Toward the Next-Generation of Heat-Health Warning Systems and Action Plans

As climate warming accelerates, heat emerges as a major planetary threat. Extended periods of elevated daytime and nighttime temperatures impose cumulative stress on the human body, significantly increasing the risk of heat-related illness and mortality. This, in turn, can overwhelm healthcare capacity, while heat waves can also trigger electricity outages and critical infrastructure and services failures, including disruptions in transport, food supply, and water accessibility. Labor productivity and economic activity also decline under heat stress, particularly in outdoor and manual work sectors such as construction and tourism. These impacts are further exacerbated and expanded by interactions with droughts, wildfires, and atmospheric pollution [1,2,3,4]. In addition to acute extreme heat events, chronic heat—recently coined to describe prolonged heat exposure lasting for months—can induce significant morbidity and reduce quality of life, including impacts such as decreased kidney function [5].

Focusing on the impact of heat on human health, this editorial critically reflects on next-generation heat-health warning systems (HHWSs) and heat-health action plans (HHAPs), building on prior commentary, reviews and research work exploring human thermal perception and heat stress, urban bioclimate, and risk management and communication [6,7,8,9]. Central to this discussion is the understanding that heat is not a single-variable phenomenon, but the product of multiple interacting influences [8]. While air temperature alone can often reveal statistical associations with adverse health outcomes—and thus serves as a convenient epidemiological indicator [9]—it falls short in meaningfully informing heat-health prevention and management [10,11]. This is because humans do not perceive temperature in isolation. Thermal perception and potentially harmful heat stress arise from the combined effects of air temperature, air humidity, short- and long radiation, and wind speed, along with clothing coverage, physical activity, and anthropometric characteristics such as sex and age [8]. This multidimensionality has contributed to the development of numerous thermal indices. Yet, many remain limited by their reliance on a narrow set of variables or by their lack of thermo-physiological grounding [12].

Accordingly, traditional warning systems that rely on meteorologically centered heat wave definitions often neglect the broader impacts of heat on human health, well-being, and productivity. Currently, such simplified systems are operated by most countries worldwide, primarily using maximum air temperature to define heat wave periods and issue alerts [13]. Broadly, a heat wave is understood as an extended period of unusual hot atmospheric conditions [14], but definitions vary widely across regions [13]. These definitions generally fall into two main categories, based on how air temperature thresholds are set. The first relies on fixed absolute values, while the second considers deviations from local norms—typically using historical percentiles, standard deviations, or absolute differences from the mean [14]. Relative thresholds are often preferred for their statistical robustness and adaptability to local climates [14,15], and have informed efforts to harmonize global definitions. For instance, the Intergovernmental Panel on Climate Change (IPCC) defines a heat wave with reference to a relative temperature threshold [16].

In practice though, the establishment of effective warning systems requires more than just a heat wave definitional framework. As World Health Organization (WHO) guidelines emphasize, the integration of epidemiological evidence is necessary to ensure that warnings are closely aligned with public health outcomes [17]. Following these guidelines, threshold-setting for warnings in some countries is based on statistical relationships between heat and mortality [13,18]. These systems, classified as HHWSs, serve as raising awareness tools, but, most importantly, as triggers for short-term interventions [17]. However, past and recent HHWS lack in terms of thermo-physiology or simplicity of thermal indices, as they still primarily conceptualize heat through temperature metrics [13,18]. Only a few countries and regions have adopted more advanced approaches that incorporate multi-variable thermal indices [7,13]. The latter are based on the human energy balance equation and are used to classify levels of thermal perception and stress in ways that are thermo-physiologically relevant to actual health risks [13].

For example, Di Napoli et al. showed that daily maximum values of Universal Thermal Climate Index (UTCI) falling within strong and very strong heat stress categories effectively captured periods of excess mortality in France [19]. Similarly, the national HHWS in Germany identifies hazardous heat conditions according to strong and extreme heat stress categories, determined from perceived temperature (PT) values predicted at 12:00 UTC [20]. Giannaros et al., moreover, found that days classified under strong heat stress conditions using the modified physiologically equivalent temperature (mPET) index were associated with increased mortality risk in Greece. Importantly, the authors also showed that the duration of exposure to strong heat stress within the day plays a critical role in shaping adverse health outcomes [11], a finding that informed the design of the HEAT-ALARM HHWS in Greece [21].

