Editing IPCC:AR6/WGII/Chapter-7 (section)

=== 7.4.2 Adaptation Strategies, Policies and Interventions ===

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==== 7.4.2.1 Current State of Health Adaptation ====

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Analysis of the NDCs to the Paris Agreement to determine how health was incorporated, including impacts, adaptation and co-benefits, concluded that most low- and middle-income countries referred to health in their NDC ( [[#Dasandi--2021|Dasandi et al., 2021]] ). Figure 7.13 shows the degree of health engagement; this engagement is based on indicators measuring the specificity and detail of health references within a country’s NDC. Many vulnerable countries had high engagement of the health sector in the country NDC. However, this analysis did not determine whether the ambition expressed was sufficient to address the health adaptation needs.

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[[File:865a3982833f789fd40a2b150648ebf6 IPCC_AR6_WGII_Figure_7_013.png]]

'''Figure 7.13 |''' '''Health engagement score in NDCs by country.''' Figure adapted from [[#Dasandi--2021|Dasandi et al. (2021)]] .

The 2018 WHO Health and Climate Change Survey, a voluntary national survey sent to all 194 WHO member states, to which 101 responded, found that national planning on health and climate change is advancing, but the comprehensiveness of strategies and plans need to be strengthened. Implementing action on key health and climate change priorities remains challenging and multi-sectoral collaboration on health and climate change policy is evident, with uneven progress ( [[#Watts--2021|Watts et al., 2021]] ). Approximately 50% of respondent countries had developed national health and climate strategies, with over two-thirds doing so within the preceding five years, and 48 of 101 countries had conducted a health vulnerability and adaptation assessment ( [[#Watts--2019|Watts et al., 2019]] ). However, most countries reported only moderate or low levels of implementation, with financing cited as the most common barrier due to a lack of information on opportunities, in turn linked to a lack of connection by health actors to climate change policy processes and a lack of capacity to participate in national planning. A review of public health systems in 34 countries found that only slightly more than half considered climate change impacts and adaptation needs ( [[#Berry--2018|Berry et al., 2018]] ). Because the health risks of climate change often vary within a country, sub-national assessments and plans are needed to help local authorities protect and promote population health in a changing climate ( [[#Aracena--2021|Aracena et al., 2021]] ; [[#Basel--2020|Basel et al., 2020]] ; [[#Schramm--2020a|Schramm et al., 2020a]] ).

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==== 7.4.2.2 Adaptation in Health Policies and Programmes ====

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''Health policies were historically not designed or implemented taking into consideration the risks of climate change and as currently structured are'' likely ''insufficient to manage the changing health burdens in coming decades'' ( ''very high confidence'' ) ''.'' The magnitude and pattern of future health burdens attributable to climate change, at least until mid-century, will be determined primarily by adaptation and development choices. Current and future emissions will play an increasing role in determining attributable burdens after mid-century. Increased investment in strengthening general health systems, along with targeted investments to enhance protection against specific climate-sensitive exposures (e.g., hazard early warning and response systems and integrated vector control programmes for VBDs) will increase resilience if implemented to at least keep pace with climate change ( ''high confidence'' ). Investments to address the social determinants of health can reduce inequities and increase resilience ( ''high confidence)'' ( [[#Thornton--2016|Thornton et al., 2016]] ; [[#Marmot--2020|Marmot et al., 2020]] ; [[#Wallace--2015|Wallace et al., 2015]] ; [[#Semenza--2021|Semenza and Paz, 2021]] ).

Peer-reviewed publications of health adaptation to climate change in low- and middle-income countries have typically focused on flooding, rainfall, drought and extreme heat through improving community resilience, DRR and policy, governance and finance ( [[#Berrang-Ford--2021|Berrang-Ford et al., 2021]] ; [[#Scheelbeek--2021|Scheelbeek et al., 2021]] ). Health outcomes of successful adaptation have included reductions in infectious disease incidence, improved access to water and sanitation and improved food security. Figure 7.14 shows a Sankey diagram of climate hazards, adaptation responses and health outcomes. The figure highlights the range of health adaptation responses that are discussed in more detail earlier in this chapter and demonstrates the potential health benefit of adaptation efforts that affect a broad range of health determinants.

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[[File:74b48a7ebfb82b48ec221f62634d76b3 IPCC_AR6_WGII_Figure_7_014.png]]

'''Figure 7.14 |''' '''Sankey diagram of climate hazards, adaptation responses and health outcomes.''' CSA is climate-smart agriculture. Source: [[#Scheelbeek--2021|Scheelbeek et al. (2021)]] .

Questions of the feasibility and effectiveness of health adaptation options differ from those in other sectors because public health is a societal enterprise that cuts across many different spheres of society. Consequently, there are dependencies that lie outside the jurisdiction of the health sector. All the health risks of a changing climate currently cause adverse outcomes, with policies and programmes implemented in at least some health programmes in some places. Policies and programmes are continuously modified to increase effectiveness; this will need to accelerate in a changing climate. Improvements are needed as more is understood about disease aetiology, changing socioeconomic and environmental conditions, obstacles to uptake and other factors.

Policies and programmes for climate-sensitive health outcomes are only beginning to incorporate the challenges and opportunities of climate change, although this is critical for increasing resilience. The fundamentals of many policies and programmes in a changing climate will remain the same: implementing infectious disease control programmes, preventing heat-related mortality and morbidity and reducing the burden of other climate-related health endpoints, but activities will need to explicitly account for climate change to continue to protect health. Even with such attention to climate change, there are limits to the feasibility and effectiveness of health adaptation options for extreme heat, controlling emerging infectious diseases and controlling cascading risk pathways.

As discussed in Sections 1.4.2 and 1.5, an adaptation option is feasible when it is capable of being implemented by one or more relevant actors. In the health sector, WHO, the United Nations Children’s Fund (UNICEF) and other organisations provide technical expertise to ministries of health, who then provide national to local healthcare and public health services. Generally, the question is less of overall feasibility, given the range of potential adaptation options that have yet to be fully explored and implemented, but more of readiness to buy into the adaptation efforts required from health and other sectors. In specific contexts, feasibility also depends on governance capacity, financial capacity, public opinion and the distribution of political and economic power (Chapter 17). In other words, adaptation to climate change is broadly feasible with adequate investment and engagement, although this has yet to materialise, and in specific contexts feasibility is contingent and time-varying, and needs to be assessed at national to sub-national scales. For example, a scoping review in the Pacific region noted the following areas where further and significant investment and support are needed to increase feasibility of climate and health action: (a) health workforce capacity development, (b) enhanced surveillance and monitoring systems and (c) research to address priorities and their subsequent translation into practice and policy ( [[#Bowen--2021|Bowen et al., 2021]] ). Vulnerability, adaptation and capacity assessments include consideration of the feasibility and effectiveness of priority health adaptation options and can help decision makers identify strategies for enhancing adaptation feasibility in specific contexts.

