Two PhD theses on Modernet topics from Grenoble

Two PHD students from Grenoble university who have previously attended Modernet conferences and presented part of their work will have their “viva voce” on the 12th and 13th of November 2015: Best wishes to Delphine Rieutort (exposomes) and Marie Delaunay (GIS). Lode Godderis will be on the jury. Please find the email addresses below for those who want to send encouragement.

Delphine Rieutort Delphine.Rieutort@imag.fr

Exposomes et Fonctions Expertes pour la Surveillance et la Détection des Evènements Emergents dans le Réseau National de Vigilance et de Prévention des Pathologies Professionnelles (RNV3P)

Exposomes and « expert functions » for the surveillance and detection of emerging events within the French national network for occupational diseases and prevention (rnv3p)

Abstract

Impact of population on the environment, and conversely, is obvious and represents a real challenge for Public Health since 2000. It has been shown an increase in cancer prevalence, respiratory disease or even reproductive disorders, for which multifactorial origins are strongly suspected. In this context, surveillance has become an essential tool to decision making in public health, and surveillance networks of health events are multiplying, giving rise to numerous databases (sometimes considered as “big data”), still poorly used.

Objective of this thesis work was to develop a new concept of surveillance, the Observational Surveillance (OS). This allows an optimal use of observational databases, extendable to different kind of databases and problematics, taking into account various multiple information available. OS is based on the exposome approach, to restructure data as a network, allowing the study of associations between information and also their structure. In this purpose, several indicators have been developed to study in the meantime the different recruited association for an event of interest, but also the evolution of their structure over time. These indicators allow generating the unique signature of the event: the spectrum.

A tool, named “Observational Surveillance Analysis” (OSA), allowing the routine use of methodology, has been developed in the R platform, which permits automation and standardization of results. Applications were used to illustrate the OS analysis and its portability and adaptability to different context and problematic. Three applications are based on the French National Occupational Diseases Surveillance and Prevention Network (RNV3P): bladder cancer, asthma and non-Hodgkin lymphoma. Three other applications are based on the Belgium occupational physicians group IDEWE: sore throat, caregivers and farmers. Thanks to different applications, it has been demonstrated the portability of the OS methodology to different databases, and also, to different analysis configuration, disease/exposures or activity/diseases. Furthermore, the “OSA” tool which has been developed, allows an easier use to routine analysis and, in the end, could be integrated in an existing surveillance network.

Keywords: Observational surveillance, exposome, database, R, multiple information

Marie Delaunay marie.delaunay@imag.fr

Approche géographique appliquée au Réseau National de Vigilance et de Prévention des Pathologies Professionnelles (RNV3P).

Geographical approach of the French national network for occupational diseases and prevention (rnv3p)

Abstract

The field of occupational health is complex because it combines many different types of data (activity sector, occupations, risk exposures, diseases), available at nested scales (communes, activity territories, employment areas, regions, etc.) and from different partners (insurers, stakeholders, monitoring systems). These multiple sources of additional data, formalized or not, are always analyzed independently, ignoring in particular the geographic dimension associated therewith (underlying activities territories).

The aim of our work is to consider one of these data sources, the rnv3p (French National Occupational Diseases Surveillance and Prevention Network), as a spatial object. Through different methods (explained Part 1) and geomatics tools, and taking into account the underlying workforce, it is primarily a description of the network in terms of recruitment, shadow and preferential recruitment areas that is made (Part 2).

Secondly, it is the confrontation of this database to other data sources describing occupational diseases (especially compensated one) which is analyzed through approaches by industry and pathology (Part 3). Finally, recommendations regarding the development of a mapping tool, built for the rnv3p database for vigilance purposes and helping various occupational health stakeholders, were made (Part 4). Key words: occupational health, work related diseases, surveillance network, Geographic Information System (GIS), spatial analysis