The impacts of climate change have been projected for a limited range of health determinants and outcomes for which the epidemiologic evidence base is well developed. The studies reviewed in Section 8.4.1 used quantitative and qualitative approaches to project the incidence and geographical range of health outcomes under different climate and socio-economic scenarios. Section 8.4.2 assesses the possible consequences of climate-change-related health impacts on particularly vulnerable populations and regions in the next few decades
Overall, climate change is projected to have some health benefits, including reduced cold-related mortality, reductions in some pollutant-related mortality, and restricted distribution of diseases where temperatures or rainfall exceed upper thresholds for vectors or parasites. However, the balance of impacts will be overwhelmingly negative (see Section 8.7). Most projections suggest modest changes in the burden of climate-sensitive health outcomes over the next few decades, with larger increases beginning mid-century. The balance of positive and negative health impacts will vary from one location to another and will alter over time as temperatures continue to rise.
8.4.1 Projections of climate-change-related health impacts
Projections of climate-change-related health impacts use different approaches to classify the risk of climate-sensitive health determinants and outcomes. For malaria and dengue, results from projections are commonly presented as maps of potential shifts in distribution. Health-impact models are typically based on climatic constraints on the development of the vector and/or parasite, and include limited population projections and non-climate assumptions. However, there are important differences between disease risk (on the basis of climatic and entomological considerations) and experienced morbidity and mortality. Although large portions of Europe and the USA may be at potential risk for malaria based on the distribution of competent disease vectors, locally acquired cases have been virtually eliminated, in part due to vector- and disease-control activities. Projections for other health outcomes often estimate populations-at-risk or person-months at risk.
Economic scenarios cannot be directly related to disease burdens because the relationships between gross domestic product (GDP) and burdens of climate-sensitive diseases are confounded by social, environmental and climate factors (Arnell et al., 2004; van Lieshout et al., 2004; Pitcher et al., 2007). The assumption that increasing per capita income will improve population health ignores the fact that health is determined by factors other than income alone; that good population health in itself is a critical input into economic growth and long-term economic development; and that persistent challenges to development are a reality in many countries, with continuing high burdens from relatively easy-to-control diseases (Goklany, 2002; Pitcher et al., 2007).
The World Health Organization conducted a regional and global comparative risk assessment to quantify the amount of premature morbidity and mortality due to a range of risk factors, including climate change, and to estimate the benefit of interventions to remove or reduce these risk factors. In the year 2000, climate change is estimated to have caused the loss of over 150,000 lives and 5,500,000 DALYs (0.3% of deaths and 0.4% of DALYs, respectively) (Campbell-Lendrum et al., 2003; Ezzati et al., 2004; McMichael, 2004). The assessment also addressed how much of the future burden of climate change could be avoided by stabilising greenhouse gas emissions (Campbell-Lendrum et al., 2003). The health outcomes included were chosen based on known sensitivity to climate variation, predicted future importance, and availability of quantitative global models (or the feasibility of constructing them):
• episodes of diarrhoeal disease,
• cases of Plasmodium falciparum malaria,
• fatal accidental injuries in coastal floods and inland floods/landslides,
• the non-availability of recommended daily calorie intake (as an indicator for the prevalence of malnutrition).
Limited adjustments for adaptation were included in the estimates.
The projected relative risks attributable to climate change in 2030 vary by health outcome and region, and are largely negative, with most of the projected disease burden being due to increases in diarrhoeal disease and malnutrition, primarily in low-income populations already experiencing a large burden of disease (Campbell-Lendrum et al., 2003; McMichael, 2004). Absolute disease burdens depend on assumptions of population growth, future baseline disease incidence and the extent of adaptation.
The analyses suggest that climate change will bring some health benefits, such as lower cold-related mortality and greater crop yields in temperate zones, but these benefits will be greatly outweighed by increased rates of other diseases, particularly infectious diseases and malnutrition in low-income countries. A proportional increase in cardiovascular disease mortality attributable to climate extremes is projected in tropical regions, and a small benefit in temperate regions. Climate change is projected to increase the burden of diarrhoeal diseases in low-income regions by approximately 2 to 5% in 2020. Countries with an annual GDP per capita of US$6,000 or more are assumed to have no additional risk of diarrhoea. Coastal flooding is projected to result in a large proportional mortality increase under unmitigated emissions; however, this is applied to a low burden of disease, so the aggregate impact is small. The relative risk is projected to increase as much in high- as in low-income countries. Large changes are projected in the risk of Plasmodium falciparum malaria in countries at the edge of the current distribution, with relative changes being much smaller in areas that are currently highly endemic for malaria (McMichael et al., 2004; Haines et al., 2006).
220.127.116.11 Malaria, dengue and other infectious diseases
Studies published since the TAR support previous projections that climate change could alter the incidence and geographical range of malaria. The magnitude of the projected effect may be smaller than that reported in the TAR, partly because of advances in categorising risk. There is greater confidence in projected changes in the geographical range of vectors than in changes in disease incidence because of uncertainties about trends in factors other than climate that influence human cases and deaths, including the status of the public-health infrastructure.