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==== 7.4.2.3 Adaptation Options for Vector-borne, Water-borne and Food-Borne Diseases ====

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''Integrated vector control approaches are crucial to effectively manage the geographic spread, distribution and transmission of VBDs associated with climate change'' ( ''high confidence'' ) ''.'' Some of the projected risks of climate change on VBDs can be offset through enhanced commitment to existing approaches to integrated case management and integrated vector control management ( [[#Cissé--2018|Cissé et al., 2018]] ; [[#Confalonieri--2017|Confalonieri et al., 2017]] ; [[#Semenza--2021|Semenza and Paz, 2021]] ). Important components include enhanced disease surveillance and early warning and response systems that can identify potential outbreaks at sub-seasonal to decadal time scales ( [[#Rocklöv--2020|Rocklöv and Dubrow, 2020]] ; [[#Semenza--2014|Semenza and Zeller, 2014]] ; Table 7.3). In many cases, the exposure dynamics of VBDs are strongly influenced by socioeconomic dynamics that should be considered when developing and deploying adaptation options ( [[#UNEP--2018|UNEP, 2018]] ). This is especially the case in low-income countries. For example, insufficient access to sanitation and the presence of standing water are important determinants of the presence of ''Aedes aegypti'' populations and the pathogens that cause visceral leishmaniasis ( ''L. donovani'' and ''L. infantum'' ) in urban and peri-urban areas. Low housing quality and lack of refuse management are associated with higher rodent infestation. Strategies expected to have important health co-benefits include those that support health systems strengthening and ecosystem health, improve access to health coverage, increase awareness and education and address the underlying conditions of uneven development and a lack of adequate housing and access to water and sanitation systems in areas endemic to mosquito-borne diseases ( [[#Semenza--2021|Semenza and Paz, 2021]] ; Cross-Chapter Box ILLNESS in Chapter 2).

'''Table 7.3 |''' Summary of adaptation options for key risks associated with climate-sensitive vector-, water- and food-borne diseases (VBDs, WBDs, FBDs).

{| class="wikitable"
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! '''Key risk'''

! '''Geographic region(s) at higher risk'''

! '''Consequence that would be considered severe and to whom'''

! '''Hazard conditions that would contribute to this risk being severe'''

! '''Exposure conditions that would contribute to this risk being severe'''

! '''Vulnerability conditions that would contribute to this risk being severe'''

! '''Adaptation options with high potential for reducing risk'''

! '''Selected key references'''

|-
| '''VBDs'''

| Global

| Increase in the incidence of some VBDs, such as malaria, dengue and other mosquito-borne diseases, in endemic areas and in new risk areas (e.g., cities, mountains and Northern Hemisphere)

| Increased climatic suitability for transmission (e.g., enhanced vectorial capacity through a temperature shift)

| Large increases in human exposure to vectors driven by growth in human and vector populations, globalisation, population mobility and urbanisation

| Few effective vaccines, weak health systems, ineffective personal and household protections, susceptibility to disease, poverty, poor hygiene conditions, insecticide resistance and behavioural factors

| Improved housing, better sanitation conditions and self-protection awareness; insecticide-treated bed nets and indoor spraying of insecticide; broader access to healthcare for the most vulnerable; establishment of disease surveillance and early warning systems for VBDs; cross-border joint control of outbreaks; effective vector control; targeted efforts to develop vaccines

| Cissé et al. (2018); [[#Semenza--2021|Semenza (2021)]] ; Rocklöv and Dubrow. (2020)

|-
| '''WBDs'''

| Mostly low- and middle-income countries (Africa and Asia); small islands; global for ''Vibrios''

| Increase in the occurrence and intensity of WBDs such as ''Vibrios'' (particularly ''V. cholerae'' ), diarrhoeal diseases and other waterborne GI illnesses

| Substantial changes in temperature and precipitation patterns, increased frequency and intensity of extreme weather events (e.g., droughts, storms and floods), ocean warming and acidification

| Large increases in exposure, particularly in flood-prone areas with poor sanitation and favourable ecological environments for WBD pathogens

| Poor hygiene conditions, lack of clean drinking water and safe food, flood- and drought-prone areas and vulnerable water and sanitation systems

| Improved WASH conditions and surveillance systems; improved personal drinking and eating habits; behaviour change

| [[#Brubacher--2020|Brubacher et al. (2020)]] ; [[#Ford--2018|Ford and Hamner (2018)]] ; [[#Lake--2018|Lake (2018)]] ; Levy et al. (2018); Nichols et al. (2018); [[#Rocklöv--2021|Rocklöv et al. (2021)]]

|-
| '''FBDs'''

| Global

| Increase in the occurrence and intensity of FBDs such as ''Salmonella'' and ''Campylobacter,'' including in high-income countries

| Substantial changes in temperature and precipitation patterns, increased frequency and intensity of extreme weather events (e.g., droughts, storms and floods), ocean warming and acidification

| Large increases in exposure, particularly in flood-prone areas with poor sanitation and favourable ecological environments for FBD pathogens

| Poor hygiene conditions; lack of clean drinking water and safe food; flood- and drought-prone areas; vulnerable water and sanitation systems, food storage systems, food processes, food preservation and cold chain/storage

| Improved WASH conditions and surveillance systems; improved personal drinking and eating habits; behaviour change; improved food storage, food processing, food preservation and cold chain/storage

| [[#Brubacher--2020|Brubacher et al. (2020)]] ; [[#Ford--2018|Ford and Hamner (2018)]] ; [[#Lake--2018|Lake (2018)]] ; Levy et al. (2018); Nichols et al. (2018); [[#Rocklöv--2021|Rocklöv et al. (2021)]]

|}

''Adaptation options for climate-related risks for WBDs and FBDs are strongly associated with wider, multi-sectoral initiatives to improve sustainable development in low-income communities'' ( ''high confidence'' ) ''.'' Effective measures include improving access to potable water and reducing exposure of water and sanitation systems to flooding and extreme weather events ( [[#Brubacher--2020|Brubacher et al., 2020]] ; [[#Cisse--2019|Cisse, 2019]] ; Table 7.3). This requires focusing on farm-level interventions that limit the spread of pathogens into adjacent waterways, preventing the ongoing contamination of water and sanitation systems and the promotion of food-safe human behaviours ( [[#Levy--2018|Levy et al., 2018]] ; [[#Nichols--2018|Nichols et al., 2018]] ). It is also important to implement well-targeted and integrated WASH interventions, including at schools and ensuring proper disposal of excreta and wastewater. Cities can integrate regional climate projections into their engineering models to produce lower-risk source waters and increase the resilience of water and sanitation technologies and management systems under a range of climate scenarios. Technologies can help abstract source waters from depth, introduce or increase secondary booster disinfection, design or modify systems to reduce residence times within pipes and/or coat exposed pipes ( [[#Levy--2018|Levy et al., 2018]] ). Other efficient interventions include source water protection, promoting water filtration, testing the presence of waterborne pathogens in shellfish, imposing trade restrictions where necessary and improving hygiene at all levels ( [[#Semenza--2021|Semenza and Paz, 2021]] ). Needed actions include early warning and response systems, strengthening the resilience of communities and health systems and promoting ecosystem health, water safety plans and sanitation safety plans ( [[#Brubacher--2020|Brubacher et al., 2020]] ; [[#Cisse--2019|Cisse, 2019]] ; [[#Ford--2018|Ford and Hamner, 2018]] ; [[#Lake--2018|Lake and Barker, 2018]] ; [[#Levy--2018|Levy et al., 2018]] ; [[#Nichols--2018|Nichols et al., 2018]] ; WHO and International Water Association, 2009; WHO, 2016a; [[#WHO--2018b|WHO, 2018b]] ; [[#Semenza--2021|Semenza, 2021]] ; [[#Rocklöv--2021|Rocklöv et al., 2021]] ).

