Impacts of extreme heat on emergency medical service calls in King County, Washington, 2007-2012: relative risk and time series analyses of basic and advanced life support

A novel climate and health decision support platform: Approach, outputs, and policy considerations

BACKGROUND

The adverse health impacts of climate change are increasingly apparent and the need for adaptation activities is pressing. Risks, drivers, and decision contexts vary significantly by location, and high-resolution, place-based information is needed to support decision analysis and risk reduction efforts at scale.

METHODS

Using the Intergovernmental Panel on Climate Change (IPCC) risk framework, we developed a causal pathway linking heat with a composite outcome of heat-related morbidity and mortality. We used an existing systematic literature review to identify variables for inclusion and the authors' expert judgment to determine variable combinations in a hierarchical model. We parameterized the model for Washington state using observational (1991-2020 and June 2021 extreme heat event) and scenario-driven temperature projections (2036-2065), compared outputs against relevant existing indices, and analyzed sensitivity to model structure and variable parameterization. We used descriptive statistics, maps, visualizations and correlation analyses to present results.

RESULTS

The Climate and Health Risk Tool (CHaRT) heat risk model contains 25 primary hazard, exposure, and vulnerability variables and multiple levels of variable combinations. The model estimates population-weighted and unweighted heat health risk for selected periods and displays estimates on an online visualization platform. Population-weighted risk is historically moderate and primarily limited by hazard, increasing significantly during extreme heat events. Unweighted risk is helpful in identifying lower population areas that have high vulnerability and hazard. Model vulnerability correlate well with existing vulnerability and environmental justice indices.

DISCUSSION

The tool provides location-specific insights into risk drivers and prioritization of risk reduction interventions including population-specific behavioral interventions and built environment modifications. Insights from causal pathways linking climate-sensitive hazards and adverse health impacts can be used to generate hazard-specific models to support adaptation planning.

Heat, heatwaves, and ambulance service use: a systematic review and meta-analysis of epidemiological evidence

Ambulance data has been reported to be a sensitive indicator of health service use during hot days, but there is no comprehensive summary of the quantitative association between heat and ambulance dispatches. We conducted a systematic review and meta-analysis to retrieve and synthesise evidence published up to 31 August 2022 about the association between heat, prolonged heat (i.e. heatwaves), and the risk of ambulance dispatches. We initially identified 3628 peer-reviewed papers and included 48 papers which satisfied the inclusion criteria. The meta-analyses showed that, for each 5 °C increase in mean temperature, the risk of ambulance dispatches for all causes and for cardiovascular diseases increased by 7% (95% confidence interval (CI): 5%, 10%) and 2% (95% CI: 1%, 3%), respectively, but not for respiratory diseases. The risk of ambulance dispatches increased by 6% (95% CI: 4%, 7%), 7% (95% CI: 5%, 9%), and 18% (95% CI: 12%, 23%) under low-intensity, severe, and extreme heatwaves, respectively. We observed two potential sources of bias in the existing literature: (1) bias in temperature exposure measurement; and (2) bias in the ascertainment of ambulance dispatch causes. This review suggests that heat exposure is associated with an increased risk of ambulance dispatches, and there is a dose-response relationship between heatwave intensity and the risk of ambulance dispatches. For future studies assessing the heat-ambulance association, we recommend that (1) using data on spatially refined gridded temperature that is either very well interpolated or derived from satellite imaging may be an alternative to reduce exposure measurement bias; and (2) linking ambulance data with hospital admission data can be useful to improve health outcome classification.

Rescue service deployment data as an indicator of heat morbidity in Frankfurt / Main, Germany (2014-2022) - Trend association with various heat exposure indicators and considerations for outreach

Many publications dealt with the monitoring of heat-related mortality. Fewer analyses referred to indicators of heat-related morbidity. The aim of this work was to describe the heat-related morbidity using rescue service data from the city of Frankfurt/Main, Germany for the time period 2014-2022, with regard to the questions: 1) How do rescue service deployments develop over the years? Is there a trend identifiable towards a decrease in deployments over the years, e.g. as an effect of either (physiological) adaptation of the population or of the measures for prevention of heat-related morbidity? 2) Which heat parameters (days with a heat warning, heat days, heat weeks, heat waves) are most strongly associated with heat-related morbidity in terms of rescue service deployments and might therefore be additionally used as an easily communicable and understandable heat-warning indicator? Rescue service data were provided by the interdisciplinary medical supply compass system "IVENA" and adjusted for population development including age development. The effect of various indicators for heat exposure, such as days with a heat warning from the German meteorological service based on the scientific concept of "perceived heat", heat days, heat wave days and heat week days on different endpoints for heat morbidity (deployments in total as well as for heat associated diagnoses) was calculated using both difference-based (difference ± 95% CI) and ratio-based (ratio ± 95% CI) effect estimators. Rescue services deployments in summer months increased overall from 2014 to 2022 in all age groups over the years (2698 to 3517/100.000 population). However, there was a significant decrease in 2020, which could be explained by the special situation of the COVID-19 pandemic, probably caused by the absence of tourists and commuters from the city. In addition, no data are available on the actual implementation of the measures by the population. Therefore, an effect of the measures taken to prevent heat-associated morbidity in Frankfurt am Main could not be directly demonstrated, and our first question cannot be answered on the basis of these data. Almost all heat definitions used for exposure (day with a heat warning, heat day, heat wave day, heat week day) showed significant effects on heat-associated diagnoses in every year. When analysing the effect on all deployments, the effect was in part strongly dependent on individual years: Heat wave days and heat week days even showed negative effects in some years. The definition heat day led to a significant increase in rescue service deployments in all single years between 2014 and 2022 (ratio 2014-2022 1.09 (95CI 1.07-1.11); with a range of 1.05 (95CI 1.01-1.09) in 2020 and 1.14 (95CI 1.08-1.21) in 2014), this was not the case for days with a heat warning (ratio 2014-2022 1.04 (95CI1.02-1.05); with a range of 1.01 (95CI 0.97-1.05) in 2017 and 1.16 (95CI 1.10-1.23). Thus being not inferior to the heat warning day, the "heat day" defined as ≥32 °C maximum temperature, easily obtainable from the weather forecast, can be recommended for the activities of the public health authorities (warning, surveillance etc.) regarding heat health action planning.

