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This is the protocol for a Campbell systematic review. The objectives are as follows: Our proposed systematic review and meta-analysis will integrate the evidence available from all sources to answer the following questions: (1) to what extent can information, behavioral and monetary interventions reduce energy consumption of households in residential buildings? (average treatment effect of interventions) (2) what is the relative effectiveness of interventions? (account for heterogeneity in treatment effects across and within studies) (3) how effective are combinations of different interventions?
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Today, more than 70 carbon pricing schemes have been implemented around the globe, but their contributions to emissions reductions remains a subject of heated debate in science and policy. Here we assess the effectiveness of carbon pricing in reducing emissions using a rigorous, machine-learning assisted systematic review and meta-analysis. Based on 483 effect sizes extracted from 80 causal ex-post evaluations across 21 carbon pricing schemes, we find that introducing a carbon price has yielded immediate and substantial emission reductions for at least 17 of these policies, despite the low level of prices in most instances. Statistically significant emissions reductions range between -5% to -21% across the schemes (-4% to -15% after correcting for publication bias). Our study highlights critical evidence gaps with regard to dozens of unevaluated carbon pricing schemes and the price elasticity of emissions reductions. More rigorous synthesis of carbon pricing and other climate policies is required across a range of outcomes to advance our understanding of "what works" and accelerate learning on climate solutions in science and policy.
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In 2023, a series of climatological and political events unfolded, partly driving forward the global climate and health agenda while simultaneously exposing important disparities and vulnerabilities to climate-related events. On the policy front, a significant step forward was marked by the inaugural Health Day at COP28, acknowledging the profound impacts of climate change on health. However, the first-ever Global Stocktake showed an important gap between the current progress and the targets outlined in the Paris Agreement, underscoring the urgent need for further and decisive action. From a Latin American perspective, some questions arise: How do we achieve the change that is needed? How to address the vulnerabilities to climate change in a region with long-standing social inequities? How do we promote intersectoral collaboration to face a complex problem such as climate change? The debate is still ongoing, and in many instances, it is just starting. The renamed regional centre Lancet Countdown Latin America (previously named Lancet Countdown South America) expanded its geographical scope adding Mexico and five Central American countries: Costa Rica, El Salvador, Guatemala, Honduras, and Panama, as a response to the need for stronger collaboration in a region with significant social disparities, including research capacities and funding. The centre is an independent and multidisciplinary collaboration that tracks the links between health and climate change in Latin America, following the global Lancet Countdown's methodologies and five domains. The Lancet Countdown Latin America work hinges on the commitment of 23 regional academic institutions, United Nations agencies, and 34 researchers who generously contribute their time and expertise. Building from the first report, the 2023 report of the Lancet Countdown Latin America, presents 34 indicators that track the relationship between health and climate change up to 2022, aiming at providing evidence to public decision-making with the purpose of improving the health and wellbeing of Latin American populations and reducing social inequities through climate actions focusing on health. This report shows that Latin American populations continue to observe a growing exposure to changing climatic conditions. A warming trend has been observed across all countries in Latin America, with severe direct impacts. In 2022, people were exposed to ambient temperatures, on average, 0.38 °C higher than in 1986-2005, with Paraguay experiencing the highest anomaly (+1.9 °C), followed by Argentina (+1.2 °C) and Uruguay (+0.9 °C) (indicator 1.1.1). In 2013-2022, infants were exposed to 248% more heatwave days and people over 65 years old were exposed to 271% more heatwave days than in 1986-2005 (indicator 1.1.2). Also, compared to 1991-2000, in 2013-2022, there were 256 and 189 additional annual hours per person, during which ambient heat posed at least moderate and high risk of heat stress during light outdoor physical activity in Latin America, respectively (indicator 1.1.3). Finally, the region had a 140% increase in heat-related mortality from 2000-2009 to 2013-2022 (indicator 1.1.4). Changes in ecosystems have led to an increased risk of wildfires, exposing individuals to very or extremely high fire danger for more extended periods (indicator 1.2.1). Additionally, the transmission potential for dengue by Aedes aegypti mosquitoes has risen by 54% from 1951-1960 to 2013-2022 (indicator 1.3), which aligns with the recent outbreaks and increasing dengue cases observed across Latin America in recent months. Based on the 2023 report of the Lancet Countdown Latin America, there are three key messages that Latin