Evaluations of heat action plans for reducing the health impacts of extreme heat: methodological developments (2012-2021) and remaining challenges

Comprehensive evaluation framework for intervention on health effects of ambient temperature

Despite the existence of many interventions to mitigate or adapt to the health effects of climate change, their effectiveness remains unclear. Here, we introduce the Comprehensive Evaluation Framework for Intervention on Health Effects of Ambient Temperature to evaluate study designs and effects of intervention studies. The framework comprises three types of interventions: proactive, indirect, and direct, and four categories of indicators: classification, methods, scope, and effects. We trialed the framework by an evaluation of existing intervention studies. The evaluation revealed that each intervention has its own applicable characteristics in terms of effectiveness, feasibility, and generalizability scores. We expanded the framework's potential by offering a list of intervention recommendations in different scenarios. Future applications are then explored to establish models of the relationship between study designs and intervention effects, facilitating effective interventions to address the health effects of ambient temperature under climate change.

Composition of factors for local heat adaptation measures at the local level in cities of the mid-latitude - An approach for the south-west of Germany

Traditional heat health warning systems focus on severe and extreme heat events at the district or regional level, often overlooking localized risk and protective factors such as healthcare access and urban green spaces. This approach considers less the varying impacts of heat within cities, including the phenomenon of Urban Heat Islands (UHIs) and the diverse needs of different populations. To address these shortcomings, a need for the development of an Urban Heat Health Warning and Information System (UHHWIS) that operates within the framework of Heat Health Action Plans is needed. Such a system integrates national acute heat health warnings with city-specific assessments of UHI effects and other relevant factors. The technical implementation of the UHHWIS involves the calculation and preprocessing of basic factors such as the Normalised Difference Vegetation Index (NDVI), imperviousness, and UHI intensity. Additionally, further factors are assessed, spatially processed, and provided in accordance with Open Geospatial Consortium (OGC) standards. An iso-area analysis is conducted to evaluate the accessibility of protective factors, such as urban green spaces, drinking wells, hospitals, physicians, and pharmacies, based on the city's road topology. One crucial factor considered in the system is the casting of shadows, which is influenced by both time and location and facilitated through deck.gl. The developed template encompasses all these components into a unified system aimed at protecting vulnerable and risk groups, such as the elderly, through resilient, climate-adapted urban planning. The system provides warnings and information tailored to the urban morphology and prevailing conditions, complemented by a catalogue of potential short- to long-term measures focused on behavioral changes and climate-resilient urban planning strategies. The template can be adapted for use in various European cities, offering valuable insights to decision-makers in city administration for mitigating thermal stress and enhancing resilience against urban heat nowadays and in future.

Vulnerability assessment of heat waves within a risk framework using artificial intelligence

Current efforts to adapt to climate change are not sufficient to reduce projected impacts. Vulnerability assessments are essential to allocate resources where they are needed most. However, current assessments that use principal component analysis suffer from multiple shortcomings and are hard to translate into concrete actions. To address these issues, this article proposes a novel data-driven vulnerability assessment within a risk framework. The framework is based on the definitions from the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, but some definitions, such as sensitivity and adaptive capacity, are clarified. Heat waves that occurred between 2001 and 2018 in Quebec (Canada) are used to validate the framework. The studied impact is the daily mortality rates per cooling degree-days (CDD) region. A vulnerability map is produced to identify the distributions of summer mortality rates in aggregate dissemination areas within each CDD region. Socioeconomic and environmental variables are used to calculate impact and vulnerability. We compared abilities of AutoGluon (an AutoML framework), Gaussian process, and deep Gaussian process to model the impact and vulnerability. We offer advice on how to avoid common pitfalls with artificial intelligence and machine-learning algorithms. Gaussian process is a promising approach for supporting the proposed framework. SHAP values provide an explanation for the model results and are consistent with current knowledge of vulnerability. Recommendations are made to implement the proposed framework quantitatively or qualitatively.

The Direct and Indirect Influences of Interrelated Regional-Level Sociodemographic Factors on Heat-Attributable Mortality in Europe: Insights for Adaptation Strategies

BACKGROUND

Heat is a significant cause of mortality, but impact patterns are heterogenous. Previous studies assessing such heterogeneity focused exclusively on risk rather than heat-attributable mortality burdens and assume predictors are independent.

OBJECTIVES

We assessed how four interrelated regional-level sociodemographic predictors-education, life expectancy, the ratio of older to younger people (aging index), and relative income-influence heterogeneity in heat-attributable mortality burdens in Europe and then derived insights into adaptation strategies.

METHODS

We extracted four outcomes from a temperature-mortality study covering 16 European countries: the rate of increase in mortality risk at moderate and extreme temperatures (moderate and extreme slope, respectively), the minimum mortality temperature percentile (MMTP), and the underlying mortality rate. We used structural equation modeling with country-level random effects to quantify the direct and indirect influences of the predictors on the outcomes.

RESULTS

Higher levels of education were directly associated with lower heat-related mortality at moderate and extreme temperatures via lower slopes and higher MMTPs. A one standard deviation increase in education was associated with a - 0.46 ± 0.14 , - 0.41 ± 0.12 , and 0.41 ± 0.12 standard deviation (± standard error ) change in the moderate slope, extreme slope, and MMTP, respectively. However, education had mixed indirect influences via associations with life expectancy, the aging index, and relative income. Higher life expectancy had mixed relations with heat-related mortality, being associated with higher risk at moderate temperatures (0.33 ± 0.11 for the moderate slope; - 0.19 ± 0.097 for the MMTP) but lower underlying mortality rates (- 0.72 ± 0.097 ). A higher aging index was associated with higher burdens through higher risk at extreme temperatures (0.13 ± 0.072 for the extreme slope) and higher underlying mortality rates (0.93 ± 0.055 ). Relative income had relatively small, mixed influences.

DISCUSSION

Our novel approach provided insights into actions for reducing the health impacts of heat. First, the results show the interrelations between possible vulnerability-generating mechanisms and suggest future research directions. Second, the findings point to the need for a dual approach to adaptation, with actions that explicitly target heat exposure reduction and actions focused explicitly on the root causes of vulnerability. For the latter, the climate crisis may be leveraged to accelerate ongoing general public health programs. https://doi.org/10.1289/EHP11766.