Heatwaves and healthcare: bridging data and frontline practice

Heatwaves and related environmental events expose critical vulnerabilities in overburdened health systems and underscore the need to integrate clinical and environmental data to support timely public health interventions. However, healthcare professionals’ participation in data collection is often limited by high workloads and fragmented, restrictive health information system architectures. This article explores strategies to strengthen the link between public health data production and clinical response to mitigate the health risks associated with heatwave events. Field immersion programs for epidemiologists enhance understanding of operational constraints and promote the design of pragmatic interventions. However, the lack of standardized health measures and a widely accepted conceptual framework limits the effectiveness of heatwave epidemiology. We argue that such approaches can systematically improve the validity, applicability, and equity of public health research and practice, and propose a framework for standardized health monitoring during heatwaves.

Les vagues de chaleur et les événements environnementaux associés révèlent les vulnérabilités des systèmes de santé surchargés et soulignent la nécessité d›intégrer les données cliniques et environnementales afin de soutenir la mise en place d’actions rapides de santé publique. Cependant, la participation des professionnels de santé à la collecte de données reste limitée en raison de charges de travail élevées et d’une architecture des systèmes d’information sanitaire souvent fragmentée et restrictive. Dans cet article, nous examinons les moyens de renforcer le lien entre la production de données de santé publique et la réponse clinique afin de mieux atténuer les risques sanitaires liés aux vagues de chaleur. Les programmes d’immersion sur le terrain pour les épidémiologistes permettent de mieux comprendre les contraintes opérationnelles et de concevoir des interventions plus pragmatiques. Toutefois, l’absence de mesures sanitaires standardisées et d’un cadre conceptuel largement accepté continue de limiter l’efficacité de l’épidémiologie des vagues de chaleur.

A RAPIDLY CHANGING CONTEXT

Healthcare systems worldwide face increasing challenges. Climate changes, reflected in the rising frequency and severity of heatwaves [1], is further compounded by the resurgence of epidemics [2], population ageing [3], and structural economic pressures [4]. Together, these factors strain healthcare organizations, exacerbate health inequalities, and heighten demands on professionals’ capacity to respond [5].

Heatwaves are gradually becoming a public health priority [6],[7]. They are directly linked to heatstroke and disrupted sleep patterns and indirectly associated with poorer mental health, increased interpersonal violence, and exacerbations of underlying cardiovascular and respiratory diseases [8],[9],[10],[11]. Although awareness of heatwaves as a public health issue has grown, their indirect health consequences remain insufficiently explored. Forest and peri-urban fires, which occur more frequently during periods of extreme heat, not only cause injuries and population displacement [12] but also increase exposure to fine particulate matter, contributing to respiratory morbidity, in addition to the physiological effects of heat stress [12]. These crises span multiple disciplines and require sustained integration of environmental and health data – including temperature, air quality, patient health indicators, and frontline care metrics – to inform effective responses. Healthcare professionals are responsible for implementing preventive and educational measures to reduce health impacts while also providing care to affected patients. At the same time, these hazards demand robust population-level analyses and early warning systems to monitor trends, alert the public and healthcare workers, and guide public policy and resource allocation. This article aims to explore strategies to strengthen the connection between public health data production and clinical response in order to mitigate the health risks associated with heatwave events.

A SHARED MONITORING SYSTEM BETWEEN EPIDEMIOLOGISTS AND HEALTHCARE PROFESSIONALS

Healthcare professionals act as the frontline monitors of their health systems. They observe, in real time, increases in admissions for heatstroke, dehydration, cardiorespiratory complications, or psychiatric crises. Heatwave-associated fires further exacerbate the situation, causing burns, trauma from evacuations, and respiratory exacerbations from fine particulate exposure.

Epidemiologists operate both retrospectively and in near-real time: they analyze historical data to better understand determinants of population health and use recent and forecast data to raise alerts – although for heatwaves, such alerts are often issued primarily by meteorological services and civil protection agencies. They act as a health radar, collecting, analyzing, and disseminating information that guides responses. By identifying the most vulnerable groups – the elderly, children, people with multiple morbidities, outdoor workers, and socially disadvantaged populations – they enable tailored prevention and targeted action [13].

The summer of 2003 remains emblematic of Western Europe’s vulnerability to heatwaves and their impact on population health. In France, Hémon and Jougla estimated excess mortality by comparing observed deaths during the first 20 days of August 2003 with the 2000-2002 average number of deaths for the same period [14]. In Portugal, between August 1 and August 31, 2003, there were 2,099 excess deaths relative to the expected baseline for the 1997–2001 period [15]. Subsequent heatwaves continued to cause substantial mortality across the region. For example, the 2015 heatwave in the Czech Republic caused a larger increase in excess mortality than the 1994 event (265% versus 240% above the baseline) [16]. In Belgium, Sciensano recorded a 4.3% excess mortality rate across all ages during the summer of 2020, when the Royal Meteorological Institute of Belgium reported two heatwaves (23-26 June and 2-17 August, 2020). The second heatwave coincided with the highest number of daily deaths for the summer period in Belgium, with 492 deaths on 13 August 2020 [17].

