scholarly journals Greening is a promising but likely insufficient adaptation strategy to limit the health impacts of extreme heat

2021 ◽  
Vol 151 ◽  
pp. 106441
Author(s):  
Mathilde Pascal ◽  
Sarah Goria ◽  
Vérène Wagner ◽  
Marine Sabastia ◽  
Agnès Guillet ◽  
...  
Author(s):  
Philip Morefield ◽  
Neal Fann ◽  
Anne Grambsch ◽  
William Raich ◽  
Christopher Weaver

Recent assessments have found that a warming climate, with associated increases in extreme heat events, could profoundly affect human health. This paper describes a new modeling and analysis framework, built around the Benefits Mapping and Analysis Program—Community Edition (BenMAP), for estimating heat-related mortality as a function of changes in key factors that determine the health impacts of extreme heat. This new framework has the flexibility to integrate these factors within health risk assessments, and to sample across the uncertainties in them, to provide a more comprehensive picture of total health risk from climate-driven increases in extreme heat. We illustrate the framework’s potential with an updated set of projected heat-related mortality estimates for the United States. These projections combine downscaled Coupled Modeling Intercomparison Project 5 (CMIP5) climate model simulations for Representative Concentration Pathway (RCP)4.5 and RCP8.5, using the new Locating and Selecting Scenarios Online (LASSO) tool to select the most relevant downscaled climate realizations for the study, with new population projections from EPA’s Integrated Climate and Land Use Scenarios (ICLUS) project. Results suggest that future changes in climate could cause approximately from 3000 to more than 16,000 heat-related deaths nationally on an annual basis. This work demonstrates that uncertainties associated with both future population and future climate strongly influence projected heat-related mortality. This framework can be used to systematically evaluate the sensitivity of projected future heat-related mortality to the key driving factors and major sources of methodological uncertainty inherent in such calculations, improving the scientific foundations of risk-based assessments of climate change and human health.


2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Nancy VanStone ◽  
Adam Van Dijk ◽  
Paul Belanger ◽  
Kieran Moore

ObjectiveTo describe the lessons learned for public health decision-makers from an analysis of Acute Care Enhanced Surveillance (ACES) data for the heatwaves experienced in Ontario, Canada in the summer of 2018.IntroductionThe Acute Care Enhanced Surveillance (ACES) system provides syndromic surveillance for Ontario’s acute care hospitals. ACES receives over 99% of acute care records for emergency department (ED) visits; mean daily volume is 17,500 visits. ACES uses a maximum entropy classifier and generates more than 80 standard syndromes, fifteen of which are actively monitored for aberrational activity and are considered of higher public health relevance, including RESP (respiratory infection, non-croup), ILI (influenza-like illness), TOX (toxicological, chemical/drug exposure), AST (asthma), OPI (opioid exposure), CELL (cellulitis), GASTRO (gastroenteritis), ENVIRO (environmental, heat/cold exposure), MH (mental health), EOH (alcohol intoxication), DERM (rash), and SEP (bacteremia, sepsis).Syndromic surveillance provides a salient source of public health surveillance during extreme heat events; monitoring real-time ED visits can inform local public health authorities of health impacts, provide situation awareness to initiate and/or inform public health response, and help decision-makers allocate resources according to geographic (or demographic) vulnerability. While the use of syndromic surveillance has been well-characterized to monitor infectious disease outbreaks, its use to monitor the heat-health impacts is relatively novel for ACES users, specifically local public health authorities. This report describes the the data collected during an extended extreme heat event in Ontario, Canada, to highlight the value of syndromic surveillance during extreme heat events and make recommendations regarding incorporating ACES data into routine workflows.MethodsTemperature data were retrieved from Environment Canada historical databases for mid-June to mid-July 2018. Aggregate counts per day for total ED visits and and for individual syndromes were retrieved from ACES databases. Descriptive statistics were used to analyze all datasets.ResultsAn extreme heat event occurred in the southern region of Ontario in early summer, 2018. Environment Canada issues heat warnings for regions throughout Canada according to region-specific criteria; for southern Ontario, heat warnings are issued when 2 or more consecutive days of daytime maximum temperatures are expected to reach 31°C or when 2 or more consecutive days of humidex values are expected to reach 40. Extended heat warnings are issued when the event lasts beyond 2 days. An extended heat event occurred June 29 to July 5, 2018. Although the region is large, temperature data from Environment Canada’s climate monitoring station at Toronto’s Pearson Airport are shown (Figure 1) as an example of the temperatures observed for this time period in the region.ConclusionsLessons learned from an analysis of ACES data during an extreme heat event:1. The ENVIRO syndrome provides real-time monitoring of the health impacts during a heat event and may provide proxy for estimating the indirect effects of heat (e.g., impacts on chronic conditions). Public health authorities can monitor local health impacts during an extreme heat event.2. Patients seeking help at the ED do not appear to be skewed in acuity, sex nor age. This does not necessarily reflect the population that experiences the greatest impact from extreme heat, but rather those that are seeking help at the ED for the direct effects of heat. That said, an increase in ENVIRO counts does not indicate whether the increase is due to greater exposure to the heat (or sun), engaging in vigorous outdoor activity during the event (recreational or occupational), or lack of access to air conditioning.3. ED visits for ENVIRO can be geolocated to determine areas experiencing greater health impacts. This may allow allocation of resources to specifically address vulnerabilities. ACES has built-in mapping capabilities that allows a geovisualization of the home addresses for patients. Furthermore, aggregate counts for relevant syndromes are available for registered users on the Public Health Information Management System (PHIMS), a web-accessible GIS tool for situational awareness that gives public health decision-makers access to real time health impacts in concert with demographics, weather, and other emergency management information. 


