Uncertainty in environmental health impact assessment: Quantitative methods and perspectives.
Environmental health impact assessment models are subjected to great uncertainty due to the complex associations between environmental exposures and health. Quantifying the impact of uncertainty is important if the models are used to support health policy decisions. We conducted a systematic review...
| Publicado en: | International Journal of Environmental Health Research Vol. 23; no. 1; pp. 16 - 31 |
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| Autores principales: | , , , |
| Formato: | research systematic review tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Feb2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104388323&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104388323 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09603123 57L jtl: International Journal of Environmental Health Research issn: 09603123 maglogo: Y pubinfo: dt: Feb2013 vid: 23 iid: 1 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 104388323 83590187 10.1080/09603123.2012.678002 NLM22515647 104388323 ppf: 16 ppct: 15 formats: fmt: @attributes: type: P tig: atl: Uncertainty in environmental health impact assessment: Quantitative methods and perspectives. aug: au: Mesa-Frias, Marco Chalabi, Zaid Vanni, Tazio Foss, Anna M. affil: Department of Social and Environmental Health Research, London School of Hygiene and Tropical Medicine, London, UK sug: subj: Health Impact Assessment Environmental Health Environmental Exposure Uncertainty Evaluation Research Methodology Evaluation Systematic Review Models, Theoretical Medline Embase Funding Source ab: Environmental health impact assessment models are subjected to great uncertainty due to the complex associations between environmental exposures and health. Quantifying the impact of uncertainty is important if the models are used to support health policy decisions. We conducted a systematic review to identify and appraise current methods used to quantify the uncertainty in environmental health impact assessment. In the 19 studies meeting the inclusion criteria, several methods were identified. These were grouped into random sampling methods, second-order probability methods, Bayesian methods, fuzzy sets, and deterministic sensitivity analysis methods. All 19 studies addressed the uncertainty in the parameter values but only 5 of the studies also addressed theuncertainty in the structure of the models. None of the articles reviewed considered conceptual sources of uncertainty associated with the framing assumptions or the conceptualisation of the model. Future research should attempt to broaden the way uncertainty is taken into account in environmental health impact assessments. pubtype: Academic Journal doctype: research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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