Delaunay M, Van der Westhuizen H, Godard V, Agius R, Le Barbier M, Godderis L, Bonneterre V
Univ. Grenoble Alpes/CNRS/TIMC-IMAG UMR 5525 (EPSP team: Environnement et Prédiction de la Santé des Populations), Grenoble F-38000, France, Univ. Paris 8/CNRS/Ladyss Laboratory UMR 7533 (Laboratoire Dynamiques sociales et recomposition des espaces), Saint-Denis F-93526, France, Modernet Network (Monitoring Occupational Diseases and new Emerging Risks in a NETwork, http://www.costmodernet.org/).
Modernet Network (Monitoring Occupational Diseases and new Emerging Risks in a NETwork, http://www.costmodernet.org/), Cape Peninsula University of Technology/Faculty of Applied Sciences/Department of Environmental and Occupational Studies, Cape Town 8000, South Africa, Katholieke Universiteit Leuven, Centre for Environment and Health, 3000 Leuven, Belgium.
Occup Med (Lond). 2015 Nov;65(8):682-92. doi: 10.1093/occmed/kqv152.
Occupational health and safety (OHS) information is often complex, diverse and unstructured and suffers from a lack of integration which usually precludes any systemic insight of the situation.
To analyse to what extent the use of geographical information systems (GISs) can help to integrate, analyse and present OHS data in a comprehensive and communicable way relevant for surveillance purposes.
We first developed a 'macro-approach' (from national to local level), mapping data related to economic activity (denominator of active workers displayed by activity sectors), as well as work-related ill-health (numerators of workers suffering from work-related ill-health). The latter data are composed of compensated occupational diseases on the one hand and work-related diseases investigated by specialized clinics on the other hand. Then, a 'micro-approach' was worked out, integrating at a plant level, using computer-aided drawing, occupational risks data and OHS surveillance data (e.g. use of medication and sickness absence data).
At the macro-level, microelectronics companies and workers were mapped at different scales. For the first time, we were able to compare, up to the enterprise level, complementary data showing different pictures of work-related ill-health, allowing a better understanding of OH issues in this sector. At the micro-level, new information arose from the integration of risk assessment data and medical data.
This work illustrates to what extent GIS is a promising tool in the OHS field, and discusses related challenges (technical, ethical, biases and interpretation) and research perspectives.
职业健康与安全(OHS)信息通常复杂、多样且无结构化,并且缺乏整合,这通常妨碍对情况有任何系统性的洞察。
分析地理信息系统(GIS)在何种程度上有助于以与监测目的相关的全面且可传播的方式整合、分析和呈现OHS数据。
我们首先开发了一种“宏观方法”(从国家层面到地方层面),绘制与经济活动相关的数据(按活动部门显示的在职员工分母)以及与工作相关的健康不良情况(患有与工作相关健康不良的员工分子)。后一类数据一方面由经补偿的职业病组成,另一方面由专科诊所调查的与工作相关的疾病组成。然后,制定了一种“微观方法”,在工厂层面进行整合,利用计算机辅助绘图、职业风险数据和OHS监测数据(例如药物使用和病假数据)。
在宏观层面,按不同比例绘制了微电子公司和员工的地图。我们首次能够在企业层面比较显示与工作相关健康不良不同情况的补充数据,从而更好地理解该部门的OH问题。在微观层面,风险评估数据和医疗数据的整合产生了新信息。
这项工作说明了GIS在OHS领域是一个多么有前景的工具,并讨论了相关挑战(技术、伦理、偏差和解释)以及研究前景。