Sari Kovats

The impact of heat waves on mortality in 9 European cities: results from the EuroHEAT project

BackgroundThe present study aimed at developing a standardized heat wave definition to estimate and compare the impact on mortality by gender, age and death causes in Europe during summers 1990-2004 and 2003, separately, accounting for heat wave duration and intensity.MethodsHeat waves were defined considering both maximum apparent temperature and minimum temperature and classified by intensity, duration and timing during summer. The effect was estimated as percent increase in daily mortality during heat wave days compared to non heat wave days in people over 65 years. City specific and pooled estimates by gender, age and cause of death were calculated.ResultsThe effect of heat waves showed great geographical heterogeneity among cities. Considering all years, except 2003, the increase in mortality during heat wave days ranged from + 7.6% in Munich to + 33.6% in Milan. The increase was up to 3-times greater during episodes of long duration and high intensity. Pooled results showed a greater impact in Mediterranean (+ 21.8% for total mortality) than in North Continental (+ 12.4%) cities. The highest effect was observed for respiratory diseases and among women aged 75-84 years. In 2003 the highest impact was observed in cities where heat wave episode was characterized by unusual meteorological conditions.ConclusionsClimate change scenarios indicate that extreme events are expected to increase in the future even in regions where heat waves are not frequent. Considering our results prevention programs should specifically target the elderly, women and those suffering from chronic respiratory disorders, thus reducing the impact on mortality.

