Module 114 : Environmental and Occupational Health Sciences


S10 | Spatializing Environmental Health

March 08th, 2017 09:00am-12:00pm

Session Introduction
Geographic Information Systems have been absolutely fundamental in revealing patterns of inequalities in environmental exposures and mapping them. Many advances (GPS, remote sensing, open geographic data…) that have occurred in the past 20 years have helped us to better understand the spatial and temporal dimensions of exposures that are either harmful or beneficial for people’s health. . We will present state-of-the-art methods, assessing environmental exposure and analyzing data on population, health events, and risk factors. We will address several methodological issues related to the use of geographic information and spatial analysis and modelling in environmental health (privacy, MAUP, ecological fallacy, homogeneity/heterogeneity…).
Case studies will be developed to illustrate the current methods used and the potential of spatial data and GIS tools (examples of different health effects, ways of exposure in urban and rural areas…)

Learning Objectives
At the end of the session, the students should be able to:
– Describe the spatial and temporal dimensions of environmental exposures
– Summarize the state of the art GIS methods assessing environmental exposures
– Discuss major methodological issues while using GIS analysis for environmental health


Required Reading
Richardson D et al., Spatial Turn in Health Research Science. 2013 March 22; 339(6126): 1390–1392
Yang, Shoff, Noah, Spatializing health research: what we know and where we are heading Geospat Health. 2013 May ; 7(2): 161–168.
Boulos K. et al, Crowdsourcing, citizen sensing and sensor web technologies for public and environmental health surveillance and crisis management: trends, OGC standards and application examples International Journal of Health Geographics 2011 10:67

Case studies
Buscail C, Upegui E, Viel JF. Mapping heatwave health risk at the community level for public health action. International Journal of Health Geographics, 2012, 11(1), pp.38.
Herbreteau V, Demoraes F, Khaungaew W, Hugot JP, et al. Use of geographic information system and remote sensing for assessing environment influence on leptospirosis incidence, Phrae province, Thailand. International Journal of Geoinformatics, 2006, 2(4), pp. 43-50.
Fabre P. Daniau C, Goria S, Crouy-Chanel P, Paez A, Empereur-Bissonnet P. Study of the incidence of cancers close to municipal solid waste incinerators. Summary. Saint Maurice (Fra): French Institute for Public Health Surveillance, July 2009, 29p.
Chevrier C, Serrano T, Lecerf R, Limon G, et al. Environmental determinants of the urinary concentrations of herbicides during pregnancy : The PELAGIE mother – child cohort (France). Environment International 63(2014): 11-18.

Supplemental Reading
Cromley E, McLafferty S, GIS and Public Health (Second Edition). 2012. New York, NY: Guilford Press. 503
Albert D, Gesler W, Levergood B. Spatial analysis, GIS and remote sensing applications in the health sciences. 2000.Sleeping bear press. 231p. (pdf available on internet)

Websites, Links

Major 231: Spatial Analysis


January 16th-20th, 2017
Coordination: Cindy Padilla

Mapping is a useful and powerful tool to represent information which varies on a territory. It is particularly true in public health issues where health determinants are multiples and may be related to individual behavior and also to neighborhood factors which are not equally distributed in the space.
Detecting clusters grouping small areas at greater health risk tends to be a appropriate method to orientate public health action. An explanatory spatial analysis can then be applied assessing the relationship between the cluster and the neighborhood characteristics in order to reveal risk factors of the health event.

Course learning objectives

After completing this course, students will be able to:
– Map geographic data
– Create geographic datasets
– Conduct basic spatial analyses
– Apply GIS to several public health disciplines

Module Structure

Session 1
Day 1: Introduction to spatial analysis and working with geographic data
Monday January 18th, 10:00 – 12:00 am and 1.00 – 4.00 pm
Day 2: Spatial analysis data maps and spatial tools – computer lab (ArcGIS)
Tuesday January 19th, 9:00 -12:00 and 1:00 – 4:00 pm
Session 2
Day 3: Spatial statistics – computer lab (ArcGIS) and conference
Wednesday January 20th, 9:00 -12:00 and 1:00 – 4:00 pm
Day 4: Detection of a cluster – computer lab (ArcGIS and Satscan)
Thursday January 24th, 9:00 -12:00 and 1:00 – 4:00 pm
Session 3
Day 5: Critical lecture of spatial article and exam
Friday January 25th, 9:00 -12:00 and 1:00 – 4:00 pm

Major 227: Health policies and health systems in Low and Middle Income Countries



January 08th-12th, 2018
Coordination: Bertrand Lefebvre

Over the past 30 years, health systems in Low & Middle Income Countries have been faced with considerable challenges in providing affordable and quality care to all their populations. From international agencies and donors contradictory injunctions, to local financial and human resources constraints, and issues related to the management of the public and private health care services, LMIC countries have experimented with various models and programs to achieve the universalization of health care services. Through the MDGs and SDGs, new models have emerged to reduce the inequalities in the access to health care services and regarding health status of the populations (Universal Health Coverage).
While there has been a clear move from the “one size fits all” approach among the main actors of international public health (WHO, WB), there is still a need to analyze these initiatives between them and compared to health policy theories and models. This module aims at offering a rich overview on how health policies and health reforms in LMIC are designed, implemented with, more often than not, unexpected results.

Course learning objectives

At the end of the module, the students will be able to:
– Identify tracks of action, in reference to the recognized strategies, programming interventions
– Implement and monitor an action plan.
– Analyze the strengths and weaknesses of health systems in developing countries by using appropriate tools.
– Discuss and propose the most efficient strategies in a contextualized intervention.

UE1SQ1 : Analyse Spatiale


Dans le cadre de l’Unité d’Enseignement 1 sur les Méthodes d’évaluation des risques et impact sanitaire des pollutions environnementales on propose aux étudiants une introduction à la cartographie et à l’analyse spatiale. Ces outils méthodologiques ont fait largement la preuve de leur utilité dans une approche spatialisée des risques et des pollutions environnementales. Dans le cadre de cette séquence d’enseignement, les étudiants doivent se familiariser avec les concepts et les méthodes de la cartographie et de l’analyse spatiale. Il s’agit de permettre aux étudiants d’acquérir une autonomie suffisante pour des traitements basiques (1) et de pouvoir travailler et interagir en connaissance de cause avec des spécialistes de ces méthodes et de ces outils (2).
Le cours prendra appui sur le logiciel QGIS, un logiciel SIG libre, gratuit et multiplateforme. Ce logiciel s’est imposé comme une alternative solide face à des logiciels payants et propriétaires (ArcGIS, MapInfo), non seulement de par sa gratuité mais aussi de par la qualité croissante de son interface, la puissance de ses fonctionnalités, et par le soutien d’une communauté active d’usagers et de partenaires institutionnels (Banque Mondiale, Global Facility for Disaster Reduction & Recovery…).

Programme de la formation

Vous suivrez un programme d’exercices qui reposera sur des instructions (fichiers PDF) et des données à traiter. Les exercices seront mis à disposition au fur et à mesure. Chaque exercice réclame autour d’une heure de travail. Un forum sera à votre disposition pour vous accompagner. Lors de la semaine de présentielle, de nouveaux exercices seront à votre disposition pour vérifier vos acquis et travailler collectivement sur les traitements d’analyse spatiale. Voici les différentes séquences :

• Installation de QGIS (J1)
• Créer une première carte et importation de données (J2)
• Travailler autour des données non-géographiques (J3)
• Croiser les données spatialement (J4)
• Créer de l’information géographique (J5)
• Buffers (J6)
• Exercices (J7)

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