Table 8.2 summarises studies that project the impact of climate change on the incidence and geographical range of malaria, dengue fever and other infectious diseases. Models with incomplete parameterisation of biological relationships between temperature, vector and parasite often over-emphasise relative changes in risk, even when the absolute risk is small. Several modelling studies used the SRES climate scenarios, a few applied population scenarios, and none incorporated economic scenarios. Few studies incorporate adequate assumptions about adaptive capacity. The main approaches used are inclusion of current 'control capacity' in the observed climate-health function (Rogers and Randolph, 2000; Hales et al., 2002) and categorisation of the model output by adaptive capacity, thereby separating the effects of climate change from the effects of improvements in public health (van Lieshout et al., 2004).
Malaria is a complex disease to model and all published models have limited parameterisation of some of the key factors that influence the geographical range and intensity of malaria transmission. Given this limitation, models project that, particularly in Africa, climate change will be associated with geographical expansions of the areas suitable for stable Plasmodium falciparum malaria in some regions and with contractions in other regions (Tanser et al., 2003; Thomas et al., 2004; van Lieshout et al., 2004; Ebi et al., 2005). Projections also suggest that some regions will experience a longer season of transmission. This may be as important as geographical expansion for the attributable disease burden. Although an increase in months per year of transmission does not directly translate into an increase in malaria burden (Reiter et al., 2004), it would have important implications for vector control.
Few models project the impact of climate change on malaria outside Africa. An assessment in Portugal projected an increase in the number of days per year suitable for malaria transmission; however, the risk of actual transmission would be low or negligible if infected vectors are not present (Casimiro et al., 2006). Some central Asian areas are projected to be at increased risk of malaria, and areas in Central America and around the Amazon are projected to experience reductions in transmission due to decreases in rainfall (van Lieshout et al., 2004). An assessment in India projected shifts in the geographical range and duration of the transmission window for Plasmodium falciparum and P. vivax malaria (Bhattacharya et al., 2006). An assessment in Australia based on climatic suitability for the main anopheline vectors projected a likely southward expansion of habitat, although the future risk of endemicity would remain low due to the capacity to respond (McMichael et al., 2003a).
Dengue is an important climate-sensitive disease that is largely confined to urban areas. Expansions of vector species that can carry dengue are projected for parts of Australia and New Zealand (Hales et al., 2002; Woodruff, 2005). An empirical model based on vapour pressure projected increases in latitudinal distribution. It was estimated that, in the 2080s, 5-6 billion people would be at risk of dengue as a result of climate change and population increase, compared with 3.5 billion people if the climate remained unchanged (Hales et al., 2002).
The projected impacts of climate change on other vector-borne diseases, including tick-borne encephalitis and Lyme disease, are discussed in the chapters dealing with Europe (Chapter 12) and North America (Chapter 14).
Evidence of the relationship between high ambient temperature and mortality has strengthened since the TAR, with increasing emphasis on the health impacts of heatwaves. Table 8.3 summarises projections of the impact of climate change on heat- and cold-related mortality. There is a lack of information on the effects of thermal stress on mortality outside the industrialised countries.
Reductions in cold-related deaths due to climate change are projected to be greater than increases in heat-related deaths in the UK (Donaldson et al., 2001). However, projections of cold-related deaths, and the potential for decreasing their numbers due to warmer winters, can be overestimated unless they take into account the effects of influenza and season (Armstrong et al., 2004).
Heat-related morbidity and mortality is projected to increase. Heat exposures vary widely, and current studies do not quantify the years of life lost due to high temperatures. Estimates of the burden of heat-related mortality attributable to climate change are reduced, but not eliminated, when assumptions about acclimatisation and adaptation are included in models. On the other hand, increasing numbers of older adults in the population will increase the proportion of the population at risk because a decreased ability to thermo-regulate is a normal part of the aging process. Overall, the health burden could be relatively small for moderate heatwaves in temperate countries, because deaths occur primarily in susceptible persons. Additional research is needed to understand how the balance of heat-related and cold-related mortality could change under different socio-economic scenarios and climate projections.
Background levels of ground-level ozone have risen since pre-industrial times because of increasing emissions of methane, carbon monoxide and nitrogen oxides; this trend is expected to continue over the next 50 years (Fusco and Logan, 2003; Prather et al., 2003). Changes in concentrations of ground-level ozone driven by scenarios of future emissions and/or weather patterns have been projected for Europe and North America (Stevenson et al., 2000; Derwent et al., 2001; Johnson et al., 2001; Taha, 2001; Hogrefe et al., 2004). Future emissions are, of course, uncertain, and depend on assumptions of population growth, economic development, regulatory actions and energy use (Syri et al., 2002; Webster et al., 2002a). Assuming no change in the
Health effect Metric
Climate scenario, with
Population proj- Main results
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