Both the HHWSs in Germany and Greece account for vulnerable and high-risk groups, particularly the elderly and outdoor workers, whose thermo-physiological and occupational characteristics increase their susceptibility to heat stress. Germany’s HHWS introduces a modified reference person, “Klima-Michel Senior”, for PT computations to reflect age-dependent reductions in thermoregulatory capacity, such as decreased sweat production and skin blood flow [20]. Similarly, the HEAT-ALARM HHWS in Greece adopts a stratified population approach using mPET to capture variability in heat stress across the population, distinguishing six demographic groups based on age, sex, and occupational exposure [21]. Both systems also incorporate short-term adaptation mechanisms into their operational logic. Specifically, the HeRATE (health-related assessment of the thermal environment) approach is used to dynamically adjust thermal stress thresholds based on acclimatization patterns over the preceding 30 days. These thresholds are tailored to regions and stratified population groups, ensuring a thermo-physiologically meaningful assessment of heat stress [20,21].

Furthermore, the systems account for urban-specific effects that shape thermal exposure and vulnerability. In Greece, urban dynamics are represented through high-resolution numerical weather prediction coupled with urban canopy modeling, while in Germany, urban heat adjustments are applied using empirically derived relationships [20,21]. These urban considerations are crucial for delivering accurate forecasts and warnings in densely populated areas. Urban bioclimatic factors become especially important at night and play a key role in shaping mitigation strategies through urban planning, design, and architecture. This is particularly relevant for indoor environments, where elevated nighttime temperatures—intensified by intra-urban heat patterns—can compromise thermal comfort and hinder thermo-physiological recovery during sleep. To address this, the HHWS in Germany includes estimates of nocturnal indoor thermal conditions using a dedicated building simulation model. Moreover, warnings are tailored to distinct elevation ranges, allowing for more realistic representations of thermal stress, particularly in areas with complex terrain and variable microclimates. In such regions, especially where population distribution is uneven, it is equally important to ensure that warnings reflect the thermal environment as experienced by people rather than relying on simple areal averages. The HEAT-ALARM HHWS addresses this by applying population-weighted spatial averaging to key forecast variables within each regional unit, thereby enhancing the relevance of its warning outputs [21].

The continued development of such advanced HHWSs requires addressing systemic limitations related to (i) lack of urban-scale realism and socioeconomic targeting, (ii) underrepresentation of co-occurring environmental stressors, and (iii) limited focus of morbidity risks and labor-related vulnerabilities. Specifically, incorporating high-resolution modeling with urban land cover data—such as local climate zones—or coupling with urban canopy models can improve the representation of intra-urban heat stress variability driven by features like sea and land breezes or downslope winds, albeit with added computational cost [22]. The consideration of socioeconomic vulnerability could be achieved by embedding spatial indicators of social disadvantage—such as income, housing quality, and access to green infrastructure—into the risk assessment and communication layers of the system [23]. This enables targeted warnings and response actions that prioritize at-risk communities and support equitable allocation of adaptation resources. Moreover, extreme heat rarely acts alone; it often coincides with elevated UV radiation, atmospheric pollutants (e.g., ozone, particulate matter), bioaerosols such as pollen, and/or rapid weather changes producing compounding exposures that disproportionately affect sensitive and risk groups [24]. Thus, it would be prudent for future HHWSs to account for such co-occurring environmental stressors. Furthermore, while reducing heat-related mortality remains a critical goal, next-generation HHWSs should increasingly emphasize morbidity and workforce functioning indicators [13,25]. Enhancing continuity of care and preserving labor productivity through morbidity-focused interventions can support more equitable and actionable early warning strategies.