America needs to further explore and advance for a health-centred climate-resilient development. Latin American countries require intersectoral public policies that simultaneously increase climate resilience, reduce social inequities, improve population health, and reduce greenhouse gas (GHG) emissions. The findings show that adaptation policies in Latin America remain weak, with a pressing need for robust vulnerability and adaptation (V&A) assessments to address climate risks effectively. Unfortunately, such assessments are scarce. Up to 2021, Brazil is the only country that has completed and officially reported a V&A to the 2021 Global Survey conducted by the World Health Organization (WHO). Argentina, Guatemala, and Panama have also conducted them, but they have not been reported (indicator 2.1.1). Similarly, efforts in developing and implementing Health National Adaptation Plans (HNAPs) are varied and limited in scope. Brazil, Chile, and Uruguay are the only countries that have an HNAP (indicator 2.1.2). Moreover, self-reported city-level climate change risk assessments are very limited in the region (indicator 2.1.3). The collaboration between meteorological and health sectors remains insufficient, with only Argentina, Brazil, Colombia, and Guatemala self-reporting some level of integration (indicator 2.2.1), hindering comprehensive responses to climate-related health risks in the region. Additionally, despite the urgent need for action, there has been minimal progress in increasing urban greenspaces across the region since 2015, with only Colombia, Nicaragua, and Venezuela showing slight improvements (indicator 2.2.2). Compounding these challenges is the decrease in funding for climate change adaptation projects in Latin America, as evidenced by the 16% drop in funds allocated by the Green Climate Fund (GCF) in 2022 compared to 2021. Alarmingly, none of the funds approved in 2022 were directed toward climate change and health projects, highlighting a critical gap in addressing health-related climate risks (indicator 2.2.3). From a vulnerability perspective, the Mosquito Risk Index (MoRI) indicates an overall decrease in severe mosquito-borne disease risk in the region due to improvements in water, sanitation, and hygiene (WASH) (indicator 2.3.1). Brazil and Paraguay were the only countries that showed an increase in this indicator. It is worth noting that significant temporal variation within and between countries still persists, suggesting inadequate preparedness for climate-related changes. Overall, population health is not solely determined by the health sector, nor are climate policies a sole responsibility of the environmental sector. More and stronger intersectoral collaboration is needed to pave development pathways that consider solid adaptation to climate change, greater reductions of GHG emissions, and that increase social equity and population health. These policies involve sectors such as finance, transport, energy, housing, health, and agriculture, requiring institutional structures and policy instruments that allow long-term intersectoral collaboration. Latin American countries need to accelerate an energy transition that prioritises people's health and wellbeing, reduces energy poverty and air pollution, and maximises health and economic gains. In Latin America, there is a notable disparity in energy transition, with electricity generation from coal increasing by an average of 2.6% from 1991-2000 to 2011-2020, posing a challenge to efforts aimed at phasing out coal (indicator 3.1.1). However, this percentage increase is conservative as it may not include all the fossil fuels for thermoelectric electricity generation, especially during climate-related events and when hydropower is affected (Panel 4). Yet, renewable energy sources have been growing, increasing by an average of 5.7% during the same period. Access to clean fuels for cooking remains a concern, with 46.3% of the rural population in Central America and 23.3% in South America lacking access to clean fuels in 2022 (indicator 3.1.2). It is crucial to highlight the concerning overreliance on fossil fuels, particularly liquefied petroleum gas (LPG), as a primary cooking fuel. A significant majority of Latin American populations, approximately 74.6%, rely on LPG for cooking. Transitioning to cleaner heating and cooking alternatives could also have a health benefit by reducing household air pollution-related mortality. Fossil fuels continue to dominate road transport energy in Latin America, accounting for 96%, although some South American countries are increasing the use of biofuels (indicator 3.1.3). Premature mortality attributable to fossil-fuel-derived PM2.5 has shown varied trends across countries, increasing by 3.9% from 2005 to 2020 across Latin America, which corresponds to 123.5 premature deaths per million people (indicator 3.2.1). The Latin American countries with the highest premature mortality rate attributable to PM2.5 in 2020 were Chile, Peru, Brazil, Colombia, Mexico, and Paraguay. Of the total premature deaths attributable to PM2.5 in 2020, 19.1% was from transport, 12.3% from households, 11.6% from industry, and 11% from agriculture. From emission and capture of GHG perspective, commodity-driven deforestation and expansion of agricultural land remain major contributors to tree cover loss in the region, accounting for around 80% of the total loss (indicator 3.3). Additionally, animal-based food production in Latin America contributes 85% to agricultural CO2 equivalent emissions, with Argentina, Brazil, Panama, Paraguay, and