Physical and economic consequences of climate change in Europe.

Quantitative estimates of the economic damages of climate change usually are based on aggregate relationships linking average temperature change to loss in gross domestic product (GDP). However, there is a clear need for further detail in the regional and sectoral dimensions of impact assessments to design and prioritize adaptation strategies. New developments in regional climate modeling and physical-impact modeling in Europe allow a better exploration of those dimensions. This article quantifies the potential consequences of climate change in Europe in four market impact categories (agriculture, river floods, coastal areas, and tourism) and one nonmarket impact (human health). The methodology integrates a set of coherent, high-resolution climate change projections and physical models into an economic modeling framework. We find that if the climate of the 2080s were to occur today, the annual loss in household welfare in the European Union (EU) resulting from the four market impacts would range between 0.2-1%. If the welfare loss is assumed to be constant over time, climate change may halve the EU's annual welfare growth. Scenarios with warmer temperatures and a higher rise in sea level result in more severe economic damage. However, the results show that there are large variations across European regions. Southern Europe, the British Isles, and Central Europe North appear most sensitive to climate change. Northern Europe, on the other hand, is the only region with net economic benefits, driven mainly by the positive effects on agriculture. Coastal systems, agriculture, and river flooding are the most important of the four market impacts assessed.

Excess mortality attributed to heat and cold: a health impact assessment study in 854 cities in Europe.

BACKGROUND: Heat and cold are established environmental risk factors for human health. However, mapping the related health burden is a difficult task due to the complexity of the associations and the differences in vulnerability and demographic distributions. In this study, we did a comprehensive mortality impact assessment due to heat and cold in European urban areas, considering geographical differences and age-specific risks. METHODS: We included urban areas across Europe between Jan 1, 2000, and Dec 12, 2019, using the Urban Audit dataset of Eurostat and adults aged 20 years and older living in these areas. Data were extracted from Eurostat, the Multi-country Multi-city Collaborative Research Network, Moderate Resolution Imaging Spectroradiometer, and Copernicus. We applied a three-stage method to estimate risks of temperature continuously across the age and space dimensions, identifying patterns of vulnerability on the basis of city-specific characteristics and demographic structures. These risks were used to derive minimum mortality temperatures and related percentiles and raw and standardised excess mortality rates for heat and cold aggregated at various geographical levels. FINDINGS: Across the 854 urban areas in Europe, we estimated an annual excess of 203 620 (empirical 95% CI 180 882-224 613) deaths attributed to cold and 20 173 (17 261-22 934) attributed to heat. These corresponded to age-standardised rates of 129 (empirical 95% CI 114-142) and 13 (11-14) deaths per 100 000 person-years. Results differed across Europe and age groups, with the highest effects in eastern European cities for both cold and heat. INTERPRETATION: Maps of mortality risks and excess deaths indicate geographical differences, such as a north-south gradient and increased vulnerability in eastern Europe, as well as local variations due to urban characteristics. The modelling framework and results are crucial for the design of national and local health and climate policies and for projecting the effects of cold and heat under future climatic and socioeconomic scenarios. FUNDING: Medical Research Council of UK, the Natural Environment Research Council UK, the EU's Horizon 2020, and the EU's Joint Research Center.

Comparison of weather station and climate reanalysis data for modelling temperature-related mortality.

Epidemiological analyses of health risks associated with non-optimal temperature are traditionally based on ground observations from weather stations that offer limited spatial and temporal coverage. Climate reanalysis represents an alternative option that provide complete spatio-temporal exposure coverage, and yet are to be systematically explored for their suitability in assessing temperature-related health risks at a global scale. Here we provide the first comprehensive analysis over multiple regions to assess the suitability of the most recent generation of reanalysis datasets for health impact assessments and evaluate their comparative performance against traditional station-based data. Our findings show that reanalysis temperature from the last ERA5 products generally compare well to station observations, with similar non-optimal temperature-related risk estimates. However, the analysis offers some indication of lower performance in tropical regions, with a likely underestimation of heat-related excess mortality. Reanalysis data represent a valid alternative source of exposure variables in epidemiological analyses of temperature-related risk.

Economic motivation for raising coastal flood defenses in Europe.

Extreme sea levels (ESLs) in Europe could rise by as much as one metre or more by the end of this century due to climate change. This poses significant challenges to safeguard coastal communities. Here we present a comprehensive analysis of economically efficient protection scenarios along Europe's coastlines during the present century. We employ a probabilistic framework that integrates dynamic simulations of all ESL components and flood inundation, impact modelling and a cost-benefit analysis of raising dykes. We find that at least 83% of flood damages in Europe could be avoided by elevating dykes in an economically efficient way along 23.7%-32.1% of Europe's coastline, specifically where high value conurbations exist. The European mean benefit to cost ratio of the investments varies from 8.3 to 14.9 while at country level this ranges between 1.6 and 34.3, with higher efficiencies for a scenario with high-end greenhouse gas emissions and strong socio-economic growth.

Modeling the impact of genetic screening technologies on healthcare: theoretical model for asthma in children.

BACKGROUND AND OBJECTIVE: This study focuses on the potential impact of genetic screening technologies on healthcare. Genetic screening for asthma in children was chosen as a case study to explore the cost effectiveness of applying early genetic screening to infants, and preventive treatment to the population at risk. Early intervention could prevent progression and facilitate clinical management of the disease. From the elite group of genetic markers that have been associated with asthma-related phenotypes, ADAM33 was the first published candidate gene detected by a positional cloning approach, marking the entry of asthma research into the genomic era. The model was, therefore, initially set for an ex ante analysis of the cost effectiveness of applying the preventive program to an infant population at risk, i.e. infants presenting wheezing episodes during the first year of life, and the ADAM33 ST+7 genetic marker, with the idea of expanding to further markers and their combinations lat a later date. METHODS: In accordance with the US National Heart, Lung, and Blood Institute, four categories of asthma were considered. A Markov model was constructed, consisting of six mutually exclusive disease states (including healthy and dead states) with a simulation horizon of 100 years and a cycle length of 1 year. We define a scenario where early genetic screening was applied to infants presenting wheezing episodes during the first year of life and a preventive treatment to those children within this group who tested positive for selected ADAM33 polymorphism (ST+7). The cost-effectiveness analysis was performed from the third-party payer and patient perspective after year 6. We applied our model to a hypothetical cohort of 100 European infants. RESULTS: The number of quality-adjusted life-years (QALYs) gained during the 6 years was 1.483, and the incremental cost-effectiveness ratio per QALY gained was euro 10,100/QALY. A sensitivity analysis was carried out that varied the discount rate and cost of genetic testing, and considered two different transition matrices for the preventive program. Three main conclusions were drawn from the sensitivity analysis. Firstly, if the discount rate for both cost and health outcomes is increased by 2%, the cost effectiveness of the preventive program does not vary significantly. Discounting costs and benefits at 5%, the preventive program appears cost effective (euro 11,100/QALY). Secondly, if the cost of genetic testing is increased to euro 100, the cost effectiveness of the preventive program remains within the limits of cost effectiveness. Thirdly, the cost of genetic screening, together with transition probabilities between health states, will determine the cost effectiveness of applying a preventive program based on genetic information. CONCLUSIONS: Preventive treatment based on an early genetic screening of those children who present wheezing episodes during the first year of life, with treatment applied to those who test positive for the asthma-associated genetic marker ADAM33 ST+7, is theoretically cost effective. The model is a valuable tool for the ex ante assessment of the cost effectiveness of preventive schemes based on genetic screening. The value of modeling prior to clinical trials lies in informing study design and setting priorities for future research.