Establishing an app-based heat-health warning system via collaboration with stakeholders

The frequency of extreme heat events, such as the summer of 2003 in Europe, and their corresponding consequences for human beings are expected to increase under a warmer climate. The joint collaboration of institutional agencies and multidisciplinary approaches is essential for a successful development of heat-health warning systems and action plans which can reduce the impacts of extreme heat on the population. The present work constitutes a state-of-the-art review of 16 European heat-health warning systems and heat-health action plans, based on the existing literature, web search (over the National Meteorological Services websites) and questionnaires. The aim of this study is to pave the way for future heat-health warning systems, such as the one currently under development in the framework of the Horizon 2020 HEAT-SHIELD project. Some aspects are highlighted among the variety of examined European warning systems. The meteorological variables that trigger the warnings should present a clear link with the impact under consideration and should be chosen depending on the purpose and target of the warnings. Setting long-term planning actions as well as pre-alert levels might prevent and reduce damages due to heat. Finally, education and communication are key elements of the success of a warning system.

Due to climate change, the intensity, duration and frequency of heatwaves are likely to increase in the coming years. Excessive heat events can increase local urban heat island intensity affecting the health and wellbeing of urban dwellers vulnerable to heat stress. Heat-Health Warning Systems (HHWSs) have been developed to warn the public of impending heat events and to advise on preventable negative health outcomes. However, metrics upon which action triggers are made in HHWSs rely on reported critical outcomes, such as heat-related excess death. Thus, human exposure to heat is underestimated in current metrics and consequently, their capacity to prevent heat-related health risks remains uncertain, particularly indoors. This study investigates how indoor heat stress in urban dwellings at a city-scale can be modelled to enhance Heat-Health Warning and Planning. First, the effects of housing typologies on indoor thermal conditions are quantified in a local urban microclimate context. We then model the dynamic relationships between outdoor climate and indoor heat exposure to identify specific outdoor climatic thresholds as action triggers for alerting urban dwellers’ indoor heat stress. Based on urban microclimate data available for a city of Birmingham UK, a proof-of-principle study is presented. The result shows the presence of large variances in the heat-health action triggers across different housing typologies. This is further extended to consider the Birmingham climate projection scenarios provided by the UKCP18. Compared to the current UK Heat-Health Alert Service, we show how indoor heat stress warnings may look like and the implications for long-term heat-health planning.

This study compared the accuracy and sensitivity of the Wet-Bulb Globe Temperature (WBGT) models developed based on domestic and international studies. The applicability of these models to formal weather observatory and user-installed sites such as the military training centers in Korea were evaluated. For the WBGT estimation, a physical model and four empirical models were used. A Liljegren model, which is known to have high accuracy, was used as the physical model. The KMA2006, JME (four-variable), KMA2016, and ABM (two-variable) models were used as the empirical models. The root-mean-square errors (RMSE) of ABM and Liljegren models obtained in this study are approximately 1 ℃ higher than RMSE results in US and New Zealand. The KMA2006 and JME models demonstrated high accuracy at RMSE of 0.45 ℃. The KMA2016 model performed better in the simulation than the physical model (RMSE of 1.06 ℃) even though only two variables were used. In particular, the KMA2016 model demonstrated good performance in the central region of the Korean peninsula, including the military training centers (RMSE of 0.75 ℃). However, it was underestimated in the southern part of the peninsula. Its performance became worse except for the time occurring maximum temperature. Therefore, at the Automated Surface Observing System stations where solar radiation and wind speed data are available, the KMA2006 and JME models can outperform other models. In the military, school, and industrial sites where only air temperature and relative humidity are observed, we expect that the WBGT can be estimated within an error range of ±0.6 ℃ using the KMA2016 model. Keywords: WBGT, Heat Stress, Heat Health Warning System, Thermal Index, ISO 7243

ZusammenfassungHintergrundMenschen sind im Zuge des Klimawandels immer stärker von Hitze und deren negativen gesundheitlichen Auswirkungen betroffen. Oftmals wird die Lufttemperatur als Maßzahl verwendet. Um jedoch Auswirkungen von Hitze auf den Menschen zu charakterisieren, müssen neben der Lufttemperatur weitere Faktoren berücksichtigt werden.Ziel der ArbeitZiel dieses Beitrags ist es, den Hitzestress von Bewohnern in Städten mithilfe der Gefühlten Temperatur während Hitzewellen zu charakterisieren und mit derjenigen von Bewohnern auf dem Land zu vergleichen sowie Unterschiede zur Lufttemperatur hervorzuheben.Material und MethodenDaten der Stadtstation Freiburg und der Station Freiburg-Flugplatz für 2019 des Deutschen Wetterdienstes (DWD) wurden für die Analyse der Lufttemperatur sowie für die Berechnung der Gefühlten Temperatur mithilfe des Klima-Michel-Modells für Freiburg verwendet. Zusätzlich werden die Hitzewarntage für Freiburg dargestellt und die nächtlichen Bedingungen der Innenraumtemperaturen des Hitzewarnsystems analysiert.Ergebnisse und DiskussionDie Gefühlte Temperatur übersteigt die Lufttemperatur während Hitzewellen um bis zu 10 °C. Während der klassische Wärmeinseleffekt anhand der Differenz der nächtlichen Lufttemperatur hoch und tagsüber gering ist, ist bei der Gefühlten Temperatur die Differenz nicht nur nachts, sondern auch tagsüber deutlich höher.FazitUm negative Auswirkungen zu quantifizieren, wird nicht nur die Lufttemperatur benötigt, sondern auch die Kenntnis über weitere Faktoren, die den Hitzestress beschreiben und steuern. Stadt-Land-Unterschiede bei Lufttemperatur und Gefühlter Temperatur bilden eine gute Möglichkeit der Quantifizierung von Hitze. Anpassungsmaßnahmen in Städten unter Berücksichtigung des Hitzestresses für Menschen sind notwendig.

