV-2, FOR OBSERVATION OF VIRAL SPREAD DYNAMICS ACROSS GEOGRAPHIC REGIONS (AIM 1) AND (II) PROVIDING MACROSCALE STRAIN SURVEILLANCE AND GENOMIC CHARACTERIZATION OF INFLUENZA AND SARS-COV-2 CIRCULATING STRAINS FOUND IN WASTEWATER (AIM 2). WE WILL ACHIEVE SPECIFIC AIM 1 THROUGH OPTIMIZATION OF OUR CURRENT SARS-COV-2 WORKFLOW FOR SIMULTANEOUS CONCENTRATION, EXTRACTION, AND QUANTIFICATION OF SARS-COV-2 AND INFLUENZA. WE WILL ACHIEVE SPECIFIC AIM 2 THROUGH OPTIMIZATION OF OUR PREVIOUSLY DESCRIBED TILED AMPLICON SEQUENCING APPROACH FOR GENOMIC CHARACTERIZATION OF VIRAL GENOMES IN WASTEWATER. MANY VACCINE EXPERTS EXPECT SARS-COV-2 TO BECOME ENDEMIC AND POTENTIALLY REQUIRE A SEASONAL VACCINE, LIKE INFLUENZA. THEREFORE, THIS WORK COULD SERVE AS A FOUNDATION FOR THE SURVEILLANCE OF BOTH VIRUSES, PROVIDING A ROBUST DATASET FOR INTERNATIONAL SURVEILLANCE PROGRAMS TO USE IN THEIR YEARLY STRAIN INCLUSION DISCUSSION AND DECISION MAKING.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $0 | 6/23/23 | ||
| Not listed | $0 | 6/7/22 | ||
| Not listed | $0 | 6/7/22 | ||
| Not listed | $0 | 6/7/22 | ||
| Not listed | $256.6k | 1/7/22 |