Tracking the spread of avian influenza viruses in live bird market networks
- Funded by European Commission
- Total publications:0 publications
Grant number: 101116387
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Key facts
Disease
UnspecifiedStart & end year
20242029Known Financial Commitments (USD)
$1,605,115.81Funder
European CommissionPrincipal Investigator
Claire GUINATResearch Location
FranceLead Research Institution
INSTITUT NATIONAL DE RECHERCHE POUR L'AGRICULTURE, L'ALIMENTATION ET L'ENVIRONNEMENTResearch Priority Alignment
N/A
Research Category
Epidemiological studiesResearch Subcategory
Disease surveillance & mappingSpecial Interest Tags
N/AStudy Type
Non-ClinicalClinical Trial Details
N/ABroad Policy Alignment
PendingAge Group
Not ApplicableVulnerable Population
Not applicableOccupations 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.