Millions at risk: defining critical climate change threats and targets

Agreements to mitigate climate change have been hampered by several things, not least their cost. But the cost might well be more acceptable if we had a clear picture of what damages would be avoided by different levels of emissions reductions, in other words, a clear idea of the pay off. The problem is that we do not. The Third Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) published this year (IPCC (2001a) and IPCC (2001b)) lists a wide range of potential impacts but has difficulty in discriminating between those that are critical in their nature and magnitude from those that are less important. Yet, the identification of critical impacts (e.g. ones that should be avoided at any reasonable cost) is obviously a key to addressing targets for mitigating climate change. Indeed, a central objective of the UN Framework Objective on Climate Change (UNFCCC) is to avoid “dangerous levels” of climate change that could threaten food security, ecosystems and sustainable development (areas of risk that are specifically mentioned in UNFCCC Article 2). For several years, we have been researching impacts in key areas of risk: hunger, water shortage, exposure to malaria transmission, and coastal flooding, as part of a global fast-track assessment (Parry and Livermore, 1999). 1 The results of our work have been reported widely and form a significant part of the IPCCs assessment of likely impacts (IPCC (2001a) and IPCC (2001b)). But they are scattered through different parts of the IPCC report and other literature and, before now, we have not brought them together. For this review, we have graphed our estimates of effects as a single measure: the additional millions of people who could be placed at risk as a result of different amounts of global warming ( Fig. 1). Full-size image (36K) - Opens new window Full-size image (36K) Fig. 1. Additional millions at risk due to climate change in 2050s and 2080s for hunger, coastal flooding, water shortage and malaria. The width of the curve indicates one standard deviation of variance around the mean, based on results from four HadCM2 experiments (Parry and Livermore, 1999; IPCC, 2000). Solid lines indicate model-based estimates. Dotted lines are inferred ( IPCC (2001a) and IPCC, 2001b. Climate change 2001: The Scientific Basis. Technical Summary of the Working Group I Report, Geneva, 2001.IPCC (2001b)) and intended as schematic. Stab. 450 (etc.)=stabilisation@450 ppmv (etc.). View Within Article The figure shows the increase in millions at risk due to higher temperatures for two time periods—2050s and 2080s. The analysis takes into account likely non-climate developments such as growth in population, and income and developments of technology, and these become important assumptions behind future trends in, for example, increases in crop yield and the building of coastal defences. These developments themselves have very great effects on the numbers at risk and represent a (non-climate change) reference case. The graph thus shows the additional millions at risk due specifically to estimated future changes in climate. But now for the caveats: the reference case is only for one future world (what the IPCC used to call a best estimate or “business-as-usual” future, now referred to as IS92a). More recently, the IPCC has explored a set of six different developmental pathways that the world may follow (IPCC, 2000), and the millions at risk in these alternative futures will certainly differ. Our work on these is in hand but will probably take a year to complete. We need also to emphasise that the graph is a global estimate which hides important regional variations and, so far, it is based on one model of future climate patterns (the UKs Hadley Centre second generation global climate model) ( Johns et al., 1997). While these are the only global impact estimates currently available, we need urgently to complete similar ones for different climate models and for a variety of development pathways. Five important points emerge from this figure. First, the curves of additional millions at risk generally become steeper over time. Less obviously, this results as much from a larger and more vulnerable exposed population in 2080 than in 2050, as from increases in temperature or inferred changes in precipitation and sea-level rise. For example, the remarkable steepness of the water shortage curve in 2080 is the outcome of very large city populations in China and India becoming newly at risk. In the case of hunger, however, the rising curve in 2080 stems from widespread heat stress of crops, while up to about 2050 lesser amounts of warming lead to yield gains in temperate regions that balance losses elsewhere and lead to only small net increases in hunger (Parry and Livermore, 1999). These complex interactions between exposure and climate change tell a clear story: there will be more millions at risk as time progresses. Secondly, the figure indicates how much we need to reduce emissions in order to draw-down significantly the numbers at risk. We have estimated effects assuming that atmospheric concentrations of CO2 are stabilised at 750 parts per million (ppmv) by 2250 and at 550 ppmv by 2150 (Arnell, in press). These are approximately equivalent, respectively, to 10 times and 20 times the reduction in emissions assumed in the Kyoto Protocol. The 750 ppmv target delays the damage but does not avoid it. By 2080, it would halve the number at risk from hunger and flooding, reduce the population at risk of malaria by perhaps a third and water shortage by about a quarter. But to bring risk levels down from hundreds to tens of millions would require a stabilisation target of about 550 ppmv. We have also indicated on the graph, but only in a schematic form, the approximate locations of 450, 650 and 1000 ppmv stabilisation pathways and their effect on millions at risk (IPCC (2001a) and IPCC (2001b)). Although impact analyses have not yet been conducted for these stabilisation levels, it appears that the 450 ppmv pathway would achieve very great reductions in millions at risk, although very high costs of mitigation would be incurred. It is precisely this kind of pay-off that needs to be analysed properly. A third conclusion is that information is now available that can help inform the selection of climate change targets. Thus far these targets, such as Kyoto, have been chosen in broadly a top–down manner, without clear knowledge of the impacts that would be avoided, and that has been partly their weakness. Now we may argue, for example, that in order to keep damages below an agreed tolerable level (for example, a given number of additional people at risk) global temperature increases would need to be kept below a given amount; and emissions targets could then be developed to achieve that objective. Fourthly, it is clear that mitigation alone will not solve the problem of climate change. Adaptation will be necessary to avoid, or at least reduce, much of the possible damage, and since we need many of the benefits of adaptation today, regardless of climate change in the future (e.g. increased drought protection of agriculture, improved flood defences, more efficient use of water, better malaria control), many of the adaptive strategies for climate change can be “win–win”. We need to find a blend of mitigation and adaptation to meet the challenge of climate change. Mitigation can buy time for adaptation (for example, delaying impacts until improved technology and management can handle them), and adaptation can raise thresholds of tolerance that need to be avoided by mitigation (for example, by increasing drought tolerance of crops). Considered separately, they appear inadequate to meet such a challenge, but combined they would make a powerful response.

