Advancing Risk Modeling for Highly Pathogenic Avian Influenza
Southeast Asia has long been the epicenter of AIV emergence. However, as demonstrated by H5NX, these viruses can quickly reach global spread and have significant impacts on poultry production and human health. Researchers at the USGS Eastern Ecological Science Center have two ongoing efforts funded by the National Science Foundation to help improve our understanding of AIV emergence, spread, and transmission in today’s rapidly changing landscape.
Outbreaks of highly pathogenic avian influenza in China and many parts of the world in the past two decades have caused substantial economic damages in poultry production and trade and posed significant threats to public health. These viruses have shown a high capacity for international spread, indicating a need to understand viral dynamics at the forefront of emergence to better prepare the world as potential new challenges emerge. However, data on the diversity and transmission of human- and animal-infected AI viruses (both highly pathogenic and low pathogenic AI viruses) in China remains scattered, limited, and incomplete, which substantially hinders development of advanced capacity towards prediction and forecasting of diversity and transmission dynamics of AI viruses. To help improve understanding of the underlying dynamics of viral spread and persistence, and subsequently prediction and forecasting capacities, we have two ongoing efforts funded by the National Science Foundation.
Our first project, a part of the NSF Ecology and Evolution of Infectious Diseases program, assembles an international and multidisciplinary team from China and USA to explore diversity and transmission dynamics of AI viruses in China since early 1980s and understand how large-scale landscape changes are impacting the disease transmission interface. This work has a particular focus on the East Asian-Australasian Flyway, but due to the global threat posed by avian influenza, has implications for the entire globe.
This project is organized into four sets of specific objectives and tasks:
- use the One-Health approach to identify and document diverse and relevant driving factors of AI viruses at the human-animal-environment interface and the Big Data approach to harness and improve disparate geospatial datasets of AI viruses and driving factors,
- use phylogenetic and phylogeographic models to investigate the diversity of AI viruses,
- combine spatial-temporal statistical and mathematical models to better understand and predict transmission dynamics of AI viruses over time and space, and
- work with China CDC and other stakeholders, and incorporate the resultant data and models to support their efforts in disease surveillance, control, and prevention.
Our second ongoing effort, part of the Predictive Intelligence for Pandemic Prevention Phase I grants, focuses on leveraging the international collaborations formed in our first project to explore the appropriate pathways for setting-up an International Center for Avian Influenza Pandemic Prediction and Prevention. This center will look to tackle the grand problem of avian influenza pandemic risk by scaling many of the lessons learned in our first project to include broader spatial distributions and leveraging additional data and collaborators. This center will also emphasize a structured decision-making approach to develop decision support systems and tools and predict their effectiveness for surveillance and intervention of AIV evolution, spillover, and transmission. The center will be focused on prediction and prevention of AIV pandemic in Eurasia and its potential linkage and risk with North America.
<< Back to Avian Influenza Research at EESC
Southeast Asia has long been the epicenter of AIV emergence. However, as demonstrated by H5NX, these viruses can quickly reach global spread and have significant impacts on poultry production and human health. Researchers at the USGS Eastern Ecological Science Center have two ongoing efforts funded by the National Science Foundation to help improve our understanding of AIV emergence, spread, and transmission in today’s rapidly changing landscape.
Outbreaks of highly pathogenic avian influenza in China and many parts of the world in the past two decades have caused substantial economic damages in poultry production and trade and posed significant threats to public health. These viruses have shown a high capacity for international spread, indicating a need to understand viral dynamics at the forefront of emergence to better prepare the world as potential new challenges emerge. However, data on the diversity and transmission of human- and animal-infected AI viruses (both highly pathogenic and low pathogenic AI viruses) in China remains scattered, limited, and incomplete, which substantially hinders development of advanced capacity towards prediction and forecasting of diversity and transmission dynamics of AI viruses. To help improve understanding of the underlying dynamics of viral spread and persistence, and subsequently prediction and forecasting capacities, we have two ongoing efforts funded by the National Science Foundation.
Our first project, a part of the NSF Ecology and Evolution of Infectious Diseases program, assembles an international and multidisciplinary team from China and USA to explore diversity and transmission dynamics of AI viruses in China since early 1980s and understand how large-scale landscape changes are impacting the disease transmission interface. This work has a particular focus on the East Asian-Australasian Flyway, but due to the global threat posed by avian influenza, has implications for the entire globe.
This project is organized into four sets of specific objectives and tasks:
- use the One-Health approach to identify and document diverse and relevant driving factors of AI viruses at the human-animal-environment interface and the Big Data approach to harness and improve disparate geospatial datasets of AI viruses and driving factors,
- use phylogenetic and phylogeographic models to investigate the diversity of AI viruses,
- combine spatial-temporal statistical and mathematical models to better understand and predict transmission dynamics of AI viruses over time and space, and
- work with China CDC and other stakeholders, and incorporate the resultant data and models to support their efforts in disease surveillance, control, and prevention.
Our second ongoing effort, part of the Predictive Intelligence for Pandemic Prevention Phase I grants, focuses on leveraging the international collaborations formed in our first project to explore the appropriate pathways for setting-up an International Center for Avian Influenza Pandemic Prediction and Prevention. This center will look to tackle the grand problem of avian influenza pandemic risk by scaling many of the lessons learned in our first project to include broader spatial distributions and leveraging additional data and collaborators. This center will also emphasize a structured decision-making approach to develop decision support systems and tools and predict their effectiveness for surveillance and intervention of AIV evolution, spillover, and transmission. The center will be focused on prediction and prevention of AIV pandemic in Eurasia and its potential linkage and risk with North America.
<< Back to Avian Influenza Research at EESC