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      Evaluation of an Early-Warning System for Heat Wave-Related Mortality in Europe: Implications for Sub-seasonal to Seasonal Forecasting and Climate Services

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          Abstract

          Heat waves have been responsible for more fatalities in Europe over the past decades than any other extreme weather event. However, temperature-related illnesses and deaths are largely preventable. Reliable sub-seasonal-to-seasonal (S2S) climate forecasts of extreme temperatures could allow for better short-to-medium-term resource management within heat-health action plans, to protect vulnerable populations and ensure access to preventive measures well in advance. The objective of this study is to assess the extent to which S2S climate forecasts could be incorporated into heat-health action plans, to support timely public health decision-making ahead of imminent heat wave events in Europe. Forecasts of apparent temperature at different lead times (e.g., 1 day, 4 days, 8 days, up to 3 months) were used in a mortality model to produce probabilistic mortality forecasts up to several months ahead of the 2003 heat wave event in Europe. Results were compared to mortality predictions, inferred using observed apparent temperature data in the mortality model. In general, we found a decreasing transition in skill between excellent predictions when using observed temperature, to predictions with no skill when using forecast temperature with lead times greater than one week. However, even at lead-times up to three months, there were some regions in Spain and the United Kingdom where excess mortality was detected with some certainty. This suggests that in some areas of Europe, there is potential for S2S climate forecasts to be incorporated in localised heat–health action plans. In general, these results show that the performance of this climate service framework is not limited by the mortality model itself, but rather by the predictability of the climate variables, at S2S time scales, over Europe.

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          Impact of regional climate change on human health.

          The World Health Organisation estimates that the warming and precipitation trends due to anthropogenic climate change of the past 30 years already claim over 150,000 lives annually. Many prevalent human diseases are linked to climate fluctuations, from cardiovascular mortality and respiratory illnesses due to heatwaves, to altered transmission of infectious diseases and malnutrition from crop failures. Uncertainty remains in attributing the expansion or resurgence of diseases to climate change, owing to lack of long-term, high-quality data sets as well as the large influence of socio-economic factors and changes in immunity and drug resistance. Here we review the growing evidence that climate-health relationships pose increasing health risks under future projections of climate change and that the warming trend over recent decades has already contributed to increased morbidity and mortality in many regions of the world. Potentially vulnerable regions include the temperate latitudes, which are projected to warm disproportionately, the regions around the Pacific and Indian oceans that are currently subjected to large rainfall variability due to the El Niño/Southern Oscillation sub-Saharan Africa and sprawling cities where the urban heat island effect could intensify extreme climatic events.
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            Climate change hot-spots

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              Skillful long-range prediction of European and North American winters

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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                06 February 2016
                February 2016
                : 13
                : 2
                : 206
                Affiliations
                [1 ]Catalan Institute of Climate Sciences (IC3), Carrer Doctor Trueta, 203, 3a, 08005 Barcelona, Spain; markel.garcia@ 123456ic3.cat (M.G.-D); joan.ballester@ 123456ic3.cat (J.B.); xavier.rodo@ 123456ic3.cat (X.R.)
                [2 ]World Health Organization (WHO) Regional Office for Europe, European Centre for Environment and Health, Platz der Vereinten Nationen 1, 53113 Bonn, Germany; creswickj@ 123456who.int
                [3 ]National Institute of Health and Medical Research, INSERM U988 and U1198, University of Montpelier, Building 24, Place Eugène Bataillon-CC105, 34095 Montpellier, Cedex 05, France; jean-marie.robine@ 123456inserm.fr
                [4 ]Ecole Pratique des Hautes Etudes, 75014 Paris, France
                [5 ]Division of Geriatrics, Department of Internal Medicine, Rehabilitation and Geriatrics, Geneva University Hospitals, University of Geneva, Chemin du., Pont-Bochet, 1226 Thônex, Switzerland; francois.herrmann@ 123456hcuge.ch
                [6 ]Catalan Institution for Research and Advanced Studies (ICREA), Passeig de Lluís Companys, 23, 08010 Barcelona, Spain
                Author notes
                [* ]Correspondence: rachel.lowe@ 123456ic3.cat ; Tel.: +34-93-567-99-77; Fax: +34-93-309-76-00
                Article
                ijerph-13-00206
                10.3390/ijerph13020206
                4772226
                26861369
                b24da192-739a-4a2c-94c7-a84de2dc56bf
                © 2016 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 30 November 2015
                : 01 February 2016
                Categories
                Article

                Public health
                temperature,extremes,heat wave,mortality model,early warning system,climate services
                Public health
                temperature, extremes, heat wave, mortality model, early warning system, climate services

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