Also, personalized thermo-physiological assessments are essential for predicting and monitoring individual heat strain, particularly in indoor settings where much heat-related morbidity and mortality occurs. Innovative tools are increasingly enabling this integration by capturing local and indoor environmental conditions and thermo-physiological and behavioral responses [26,27]. However, implementing such personalized solutions at scale remains challenging. To overcome this, approaches driven by artificial intelligence (AI) can be widely implemented to generate indoor environment forecasts tailored to specific locations, supporting more precise and responsive HHWSs [28]. AI can also be employed to predict heat stress indices, like UTCI, at street-level resolution, offering a computationally efficient alternative to full-scale urban climate models for mapping intra-urban variations in thermal exposure [29]. In parallel, AI-driven analysis of electronic health records can help identify at-risk patients—under adherence to strict standards for data security and confidentiality—supporting timely, personalized warnings and guidance aimed at preventing heat-related health crises and reducing the burden on emergency services [30].

Importantly, HHWSs should be embedded within comprehensive HHAPs to maximize their effectiveness and overcome persistent barriers to adoption, coordination, and operational integration that limit the performance of many existing systems. In particular, the issuance of a warning represents only an initial step; it must be supported by coordinated and context-specific follow-up actions. Effective HHAPs consist of multiple pillars operating across temporal and spatial scales, ranging from long-term resilience planning to medium-term preparatory actions ahead of the warm season, to immediate response measures during severe heat events [17,23]. Among these, information and communication represent a critical foundation.

Beginning with warning levels, a multi-tiered structure—typically comprising four stages—is a standard practice [17]. Communication at each level should ideally be timely, clear, and actionable, informing both the public and institutions about the nature of the threat, its expected impacts, and the corresponding protective measures, which escalate with each stage. For institutions, an effective approach is the use of an “information cascade”, in which warnings are relayed through designated channels to key stakeholders. This enables intermediaries—such as care facilities and social services—to implement timely, sector-specific actions that ensure vulnerable and high-risk populations are adequately protected [31]. One must also consider the challenge of familiarity. Frequent issuance of warnings can lead to public desensitization, reducing perceived urgency and diminishing response effectiveness. Clear differentiation between warning levels and consistent messaging are therefore critical to maintaining trust and ensuring that protective actions are taken when most needed [6].

Concerning responsibilities, the issuance of heat-health warnings and the execution of associated response measures often involve a diverse array of institutional actors, including public health authorities, emergency services, local administrations, and sectoral agencies. In metropolitan areas, coordination may span multiple administrative tiers, requiring clearly assigned roles and robust interdepartmental collaboration. In smaller or more centralized contexts, actions may be coordinated more directly [6,23]. Ensuring consistency and efficiency in such distributed systems necessitates a common framework and operational language. Terms like “heat”, “extreme heat”, “heat waves”, and “heat-health warnings” must be clearly defined and harmonized across meteorological, statistical, epidemiological, and operational perspectives. While meteorology emphasizes atmospheric conditions, epidemiology prioritizes health risk thresholds, and forecasters focus on actionable criteria. A coherent integration of these perspectives supports transparent communication, improves stakeholder alignment, and enhances the effectiveness of interventions throughout the warning-to-response cascade.

Expanding the scope and operational focus of HHAPs is increasingly necessary in light of evolving vulnerability patterns. Aging populations and the rising prevalence of non-communicable diseases—such as cardiovascular and respiratory illnesses, diabetes, and dementia—are making societies more susceptible to heat-related health impacts. In parallel, many urban areas are becoming less resilient, with shrinking green spaces, increasing imperviousness, and inadequate building materials (e.g., metal roofing) that amplify indoor and outdoor heat exposure. While HHAPs traditionally focus on acute heatwave events, the cumulative effects of chronic heat also pose significant threats to public health and workforce productivity, as highlighted by Cruz [5]. Furthermore, conventional HHAPs often operate at national or regional levels, overlooking the localized risk factors and protective conditions that shape heat vulnerability, particularly in densely populated or socioeconomically diverse areas. Addressing these gaps calls for the integration of context-specific assessments—considering local geography, land use, and population characteristics—to inform more responsive and equitable interventions [23]. Ultimately, enhancing awareness, strengthening intersectoral coordination, and tailoring interventions to local and socio-demographic realities will be key to protecting health in a warming world.