Tracking the spread of avian influenza viruses in live bird market networks

Grant number: 101116387

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Key facts

  • Disease

    Unspecified
  • Start & end year

    2024
    2029
  • Known Financial Commitments (USD)

    $1,605,115.81
  • Funder

    European Commission
  • Principal Investigator

    Claire GUINAT
  • Research Location

    France
  • Lead Research Institution

    INSTITUT NATIONAL DE RECHERCHE POUR L'AGRICULTURE, L'ALIMENTATION ET L'ENVIRONNEMENT
  • Research Priority Alignment

    N/A
  • Research Category

    Epidemiological studies
  • Research Subcategory

    Disease surveillance & mapping
  • Special Interest Tags

    N/A
  • Study Type

    Non-Clinical
  • Clinical Trial Details

    N/A
  • Broad Policy Alignment

    Pending
  • Age Group

    Not Applicable
  • Vulnerable Population

    Not applicable
  • Occupations of Interest

    Not applicable

Abstract

Avian influenza viruses (AIV) represent tenacious and major public and animal health problems across the world. Controlling AIV at its poultry source in Asia is essential to decrease the virus load in susceptible avian species and environment, limit the risk of human infection with AIV and minimize the risk for future global AIV pandemics. In TrackFLU, I will improve our capacity to quantify, model and predict the AIV spread in live bird market (LBM) networks in Asia, which are urgently needed if the impact of future epidemics of AIV is to be mitigated and thus, represent key elements for pandemic preparedness. For the first time, extensive field work will be combined with state-of-the-art network analysis, phylodynamic and disease modelling tools with the view to successfully influence policy-making. I will use this unique and innovative analytical pipeline to address the following key objectives: O1) Identify the factors shaping the connectivity of LBM networks, O2) Quantify the transmission dynamics of AIV in LBM networks and O3) Optimize strategies to limit AIV spread in LBM networks. TrackFLU will help us to disentangle the LBM networks' connectivity and to resolve the AIV transmission dynamics in LBM networks. TrackFLU will result in a cutting-edge predictive model of AIV spread that incorporates, for the first time, most of the biological complexities of AIV spread in LBM networks in Asia. The model and its associated web-application will represent very powerful and innovative tools for the design of novel control strategies tailored to the key features of AIV transmission in LBM networks. TrackFLU will thus contribute to the active research issue of improving capacity to predict AIV transmission in these complex systems in Asia, hence addressing the unmet need of local stakeholders and decision makers for better predictive tools. With TrackFLU, I anticipate very promising results, with huge impacts on animal and public health.