Uruguay ranking highest in per capita emissions (indicator 3.4.1). From a health perspective, in 2020, approximately 870,000 deaths were associated with imbalanced diets, of which 155,000 (18%) were linked to high intake of red and processed meat and dairy products (indicator 3.4.2). Energy transition in Latin America is still in its infancy, and as a result, millions of people are currently exposed to dangerous levels of air pollution and energy poverty (i.e., lack of access to essential energy sources or services). As shown in this report, the levels of air pollution, outdoors and indoors, are a significant problem in the whole region, with marked disparities between urban and rural areas. In 2022, Peru, Chile, Mexico, Guatemala, Colombia, El Salvador, Brazil, Uruguay, Honduras, Panama, and Nicaragua were in the top 100 most polluted countries globally. Transitioning to cleaner sources of energy, phasing out fossil fuels, and promoting better energy efficiency in the industrial and housing sectors are not only climate mitigation measures but also huge health and economic opportunities for more prosperous and healthy societies. Latin American countries need to increase climate finance through permanent fiscal commitments and multilateral development banks to pave climate-resilient development pathways. Climate change poses significant economic costs, with investments in mitigation and adaptation measures progressing slowly. In 2022, economic losses due to weather-related extreme events in Latin America were US$15.6 billion -an amount mainly driven by floods and landslides in Brazil-representing 0.28% of Latin America's Gross Domestic Product (GDP) (indicator 4.1.1). In contrast to high-income countries, most of these losses lack insurance coverage, imposing a substantial financial strain on affected families and governments. Heat-related mortality among individuals aged 65 and older in Latin America reached alarming levels, with losses exceeding the equivalent of the average income of 451,000 people annually (indicator 4.1.2). Moreover, the total potential income loss due to heat-related labour capacity reduction amounted to 1.34% of regional GDP, disproportionately affecting the agriculture and construction sectors (indicator 4.1.3). Additionally, the economic toll of premature mortality from air pollution was substantial, equivalent to a significant portion of regional GDP (0.61%) (indicator 4.1.4). On a positive note, clean energy investments in the region increased in 2022, surpassing fossil fuel investments. However, in 2020, all countries reviewed continued to offer net-negative carbon prices, revealing fossil fuel subsidies totalling US$23 billion. Venezuela had the highest net subsidies relative to current health expenditure (123%), followed by Argentina (10.5%), Bolivia (10.3%), Ecuador (8.3%), and Chile (5.6%) (indicator 4.2.1). Fossil fuel-based energy is today more expensive than renewable energy. Fossil fuel burning drives climate change and damages the environment on which people depend, and air pollution derived from the burning of fossil fuels causes seven million premature deaths each year worldwide, along with a substantial burden of disease. Transitioning to sustainable, zero-emission energy sources, fostering healthier food systems, and expediting adaptation efforts promise not only environmental benefits but also significant economic gains. However, to implement mitigation and adaptation policies that also improve social wellbeing and prosperity, stronger and solid financial systems are needed. Climate finance in Latin American countries is scarce and strongly depends on political cycles, which threatens adequate responses to the current and future challenges. Progress on the climate agenda is lagging behind the urgent pace required. While engagement with the intersection of health and climate change is increasing, government involvement remains inadequate. Newspaper coverage of health and climate change has been on the rise, peaking in 2022, yet the proportion of climate change articles discussing health has declined over time (indicator 5.1). Although there has been significant growth in the number of scientific papers focusing on Latin America, it still represents less than 4% of global publications on the subject (indicator 5.3). And, while health was mentioned by most Latin American countries at the UN General Debate in 2022, only a few addressed the intersection of health and climate change, indicating a lack of awareness at the governmental level (indicator 5.4). The 2023 Lancet Countdown Latin America report underscores the cascading and compounding health impacts of anthropogenic climate change, marked by increased exposure to heatwaves, wildfires, and vector-borne diseases. Specifically, for Latin America, the report emphasises three critical messages: the urgent action to implement intersectoral public policies that enhance climate resilience across the region; the pressing need to prioritise an energy transition that focuses on health co-benefits and wellbeing, and lastly, that need for increasing climate finance by committing to sustained fiscal efforts and engaging with multilateral development banks. By understanding the problems, addressing the gaps, and taking decisive action, Latin America can navigate the challenges of climate change, fostering a more sustainable and resilient future for its population. Spanish and Portuguese translated versions of this Summary can be found in Appendix B and C, respectively. The full translated report in Spanish is available in Appendix D.