Just Plain Hot: Examining Summer Daily High Heat Indices and Community-Level Social Vulnerability on Emergency Medical Services On-Scene Responses in San Antonio, Texas, 2015-2018

Introduction Increased summer heat has a deleterious effect on people's health and the healthcare system. Emergency Medical Services (EMS) are at the healthcare system frontline, responsive to the community and environmental conditions. The present study examined how EMS on-scene response is affected by community-level social vulnerability and heat. Methods The Centers for Disease Control and Prevention's Social Vulnerability Index, heat and humidity data from the National Weather Service, and City of San Antonio EMS data were collected. Data were analyzed using negative binomial regression models with time-stratified case-crossover design to observe independent and interactive effects of heat and social vulnerability on EMS on-scene response over four constricted calendar years. Results Results indicated that community-based social vulnerability and heat, independently and interactively, are associated with increased EMS on-scene responses. Conclusion Even when examining normal summertime heat conditions, there is evidence of the relationships between geographic and environmental conditions and the healthcare system.

A Systematic Literature Review of the Impact of Climate Change on the Global Demand for Psychiatric Services

Climate Change (CC) imposes important global health risks, including on mental health (MH). They are related mostly to psychological suffering caused by climate-related events and to the heat-vulnerability caused by psychiatric disorders. This growing burden may press MH services worldwide, increasing demand on public and private systems in low-, middle-, and high-income countries. According to PRISMA, two independent reviewers searched four databases for papers published before May 2022 that associated climate-related events with healthcare demand for psychiatric conditions. Of the 7432 papers retrieved, we included 105. Only 29 were carried out in low- and middle-income countries. Twelve related the admission numbers to (i) extreme events, while 93 to (ii) meteorological factors-mostly heat. Emergency visits and hospitalizations were significantly higher during hot periods for MH disorders, especially until lag 5-7. Extreme events also caused more consultations. Suicide (completed or attempted), substance misuse, schizophrenia, mood, organic and neurotic disorders, and mortality were strongly affected by CC. This high healthcare demand is evidence of the burden patients may undergo. In addition, public and private services may face a shortage of financial and human resources. Finally, the increased use of healthcare facilities, in turn, intensifies greenhouse gas emissions, representing a self-enforcing cycle for CC. Further research is needed to better clarify how extreme events affect MH services and, in addition, if services in low- and middle-income countries are more intensely demanded by CC, as compared to richer countries.

Association of ambient extreme heat with pediatric morbidity: a scoping review

Global climate change is leading to higher ambient temperatures and more frequent heatwaves. To date, impacts of ambient extreme heat on childhood morbidity have been understudied, although-given children's physiologic susceptibility, with smaller body surface-to-mass ratios, and many years of increasing temperatures ahead-there is an urgent need for better information to inform public health policies and clinical approaches. In this review, we aim to (1) identify pediatric morbidity outcomes previously associated with extreme heat, (2) to identify predisposing co-morbidities which may make children more susceptible to heat-related outcomes, and (3) to map the current body of available literature. A scoping review of the current full-text literature was conducted using the Arksey and O'Malley framework Int J Soc Res Methodol 8:19-32, (2015). Search terms for (1) pediatric population, (2) heat exposures, (3) ambient conditions, and (4) adverse outcomes were combined into a comprehensive PubMed and Medline literature search. Of the 1753 publications identified, a total of 20 relevant studies were ultimately selected based on selection criteria of relevance to US urban populations. Most identified studies supported positive associations between high extreme temperature exposures and heat-related illness, dehydration/electrolyte imbalance, general symptoms, diarrhea and digestion disorders, infectious diseases/infections, asthma/wheeze, and injury. Most studies found no association with renal disease, cardiovascular diseases, or diabetes mellitus. Results were mixed for other respiratory diseases and mental health/psychological disorders. Very few of the identified studies examined susceptibility to pre-existing conditions; Cystic Fibrosis was the only co-morbidity for which we found significant evidence. Further research is needed to understand the nuances of associations between extreme heat and specific outcomes-particularly how associations may vary by child age, sex, race/ ethnicity, community characteristics, and other pre-existing conditions.

Warmer summer nocturnal surface air temperatures and cardiovascular disease death risk: a population-based study

BACKGROUND

In recent summers, some populous mid-latitude to high-latitude regions have experienced greater heat intensity, more at night than by day. Such warming has been associated with increased cause-specific adult mortality. Sex-specific and age-specific associations between summer nocturnal surface air temperatures (SAT) and cardiovascular disease (CVD) deaths have yet to be established.