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==== 7.4.2.4 Adaptation Options for Heat-Related Morbidity and Mortality ====

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Adaptations options for heat refer to strategies implemented at short time scales such as air conditioning and HAPs, including heat warning systems and longer-term solutions such as urban design and planning and NbS (Table 7.4).

'''Table 7.4 |''' Summary of adaptation options for key health risks associated with heat.

{| class="wikitable"
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! '''Key risk'''

! '''Geographic region'''

! '''Consequence that would be considered severe, and to whom'''

! '''Hazard conditions that would contribute to this risk being severe'''

! '''Exposure conditions that would contribute to this risk being severe'''

! '''Vulnerability conditions that would contribute to this risk being severe'''

! '''Adaptation options with high potential for reducing risk'''

! '''Selected key references'''

|-
| Heat-related mortality, morbidity and mental illness

| * Global but especially where temperature extremes beyond physical and mental health and thermal comfort threshold levels are expected to increase

| * Substantial increase in heat-related mortality and morbidity rates, especially in urban centres (heat island effect) and rural areas (outside workers), outdoors in general (sports and related activities) and for people suffering from obesity, weak cardiovascular capacity /physical fitness
* Increased risk of respiratory disease and CVD mortality
* Loss of economic productivity
* Substantial increase in mental illness compared to base rate

| * Substantial increase in frequency and duration of extreme heat events, especially in cities where heat will be exacerbated by UHI effects
* Unintended increases in urban temperatures from anthropogenic heat (vehicles, air conditioning, urban metabolism)
* Increased number of days with high temperatures in non-urban settings such as agricultural areas

| * Large increases in urban heat and population heat exposure driven by demographic change (e.g., aging) and increasing urbanisation
* Exposure will increase amongst agricultural and construction workers

| * Mortality/morbidity: Increases in the number of very young and elderly and of those with other health conditions such as lack of physical fitness, obesity, diabetes and associated comorbidities; lack of adaptation capacity
* Mental illness: Lack of air conditioning; lack of access to healthcare systems and services

| * Heat warning systems.
* Improved building and urban design (including green and blue infrastructure) and passive cooling systems, acknowledging that not all will have access to air conditioning
* Broader understanding of heat hazard and better access to public health systems for the most vulnerable
* Application where possible of renewable energy sources
* Communication around drinking water; availability of clean water via simple effective water purification systems in low water quality settings; water spray cooling
* Mental health support

| [[#Benmarhnia--2016|Benmarhnia et al. (2016)]] ; [[#Chen--2019|Chen et al. (2019)]] ; [[#Jay--2021|Jay et al. (2021)]] ; [[#Heo--2019b|Heo et al. (2019b)]] ; [[#Martinez-Solanas--2019|Martinez-Solanas and Basagana (2019)]] ; [[#Morabito--2021|Morabito et al. (2021)]] ; [[#Schwingshackl--2021|Schwingshackl et al. (2021)]]

|}

To date, air conditioning is the main adaptation approach for mitigating the health effects of high temperatures, especially in relation to cardiorespiratory health ( [[#Madureira--2021|Madureira et al., 2021]] ). However, air conditioning may constitute a maladaptation because of its high demands on energy and associated heat emissions, especially in high-density cities ( [[#Eriksen--2021|Eriksen et al., 2021]] ; [[#Magnan--2016|Magnan et al., 2016]] ; [[#Schipper--2020|Schipper, 2020]] ), and also lead to ‘heat inequities’ as this is not an affordable or practical option for many ( [[#Jay--2021|Jay et al., 2021]] ; [[#Turek-Hankins--2021|Turek-Hankins et al., 2021]] ). HAPs link weather forecasts with alert and communication systems and response activities, including public cooling centres, enhanced heat-related disease surveillance and a range of individual actions designed to reduce the health effects of extreme heat events such as seeking shade and altering the pattern of work ( [[#McGregor--2015|McGregor et al., 2015]] ). While well-designed and operationalisable HAPs possess the potential to reduce the likelihood of mortality from extreme heat events ( ''medium confidence'' ) ( [[#Benmarhnia--2016|Benmarhnia et al., 2016]] ; [[#Heo--2019b|Heo et al., 2019b]] ; [[#Martinez-Solanas--2019|Martinez-Solanas and Basagana, 2019]] ; [[#Martinez--2019|Martinez et al., 2019]] ; [[#De’Donato--2018|De’Donato et al., 2018]] ), full process and outcome-based evaluations of HAPs and their constituent components are lacking ( [[#Boeckmann--2014|Boeckmann and Rohn, 2014]] ; [[#Chiabai--2018b|Chiabai et al., 2018b]] ; [[#Boeckmann--2014|Boeckmann and Rohn, 2014]] ; [[#Nitschke--2016|Nitschke et al., 2016]] ; [[#Diaz--2019|Diaz et al., 2019]] ; [[#Benmarhnia--2016|Benmarhnia et al., 2016]] ; [[#Heo--2019a|Heo et al., 2019a]] ; [[#Heo--2019b|Heo et al., 2019b]] ; [[#Ragettli--2019|Ragettli and Roosli, 2019]] ). Evaluations of heatwave early warning systems as a component within HAPs show inconsistent results in terms of their impact on predicting mortality rates ( [[#Nitschke--2016|Nitschke et al., 2016]] ; [[#Benmarhnia--2016|Benmarhnia et al., 2016]] ; [[#Heo--2019a|Heo et al., 2019a]] ; [[#Heo--2019b|Heo et al., 2019b]] ; [[#Ragettli--2019|Ragettli and Roosli, 2019]] ; [[#Martinez--2019|Martinez et al., 2019]] ; [[#De’Donato--2018|De’Donato et al., 2018]] ; [[#Weinberger--2018b|Weinberger et al., 2018b]] ), indicating climate-based heat warning systems, which use a range of heat stress metrics ( [[#Schwingshackl--2021|Schwingshackl et al., 2021]] ), are not sufficient as a stand-alone approach to heat risk management ( ''high confidence'' ). To support HAP and heat risk-related policy development, identification and mapping of heat vulnerability ‘hot spots’ within urban areas have been proposed ( [[#Chen--2019|Chen et al., 2019]] ; [[#Hatvani-Kovacs--2018|Hatvani-Kovacs et al., 2018]] )

