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: https://www.ghostery.com/fr/products/

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: http://www.youronlinechoices.com/fr/controler-ses-cookies/, 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

Realytics
Google Analytics
Spoteffects
Optimizely

Targeted advertising cookies

DoubleClick
Mediarithmics

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 cil-dpo@inra.fr or by post at:

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

Dernière mise à jour : Mai 2018

Menu Institut Sophia Agrobiotech Logo Marque Etat - République Française Logo_INRAE_noir Logo Université Côte d'Azur CNRS

Home page

Institut Sophia Agrobiotech

UMR INRA - Univ. Nice Sophia Antipolis - Cnrs

http://www.paca.inra.fr/institut-sophia-agrobiotech_eng/

Ecological Modelling

06 June 2018

Ecological Modelling
© 2018 Elsevier B.V.
Between-group pathogen transmission: From processes to modeling

Abstract

Pathogen transmission is a key process in epidemiology and its mathematical form plays a pivotal role when modeling pathogen spread. Much work has been devoted to the transmission function applied to a homogeneous population structure. However, between-group transmission functions, required when different groups are identified to account for a distinct epidemiological risk, are much less documented. The aim of this study is to detail the mathematical form of five between-group transmission functions and to assess its influence on predictions in epidemiological modeling. Simulations with a two-group model were carried out so as to generate prediction differences among between-group transmission functions for a large range of situations, defined by the within-group transmission pattern, the basic reproduction number, the proportion of the whole transmission due to between-group transmission and the ratio of population sizes. Pathogen spread simulations highlighted differences in prevalence among four transmission functions (frequency-dependent, density-dependent and functions representing either a temporary mixing or a proportion of visitors exposed to infectious individuals). The differences could be seen either in long-term or in transient simulated dynamics. The fifth one, representing limited interactions at a gate, was shown to be equivalent to the density-dependent function in our parametrization when keeping constant group sizes. When considering population dynamics, particularly with increasing group sizes, this function and the density-dependent one were shown to behave opposite from each other and to differ from the other functions. This work highlights the need to carefully define the between-group transmission function when modeling pathogen spread in a heterogeneous structure. Our work brings insight into the biological grounds that could guide the choice of such a function.

Keywords

  • Epidemiology; 
  • SIR model; 
  • Heterogeneous population; 
  • Transmission; 
  • Population dynamics

Hoch, T., Touzeau, S., Viet, A.-F., and Ezanno, P. (2018). Between-group pathogen transmission: From processes to modeling. Ecological Modelling 383, 138–149. DOI: 10.1016/j.ecolmodel.2018.05.016

Site : View online >>