METHODS

A monthly time series analysis (June-July, 2001-2015) was performed on sex-specific CVD deaths in England and Wales of adults aged 60-64 and 65-69 years. Using negative binomial regression with autocorrelative residuals, associations between summer (June-July) nocturnal SAT anomalies (primary exposure) and CVD death rates (outcome) were computed, controlling for key covariates. To explore external validity, similar associations with respect to CVD death in King County, Washington, USA, also were calculated, but only for men aged 60-64 and 65-69 years. Results are reported as incidence rate ratios.

RESULTS

From 2001 to 2015, within these specific cohorts, 39 912 CVD deaths (68.9% men) were recorded in England and Wales and 488 deaths in King County. In England and Wales, after controlling for covariates, a 1°C rise in anomalous summer nocturnal SAT associated significantly with a 3.1% (95% CI 0.3% to 5.9%) increased risk of CVD mortality among men aged 60-64, but not older men or either women age groups. In King County, after controlling for covariates, a 1°C rise associated significantly with a 4.8% (95% CI 1.7% to 8.1%) increased risk of CVD mortality among those <65 years but not older men.

CONCLUSION

In two mid-latitude regions, warmer summer nights are accompanied by an increased risk of death from CVD among men aged 60-64 years.

Hot weather as a risk factor for kidney disease outcomes: A systematic review and meta-analysis of epidemiological evidence

BACKGROUND

The occurrence or exacerbation of kidney disease has been documented as a growing problem associated with hot weather. The implementation of effective prevention measures requires a better understanding of the risk factors that increase susceptibility. To fill gaps in knowledge, this study reviews the current literature on the effects of heat on kidney-disease outcomes (ICD-10 N00-N39), including morbidity and mortality.

METHODS

Databases were systematically searched for relevant literature published between 1990 and 2020 and the quality of evidence evaluated. We performed random effects meta-analysis to calculate the pooled relative risks (RRs) of the association between high temperatures (and heatwaves) and kidney disease outcomes. We further evaluated vulnerability concerning contextual population characteristics.

RESULTS

Of 2739 studies identified, 91 were reviewed and 82 of these studies met the criteria for inclusion in a meta-analysis. Findings showed that with a 1 °C increase in temperature, the risk of kidney-related morbidity increased by 1% (RR 1.010; 95% CI: 1.009-1.011), with the greatest risk for urolithiasis. Heatwaves were also associated with increased morbidity with a trend observed with heatwave intensity. During low-intensity heatwaves, there was an increase of 5.9% in morbidity, while during high-intensity heatwaves there was a 7.7% increase. There were greater RRs for males, people aged ≤64 years, and those living in temperate climate zones. Similarly, for every 1 °C temperature increase, there was a 3% (RR 1.031; 95% CI: 1.018-1.045) increase in the risk of kidney-related mortality, which also increased during heatwaves.

CONCLUSIONS

High temperatures (and heatwaves) are associated with an elevated risk of kidney disease outcomes, particularly urolithiasis. Preventive measures that may minimize risks in vulnerable individuals during hot spells are discussed.

Temperature-sensitive morbidity indicator: consequence from the increased ambulance dispatches associated with heat and cold exposure

Current development of temperature-related health early warning systems mainly arises from knowledge of temperature-related mortality or hospital-based morbidity. However, due to the delay in data reporting and limits in hospital capacity, these indicators cannot be used in health risk assessments timely. In this study, we examine temperature impacts on emergency ambulance and discuss the benefits of using this near real-time indicator for risk assessment and early warning. We collected ambulance dispatch data recording individual characteristics and preliminary diagnoses between 2015 and 2016 in Shenzhen, China. Distributed lag nonlinear model was used to examine the effects of high and low temperatures on ambulance dispatches during warm and cold seasons. Lag effects were also assessed to evaluate the sensitivity of ambulance dispatches in reflecting immediate health reactions. Stratified analyses by gender, age, and a wide range of diagnoses were performed to identify vulnerable subgroups. Disease-specific numbers of ambulance dispatches attributable to non-optimal temperature were calculated to determine the related medical burdens. Effects of temperature on ambulance dispatches appeared to be acute on the current day. Males, people aged 18-44 years, were more susceptible to non-optimal temperatures. Highest RR during heat exposure by far was for urinary disease, alcohol intoxication, and traumatic injury, while alcohol intoxication and cardiovascular disease were especially sensitive to cold exposure, causing the main part of health burden. The development of local health surveillance systems by utilizing ambulance dispatch data are important for temperature impact assessments and medical resource reallocation.

Impact of short-term exposure to extreme temperatures on diabetes mellitus morbidity and mortality? A systematic review and meta-analysis

The relationship between diabetes mellitus and short-term exposure to extreme temperatures remains controversial. A systematic review and meta-analysis were performed to assess the association between extreme temperatures and diabetes mellitus morbidity and mortality. PubMed, Embase, the Cochrane Library, Web of Science, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) were searched since inception to January 1, 2019, and updated on November 17, 2020. The results were combined using random effects model and reported as relative risk (RR) with 95% confidence interval (CI). In total, 32 studies met the inclusion criteria. (1) Both heat and cold exposures have impact on diabetes. (2) For heat exposure, the subgroup analysis revealed that the effect on diabetes mortality (RR=1.139, 95% CI: 1.089-1.192) was higher than morbidity (RR=1.012, 95% CI: 1.004-1.019). (3) With the increase of definition threshold, the impact of heat exposure on diabetes rose. (4) A stronger association between heat exposure and diabetes was observed in the elderly (≥ 60 years old) (RR=1.040, 95% CI: 1.017-1.064). In conclusion, short-term exposure to both heat and cold temperatures has impact on diabetes. The elderly is the vulnerable population of diabetes exposure to heat temperature. Developing definitions of heatwaves at the regional level are suggested.