''A multi-sectoral approach, including the engagement of a range of stakeholders will'' likely ''benefit the response to longer-term heat risks through the implementation of measures such as climate-sensitive urban design and planning that mitigates UHI effects'' ( ''high confidence'' ) ''( [[#Ebi--2019|Ebi, 2019]] ; [[#Jay--2021|Jay et al., 2021]] ; [[#Alexander--2016|Alexander et al., 2016]] ; [[#Levy--2016|Levy, 2016]] ; [[#Masson--2018|Masson et al., 2018]] ; [[#McEvoy--2019|McEvoy, 2019]] ; [[#Pisello--2018|Pisello et al., 2018]] )'' . In the shorter-term, potentially localised solutions can include awnings, louvers, directional reflective materials, altering roof albedo, mist sprays, evaporative materials, green roofs and building facades and cooling centres ( [[#Jay--2021|Jay et al., 2021]] ; [[#Macintyre--2019|Macintyre and Heaviside, 2019]] ; [[#Spentzou--2021|Spentzou et al., 2021]] ; [[#Takebayashi--2018|Takebayashi, 2018]] ). NbS to reduce heat that offer co-benefits for ecological systems include green and blue infrastructure (e.g., urban greening/forestry and the creation of water bodies) ( [[#Koc--2018|Koc et al., 2018]] ; [[#Lai--2019|Lai et al., 2019]] ; [[#Shooshtarian--2018|Shooshtarian et al., 2018]] ; [[#Ulpiani--2019|Ulpiani, 2019]] ; [[#Zuvela-Aloise--2016|Zuvela-Aloise et al., 2016]] ; [[#Hobbie--2020|Hobbie and Grimm, 2020]] ). The implementation of climate-sensitive design and planning can be constrained by governance issues ( [[#Jim--2018|Jim et al., 2018]] ) and the benefits are not always evenly distributed among residents. Implementation of climate-sensitive design and NbS does, however, need to be carried out within the context of wider public health planning because water bodies and moist vegetated surfaces provide suitable habitats for a range of disease vectors ( [[#Nasir--2017|Nasir et al., 2017]] ; [[#Tian--2016|Tian et al., 2016]] ; [[#Trewin--2020|Trewin et al., 2020]] ). Solutions recommended for managing exposure to heat in outdoor workers include improved basic protection (including shade and planned rest breaks), heat-appropriate personal protective equipment, work scheduling for cooler times of the day, heat acclimation, improved aerobic fitness, access to sufficient cold drinking water and on-site cooling facilities and mechanisation of work ( [[#Morabito--2021|Morabito et al., 2021]] ; [[#Morris--2020|Morris et al., 2020]] ; [[#Varghese--2020|Varghese et al., 2020]] ; [[#Williams--2020|Williams et al., 2020]] ).

Most adaptation options were developed in high- and middle-income countries and typically require significant financial resources for their planning and implementation. Studies are needed of the benefits of indigenous and non-Western approaches to managing and adapting to extreme heat risk. Recently published reviews of approaches to heat adaptation outline the nature and limitations of a range of cooling strategies with optimal solutions for a number of settings recommended ( [[#Jay--2021|Jay et al., 2021]] ; [[#Turek-Hankins--2021|Turek-Hankins et al., 2021]] ).

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==== 7.4.2.5 Adaptation Options for Air Pollution-related Health Effects ====

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As noted in [[#7.3.1.6|Section 7.3.1.6]] , air pollution projections indicate ambitious emission reduction scenarios or stabilisation of global temperature change at 2°C or below would yield substantial co-benefits for air quality-related health outcomes. Improvements in air quality could be achieved by the deliberate adoption of a range of adaptation options to complement mitigation measures such as decarbonisation (e.g., renewable energy, fuel switching, energy efficiency gains and carbon capture storage and utilisation) and negative emissions technologies (e.g., bioenergy carbon capture and storage, soil carbon sequestration, afforestation and reforestation and wetland construction and restoration).

Adaptation options for air pollution include implementing ozone precursor emission control programmes; developing mass transit/efficient public transport systems in large cities; encouraging car-pooling, cycling and walking (active transport); traffic congestion charges; low emission zones in cities; integrated urban planning implementing NbS such as green infrastructure for pollutant interception and removal; managing wildfire risk regionally and across jurisdictional boundaries; developing air quality warning systems; altering activity on high pollution days; effective air pollution risk communication and education; wearing protective equipment such as face masks; avoiding solid fuels for cooking and indoor heating; ventilating and isolating cooking areas; and using portable air cleaners fitted with high-efficiency particulate air filters ( [[#Abhijith--2017|Abhijith et al., 2017]] ; [[#Carlsten--2020|Carlsten et al., 2020]] ; [[#Cromar--2020|Cromar et al., 2020]] ; [[#Ding--2021|Ding et al., 2021]] ; [[#Holman--2015|Holman et al., 2015]] ; [[#Jennings--2021|Jennings et al., 2021]] ; [[#Kelly--2021|Kelly et al., 2021]] ; [[#Kumar--2019|Kumar et al., 2019]] ; [[#Masselot--2019|Masselot et al., 2019]] ; [[#Ng--2021|Ng et al., 2021]] ; [[#Riley--2021|Riley, 2021]] ; [[#Voordeckers--2021|Voordeckers et al., 2021]] ; [[#Xu--2017|Xu et al., 2017]] ; Table 7.5). While the range of air pollution adaptation options is potentially extensive, barriers may need to be overcome to achieve successful implementation, including financial, institutional, political (i.e. inter- and intra-governmental) and social barriers ( [[#Barnes--2014|Barnes et al., 2014]] ; [[#Ekstrom--2018|Ekstrom and Bedsworth, 2018]] ; [[#Fogg-Rogers--2021|Fogg-Rogers et al., 2021]] ; [[#Schumacher--2019|Schumacher and Shandas, 2019]] ).

'''Table 7.5 |''' Summary of adaptation options for key health risks associated with air pollution.

{| class="wikitable"
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! '''Key risk'''

! '''Geographic region'''

! '''Consequence that would be considered severe and to whom'''

! '''Hazard conditions that would contribute to this risk being severe'''

! '''Exposure conditions that would contribute to this risk being severe'''

! '''Vulnerability conditions that would contribute to this risk being severe'''

! '''Adaptation options with high potential for reducing risk'''