Impact of climate change on global malaria distribution

Significance This study is the first multimalaria model intercomparison exercise. This is carried out to estimate the impact of future climate change and population scenarios on malaria transmission at global scale and to provide recommendations for the future. Our results indicate that future climate might become more suitable for malaria transmission in the tropical highland regions. However, other important socioeconomic factors such as land use change, population growth and urbanization, migration changes, and economic development will have to be accounted for in further details for future risk assessments. Malaria is an important disease that has a global distribution and significant health burden. The spatial limits of its distribution and seasonal activity are sensitive to climate factors, as well as the local capacity to control the disease. Malaria is also one of the few health outcomes that has been modeled by more than one research group and can therefore facilitate the first model intercomparison for health impacts under a future with climate change. We used bias-corrected temperature and rainfall simulations from the Coupled Model Intercomparison Project Phase 5 climate models to compare the metrics of five statistical and dynamical malaria impact models for three future time periods (2030s, 2050s, and 2080s). We evaluated three malaria outcome metrics at global and regional levels: climate suitability, additional population at risk and additional person-months at risk across the model outputs. The malaria projections were based on five different global climate models, each run under four emission scenarios (Representative Concentration Pathways, RCPs) and a single population projection. We also investigated the modeling uncertainty associated with future projections of populations at risk for malaria owing to climate change. Our findings show an overall global net increase in climate suitability and a net increase in the population at risk, but with large uncertainties. The model outputs indicate a net increase in the annual person-months at risk when comparing from RCP2.6 to RCP8.5 from the 2050s to the 2080s. The malaria outcome metrics were highly sensitive to the choice of malaria impact model, especially over the epidemic fringes of the malaria distribution.

Perceptions of heatwave risks to health: interview-based study of older people in London and Norwich, UK

BACKGROUND Most projections of climate change suggest an increased frequency of heatwaves in England over coming decades; older people are at particular risk. This could result in substantial mortality and morbidity. OBJECTIVE To determine elderly peoples knowledge and perceptions of heat-related risks to health, and of protective behaviours. METHODS Semi-structured interviews: 73 men and women, 72-94 years, living in their own homes in London and Norwich, UK. RESULTS Few respondents considered themselves either old or at risk from the effects of heat, even though many had some form of relevant chronic illness; they did recognize that some medical conditions might increase risks in others. Most reported that they had taken appropriate steps to reduce the effects of heat. Some respondents considered it appropriate for the government to take responsibility for protecting vulnerable people, but many thought state intervention was unnecessary, intrusive and unlikely to be effective. Respondents were more positive about the value of appropriately disseminated advice and solutions by communities themselves. CONCLUSION The Heatwave Plan should consider giving greater emphasis to a population-based information strategy, using innovative information dissemination methods to increase awareness of vulnerability to heat among the elderly and to ensure clarity about behaviour modification measures.

Climate, climate change and human health in Asian cities

Climate change will affect the health of urban populations. It represents a range of environmental hazards and will affect populations where the current burden of climate-sensitive disease is high — such as the urban poor in low- and middle-income countries. Understanding the current impact of weather and climate variability on the health of urban populations is the first step towards assessing future impacts. In this paper, we have reviewed the scientific evidence for the effects of temperature, rainfall and extreme events on human health, in particular the impacts of heat waves and floods. The methods for assessing the risks of climate change are undergoing development, and there is a need to shift the focus from global and regional to local studies. Sectoral approaches to climate change impact assessments often ignore the effects on health. There is a need to better describe the risks to health from extreme weather events as well as improve the effectiveness of public health interventions. Improving the resilience of cities to climate change also requires improvements in the urban infrastructure, but such improvements may not be achieved quickly enough to avoid an increased burden of disease due to global climate change.