Use of a metalearner to predict emergency medical services demand in an urban setting

OBJECTIVE

To develop and internally validate a metalearner algorithm to predict the hourly rate of emergency medical services (EMS) dispatches in an urban setting.

METHODS

We performed an analysis of EMS data from New York City between years 2015-2019. Our outcome was hourly EMS dispatches, expressed as continuous data. Hours were split into derivation (75%) and validation (25%) datasets. Candidate variables included averages of prior rates, temporal and weather characteristics. We used a metalearner to evaluate and aggregate individual learners (generalized linear model, generalized additive model, random forest, multivariable adaptive regression splines, and extreme gradient boost). Four models were investigated: 1) temporal variables, 2) weather and temporal variables, and datasets in which weather data were lagged by 3) six and 4) twelve hours. In exploratory analyses, we constructed learners for high acuity and trauma encounters.

RESULTS

7,364,275 EMS dispatches occurred during the 43,823-hour period. When using temporal variables, the mean absolute error (MAE) rate was 11.5 dispatches in the validation dataset. These were slightly improved following incorporation of weather variables (MAE 11.3). When using 6- and 12-hour lagged weather variables, learners demonstrated lower accuracy (MAE 11.8 in 6-hour lagged datasets; 12.2 in 12-hour lagged dataset). All models had a coefficient of determination (R²) ≥0.91. The extreme gradient boosting and random forest learners were assigned the highest coefficients. In an investigation of variable importance, hour of day and average EMS dispatches over the previous six hours were the most important variables in both the extreme gradient boosting and random forest learners. The algorithm performed well at predicting frequently occurring peaks, with greater challenges at both extremes. Learners created high-acuity and for trauma-related encounters demonstrated superior MAE, but with lower R² in the validation cohort (MAE 6.9 and R² 0.84 for high acuity encounters; MAE 5.3 and R² 0.79 for trauma in learners using time and weather variables).

CONCLUSION

We developed an ensemble machine learning algorithm to predict EMS dispatches in an urban setting. These models demonstrated high accuracy, with MAEs <12 per hour in all. These algorithms may carry benefit in the real-time prediction of EMS responses, allowing for improved resource utilization.

Geospatial indicators of exposure, sensitivity, and adaptive capacity to assess neighbourhood variation in vulnerability to climate change-related health hazards

BACKGROUND

Although the frequency and magnitude of climate change-related health hazards (CCRHHs) are likely to increase, the population vulnerabilities and corresponding health impacts are dependent on a community's exposures, pre-existing sensitivities, and adaptive capacities in response to a hazard's impact. To evaluate spatial variability in relative vulnerability, we: 1) identified climate change-related risk factors at the dissemination area level; 2) created actionable health vulnerability index scores to map community risks to extreme heat, flooding, wildfire smoke, and ground-level ozone; and 3) spatially evaluated vulnerability patterns and priority areas of action to address inequity.

METHODS

A systematic literature review was conducted to identify the determinants of health hazards among populations impacted by CCRHHs. Identified determinants were then grouped into categories of exposure, sensitivity, and adaptive capacity and aligned with available data. Data were aggregated to 4188 Census dissemination areas within two health authorities in British Columbia, Canada. A two-step principal component analysis (PCA) was then used to select and weight variables for each relative vulnerability score. In addition to an overall vulnerability score, exposure, adaptive capacity, and sensitivity sub-scores were computed for each hazard. Scores were then categorised into quintiles and mapped.

RESULTS

Two hundred eighty-one epidemiological papers met the study criteria and were used to identify 36 determinant indicators that were operationalized across all hazards. For each hazard, 3 to 5 principal components explaining 72 to 94% of the total variance were retained. Sensitivity was weighted much higher for extreme heat, wildfire smoke and ground-level ozone, and adaptive capacity was highly weighted for flooding vulnerability. There was overall varied contribution of adaptive capacity (16-49%) across all hazards. Distinct spatial patterns were observed - for example, although patterns varied by hazard, vulnerability was generally higher in more deprived and more outlying neighbourhoods of the study region.

CONCLUSIONS

The creation of hazard and category-specific vulnerability indices (exposure, adaptive capacity and sensitivity sub-scores) supports evidence-based approaches to prioritize public health responses to climate-related hazards and to reduce inequity by assessing relative differences in vulnerability along with absolute impacts. Future studies can build upon this methodology to further understand the spatial variation in vulnerability and to identify and prioritise actionable areas for adaptation.