! '''Selected key references'''

|-
| Air pollution-related health effects

| * Global, but especially in regions with existing poor air quality, particularly in relation to PM and ozone
* Greatest climate change driven ozone-related mortality is expected for East Asia and North America
* For PM the highest climate and air quality-related mortalities are projected for India, the Middle East, Former Soviet Union and East Asia

| * Substantial increase in air pollution-related mortality and morbidity rates, especially in urban centres, related to both severe pollution episodes and longer-term deterioration of air quality
* People particularly vulnerable include those with RTIs and CVD
* Increase in mental illness (depression) as a result of poor air quality and visibility

| * Non-achievement of emission reduction targets
* Substantial increase in frequency and duration of meteorological conditions conducive to the buildup of both primary and secondary air pollutants (e.g., greater frequency of calm atmospheric ‘blocking’ conditions) and no long-term improvement in air quality at a range of geographical scales (global to local)
* Increase in frequency and intensity of wildfires and dust storms
* Increase in the intensity of UHIs, especially in the summer, and the occurrence of ozone episodes due to anomalously high urban temperatures

| * Large increases in exposure to air pollutants driven by demographic change (e.g., aging) and increasing urbanisation
* For arid regions increases in exposure to dust storms
* Areas adjacent/downwind of major wildfires
* For urban populations intensifying UHIs and enhanced formation of secondary pollutants

| * Increases in the number of very young and elderly and those with respiratory or cardiovascular conditions, and lack of adaptation capacity (e.g., reduced reliance on solid fuel for cooking/heating)
* Mental illness: Lack of access to healthcare systems and services

| * Air quality management policies, air quality warning systems, efficient and cheap mass transit systems, integrated urban planning (including NbS and green infrastructure)
* Broader understanding of air pollution hazard and better access to public health systems for the most vulnerable
* Application where possible of renewable energy sources to reduce emissions

| [[#Carlsten--2020|Carlsten et al. (2020)]] ; Doherty et al. (2017); Jennings et al. (2021); [[#Kumar--2019|Kumar et al. (2019)]] ; Orru et al. (2017); [[#Orru--2019|Orru et al. (2019)]] ; [[#Schumacher--2019|Schumacher and Shandas (2019)]] ; [[#Silva--2017|Silva et al. (2017)]] ; [[#Voordeckers--2021|Voordeckers et al. (2021)]]

|}

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==== 7.4.2.6 Multi-sectoral Adaptation for Risks of Malnutrition ====

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''Adaptation to reduce the risk of malnutrition requires multi-sectoral, integrated approaches'' ( ''very high confidence'' ) ''.'' Adaptation actions include access to healthy, affordable diverse diets from sustainable food systems ''(high confidence)'' ; a combination of access to health—including maternal, child and reproductive health— and nutrition services, water and sanitation ( ''high confidence'' ); access to nutrition-sensitive and shock-responsive social protection ( ''high confidence'' ); and early warning systems ( ''high agreement'' ), risk sharing, transfer, and risk reduction schemes such as index-based weather insurance ''(medium confidence)'' ( [[#Mbow--2019|Mbow et al., 2019]] ; [[#Swinburn--2019|Swinburn et al., 2019]] ; UNICEF/WHO/WBG, 2019; [[#FAO--2021|FAO et al., 2021]] ; [[#Macdiarmid--2019|Macdiarmid and Whybrow, 2019]] ; [[#Liverpool-Tasie--2021|Liverpool-Tasie et al., 2021]] ). Common enablers across adaptation actions that enhance the effectiveness and feasibility of the adaptation include: education, women’s and girls’ empowerment ( ''high confidence'' ), rights-based governance and peacebuilding social cohesion initiatives such as the framework of the Humanitarian Development and Peace Nexus ''(medium confidence).''

''Nutrition-sensitive and integrated agroecological farming systems offer opportunities to increase dietary diversity at household levels while building local resilience to climate-related food insecurity'' ( ''high confidence'' ) ''( [[#Bezner%20Kerr--2021|Bezner Kerr et al., 2021]] ; [[#IPES-Food--2020|IPES-Food, 2020]] ; [[#Altieri--2015|Altieri et al., 2015]] )'' especially when gender equity, racial equity and social justice are integrated ( [[#Bezner%20Kerr--2021|Bezner Kerr et al., 2021]] ). Adaptation responses include a combination of healthy, culturally appropriate and sustainable food systems and diets; soil and water conservation; social protection schemes and safety nets; access to health services; nutrition-sensitive risk reduction; community-based development; women’s empowerment; nutrition-smart investments; increased policy coherence; and institutional and cross-sectoral collaboration ''(high agreement, medium evidence)'' ( [[#FAO--2018|FAO et al., 2018]] ; [[#Mbow--2019|Mbow et al., 2019]] ; [[#Pozza--2020|Pozza and Field, 2020]] ; [[#FAO--2021|FAO et al., 2021]] ; Table 7.7). Nutrition security can be enhanced through consideration of nutrient flows in food systems ( [[#Harder--2021|Harder et al., 2021]] ).This ‘circular nutrient economy’ perspective highlights the potential for adaptations throughout the food supply chain, including sustainable production practices that promote nutrient diversity and density, processing, storage, and distribution that conserves nutrition; equitable access and consumption of available, affordable, appropriate, and healthy foods; and waste management that supports nutrient recovery ( [[#Harder--2021|Harder et al., 2021]] ; [[#Boon--2020|Boon and Anuga, 2020]] ; [[#FAO--2021|FAO et al., 2021]] ; [[#Pozza--2020|Pozza and Field, 2020]] ; [[#Ritchie--2018|Ritchie et al., 2018]] ). Traditional, indigenous and small-scale agroecology and regional food systems provide context-specific adaptations that promote food and nutrition security as well as principles of food sovereignty and food systems resilience ( [[#HLPE--2020|HLPE, 2020]] ; [[#Bezner%20Kerr--2021|Bezner Kerr et al., 2021]] ; [[#IPES-Food--2020|IPES-Food, 2020]] ; [[#IPES-Food--2018|IPES-Food, 2018]] ).

A feasibility and effectiveness assessment was conducted for six adaptation strategies often used and recommended by the UN to respond to malnutrition risks that combined a literature review and expert judgment assessment of 80 peer-reviewed studies (UNSCN, 2010; Tirado et al. 2013; methods adapted from de Coninck et al. (2018) and Singh et al. (2020)). Nineteen indicators of six dimensions of feasibility (economic, technical, social, institutional, environmental and geophysical) were considered. The lead time to initiate and the expected longevity of each option were examined. Feasibility was defined as how significant the reported barriers were to implement a particular adaptation option. Highly feasible options were those where no or very few barriers were reported. Moderately feasible were those where barriers existed but did not have a strong negative effect on the adaptation option (or evidence was mixed). Low feasibility options had multiple barriers reported that could block implementation. Effectiveness ratings were based on expert consultation and reflected the potential of the adaptation option to reduce risk. The final effectiveness and feasibility scores were categorised as high, medium or low and reflect the combined results of all studies for a given adaptation option (Table 7.6).

'''Table 7.6 |''' Feasibility and effectiveness assessments of multi-sectoral adaptation for food security and nutrition.

[[File:67e7bd220e017716d8b76889691a94a7 IPCC_AR6_WGII_Chapter7_Table_7_6.png]]

Adaptive social protection programmes and mechanisms that can support food insecure households and individuals include cash transfers or public work programmes, land reforms, and extension of credit and insurance services that reduce food insecurity and malnutrition during times of environmental stress ( [[#Carter--2018|Carter and Janzen, 2018]] ; [[#Johnson--2013|Johnson et al., 2013]] ; [[#Alderman--2016|Alderman, 2016]] ). For example, children from families participating in Ethiopia’s Productive Safety Net Program experienced improved nutritional outcomes, partly due to better household food consumption patterns and reduced child labour ( [[#Porter--2016|Porter and Goyal, 2016]] ). School feeding programmes improve nutritional outcomes, especially among girls, by promoting education, and by reducing child pregnancy and fertility rates ( [[#Bukvic--2017|Bukvic and Owen, 2017]] ). Adaptive social protection is most effective when it combines climate risk assessment with DRR and wider socioeconomic development objectives ( [[#Davies--2013|Davies et al., 2013]] ).