When systematically structured and shared, the above-described observations serve as indicators for refining epidemiological models and identifying early warning signs. Belgium’s integration of real-time mortality data with climate indicators demonstrates the added value of such cross-sector collaboration. However, such monitoring remains absent in many European countries.

DIFFERENT LEVELS OF DEVELOPMENT ACROSS EPIDEMIOLOGICAL DISCIPLINES

Infectious disease epidemiology relies on well-established surveillance systems, with routine protocols that enable rapid outbreak alerts [18]. By contrast, environmental epidemiology – focused on heatwaves, wildfires, and air pollution – remains less systematized and is often constrained by fragmented data and slower reporting [19]. Although advances such as high-resolution sensors and exposome approaches are expanding the capacities of environmental epidemiologists, the field continues to face challenges in translating environmental data into timely public health alerts [19],[20]. Ethical frameworks are only recently being consolidated to ensure rigor in studies examining the health effects of multiple, interacting, or time-varying exposures [21]. Strengthening collaboration with meteorological services and hospital emergency units is therefore essential, as alerts for heatwaves and wildfires often originate outside the health sector and must be integrated before they can effectively inform public health action.

HEALTHCARE PROFESSIONALS’ READINESS TO PARTICIPATE IN EPIDEMIOLOGICAL DATA COLLECTION

The main barrier to healthcare professionals’ participation in epidemiological data collection is their workload, particularly during emergency events. Professionals already operate under chronic pressure – staff shortages, ageing patient populations, rising admissions [22],[23]. Climate-related extreme events further intensify this strain [5]. For instance, the convergence of heatwaves with the COVID-19 pandemic in 2020 highlighted the strain being placed on healthcare workers’ resilience [24],[25]. Such an overload not only restricts participation in surveillance and data-sharing initiatives but also serves as a warning: the distribution of skills and the organization of care need to be reexamined [26].

Another obstacle lies in the fragmented and often restrictive architecture of health information systems. Excessive data restrictions and limited interoperability can significantly hinder epidemiological research [27]. When data sets are incomplete or confined to specific diagnostic categories, many potential studies become unfeasible. The lack of data standardization, logistical challenges in data collection and management, and the absence of systematic local ethics committees further complicate the implementation of comparable and reproducible studies [28].

The use of standardized nursing terminologies and consistent documentation practices has been shown to improve care quality, ensure continuity, and increase the utility of collected data [29]. However, these tools remain underused, often due to workload constraints and limited digital literacy. Incorporating these skills into the initial training of professionals could help bridge the gap between clinical documentation, research, and population-level monitoring.

Finally, another barrier to healthcare professionals’ participation in epidemiological data collection is the level of their motivation to engage in research. A recent systematic review has highlighted that limited time for research, organizational constraints, lack of funding, and insufficient institutional support all reduce healthcare professionals’ willingness to invest their efforts in research [30]. Without addressing these factors, healthcare professionals are less likely to integrate epidemiological reasoning into their practice.

REEXAMINING HEALTHCARE TRAINING

The limited role of epidemiology and statistics in the early stages of medical and nursing education may contribute to healthcare professionals’ limited familiarity with and use of health data in practice. Conversely, structured training programs that integrate public health research and practice – such as those implemented in Quebec, Canada – strengthen direct engagement with population health data, surveillance systems, and applied research projects, thereby enhancing healthcare workers’ ability to interpret data, anticipate health risks, and adopt preventive measures in their practice [31],[32]. Building on such approaches, integrating a culture of public health and preparedness for climate-related extreme events in initial training has become essential [33],[34]. Importantly, such reform could also help address the current crisis of wellbeing and recognition among healthcare professionals. Evidence shows that new graduates often enter the workforce underprepared for its psychological and organizational demands, which has a considerable impact on their mental health and retention [35].

The healthcare landscape is undergoing a significant transformation. Enrolment in Master of Public Health (MPH) and Advanced Practice Nursing (APN) programs has increased, reflecting both the growing demand for interdisciplinary and analytical skills and the urgent need to address the global nursing shortage [36],[37]. APN roles are redefining traditional care hierarchies by expanding clinical autonomy, promoting cross-sector collaboration, and strengthening links between patient care and research [38]. Similarly, the increasing presence of MPH graduates within hospital and community settings signals a convergence between clinical expertise and population health competencies [39] – a positive development for bridging the persistent gap between frontline practice and epidemiological insight.

