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Research Spending & Results

Award Detail

Awardee:UNIVERSITY OF MISSOURI SYSTEM
Doing Business As Name:University of Missouri-Columbia
PD/PI:
  • Xiu-Feng H Wan
  • (573) 882-8943
  • wanx@missouri.edu
Co-PD(s)/co-PI(s):
  • Michael E Emch
  • Richard J Webby
Award Date:06/22/2021
Estimated Total Award Amount: $ 2,499,991
Funds Obligated to Date: $ 1,999,992
  • FY 2021=$1,999,992
Start Date:09/01/2021
End Date:08/31/2026
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.074
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:US-China Collab: Comparative evolution and ecology of swine influenza viruses in China and the United States
Federal Award ID Number:2109745
DUNS ID:153890272
Parent DUNS ID:006326904
Program:Ecology of Infectious Diseases
Program Officer:
  • Katharina Dittmar
  • (703) 292-7799
  • kdittmar@nsf.gov

Awardee Location

Street:115 Business Loop 70 W
City:COLUMBIA
State:MO
ZIP:65211-0001
County:Columbia
Country:US
Awardee Cong. District:04

Primary Place of Performance

Organization Name:University of Missouri-Columbia
Street:115 Business Loop 70 W
City:COLUMBIA
State:MO
ZIP:65211-0001
County:Columbia
Country:US
Cong. District:04

Abstract at Time of Award

Influenza A viruses are responsible for substantial human morbidity and mortality and continue to present an overwhelming public health challenge. It has been proposed that pigs are intermediate host “mixing vessels” that generate pandemic influenza strains through genetic reassortment among avian, swine, and/or human influenza viruses. Although evolutionary events (i.e., reassortment and mutations) have been routinely detected in swine population, it is not yet clear which are typical, which are atypical, which evolutionary events for these influenza viruses increase threats to human and animal health, and which ecological and evolutionary principals are driving such events. The overall goal of this study is to develop and apply interdisciplinary approaches to study and compare the evolution and ecology of swine influenza A viruses through synergistic studies in China and the US, the two largest pork producing countries on the planet, by assembling an international and multi-disciplinary team. Specifically, this project will 1) identify and determine the evolutionary dynamics of novel swine influenza viruses in swine populations in the two countries through influenza surveillance and advanced evolutionary analyses, 2) determine unique, common, and synergistic ecological drivers through geospatial modeling and machine learning, and 3) develop an influenza risk assessment tool using Big Data and Artificial Intelligence. This project will train graduate, undergraduate, veterinary, and medical students in interdisciplinary research skills for studying evolutionary biology, disease ecology, epidemiology, geospatial modeling, Big Data, and AI. Through internship and outreach activities, this project will also educate the public and non-academic stakeholders on ecology and evolution and transmission of infectious diseases, which may lead to the optimization of swine industry management and changes in human behaviors that could reduce the influenza evolutionary events in pigs, disease transmission among pig populations, and spillover of swine influenza virus to humans. This study will illustrate the evolutionary dynamics of swine influenza viruses leading to enhanced zoonotic and pandemic risk and identify atypical evolutionary events by defining a baseline for influenza prevalence and evolution. It is expected that ecological drivers associated with emergence and spread of novel swine influenza viruses within swine populations and at the animal-human interface will be identified. In addition, data from two unique but linked ecological settings will be integrated using an interdisciplinary approach to facilitate the comprehensive understanding of the evolution and ecology of influenza A viruses within swine populations and at the animal-human interface. Furthermore, Big Data and AI-based computational tools will be developed and shared to advance computational methods linking medical, veterinary, social, and environmental sciences, enhancing our ability to respond to emerging and reemerging infectious diseases. This study aims to facilitate our understanding of the natural history of influenza viruses and advance ecological theories for influenza viruses. The knowledge from this study will help inform and optimize policies and countermeasures for influenza pandemic preparedness. 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.

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