Transformative approaches towards healthier, more sustainable, plant-based diets require integrated strategies, policies and measures, including economic incentives for the agroecological production and equitable access to and consumption of more fruits, vegetables and pulses; inclusion of sustainability criteria in dietary guidelines, labelling and public education programmes; and promoting collaboration, good governance and policy coherence (Glover, 2019).

'''Table 7.7 |''' Summary of adaptation options for key risks associated with malnutrition.

{| class="wikitable"
|-
! '''Key risk'''

! '''Geographic region'''

! '''Consequence that would be considered severe and to whom'''

! '''Hazard conditions that would contribute to this risk being severe'''

! '''Exposure conditions that would contribute to this risk being severe'''

! '''Vulnerability conditions that would contribute to this risk being severe'''

! '''Adaptation options with high potential for reducing risk'''

! '''Selected key references'''

|-
| Malnutrition due to decline in food availability and increased cost of healthy food

| * Global, with greater risks in Africa, south Asia, Southeast Asia, Latin America, the Caribbean and Oceania

| * Substantial number of additional people at risk of hunger, stunting, and diet-related morbidity and mortality, including decreased mental health and cognitive function
* Micro- and macronutrient deficiencies
* Severe impacts on low-income populations from LIMICs
* Risks especially high for groups that suffer greater inequality and marginalisation

| * Climate changes leading to reductions in crop, livestock or fisheries yields, including temperature and precipitation changes and extremes, drought, and ocean warming and acidification

| * Large numbers of people in areas and markets particularly affected by climate impacts on food security and nutrition

| * High levels of inequality (including gender inequality) and substantial numbers of people subject to poverty or violent conflict, in marginalised groups or with low education levels
* Slow economic development.
* Ineffective social protection systems, nutrition services, and health services

| * Multi-sectoral approach to nutrition-sensitive adaptation and disaster risk reduction/management, including food, health and social protection systems
* Inclusive governance involving marginalised groups
* Improved education for girls and women
* Maternal and child health, water and sanitation, gender equality, climate services and social protection mechanisms

| [[#Glover--2019|Glover and Poole (2019)]] ; [[#Mbow--2019|Mbow et al. (2019)]] ; [[#Swinburn--2019|Swinburn et al. (2019)]]

|}

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<span id="adaptation-options-for-risks-to-mental-health"></span>
==== 7.4.2.7 Adaptation Options for Risks to Mental Health ====

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''Adaptation options for reducing mental health risks associated with extreme weather include preventive and post-event responses'' ( ''high confidence'' ) ''( [[#Brown--2017|Brown et al., 2017]] ; Cohen, 2019; [[#James--2020|James et al., 2020]] ; Table 7.8)'' . Responses include improving funding and access to mental healthcare, which is under-resourced (WHO, 2019a); surveillance and monitoring of psychosocial impacts of extreme weather events; community-level planning for mental health as part of climate-resilience planning ( [[#Clayton--2017|Clayton et al., 2017]] ); and mental health and psychological first aid training for care providers and first responders ( [[#Hayes--2018|Hayes et al., 2018]] ; [[#O’Donnell--2021|O’Donnell et al., 2021]] ; [[#Hayes--2018|Hayes et al., 2018]] ; [[#Taylor--2020|Taylor, 2020]] ; [[#Morgan--2018|Morgan et al., 2018]] ; [[#Sijbrandij--2020|Sijbrandij et al., 2020]] ). Legislation can ensure access to services as well as establish a regulatory framework ( [[#Ayano--2018|Ayano, 2018]] ). Advanced disaster risk planning reduces post-event mental health challenges. One example is from China, where pre-planning of temporary shelters resulted in significantly lower rates of anxiety, depression and PTSD in the aftermath of flooding among displaced people who accessed them ( [[#Zhong--2020|Zhong et al., 2020]] ). Key elements of successful initiatives include coordinated planning and action between key regional agencies and governments with a focus on improving accountability and removing barriers to implementation and subsequent access to programmes ( [[#Ali--2020|Ali et al., 2020]] ). As an example, following the 2019/2020 Australian bushfires, the federal government allocated funds to support mental health through free counselling for those affected, increased access to telehealth, extended hours for mental health services and programmes designed specifically for youth ( [[#Newnham--2020|Newnham et al., 2020]] ).

'''Table 7.8 |''' Summary of adaptation options for key risks associated with mental health.

{| class="wikitable"
|-
! '''Key Risk'''

! '''Geographic region'''

! '''Consequence that would be considered severe and to whom'''

! '''Hazard conditions that would contribute to this risk being severe'''

! '''Exposure conditions that would contribute to this risk being severe'''

! '''Vulnerability conditions that would contribute to this risk being severe'''

! '''Adaptation options with high potential for reducing risk'''

! '''Selected key references'''

|-
| Mental health impacts in response to floods, storms, and wildfires

| * Global; some areas at greater risk for storms, flooding, or wildfires

| * Substantial increase in mental illness compared to base rate

| * Increased frequency of major storms, weather-related flooding or wildfires

| * Low-lying areas, dry areas, urban areas

| * Physical infrastructure that is vulnerable to extreme weather, inadequate emergency response and mental health services, social inequality

| * Improved urban infrastructure, warning systems, and post-disaster social support
* Improved funding and access to mental healthcare
* Improved surveillance and monitoring of mental health impacts of extreme weather events
* Climate change resilience planning in the mental health system (including at a community level
* Mental health first aid training for care providers and first responders

| [[#Ali--2020|Ali et al. (2020)]] ; [[#Ayano--2018|Ayano (2018)]] ; [[#Buckley--2019|Buckley et al. (2019)]] ; [[#Clayton--2017|Clayton et al. (2017)]] ; Hayes et al. (2019); [[#James--2020|James et al. (2020)]] ; [[#Sijbrandij--2020|Sijbrandij et al. (2020)]]

|}

''Because mental health is fundamentally inter-twined with social and economic well-being, adaptation for climate-related mental health risks benefits from wider multi-sectoral initiatives to enhance well-being, with the potential for co-benefits to emerge'' ( ''high confidence'' ) ''.'' Improvements in education, quality of housing, safety and social protection support enhance general well-being and make individuals more resilient to climate risks ( [[#Lund--2018|Lund et al., 2018]] ; Hayes et al., 2019). Among Indigenous Peoples, connections to traditional culture and to place are associated with health and well-being ( [[#Bourke--2018|Bourke et al., 2018]] ) as well as with resilience to environmental change ( [[#Ford--2020|Ford et al., 2020]] ). As an example of the connection between infrastructure improvements and mental health, a study of domestic rainwater harvesting initiatives to promote household water security also improved mental health in participating households ( [[#Mercer--2017|Mercer and Hanrahan, 2017]] ). Adaptive urban design that provides access to healthy natural spaces—an option for reducing risks associated with heat stress—also promotes social cohesion and mitigates mental health challenges ''(high confidence)'' ( [[#Buckley--2019|Buckley et al., 2019]] ; [[#Clayton--2017|Clayton et al., 2017]] ; [[#Jennings--2019|Jennings and Bamkole, 2019]] ; [[#Liu--2020b|Liu et al., 2020b]] ; [[#Mygind--2019|Mygind et al., 2019]] ; [[#Marselle--2020|Marselle et al., 2020]] ).