Heat-health early warning systems (HHWS) are an important collaborative activity between the meteorological and health communities. This study aimed to map the evidence on the socioeconomic assessment of HHWS and their effectiveness in terms of averting heat related health outcomes. It also aimed to map the technical, structural, and societal barriers and facilitators to implementation and use of HHWS. We use two methods: (i) a scoping review of literature on the economic assessment and health benefit of climate services for heat-health adaptation (ii) a set of interviews with climate service developers and providers in Europe and Africa to understand further technical and societal aspects as well as evaluation of such services. We find that HHWS can be a cost-effective adaptation option that can reduce heat-related mortality and morbidity, especially in vulnerable groups like the elderly. We find that challenges such as lack of long-term and reliable funding, difficulties in making the climate data relevant, comprehensible, and accessible to different end-users, cultural differences between climate and health professionals, and limited ability to assess the services' real impact need to be accounted for while implementing these services.

Purpose of ReviewHeat Health Warning Systems (HHWS) reduce heat-related morbidity and mortality. We reviewed scientific studies on HHWS that use meteorological variables, local climate-epidemiological evidence, personalization, and built environment factors to determine heat stress thresholds. We identified key factors to enhance their precision and effectiveness.Recent FindingsWe categorized the findings into three groups. First, most HHWS rely on temperature-mortality relationships. Second, future HHWS should integrate climate-epidemiology data, including cause-specific mortality and morbidity. Third, improvements can be made by incorporating local, built environment, and personalized factors. Our findings highlight a diverse range of factors that can influence the nature of heat warnings and contribute to improving HHWS.SummaryTemperature based HHWS are predominantly used across the world while other meteorological variables that include humidity and take actual health impact outcomes based on heat stress indices should be included for better protection. The precision of HHWS can be improved by tapping advancements in digital technologies to develop more targeted HHWS without the need for authorities to issue warnings, and by considering built environment, and personalized factors. The effectiveness of HHWS can be further improved by considering local climate-epidemiological evidence including morbidity and actual health outcomes.

In Portugal a Heat Health Watch Warning exists since 1999—the íCARO Surveillance System. It is a system for monitoring heatwaves with potential impacts on population's morbidity and mortality, which is set in motion every year between May and September. This system was based on a model for the relation between heat and mortality calibrated with the district of Lisbon data for the big heatwaves of June 1981 and July 1991.The occurrence of 2003's big heatwave brought opportunity for updating existing models.The fact that this heatwave has been particularly long and had characteristics that were not described in the previously known heatwave episodes also allowed the chance to investigate the mechanism of the relation between occurrence of extreme heat and mortality.The aim of this work was to update the existing íCARO model and contribute to increase the knowledge on the phenomena of the heatwave's impact on mortality.Thus, four models were assayed, that represent four distinct proposals for reference temperature's thresholds and in the generalization of the main used variable accumulated thermal overcharge (ATO).All the assayed models showed a good adaptation to the observed mortality data for the district of Lisbon for the three known big heatwaves.It is concluded that the rational generalized accumulated thermal overload (GATO) adapts well to the relation between heat and mortality. The best model was chosen as the one that considered a dynamic threshold that follows the ascending phase of the temperatures of summer until reaching its maximum level in the end of the month of August remaining thereafter constant until the end of the summer, thus recurring to a rational of population's adaptation to heat, contrarily to what happens to air temperatures that decrease at end of the summer. Copyright © 2007 Royal Meteorological Society

<title>Abstract</title> Heat-related mortality during extreme heat events exhibits delayed, non-linear dynamics that cannot be explained by static environmental thresholds or simple cumulative exposure metrics alone. This paper introduces <bold>PYROX</bold> (Populational Yield for Relative Outdoor eXposure), a control-theory-inspired framework that models human heat stress response as a cascaded dual-process system with <bold>bidirectional feedback</bold> . The model formalizes the dynamic interaction between <bold>short-term physiological acclimatization (α)</bold> and <bold>cumulative physiological strain (Σ)</bold> , coupling them through a closed loop in which accumulated strain progressively suppresses acclimatization capacity, and diminished acclimatization in turn increases the rate of strain accumulation. This mutual feedback creates a non-linear instability mechanism. Using a discrete-time formulation, I demonstrate the existence of a <bold>critical strain threshold (Σ_critical)</bold> beyond which adaptation collapses and the system becomes unstable, leading to runaway decompensation under continued exposure. Analytical stability analysis shows this threshold emerges as a mathematical property of the feedback structure. The framework provides a mechanistic explanation for delayed mortality peaks and abrupt health deterioration during prolonged heatwaves. It enables explicit prediction of <bold>intervention windows</bold> , <bold>time-to-critical transitions</bold> , and <bold>population-specific vulnerability</bold> , offering a dynamic alternative to current heat-health warning systems.

This study assesses the relationship between daily maximum temperature and healthcare interactions (admissions and emergency visits) among patients with cardiovascular, respiratory, and diabetic conditions in Vallès Occidental, Spain (2015–2022). Using distributed lag non-linear models (DLNM), we quantify temperature-related risk while accounting for lagged effects and seasonality. Results show significant associations especially with higher temperatures. These findings underscore the need for improved, disease-specific heat-health warning systems and more granular consideration of comorbidities in climatehealth vulnerability assessments.