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Public perception of emerging climate technologies, such as greenhouse gas removal (GGR) and solar radiation management (SRM), will strongly influence their future development and deployment. Studying perceptions of these technologies with traditional survey methods is challenging, because they are largely unknown to the public. Social media data provides a complementary line of evidence by allowing for retrospective analysis of how individuals share their unsolicited opinions. Our large-scale, comparative study of 1.5 million tweets covers 16 GGR and SRM technologies and uses state-of-the-art deep learning models to show how attention, and expressions of sentiment and emotion developed between 2006 and 2021. We find that in recent years, attention has shifted from general geoengineering themes to specific GGR methods. On the other hand, there is little attention to specific SRM technologies and they often coincide with conspiracy narratives. Sentiments and emotions in GGR tweets tend to be more positive, particularly for methods perceived to be natural, but are more negative when framed in the geoengineering context.
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Cambio Climático , Envejecimiento Saludable , Humanos , Salud Global , Política de Salud , ChinaAsunto(s)
Cambio Climático , Combustibles Fósiles , Humanos , Salud Global , Política de Salud , Informe de InvestigaciónRESUMEN
Climate change adaptation responses are being developed and delivered in many parts of the world in the absence of detailed knowledge of their effects on public health. Here we present the results of a systematic review of peer-reviewed literature reporting the effects on health of climate change adaptation responses in low- and middle-income countries (LMICs). The review used the 'Global Adaptation Mapping Initiative' database (comprising 1682 publications related to climate change adaptation responses) that was constructed through systematic literature searches in Scopus, Web of Science and Google Scholar (2013-2020). For this study, further screening was performed to identify studies from LMICs reporting the effects on human health of climate change adaptation responses. Studies were categorised by study design and data were extracted on geographic region, population under investigation, type of adaptation response and reported health effects. The review identified 99 studies (1117 reported outcomes), reporting evidence from 66 LMICs. Only two studies were ex ante formal evaluations of climate change adaptation responses. Papers reported adaptation responses related to flooding, rainfall, drought and extreme heat, predominantly through behaviour change, and infrastructural and technological improvements. Reported (direct and intermediate) health outcomes included reduction in infectious disease incidence, improved access to water/sanitation and improved food security. All-cause mortality was rarely reported, and no papers were identified reporting on maternal and child health. Reported maladaptations were predominantly related to widening of inequalities and unforeseen co-harms. Reporting and publication-bias seems likely with only 3.5% of all 1117 health outcomes reported to be negative. Our review identified some evidence that climate change adaptation responses may have benefits for human health but the overall paucity of evidence is concerning and represents a major missed opportunity for learning. There is an urgent need for greater focus on the funding, design, evaluation and standardised reporting of the effects on health of climate change adaptation responses to enable evidence-based policy action.
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BACKGROUND: The global literature on the links between climate change and human health is large, increasing exponentially, and it is no longer feasible to collate and synthesise using traditional systematic evidence mapping approaches. We aimed to use machine learning methods to systematically synthesise an evidence base on climate change and human health. METHODS: We used supervised machine learning and other natural language processing methods (topic modelling and geoparsing) to systematically identify and map the scientific literature on climate change and health published between Jan 1, 2013, and April 9, 2020. Only literature indexed in English were included. We searched Web of Science Core Collection, Scopus, and PubMed using title, abstract, and keywords only. We searched for papers including both a health component and an explicit mention of either climate change, climate variability, or climate change-relevant weather phenomena. We classified relevant publications according to the fields of climate research, climate drivers, health impact, date, and geography. We used supervised and unsupervised machine learning to identify and classify relevant articles in the field of climate and health, with outputs including evidence heat maps, geographical maps, and narrative synthesis of trends in climate health-related publications. We included empirical literature of any study design that reported on health pathways associated with climate impacts, mitigation, or adaptation. FINDINGS: We predict that there are 15 963 studies in the field of climate and health published between 2013 and 2019. Climate health literature is dominated by impact studies, with mitigation and adaptation responses and their co-benefits and co-risks remaining niche topics. Air quality and heat stress are the most frequently studied exposures, with all-cause mortality and infectious disease incidence being the most frequently studied health outcomes. Seasonality, extreme weather events, heat, and weather variability are the most frequently studied climate-related hazards. We found major gaps in evidence on climate health research for mental health, undernutrition, and maternal and child health. Geographically, the evidence base is dominated by studies from high-income countries and China, with scant evidence from low-income counties, which often suffer most from the health consequences of climate change. INTERPRETATION: Our findings show the importance and feasibility of using automated machine learning to comprehensively map the science on climate change and human health in the age of big literature. These can provide key inputs into global climate and health assessments. The scant evidence on climate change response options is concerning and could significantly hamper the design of evidence-based pathways to reduce the effects on health of climate change. In the post-2015 Paris Agreement era of climate solutions, we believe much more attention should be given to climate adaptation and mitigation options and their effects on human health. FUNDING: Foreign, Commonwealth & Development Office.