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<span id="adaptation-options-to-facilitate-early-warning-and-response-systems"></span>
==== 7.4.2.8 Adaptation Options to Facilitate Early-Warning and Response Systems ====

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''Early warning systems are a potentially valuable tool in adapting to climate-related risks associated with infectious diseases when based on forecasts with high skill and when there are effective responses within the time frame of the forecast'' ( ''high confidence'' ) ''.'' Through advanced seasonal weather forecasting that draws upon established associations between weather/climate and infection/transmission conditions, conditions conducive to disease outbreaks can be identified months in advance, providing time to implement effective population health responses ( [[#Morin--2018|Morin et al., 2018]] ). Most current early warning systems are focused on malaria and dengue but there are examples for other diseases, such as an early warning system developed for ''Vibrios'' monitoring in the Baltic Sea ( [[#Semenza--2017|Semenza et al., 2017]] ). An early warning system for dengue outbreaks in Colombia based on temperature, precipitation and humidity successfully detected 75% of all outbreaks between one and five months in advance, detecting 12.5% in the same month ( [[#Lee--2017b|Lee et al., 2017b]] ). Dengue warning systems in Brazil, Malaysia and Mexico have generated satisfactory results ( [[#Hussain-Alkhateeb--2018|Hussain-Alkhateeb et al., 2018]] ). An effective early warning system for malaria was implemented in the Amhara region of Ethiopia ( [[#Merkord--2017|Merkord et al., 2017]] ).

''Early warning systems are effective at detecting and potentially reducing food security and nutrition risks'' ( ''high confidence'' ) ''.'' Examples of proven systems include the United States Agency for International Development (USAID) Famine Early Warning System, the Food and Agricultural Organization’s Global Information and Early Warning System and the World Food Programme’s Corporate Alert System. Such systems are fundamental for anticipating when a crisis might occur and setting priorities for interventions ( [[#Funk--2019|Funk et al., 2019]] ). Financial investments to develop early warning systems are cost-effective and reduce human suffering ( [[#Choularton--2019|Choularton and Krishnamurthy, 2019]] ) ( ''high confidence'' ). For instance, during the 2017 drought-induced food crisis in Kenya, 500,000 fewer people required humanitarian assistance than would have been expected based on past experiences; this was largely due to timely and effective interventions triggered by the early warning ( [[#Funk--2018|Funk et al., 2018]] ).

Early warning systems have been established for other climate-sensitive health outcomes, such as respiratory diseases associated with air pollution ( [[#Shih--2019|Shih et al., 2019]] ; [[#Li--2018|Li and Zhu, 2018]] ; [[#Yang--2017|Yang and Wang, 2017]] ). Early warning systems for non-heat extreme weather and climate events, such as storms and floods, are designed to protect human health and well-being; disaster risk management organisations and institutions typically communicate these warnings through their networks. Research is ongoing to extend the time period for warnings.

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<span id="incorporating-disaster-risk-reduction-into-health-adaptation"></span>
==== 7.4.2.9 Incorporating Disaster Risk Reduction into Health Adaptation ====

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''Integrating health into national disaster risk management plans has wider benefits for resilience and adaptation to climate change risks'' ( ''high confidence'' ) ''( [[#UNFCCC--2017a|UNFCCC, 2017a]] ; [[#Watts--2019|Watts et al., 2019]] )'' . DRR, including disaster preparedness, management and response, is widely recognised as important for reducing health consequences of climate-related hazards and extreme weather events ( [[#Keim--2008|Keim, 2008]] ; [[#Phalkey--2016|Phalkey and Louis, 2016]] ). A systematic review by [[#Islam--2020|Islam et al. (2020)]] identified multiple, ongoing challenges to integrating climate adaptation and DRR at global and national levels, including a lack of capacity among key actors and institutions, a lack of coordination and collaboration across scales of government and general lack of funding—challenges that are particularly relevant for the health sector. Global events, including climate-related extreme events and public health emergencies of international concern (for example, Ebola, Middle East respiratory syndrome (MERS) and COVID-19) have influenced the development of national public health preparedness and response systems and attracted significant investment over the last two decades ( [[#Khan--2015|Khan et al., 2015]] ; [[#Murthy--2017|Murthy et al., 2017]] ; [[#Watson--2017|Watson et al., 2017]] ). The Sendai Framework for Disaster Risk Reduction and the International Health Regulations establish important global and regional goals for increasing health system resilience and reducing health impacts from biological hazards and extreme climate events ( [[#Aitsi-Selmi--2015|Aitsi-Selmi et al., 2015]] ; [[#Maini--2017|Maini et al., 2017]] ; [[#UNFCCC--2017b|UNFCCC, 2017b]] ; [[#Wright--2020|Wright et al., 2020]] ). There are explicit links between the health aspect of the Sendai Framework and UN SDGs 1, 2, 3, 4, 6, 9, 11, 13, 14, 15 and 17 ( [[#Wright--2020|Wright et al., 2020]] ). More specifically, reducing the number of disaster-related deaths, illnesses and injuries, as well as damage to health facilities are key indicators for achieving the goals set out in the Sendai Framework ( [[#UNFCCC--2017b|UNFCCC, 2017b]] ).

The intersection of health and multi-sectoral DRR and management, generally described as health emergency and disaster risk management (health-EDRM), encompasses multi-sectoral approaches from epidemic preparedness and response including the capacities for implementing the International Health Regulations (IHR, 2005), health systems strengthening and health systems resilience ( [[#Lo%20Iacono--2017|Lo Iacono et al., 2017]] ; WHO 2019; [[#Wright--2020|Wright et al., 2020]] ). Health-EDRM costs to governments are notably lower than the cost of inaction ( [[#Peters--2019|Peters et al., 2019]] ). Additional per capita costs in low-income countries have been estimated to range from USD 4.33 (capital) and USD 4.16 (annual recurrent costs), and in upper middle-income countries to an additional USD 1.35 in capital costs and USD 1.41 in extra annual recurrent costs ( [[#Peters--2019|Peters et al., 2019]] ). Adopting a health-EDRM approach supports the systematic integration of health and multi-sectoral EDRM to ensure a holistic approach to health risks and assists in the alignment of action in health security, climate change and sustainable development ( [[#Chan--2017|Chan and Peijun, 2017]] ; [[#Dar--2014|Dar et al., 2014]] ; WHO, 2019; [[#Wright--2020|Wright et al., 2020]] ).