Editorial Reducing risks to cities from disasters and climate change

The lives and livelihoods of hundreds of millions of people will be affected by what is done (or not done) in cities with regard to climate change over the next 5–10 years. As the paper by Patricia Romero Lankao points out, cities are key players both in the generation of greenhouse gases and in strategies to reduce this generation, especially in reducing our dependence on carbon-based fuels. Cities also concentrate a large proportion of those most at risk from the effects of climate change. While the need for city governments and civil society groups to act to reduce greenhouse gas emissions is well established – and with many city governments in Europe and North America already acting on this – the need to act to reduce vulnerability to climate change is not. In addition, most of the cities (and nations) that face the highest risks from the negative effects of climate change are those with almost negligible contributions to atmospheric greenhouse gases. Take, for instance, Cotonou, the economic capital of Benin, with around one million inhabitants, whose vulnerability to climate change is described in the paper by Krystel Dossou and Bernadette Glehouenou-Dossou. In 2004, average emissions of carbon dioxide per person in Benin were around one-fi ftieth that in highincome nations – or one-eightieth that in the USA.(1) Like many cities on the coast of West Africa, large parts of Cotonou’s economy and residential neighbourhoods are particularly vulnerable to sea-level rise and storm surges. Some roads, beaches and buildings have already been destroyed by the regression of the coastline in the last 10 years. Many other cities in Africa are also at risk from sea-level rise and storm surges. Half of the continent’s 37 “million cities” are either within or have parts that are within the low elevation coastal zone. Banjul, Lagos and Alexandria are among the cities most at risk, although many others are also likely to face much increased risks from storms and fl ooding – but because of the lack of local analysis, the scale of these risks has yet to be documented.(2) Many Asian cities are also particularly at risk. Asia has many of the world’s largest cities/ metropolitan areas that are in the fl oodplains of major rivers (e.g. the Ganges–Brahmaputra, the Mekong and the Yangtze) and cycloneprone coastal areas (the Bay of Bengal, the South China Sea, Japan and the Philippines).The IPCC (Intergovernmental Panel on Climate Change) has emphasized how river deltas are among the world’s most valuable, heavily populated Saleemul Huq, Hannah Reid and David Satterthwaite are at the International Institute for Environment and Development (IIED); Saleemul Huq and Hannah Reid with the Climate Change Group, David Satterthwaite with the Human Settlements Group. Sari Kovats is with the London School of Hygiene and Tropical Medicine. Saleemul Huq, Sari Kovats and David Satterthwaite also contribute to the Intergovernmental Panel on Climate Change’s Working Group II.

Drinking Water Salinity and Maternal Health in Coastal Bangladesh: Implications of Climate Change.

Background: Drinking water from natural sources in coastal Bangladesh has become contaminated by varying degrees of salinity due to saltwater intrusion from rising sea levels, cyclone and storm surges, and upstream withdrawal of freshwater. Objective: Our objective was to estimate salt intake from drinking water sources and examine environmental factors that may explain a seasonal excess of hypertension in pregnancy. Methods: Water salinity data (1998–2000) for Dacope, in rural coastal Bangladesh, were obtained from the Centre for Environment and Geographic Information System in Bangladesh. Information on drinking water sources, 24-hr urine samples, and blood pressure was obtained from 343 pregnant Dacope women during the dry season (October 2009 through March 2010). The hospital-based prevalence of hypertension in pregnancy was determined for 969 pregnant women (July 2008 through March 2010). Results: Average estimated sodium intakes from drinking water ranged from 5 to 16 g/day in the dry season, compared with 0.6–1.2 g/day in the rainy season. Average daily sodium excretion in urine was 3.4 g/day (range, 0.4–7.7 g/day). Women who drank shallow tube-well water were more likely to have urine sodium > 100 mmol/day than women who drank rainwater [odds ratio (OR) = 2.05; 95% confidence interval (CI), 1.11–3.80]. The annual hospital prevalence of hypertension in pregnancy was higher in the dry season (OR = 12.2%; 95% CI, 9.5–14.8) than in the rainy season (OR = 5.1%; 95% CI, 2.91–7.26). Conclusions: The estimated salt intake from drinking water in this population exceeded recommended limits. The problem of saline intrusion into drinking water has multiple causes and is likely to be exacerbated by climate change–induced sea-level rise.