Binary Programming Model for Rostering Ambulance Crew-Relevance for the Management and Business

The nature of health care services is very complex and specific, thus delays and organizational imperfections can cause serious and irreversible consequences, especially when dealing with emergency medical services. Therefore, constant improvements in various aspects of managing and organizing provision of emergency medical services are vital and unavoidable. The main goal of this paper is the development and application of a binary programming model to support decision making process, especially addressing scheduling workforce in organizations with stochastic demand. The necessary staffing levels and human resources allocation in health care organizations are often defined ad hoc, without empirical analysis and synchronization with the demand for emergency medical services. Thus, irrational allocation of resources can result in various negative impacts on the financial result, quality of medical services and satisfaction of both patients and employees. We start from the desired staffing levels determined in advance and try to find the optimal scheduling plan that satisfies all significant professional and regulatory constraints. In this paper a binary programming model has been developed and implemented in order to minimize costs, presented as the sum of required number of ambulance crews. The results were implemented for staff rostering process in the Ambulance Service Station in Subotica, Serbia. Compared to earlier scheduling done ad hoc at the station, the solution of the formulated model provides a better and equable engagement of crews. The developed model can be easily modified and applied to other organizations with the same, stochastic, nature of the demand.

The Influence of Extreme Heat on Police and Fire Department Services in 23 U.S. Cities

Recent research suggests that extreme heat affects the demand for emergency services, including police and fire department incidents. Yet there is limited understanding of impacts across U.S. cities, with varying population sizes, and between different climates. This study sought to examine the daily utilization of police and fire department services, during hot days in 23 U.S. cities representing six climate zones using relative risk (RR) and time series analyses of daily police and fire department incidents. The warm season analyses utilized three temperature metrics: daily maximum temperature (TMAX), daily maximum heat index (HIMAX), and the preceding daily minimum temperature (TMIN). Across these cities, the RR of police department incidents on days where TMAX was at or above the 95th percentile significantly increased within a range from 3% (95% confidence interval [CI]: 0.3%, 6.3%) to 57% (95% CI: 24.5%, 89.7%), compared with a nonhot day. At the same temperature thresholds, the RR of fire department dispatches increased from 6% (95% CI: 3.0%, 8.6%) to 18% (95% CI: 15.2%, 21.6%). These results remained consistent across temperature metrics and consecutive days of extreme heat. The estimated effects of daily maximum temperature, daily maximum heat index, and daily minimum temperature were nonlinear for police and fire department incidents across all cities. These findings inform climate change adaptation strategies, preparing budgets and personnel for emergency agencies to ensure resilience as periods of extreme heat increase in frequency, severity, and duration.

Effects of social vulnerability and heat index on emergency medical service incidents in San Antonio, Texas, in 2018

BACKGROUND

Excessive heat is a leading weather-related cause of fatalities in the USA. Vulnerable populations can face greater exposure to health risks during extreme heat events. The aim of this study is to examine the effects of excessive heat and community-level social vulnerability on morbidity in San Antonio, Texas, in 2018.

METHODS

Heat Index (HI) data are from the National Oceanic and Atmospheric Administration. Social vulnerability is measured using the Centres for Disease Control and Prevention's Social Vulnerability Index (SVI). Morbidity is measured as the number of emergency medical service (EMS) incidents. Sixty-one zip codes were analysed for the 153 constrained calendar days from 1 May to 30 September 2018. Negative binomial regression analysis with the time-stratified case-crossover design was conducted to predict the effects of HI and SVI on the rate of EMS incidents.

RESULTS

HI is significantly and positively associated with the rate of EMS incidents. Social vulnerability has a statistically significant association with EMS incidents, with higher levels of community-level social vulnerability associated with higher rates of EMS incidents. The effect of the HI on the rate of EMS incidents is significantly and positively moderated by the SVI.

CONCLUSIONS

Social vulnerability and excessive heat increase the rate of EMS incidents. As the number of excessive heat days increases and San Antonio continues to have extreme disparities by location, there will be an effect on health systems, including EMSs.

Weather and temporal models for emergency medical services: An assessment of generalizability

BACKGROUND

Emergency medical services (EMS) response volume has been linked to weather and temporal factors in a regional EMS system. We aimed to identify if models of EMS utilization incorporating these data are generalizable through geographically disparate areas in the United States.

METHODS

We performed a retrospective analysis of EMS dispatch data from four regions: New York City, San Francisco, Cincinnati, and Marin County for years 2016-2019. For each model, we used local weather data summarized from the prior 6 h into hourly bins. Our outcome for each model was EMS dispatches as count data. We fit and optimized a negative binomial regression model for each region, to estimate incidence rate ratios. We compared findings to a prior study performed in Western Pennsylvania.

RESULTS

We included 5,940,637 EMS dispatches from New York City, 809,405 from San Francisco, 260,412 from Cincinnati, and 77,461 from Marin County. Models demonstrated consistency with the Western Pennsylvania model with respect to temperature, season, wind speed, dew point, and time of day; both in terms of direction and effect size when expressed as incidence rate ratios. Precipitation was associated with increasing dispatches in the New York City, Cincinnati, and Marin County models, but not the San Francisco model.

CONCLUSION

With minor differences, regional models demonstrated consistent associations between dispatches and time and weather variables. Findings demonstrate the generalizability of associations between these variables with respect to EMS use. Weather and temporal factors should be considered in predictive modeling to optimize EMS staffing and resource allocation.

