Understand the dynamics of Highly Pathogenic Avian Influenza (HPAI) through integrative modelling approaches.

  • Funded by Canadian Institutes of Health Research (CIHR)
  • Total publications:0 publications

Grant number: 507229

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Key facts

  • Disease

    Influenza caused by Influenza A virus subtype H5
  • start year

    2024
  • Known Financial Commitments (USD)

    $109,549.84
  • Funder

    Canadian Institutes of Health Research (CIHR)
  • Principal Investigator

    Nasri Bouchra, Ma Junling
  • Research Location

    Canada
  • Lead Research Institution

    Université de Montréal
  • Research Priority Alignment

    N/A
  • Research Category

    Pathogen: natural history, transmission and diagnostics

  • Research Subcategory

    Pathogen genomics, mutations and adaptations

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

Although highly pathogenic avian influenza (HPAI) H5N1 is primarily avian in origin, with limited human infections and no evidence of human-to-human transmission, avian influenza viruses (AIV) are becoming a growing threat to wildlife, livestock, and human health. Recent viral adaptations have been found in various mammals as well as cattle in the United States. These outbreaks in cattle have been linked to some human cases, raising concerns about the potential zoonotic risk of HPAI in humans. While cattle infections and human transmission events have not been observed in Canada, the risk remains because infections on farms tend to lead to herd immunity which influences viral evolution. Using a One Health-based approach, the team will collaborate with a range of multi-sector organizations in Canada and internationally to use critical data on HPAI detection in domestic and wild birds, genomics, and HPAI cases. In addition, we will leverage non-traditional data such as social media for near real-time early warning signals of HPAI transmission through artificial intelligence techniques. Finally, using an integrative modelling approach, we will assess the risk of wild bird spillover and transmission within and between poultry and livestock farms, and monitor the emergence of new HPAI strains. Our comprehensive approach aims to establish a robust surveillance system for HPAI and improve strategies for its effective control. By providing policymakers with practical tools, our project aims to prevent and mitigate HPAI outbreaks.