Association of mortality with high temperatures in a temperate climate: England and Wales

Background It is well known that high ambient temperatures are associated with increased mortality, even in temperate climates, but some important details are unclear. In particular, how heat–mortality associations (for example, slopes and thresholds) vary by climate has previously been considered only qualitatively. Methods An ecological time-series regression analysis of daily counts of all-cause mortality and ambient temperature in summers between 1993 and 2006 in the 10 government regions was carried out, focusing on all-cause mortality and 2-day mean temperature (lags 0 and 1). Results All regions showed evidence of increased risk on the hottest days, but the specifics, in particular the threshold temperature at which adverse effects started, varied. Thresholds were at about the same centile temperatures (the 93rd, year-round) in all regions—hotter climates had higher threshold temperatures. Mean supra-threshold slope was 2.1%/°C (95% CI 1.6 to 2.6), but regions with higher summer temperatures showed greater slopes, a pattern well characterised by a linear model with mean summer temperature. These climate-based linear-threshold models capture most, but not all, the association; there was evidence for some non-linearity above thresholds, with slope increasing at highest temperatures. Conclusion Effects of high daily summer temperatures on mortality in English regions are quite well approximated by threshold-linear models that can be predicted from the regions climate (93rd centile and mean summer temperature). It remains to be seen whether similar relationships fit other countries and climates or change over time, such as with climate change.

The effect of high temperatures on cause-specific mortality in England and Wales

Objectives Several observational studies have suggested an association between high temperatures and all-cause mortality. However, estimates on more specific mortality outcomes are sparse, and frequently assessed in studies using different analytical methods. Methods A time series analysis was performed on 10 regions in England and Wales during the summers (June–September) of 1993–2006. Average percentage linear increases in risk for a 1°C increase in temperature above region-specific thresholds and attributable deaths were computed by cause-specific mortality and age groups (0–64, 65–74, 75–84, 85+). Results There was evidence of increased mortality with heat for almost all cause-of-death groups examined, with an overall increase in all-cause mortality of 2.1% (95% CI 1.6% to 2.6%) for a 1°C rise above the regional heat threshold. Among main causes, the steepest increase in risk was for respiratory mortality (+4.1% (3.5% to 4.8%) per 1°C). It was much smaller for cardiovascular causes (+1.8% (1.2% to 2.5%)) and myocardial infarction (+1.1% (0.7% to 1.5%)), but comparatively high for arrhythmias (+5.0% (3.2% to 6.9%)) and pulmonary heart disease (+8.3% (2.7% to 14.3%)). Among non- cardiorespiratory causes, the strongest effects were for genitourinary (+3.8% (2.9% to 4.7%)) and nervous system (+4.6% (3.7% to 5.4%)) disorders. 33.9% of heat deaths were attributable to cardiovascular causes, 24.7% to respiratory causes and 41.3% to all other causes combined. Conclusions These results suggest that the risk of heat-related mortality is distributed across a wide range of different causes, and that targeting of preventative actions based on pre-existing disease is unlikely to be efficient.

The impact of the 2003 heat wave on mortality in Shanghai, China

In 2003, Shanghai recorded the hottest summer in over 50years. We investigated the impact on the mortality of a heat wave in 2003 in Shanghai. We calculated excess mortality and rate ratios (RRs) during the heat wave (July 19-August 6, 2003) compared to a reference (non-heatwave) period (June 28-July 9, and August 16-August 22). During the heat wave, the RR of total mortality was 1.13 (95% CI: 1.06-1.20), and the impact was greatest for cardiovascular (RR=1.19, 95% CI: 1.08-1.32) and respiratory (RR=1.23, 95% CI: 1.02-1.48) mortality. Gender did not make a statistically significant difference for the heat-wave impact. Elderly people (over 65years) were most vulnerable to the heat wave. Our analysis showed that the 2003 heat wave had a substantial effect on mortality in Shanghai. Public health programs should be implemented to prevent heat wave-related health problems in the city.