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Contaminación del Aire , Enfermedades Transmisibles , Adaptación Fisiológica , Niño , Cambio Climático , Humanos , Aprendizaje AutomáticoRESUMEN
Cities produce more than 70% of global greenhouse gas emissions. Action by cities is therefore crucial for climate change mitigation as well as for safeguarding the health and wellbeing of their populations under climate change. Many city governments have made ambitious commitments to climate change mitigation and adaptation and implemented a range of actions to address them. However, a systematic record and synthesis of the findings of evaluations of the effect of such actions on human health and wellbeing is currently lacking. This, in turn, impedes the development of robust knowledge on what constitutes high-impact climate actions of benefit to human health and wellbeing, which can inform future action plans, their implementation and scale-up. The development of a systematic record of studies reporting climate and health actions in cities is made challenging by the broad landscape of relevant literature scattered across many disciplines and sectors, which is challenging to effectively consolidate using traditional literature review methods. This protocol reports an innovative approach for the systematic development of a database of studies of climate change mitigation and adaptation actions implemented in cities, and their benefits (or disbenefits) for human health and wellbeing, derived from peer-reviewed academic literature. Our approach draws on extensive tailored search strategies and machine learning methods for article classification and tagging to generate a database for subsequent systematic reviews addressing questions of importance to urban decision-makers on climate actions in cities for human health and wellbeing.
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Climate change is already affecting health in populations around the world, threatening to undermine the past 50 years of global gains in public health. Health is not only affected by climate change via many causal pathways, but also by the emissions that drive climate change and their co-pollutants. Yet there has been relatively limited synthesis of key insights and trends at a global scale across fragmented disciplines. Compounding this, an exponentially increasing literature means that conventional evidence synthesis methods are no longer sufficient or feasible. Here, we outline a protocol using machine learning approaches to systematically synthesize global evidence on the relationship between climate change, climate variability, and weather (CCVW) and human health. We will use supervised machine learning to screen over 300,000 scientific articles, combining terms related to CCVW and human health. Our inclusion criteria comprise articles published between 2013 and 2020 that focus on empirical assessment of: CCVW impacts on human health or health-related outcomes or health systems; relate to the health impacts of mitigation strategies; or focus on adaptation strategies to the health impacts of climate change. We will use supervised machine learning (topic modeling) to categorize included articles as relevant to impacts, mitigation, and/or adaptation, and extract geographical location of studies. Unsupervised machine learning using topic modeling will be used to identify and map key topics in the literature on climate and health, with outputs including evidence heat maps, geographic maps, and narrative synthesis of trends in climate-health publishing. To our knowledge, this will represent the first comprehensive, semi-automated, systematic evidence synthesis of the scientific literature on climate and health.
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Active learning for systematic review screening promises to reduce the human effort required to identify relevant documents for a systematic review. Machines and humans work together, with humans providing training data, and the machine optimising the documents that the humans screen. This enables the identification of all relevant documents after viewing only a fraction of the total documents. However, current approaches lack robust stopping criteria, so that reviewers do not know when they have seen all or a certain proportion of relevant documents. This means that such systems are hard to implement in live reviews. This paper introduces a workflow with flexible statistical stopping criteria, which offer real work reductions on the basis of rejecting a hypothesis of having missed a given recall target with a given level of confidence. The stopping criteria are shown on test datasets to achieve a reliable level of recall, while still providing work reductions of on average 17%. Other methods proposed previously are shown to provide inconsistent recall and work reductions across datasets.
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Aprendizaje Automático , Revisiones Sistemáticas como Asunto , Humanos , InvestigaciónRESUMEN
The volume of published academic research is growing rapidly and this new era of "big literature" poses new challenges to evidence synthesis, pushing traditional, manual methods of evidence synthesis to their limits. New technology developments, including machine learning, are likely to provide solutions to the problem of information overload and allow scaling of systematic maps to large and even vast literatures. In this paper, we outline how systematic maps lend themselves well to automation and computer-assistance. We believe that it is a major priority to consolidate efforts to develop and validate efficient, rigorous and robust applications of these novel technologies, ensuring the challenges of big literature do not prevent the future production of systematic maps.