The Influence of Heat on Daily Police, Medical, and Fire Dispatches in Boston, Massachusetts: Relative Risk and Time-Series Analyses

Objectives. To examine the impact of extreme heat on emergency services in Boston, MA.Methods. We conducted relative risk and time series analyses of 911 dispatches of the Boston Police Department (BPD), Boston Emergency Medical Services (BEMS), and Boston Fire Department (BFD) from November 2010 to April 2014 to assess the impact of extreme heat on emergency services.Results. During the warm season, there were 2% (95% confidence interval [CI] = 0%, 5%) more BPD dispatches, 9% (95% CI = 7%, 12%) more BEMS dispatches, and 10% (95% CI = 5%, 15%) more BFD dispatches on days when the maximum temperature was 90°F or higher, which remained consistent when we considered multiple days of heat. A 10°F increase in daily maximum temperature, from 80° to 90°F, resulted in 1.016, 1.017, and 1.002 times the expected number of daily BPD, BEMS, and BFD dispatch calls, on average, after adjustment for other predictors.Conclusions. The burden of extreme heat on local emergency medical and police services may be agency-wide, and impacts on fire departments have not been previously documented.Public Health Implications. It is important to account for the societal burden of extreme heat impacts to most effectively inform climate change adaptation strategies and planning.

Impacts of climate change on the public health of the Mediterranean Basin population - Current situation, projections, preparedness and adaptation

The Mediterranean Basin is undergoing a warming trend with longer and warmer summers, an increase in the frequency and the severity of heat waves, changes in precipitation patterns and a reduction in rainfall amounts. In this unique populated region, which is characterized by significant gaps in the socio-economic levels particularly between the North (Europe) and South (Africa), parallel with population growth and migration, increased water demand and forest fires risk - the vulnerability of the Mediterranean population to human health risks increases significantly. Indeed, climatic changes impact the health of the Mediterranean population directly through extreme heat, drought or storms, or indirectly by changes in water availability, food provision and quality, air pollution and other stressors. The main health effects are related to extreme weather events (including extreme temperatures and floods), changes in the distribution of climate-sensitive diseases and changes in environmental and social conditions. The poorer countries, particularly in North Africa and the Levant, are at highest risk. Climate change affects the vulnerable sectors of the region, including an increasingly older population, with a larger percentage of those with chronic diseases, as well as poor people, which are therefore more susceptible to the effects of extreme temperatures. For those populations, a better surveillance and control systems are especially needed. In view of the climatic projections and the vulnerability of Mediterranean countries, climate change mitigation and adaptation become ever more imperative. It is important that prevention Health Action Plans will be implemented, particularly in those countries that currently have no prevention plans. Most adaptation measures are "win-win situation" from a health perspective, including reducing air pollution or providing shading solutions. Additionally, Mediterranean countries need to enhance cross-border collaboration, as adaptation to many of the health risks requires collaboration across borders and also across the different parts of the basin.

Effect of apparent temperature on daily emergency admissions for mental and behavioral disorders in Yancheng, China: a time-series study

BACKGROUND

Very few studies have focused on the relationship between ambient apparent temperature (AT) and admission of mental and behaviour disorders (MDs). Therefore, a time-series study was conducted in Yancheng, China, to explore the effects of AT on the daily emergency admissions of patients with MDs over the period of 2014-17.

METHODS

A quasi-Poisson generalized linear model (GLM) combined with a distributed lag non-linear model (DLNM) was adopted to explore the associations after adjusting for time trend, day of the week, humidity, sunshine duration, rainfall, holidays and air pollutants. In the subgroup analysis, the modification effects of age and sex were also examined.

RESULTS

Overall, 8438 cases of MDs emergency admissions were identified. With the apparent temperature with the minimum number of admissions (- 3.4 °C) serving as a reference, a positive correlation emerged between high AT and daily emergency admissions of patients with MDs in Yancheng, China, with the lagged effect of 1 to 5 days. The subgroup analysis demonstrated a positive relationship between AT and MDs emergency admissions among males and individuals younger than 45 years old, with no lagged effect.

CONCLUSIONS

The results will provide important scientific evidence for mental health policy-makers and practitioners for possible intervention, especially among the vulnerable populations.

Association between work in deforested, compared to forested, areas and human heat strain: An experimental study in a rural tropical environment

BACKGROUND

With climate change, adverse human health effects caused by heat exposure are of increasing public health concern. Forests provide beneficial ecosystem services for human health, including local cooling. Few studies have assessed the relationship between deforestation and heat-related health effects in tropical, rural populations. We sought to determine whether deforested compared to forested landscapes are associated with increased physiological heat strain in a rural, tropical environment.

METHODS

We analyzed data from 363 healthy adult participants from ten villages who participated in a two-by-two factorial, randomized study in East Kalimantan, Indonesia from 10/1/17 to 11/6/17. Using simple randomization, field staff allocated participants equally to different conditions to conduct a 90-minute outdoor activity, representative of typical work. Core body temperature was estimated at each minute during the activity using a validated algorithm from baseline oral temperatures and sequential heart rate data, measured using chest band monitors. We used linear regression models, clustered by village and with a sandwich variance estimator, to assess the association between deforested versus forested conditions and the number of minutes each participant spent above an estimated core body temperature threshold of 38.5°C.

RESULTS

Compared to those in the forested condition (n=172), participants in the deforested condition (n=159) spent an average of 3.08 (95% CI 0.57, 5.60) additional minutes with an estimated core body temperature exceeding 38.5°C, after adjustment for age, sex, body mass index, and experiment start time, with a larger difference among those who began the experiment after 12 noon (5.17 [95% CI 2.20, 8.15]).

CONCLUSIONS

In this experimental study in a tropical, rural setting, activity in a deforested versus a forested setting was associated with increased objectively measured heat strain. Longer durations of hyperthermia can increase the risk of serious health outcomes. Land use decisions should consider the implications of deforestation on local heat exposure and health as well as on forest services, including carbon storage functions that impact climate change mitigation.