2020 ◽  
Author(s):  
Eunice Lo ◽  
Dann Mitchell ◽  
Antonio Gasparrini ◽  
Ana Vicedo-Cabrera

<p>Extreme heat is associated with increased risks of human mortality. In a warming climate, extreme heat events are projected to intensify and become more frequent, potentially adversely affecting human health. The Paris Agreement aims at limiting global mean temperature rise this century to well below 2°C above pre-industrial levels, but mitigation ambition as established in nations’ initial Nationally Determined Contributions still implies ~3°C warming. Quantifying the differences in extreme heat-related mortality between 1.5, 2 and 3°C warming is essential to understanding the public health impacts of climate policies and how societies may adapt to a warming climate.</p><p>In this talk, I will show a new approach to projecting extreme heat-related mortality using the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) large ensemble and health models. The large ensemble of HAPPI simulations of the 1.5, 2 and 3°C warmer worlds allows extreme heat events and their health impacts in these worlds to be examined, rather than the mean climates. Using published case studies of the United States and Europe; I will demonstrate that limiting global mean warming from 3°C to 2°C or 1.5°C above pre-industrial levels could reduce heat-related mortality associated with extreme heat events, with the 1.5°C limit being substantially more beneficial to public health than 2°C. In addition to climate change, I will discuss the roles of urbanisation, population changes and adaptation in future extreme heat exposure and heat-related mortality.</p>


2021 ◽  
pp. 111738
Author(s):  
Jihoon Jung ◽  
Christopher K. Uejio ◽  
Temilayo E. Adeyeye ◽  
Kristina W. Kintziger ◽  
Chris Duclos ◽  
...  

2013 ◽  
Vol 52 (12) ◽  
pp. 2669-2698 ◽  
Author(s):  
Barbara Casati ◽  
Abderrahmane Yagouti ◽  
Diane Chaumont

AbstractPublic health planning needs the support of evidence-based information on current and future climate, which could be used by health professionals and decision makers to better understand and respond to the health impacts of extreme heat. Climate models provide information regarding the expected increase in temperatures and extreme heat events with climate change and can help predict the severity of future health impacts, which can be used in the public health sector for the development of adaptation strategies to reduce heat-related morbidity and mortality. This study analyzes the evolution of extreme temperature indices specifically defined to characterize heat events associated with health risks, in the context of a changing climate. The analysis is performed by using temperature projections from the Canadian Regional Climate Model. A quantile-based statistical correction is applied to the projected temperatures, in order to reduce model biases and account for the representativeness error. Moreover, generalized Pareto distributions are used to extend the temperature distribution upper tails and extrapolate the statistical correction to extremes that are not observed in the present but that might occur in the future. The largest increase in extreme daytime temperatures occurs in southern Manitoba, Canada, where the already overly dry climate and lack of soil moisture can lead to an uncontrolled enhancement of hot extremes. The occurrence of warm nights and heat waves, on the other hand, is already large and will increase substantially in the communities of the Great Lakes region, characterized by a humid climate. Impact and adaptation studies need to account for the temperature variability due to local effects, since it can be considerably larger than the model natural variability.


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