PhD project: Modelling avian influenza virus transmission along poultry production and distribution networks

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INRAE presentation

The French National Research Institute for Agriculture, Food, and Environment (INRAE) is a major player in research and innovation. It is a community of 12,000 people with 272 research, experimental research, and support units located in 18 regional centres throughout France. Internationally, INRAE is among the top research organisations in the agricultural and food sciences, plant and animal sciences, as well as in ecology and environmental science. It is the world’s leading research organisation specialising in agriculture, food and the environment. INRAE’s goal is to be a key player in the transitions necessary to address major global challenges. Faced with a growing world population, climate change, resource scarcity, and declining biodiversity, the Institute has a major role to play in building solutions and supporting the necessary acceleration of agricultural, food and environmental transitions.

Work environment, missions and activities

The intensification of livestock production is a major factor influencing the emergence of zoonotic pathogens. In many settings, this process creates a complex mosaic of animal production and distribution modes. Yet, the ways in which the resulting networks – through which animals are raised, traded and consumed – shape pathogen transmission and persistence remain poorly understood. This is particularly true in regions at high risk of disease emergence, such as Bangladesh, where poultry production is rapidly intensifying and multiple avian influenza virus (AIV) lineages, including highly pathogenic H5N1, circulate endemically.

This PhD project aims to explore how the structure of poultry production and distribution networks influence AIV transmission dynamics, and to assess the effectiveness of structural interventions to mitigate disease risk. The successful candidate will develop mechanistic models and apply a novel modelling framework, EPINEST, to simulate the spread of AIVs in Bangladesh. The project will leverage extensive datasets on network structure, viral prevalence and genetic sequences. A key focus will be the integration of phylodynamic analysis to inform the mechanistic models, linking viral genomic data to transmission patterns. Control strategies altering the network structure will be simulated and their impact of AIV transmission risk will be explored.

The PhD student will be primarily based in the EPIA unit (EPIdémiologie des maladies Animales et zoonotiques), on the VetAgroSup campus near Lyon, France, and collaborate closely with the Royal Veterinary College (United Kingdom), Chattogram Veterinary and Animal Science University and the Bangladesh Livestock Research Institute (Bangladesh). The position will involve on-site visits at the Royal Veterinary College.

Through this PhD programme, the student will develop robust skills in mechanistic modelling and phylodynamic analyses. Furthermore, as part of an international collaboration, the candidate will thrive in a stimulating interdisciplinary environment. This setting will not only enhance their research skills but also broaden their professional network and expose them to diverse scientific perspectives and methodologies.

References:

Pinotti et al (2024) EPINEST, an agent-based model to simulate epidemic dynamics in large-scale poultry production and distribution networks. PLOS Computational Biology, 20(2):e1011375

Pinotti F et al (2024) Modelling the transmission dynamics of H9N2 avian influenza viruses in a live bird market. Nature Communications, 15(1):3494.

Carnegie et al (2023) H9N2 avian influenza virus dispersal along Bangladeshi poultry trading networks. Virus Evolution, 9(1):vead014.

Training and skills

Completion of a postgraduate degree, or at least an undergraduate degree, in epidemiology, network science, biostatistics, computational biology, mathematics, physics, or another relevant quantitative discipline.

Proficiency in both written and spoken English.

Willingness to supervise research degree students, and to be able to work as part of a multidisciplinary team.

Knowledge in mathematical modelling, a prior experience in quantitative analyses and in modelling the spread of infectious diseases would be an asset, as well as proficiency in R and/or a computer programming language such as C/C++ or Python.

INRAE's life quality

By joining our teams, you benefit from (depending on the type of contract and its duration):

- up to 30 days of annual leave + 15 days "Reduction of Working Time" (for a full time);
- parenting support: CESU childcare, leisure services;
- skills development systems: training, career advise;
- social support: advice and listening, social assistance and loans;
- holiday and leisure services: holiday vouchers, accommodation at preferential rates;
- sports and cultural activities;
- collective catering.

How to apply

I send my CV and my motivation letter