Weather and Temporal Factors Associated with Use of Emergency Medical Services

Background: Fluctuations in emergency medical services (EMS) responses can have a substantial impact on the ability of agencies to meet resource needs within an EMS system. We aimed to identify weather characteristics as potentially predictable factors associated with EMS responses. Methods: We reviewed hourly counts of scene responses documented by 24 EMS agencies in Western Pennsylvania from January 1, 2014 to December 31, 2017 and compared rates of responses to weather characteristics. Responses to counties nonadjacent to the studied weather reporting station and interfacility/scheduled transports were excluded. We identified the mean temperature, meters visibility, dew point, wind speed, total millimeters of precipitation, and presence of rain or snow in 6-hour windows prior to dispatch, in addition to temporal factors of time of day and weekend vs. weekday. Analysis was performed using multivariable linear regression of a negative binomial distribution, reporting incidence rate ratios (IRR) with 95% confidence intervals (CI). Secondary analyses were performed for transports to the hospital and cases involving transports for traumatic complaints and pediatric patients (age <18 years). Results: We included 529,058 responses (54.8% female, mean age 57.2 ± SD 24.7 years). In our multivariable model, responses were associated with (IRR, 95% CI) rain (1.10, 1.08-1.11) snow (1.07, 1.05-1.09), and both rain and snow (1.15, 1.11-1.19). A lower incidence of responses occurred on weekends (0.84, 0.83-0.85) and at night (0.62, 0.61-0.62). Increasing temperature in 5 °C increments was associated with an increase in responses across seasons with an effect that varied between 1.16 (1.15-1.17) in winter to 1.31 (1.28-1.33) in summer. Windy weather was associated with increased responses from light breeze (1.10, 1.09-1.11) to fresh breeze or greater (1.23, 1.16-1.30). Transports occurred in a similar pattern to responses. Trauma transports (n = 64,235) occurred more during weekends (1.04, 1.02-1.06). Pediatric transports (n = 21,880) were not significantly associated with precipitation or season. Conclusion: EMS responses increased with rising temperature and following rain and snow. These findings may assist in planning by EMS agencies and emergency departments to identify periods of greatest resource utilization.

The impact of a heat wave on mortality in the emergency department

Extreme heat wave increases the number of emergency department (ED) admissions and mortality rates. The purpose of our study is to investigate the effects of the heat wave experienced in Izmir province of Turkey on mortality.During a 9-day period between 17th and 25th June 2016 (study period), air temperature values were higher than the seasonal norms in Izmir, Turkey. In this cross-sectional study, nontraumatic admissions and in-hospital mortality rates were compared this historical interval of the extreme heat wave with the same period of the previous year and the other 21 days of June 2016.The average air temperature between 17th and 25th June 2016, was higher than the average air temperature of the previous year's same period and the average air temperature from the other 21 days of June 2016 (27.8 ± 3.6 °C, (24.5 ± 1.9°C, 24.1 ± 2.1°C, respectively) (P <.01)During the study period, the mean number of ED visits and mortality rates were significantly higher than the previous year's same period (320 ± 30/day vs 269 ± 27/day, [P <.01], and 1.6% vs 0.7%, [P <.01]).Although the admission rate was similar between the study period and the other 21 days of June 2016 (320 ± 30/day vs 310 ± 32/ day, [P = .445]); in-hospital mortality rate was significantly higher during study period (1.6% vs 0.7%, [P <.01]).During the extreme heat waves, ED admissions and in-hospital mortality rates are increased. Precautions should be addressed for adaptation of people to extreme hot weather.

Effects of ambient temperature on ambulance emergency call-outs in the subtropical city of Shenzhen, China

The associations between meteorological factors and mortality have been well documented worldwide, but limited evidence is available for the non-fatal health impacts of ambient temperature, particularly there are few population-based investigations on the impacts of emergency ambulance dispatches in Asia. In this study, based on 809,906 ambulance emergency call-outs (AECOs) for the total population from 2010-2016 in the subtropical city of Shenzhen, China, a Poisson regression combined with a distributed lag nonlinear model was used to simultaneously assess the nonlinear and lag effects of daily mean temperature on AECOs. Stratified analyses by age and sex were performed to identify vulnerable subpopulations. A U-shaped relationship was found between temperature and AECOs. Cold effects were delayed and persisted for 3-4 weeks, with a cumulative relative risk (RR) and 95% confidence interval (CI) of 1.23 (1.10-1.38) and 1.25 (1.16-1.35) over lag 0-28 when comparing the 1st and 5th percentile of the temperature distribution to the optimal (i.e. minimum AECOs) temperature, respectively. Hot effects were immediate and diminished quickly in 5 days, with an increase of 19% (RR = 1.19, 95%CI: 1.14-1.23) and 21% (RR = 1.21, 95%CI: 1.16-1.26) in AECOs over lag 0-5 when comparing the 95th and 99th percentile of temperature to the optimal temperature. Children and the elderly were more vulnerable to cold effects. The youth and middle-aged people suffered more from high temperature. The effects of temperature were similar between males and females. In summary, significant increases were observed in the frequency of AECOs during cold and hot days, and the weather-associated increases in AECOs are different among age groups. This information has valuable implications in ambulance demand prediction and service provision planning.