Climate-informed health-EDRM is crucial for the climate resilience of health systems ( [[#WHO--2015a|WHO, 2015a]] ), particularly to account for additional risks and uncertainties associated with climate change and allow for well-planned, effective and appropriate EDRM and adaptation ( [[#Watts--2018a|Watts et al., 2018a]] ; [[#WHO--2013|WHO, 2013]] ; [[#WHO--2015a|WHO, 2015a]] ). Potential coherent approaches to addressing climate change and disaster risks to health include: strengthening health systems; vulnerability and risk assessments that incorporate disaster and climate change risk; building resilience of health systems and health infrastructure; and climate-informed EWSs ( [[#Banwell--2018|Banwell et al., 2018]] ; [[#Phalkey--2016|Phalkey and Louis, 2016]] ). However, a review of DRR projects including climate change in south Asia found that the health sector was the least represented with only 2% of 371 projects relating to health ( [[#Mall--2019|Mall et al., 2019]] ), indicating a need to strengthen the incorporation of climate change in health-EDRM. Current tracking under the Sendai Framework of Disaster Risk Reduction 2015–2030 shows that most countries (particularly low-income countries and lower middle-income countries) still lack robust systems for integrated risk monitoring and early warning ( [[#UNEP--2018|UNEP, 2018]] ). The incorporation of DRR and management strategies into climate adaptation for health and health systems at local scales is particularly important, given that it is at local scales where health services are most often delivered and where knowledge of specific needs and challenges is often greatest ( [[#Amaratunga--2018|Amaratunga et al., 2018]] ; [[#Schramm--2020a|Schramm et al., 2020a]] ). Indigenous knowledge has been shown to be valuable in DRR, with particularly strong evidence existing for drought risk reduction in sub-Saharan Africa ( [[#Fummi--2017|Fummi et al., 2017]] ; [[#Muyambo--2017|Muyambo et al., 2017]] ; [[#Dube--2018|Dube and Munsaka, 2018]] ; [[#Macnight%20Ngwese--2018|Macnight Ngwese et al., 2018]] ). In the USA, DRR strategies that draw upon traditional knowledge and local expertise are being incorporated into climate adaptation planning for health in a number of indigenous communities under the ‘Climate-ready Tribes Initiative’ ( [[#Schramm--2020b|Schramm et al., 2020b]] ).

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<span id="monitoring-evaluation-and-learning"></span>
==== 7.4.2.10 Monitoring, Evaluation and Learning ====

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''Monitoring, evaluation and learning (MEL) can assess the ability of nations and communities to prepare for and adequately respond to the health risks of climate change over time'' ( ''high confidence'' ) ''( [[#Boyer--2020|Boyer et al., 2020]] ).'' MEL describes a process that includes baseline assessment, prioritising actions and activities, identifying key indicators to track, ongoing data collection and periodically considering new information (Kruk et al., 2015). MEL determines whether adaptation options achieved their goals and whether resources were used effectively and efficiently ( [[#Boyer--2020|Boyer et al., 2020]] ). One of the challenges for MEL in the context of adaptation is that climate risks vary as a function of time, location, socioeconomic development, demographics and activities in other sectors ( [[#Ebi--2018a|Ebi et al., 2018a]] ). MEL indicators in the health sector need to account for factors related to governance, implementation and learning as well as for exposures, impacts and programmatic activities, all of which are context dependent and are often outside the health sector ( [[#Boyer--2020|Boyer et al., 2020]] ; [[#Ebi--2018a|Ebi et al., 2018a]] ; [[#Fox--2019|Fox et al., 2019]] ).

''No universal standardised approach exists for monitoring or evaluating adaptation activities in the health sector'' ( ''high confidence'' ) ''.'' Candidate indicators of climate change health impacts and adaptation activity, typically at the national level, are available ( [[#Bowen--2017|Bowen and Ebi, 2017]] ; [[#Cheng--2013|Cheng and Berry, 2013]] ; [[#Kenney--2016|Kenney et al., 2016]] ; [[#Navi--2017|Navi et al., 2017]] ; [[#WHO--2015b|WHO, 2015b]] ). Indicators are best grouped by category of activity, that is, vulnerability, risk and exposure; impacts; and adaptation and resilience ( [[#Ebi--2018a|Ebi et al., 2018a]] ). As health adaptation expands, enhanced monitoring will be needed to ensure that scientific advances are translated into policy and practice. A promising initiative that emerged since the AR5 is the ''Lancet Countdown'' , which represents a global effort at tracking various indicators of exposures, impacts, adaptation activities, finance and media activity related to climate change and health ( [[#Watts--2018a|Watts et al., 2018a]] ), although this effort is principally focused on monitoring and does not explicitly focus on evaluation adaptation efforts or learning from adaptation efforts.

Community-based monitoring of adaptation responses to health impacts, especially by Indigenous Peoples, has not been widely undertaken, despite its potential to improve monitoring of and local adaptation to environmental change ( [[#Kipp--2019|Kipp et al., 2019]] ). The health sector has been particularly weak at recognising the climate impacts on and the adaptation needs of Indigenous Peoples and in engaging Indigenous Peoples in monitoring progress ( [[#Ford--2018|Ford et al., 2018]] ; [[#David-Chavez--2018|David-Chavez and Gavin, 2018]] ; [[#Ramos-Castillo--2017|Ramos-Castillo et al., 2017]] ). Successful adaptation to the health impacts of climate change in Indigenous Peoples requires recognition of their rights to self-determination, focusing on indigenous conceptualisations of well-being, prioritising Indigenous knowledge and understanding the broader agenda of decolonisation, health and human rights ( ''high confidence)'' ( [[#Ford--2015|Ford and King, 2015]] ; [[#Green--2014|Green and Minchin, 2014]] ; [[#Hoy--2014|Hoy et al., 2014]] ; [[#Jones--2019|Jones, 2019]] ; [[#Jones--2014|Jones et al., 2014]] ; [[#Mugambiwa--2018|Mugambiwa, 2018]] ; [[#Nursey-Bray--2018|Nursey-Bray and Palmer, 2018]] ).

Indicators should capture measures of processes that drive adaptation readiness, including leadership, institutional learning and inter-sectoral collaboration ( [[#Boyer--2020|Boyer et al., 2020]] ; [[#Ford--2015|Ford and King, 2015]] ) as well as outcome measures such as the presence of programming known to reduce risks ( [[#Ebi--2018a|Ebi et al., 2018a]] ). Additionally, indicators related to scaling up of effective interventions and relying on the implementation of science frameworks are important ( [[#Damschroder--2009|Damschroder et al., 2009]] ; [[#Theobald--2018|Theobald et al., 2018]] , 2020; [[#Ebi--2018a|Ebi et al., 2018a]] ; [[#Fox--2019|Fox et al., 2019]] ). Measuring impacts attributable to climate change could be addressed with a combination of indicators related to overall health system performance and population vulnerability ( [[#Ebi--2017|Ebi et al., 2017]] ; [[#Ebi--2018a|Ebi et al., 2018a]] ).

<div id="7.4.3" class="h2-container"></div>

<span id="enabling-conditions-and-constraints-for-health-adaptation"></span>