This paradigm shift reflects the dedication of healthcare professionals to participating in an educational reform that is both integrative and forward-thinking. Training in health surveillance, modelling, risk communication, and the responsible use of digital technologies enables professionals to interpret complex data ecosystems, understand the structural determinants of health, and actively contribute to public health intelligence [38],[39]. By rethinking education to better align with day-to-day practical experience and emerging public health needs, Europe has the opportunity not only to strengthen resilience but also to enhance recognition, attractiveness, and sustainability of the professions that are under strain.

RECONNECTING EPIDEMIOLOGISTS WITH THE CONTEXT BEHIND THE DATA

Epidemiologists would benefit from periodic immersion in clinical environments to directly observe practical constraints such as workload pressures, patient diversity, and competing priorities. A recent study aimed at developing a guide for designing epidemiology courses demonstrates the effectiveness of an immersive and reflective learning environment [40]. In concrete terms, programs such as the Centers for Disease Control and Prevention’s Epidemic Intelligence Service (EIS) illustrate this practical approach: officers gain real-world field experience under close mentorship, learning to translate data into practical public health solutions and ensuring that surveillance systems and response efforts remain grounded in the frontline context of healthcare [41]. Such first-hand exposure clarifies why certain data remain difficult to capture or why guidelines may not always translate effectively into practice, while fostering more grounded, pragmatic modelling and intervention design [41].

This approach is also supported by evidence from other field epidemiology training programs. Field Epidemiology Training Programs (FETPs) are two-year, ‘learning by doing’ initiatives designed to strengthen both the workforce and the public health surveillance systems. Similarly, the European Programme for Intervention Epidemiology Training (EPIET) trains field epidemiologists – often in collaboration with national programs – highlighting the importance of structured mentoring, field assignment rotation, and iterative reflection on operational challenges in strengthening epidemiological capacity and data literacy [42].

Treadwell et al. [43] call for a reform of data collection practices to include more disaggregated information, enabling a clearer understanding of – and response to – health inequalities. They argue that this requires a fundamental transformation of data collection methods and structures.

Collectively, these perspectives suggest that combining field immersion, well-designed collaborative networks, and targeted training can help reconnect epidemiologists with the operational context underpinning the data, thereby enhancing the validity, applicability, and equity of public health research and practice.

BUILDING A COMMON FRAMEWORK FOR HEATWAVE HEALTH MONITORING

The example of heatwaves is particularly illustrative of the gap between epidemiologists and healthcare professionals in interpreting and using data, as no widely accepted conceptual framework or standardized set of health metrics currently exists to measure their impact. While numerous studies quantify excess mortality [44],[45] or excess hospitalizations [46], these efforts often rely on different methodologies, making it difficult to compare results or establish a shared language across disciplines.

In acute clinical settings, indicators such as excess mortality, hospital bed occupancy, and intensive care unit (ICU) admissions provide actionable, real-time signals for both clinicians and public health authorities. Beyond these immediate measures, population health indicators – including prevalence, incidence, premature mortality, morbidity, and disability, as used in the Global Burden of Disease (GBD) Study [47] – offer a standardized method for quantifying both mortality and morbidity across populations and comparing the relative impact of different causes of disease and injury. Summary measures such as disability-adjusted life years (DALYs), developed as part of the GBD Study, integrate these indicators into a single metric of overall disease burden, while quality-adjusted life years (QALYs) capture the impact of health conditions on patients’ quality of life, linking clinical outcomes to lived experience.

Establishing a common set of such indicators at the European level could facilitate clearer communication between epidemiologists, healthcare professionals, and policymakers by providing a shared reference for measuring health impact, setting public health targets, and prioritizing interventions. These measures are particularly valuable for anticipating health risks, planning preventive strategies, evaluating progress over time, and comparing burden across different causes of disease, rather than serving solely as tools for immediate crisis response [48],[49].

CONCLUSION

In a world where heatwaves, fires, epidemics, and socio-economic crises are intensifying, it is essential to raise awareness among both epidemiologists and healthcare professionals about the benefits of closer collaboration. Reconciling these two complementary and interdependent fields requires the development of a clear conceptual framework and a shared language. Rethinking training programs in both domains could represent a long-term strategy to strengthen the resilience of health systems.

LIST OF ACRONYMS

APN – Advanced Practice Nursing
DALYs – disability-adjusted life years
EIS – Epidemic Intelligence Service
EPIET – European Programme for Intervention Epidemiology Training
FETPs – Field Epidemiology Training Programs
GBD Study – The Global Burden of Disease Study
ICU – intensive care unit
MPH – Master of Public Health
QALYs – quality-adjusted life years