Know more

Our use of cookies

Cookies are a set of data stored on a user’s device when the user browses a web site. The data is in a file containing an ID number, the name of the server which deposited it and, in some cases, an expiry date. We use cookies to record information about your visit, language of preference, and other parameters on the site in order to optimise your next visit and make the site even more useful to you.

To improve your experience, we use cookies to store certain browsing information and provide secure navigation, and to collect statistics with a view to improve the site’s features. For a complete list of the cookies we use, download “Ghostery”, a free plug-in for browsers which can detect, and, in some cases, block cookies.

Ghostery is available here for free:

You can also visit the CNIL web site for instructions on how to configure your browser to manage cookie storage on your device.

In the case of third-party advertising cookies, you can also visit the following site:, offered by digital advertising professionals within the European Digital Advertising Alliance (EDAA). From the site, you can deny or accept the cookies used by advertising professionals who are members.

It is also possible to block certain third-party cookies directly via publishers:

Cookie type

Means of blocking

Analytical and performance cookies

Google Analytics

Targeted advertising cookies


The following types of cookies may be used on our websites:

Mandatory cookies

Functional cookies

Social media and advertising cookies

These cookies are needed to ensure the proper functioning of the site and cannot be disabled. They help ensure a secure connection and the basic availability of our website.

These cookies allow us to analyse site use in order to measure and optimise performance. They allow us to store your sign-in information and display the different components of our website in a more coherent way.

These cookies are used by advertising agencies such as Google and by social media sites such as LinkedIn and Facebook. Among other things, they allow pages to be shared on social media, the posting of comments, and the publication (on our site or elsewhere) of ads that reflect your centres of interest.

Our EZPublish content management system (CMS) uses CAS and PHP session cookies and the New Relic cookie for monitoring purposes (IP, response times).

These cookies are deleted at the end of the browsing session (when you log off or close your browser window)

Our EZPublish content management system (CMS) uses the XiTi cookie to measure traffic. Our service provider is AT Internet. This company stores data (IPs, date and time of access, length of the visit and pages viewed) for six months.

Our EZPublish content management system (CMS) does not use this type of cookie.

For more information about the cookies we use, contact INRA’s Data Protection Officer by email at or by post at:

24, chemin de Borde Rouge –Auzeville – CS52627
31326 Castanet Tolosan CEDEX - France

Dernière mise à jour : Mai 2018

Menu Logo Principal Oniris

Home page

Beaunée Gaël

Mechanistic multiscale modeling of the spread of Mycobacterium avium subsp paratuberculosis to assess control strategies at a regional scale

Abstract :

Animals trade movements form complex and dynamic networks of contacts between herds, and are the major mechanism of pathogens spread. Bovine paratuberculosis, due to Mycobacterium avium subsp. paratuberculosis (Map), is a widespread endemic disease, transmitted among cattle through trade movements of undetected infected animals. This disease with a strong economic impact induces production losses and premature culling. This chronic disease is characterized by a long incubation period and poorly sensitive screening tests. Therefore, field observation of Map spread is barely possible and its control remains a major challenge. The objective of this thesis is to better understand the spread of Map at a regional scale using a modeling approach, and compare control strategies combining internal and external biosecurity measures. Our model is the first multiscale mechanistic model of Map spread between dairy cattle
herds, considering stochastic intra-herd dynamics (demography and infection), explicit indirect transmission, and heterogeneity of herds characteristics and livestock trade movements based on field data. Our results provide the essential foundation for a better understanding of Map spread in an endemic area, highlighting the importance of wholesalers holdings. Applied to the Britanny region, the model allows the assessment of the effectiveness of a large panel of control measures used alone and in combination, highlighting the key role of calf management. Using Bayesian inference from epidemiological data allowed to inform on the risk of introducting an infected animal through animal purchase and the within-herd transmission rate. The effectiveness of controlling Map will depend on an efficient coordination of interventions and available diagnostic tools.

Key words :

Epidemiological model, multiscale modeling, metapopulation, contact network, Bayesian inference, paratuberculosis, Mycobacterium avium subsp. paratuberculosis, control strategies