Postdoctoral position in mathematical/statistical modelling of animal infectious diseases in Paris

Environment

The Epidemiology Unit at the French Agency for Food, Environmental and Occupational Health and Safety (ANSES, www.anses.fr) is one of the four research units of the Laboratory for Animal Health (LSAn, www.anses.fr/en/content/maisons-alfort-laboratory-animal-health), and is directed by Dr Benoit Durand.

The research focus of the unit is to contribute to the understanding of the mechanisms of emergence, re-emergence and spread of major animal infectious diseases, through the development of mathematical, statistical and simulation models, and to use these models to design, evaluate and/or optimize surveillance and control systems.

Our primary focus is the study of infectious disease dynamics, detection, surveillance and control. The studied diseases are major animal health risks (e.g. foot and mouth disease [FMD]) and/or zoonotic diseases (e.g. bovine tuberculosis [bTB]). Some are directly-transmitted and other are vector-borne (e.g. bluetongue or West Nile fever). Our work benefits from strong collaborations with reference laboratories (hosted by LSAn) and with the French platform for epidemiological surveillance. We also collaborate with other centres of excellence in epidemiological modelling. Our approach is therefore highly multidisciplinary, looking at infectious diseases through multiple perspectives (epidemiology, surveillance, control, policy making, microbiology), multiple scales and multiple data streams.

Job description

The postdoc will develop real-time modelling tools that can be deployed during epizooties (bluetongue, bTB and/or FMD) to advice on optimal surveillance and control strategies.

The detection and control of major farm animal infectious diseases are supported by state, and defined by regulations at the Community and national levels. When epizootic occur, the public decision-maker has however to choose between several strategies (e.g. organizing a mass vaccination campaign against FMD or not). The relevant choice depends on the severity of the epizootic and on the available human and material resources. The postdoc will use observational data (bluetongue, bTB) and simulated data (FMD) to design and evaluate real-time modelling tools for a quick assessment of an epizootic trend under several detection and control scenarios.

Short-term planning of control measures is a key problem for decision-makers both at the local level (prevision of work load and of the needed material resources –e.g. vaccine) and at the national level (mutualisation of resources between regions). The postdoc will use the real-time modelling tools to propose short-term prevision of likely resource needs (both human and material).

The efficacy of real-time modelling critically depends on the data available in near real-time, and on the quality of these data. Besides possible control measures, regulations concerning major farm animal infectious diseases often define measures for disease detection, such as serosurveys or outbreak investigations in infected premises. In a context of limited resources, the public decision-maker has to distribute these resources between control tasks and detection tasks, the latter being often neglected. Based on simulation tools (already existing for FMD and bTB, under development for Bluetongue), the postdoc will investigate how the nature, amount and quality of epidemiological data impact the relevance of short-term predictions produced by real-time modelling tools.

Public decision-makers (from the agriculture ministry) will be involved in this work with the aim of incorporating more explicitly data collection in regulations and emergency plans.

 

The postdoc will be supervised by Benoit Durand (ANSES) and Simon Cauchemez (Institut Pasteur). She/he will be expected to use state-of-the-art statistical methodology that may involve Markov Chain Monte Carlo Sampling (MCMC), Sequential Monte Carlo sampling, Particle MCMC, Approximate Bayesian Computation or tree reconstruction techniques.

 

This proposal is part of a larger project that aims to strengthen the contribution of modelling in the detection, monitoring and management of epidemics in human and animal in France. Overall, three postdocs will be recruited to develop such approaches in a partnership between three leading French Institutions on health related issues (ANSES, ANSP and Institut Pasteur).

Applicants will be given a one-year contract with possibility to extend it for another 2 years, should both parties agree. 3

 

Interested candidates should contact email Ana de Casas (ana.de-casas@pasteur.fr) with a CV, statement of interest and two references (to be sent directly by referees).

Closing date

The deadline for applications is 7 November 2016.

Location

The postdoc will be primarily based at ANSES but will also spend a small proportion of his/her time at Institut Pasteur.

  • Unité Epidémiologie des maladies animales infectieuses, ANSES, 14 rue Pierre et Marie Curie, 94700 Maison-Alfort.
  • Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, 28 rue du Docteur Roux, 75724 Paris Cedex 15, France.

Requirements

  • Research experience of working with mathematical and/or statistical models.
  • A strong interest in infectious disease epidemiology.
  • Ability to collate and analyse data, interpret and present results to a high standard using a range of specialised research techniques.
  • Programming experience in C, C++ or Java.
  • Knowledge of a statistical programming language (preferably R).
  • Excellent verbal and written communication skills.
  • Experience in communicating research findings to a non-specialist audience.
  • Ability to work independently but also as part of a larger interdisciplinary research team.
  • PhD in one of the following areas: infectious disease epidemiology, mathematics, statistics, physics, computer science, population biology or a similarly quantitative discipline.