Evaluating the impact of solar radiation on pediatric heat balance within enclosed, hot vehicles

Pediatric deaths due to children being left in hot cars remain a significant yet preventable public health concern. The current study aims to demonstrate the influence of vehicle type, time of day, and solar exposure (sun or shade) on the energy balance and core temperature (T_c) of a hypothetical two-year old boy left in a vehicle on a hot day. Cabin temperatures and relative humidity were collected within six enclosed vehicles under sun or full shade in Tempe, Arizona. These variables and radiation estimates were used to estimate the human energy balance and final T_c across 76 measurement cycles lasting approximately 60minutes. Interior temperatures averaged 39.5°C and 47.6°C in the shade and sun, respectively, at steady-state. Based on the specific heat of a human body, the average T_c after 60 minutes in shaded or sun-exposed vehicles was estimated to reach 38.2±0.29°C and 39.1±0.41°C, respectively, with a significantly higher final T_c in sun-exposed vehicles across all days and in the shaded minivan. Extrapolation to 2 hours is estimated to result in heat injury in the sun. Results demonstrate the influence of radiation on a child's thermal balance in a hot and dry environment. In real-world situations, it is critical to acknowledge variability between children, the starting car environment, and climate (e.g., humid versus dry), and that a child left in any vehicle car can experience potentially lethal core temperatures if forgotten, as shown by vehicular heat stroke statistics. Findings may improve public messaging and reinforce the need for policy action and technological adoption to prevent injury and death.

Examining the Association Between Apparent Temperature and Mental Health-Related Emergency Room Visits in California

The association between ambient temperature and morbidity has been explored previously. However, the association between temperature and mental health-related outcomes, including violence and self-harm, remains relatively unexamined. For the period 2005-2013, we obtained daily counts of mental health-related emergency room visits involving injuries with an external cause for 16 California climate zones from the California Office of Statewide Health Planning and Development and combined them with data on mean apparent temperature, a combination of temperature and humidity. Using Poisson regression models, we estimated climate zone-level associations and then used random-effects meta-analyses to produce overall estimates. Analyses were stratified by season (warm: May-October; cold: November-April), race/ethnicity, and age. During the warm season, a 10°F (5.6°C) increase in same-day mean apparent temperature was associated with 4.8% (95% confidence interval (CI): 3.6, 6.0), 5.8% (95% CI: 4.5, 7.1), and 7.9% (95% CI: 7.3, 8.4) increases in the risk of emergency room visits for mental health disorders, self-injury/suicide, and intentional injury/homicide, respectively. High temperatures during the cold season were also positively associated with these outcomes. Variations were observed by race/ethnicity, age group, and sex, with Hispanics, whites, persons aged 6-18 years, and females being at greatest risk for most outcomes. Increasing mean apparent temperature was found to have acute associations with mental health outcomes and intentional injuries, and these findings warrant further study in other locations.

Effects of high ambient temperature on ambulance dispatches in different age groups in Fukuoka, Japan

BACKGROUND

The elderly population has been the primary target of intervention to prevent heat-related illnesses. According to the literature, the highest risks have been observed among the elderly in the temperature-mortality relationship. However, findings regarding the temperature-morbidity relationship are inconsistent.

OBJECTIVES

This study aimed to examine the association of temperature with ambulance dispatches due to acute illnesses, stratified by age group. Specifically, we explored the optimum temperature, at which the relative health risks were found to be the lowest, and quantified the health risk associated with higher temperatures among different age groups.

METHODS

We used the data for ambulance dispatches in Fukuoka, Japan, during May and September from 2005 to 2012. The data were grouped according to age in 20-year increments. We explored the pattern of the association of ambulance dispatches with temperature using a smoothing spline curve to identify the optimum temperature for each age group. Then, we applied a distributed lag nonlinear model to estimate the risks of the 85th-95th percentile temperature relative to the overall optimum temperature, for each age group.

RESULTS

The relative risk of ambulance dispatches at the 85th and 95th percentile temperature for all ages was 1.08 [95% confidence interval (CI): 1.05, 1.12] and 1.12 (95% CI: 1.08, 1.16), respectively. In comparison, among age groups, the optimum temperature was observed as 25.0°C, 23.2°C, and 25.3°C for those aged 0-19, 60-79, and ≥80, respectively. The optimum temperature could not be determined for those aged 20-39 and 40-59. The relative risks of high temperature tended to be higher for those aged 20-39 and 40-59 than those for other age groups.

CONCLUSIONS

We did not find any definite difference in the effect of high temperature on ambulance dispatches for different age groups. However, more measures should be taken for younger and middle-aged people to avoid heat-related illnesses.

Spatial variability in threshold temperatures of heat wave mortality: impact assessment on prevention plans

Spain's current heat wave prevention plans are activated according to administrative areas. This study analyses the determination of threshold temperatures for triggering prevention-plan activation by reference to isoclimatic areas, and describes the public health benefits. We subdivided the study area - the Madrid Autonomous Region (MAR) - into three, distinct, isoclimatic areas: 'North', 'Central' and 'South', and grouped daily natural-cause mortality (ICD-10: A00-R99) in towns of over 10,000 inhabitants (2000-2009 period) accordingly. Using these three areas rather than the MAR as a whole would have resulted in a possible decrease in mortality of 73 persons (38-108) in the North area, and in aborting unnecessary activation of the plan 153 times in the Central area and 417 times in the South area. Our results indicate that extrapolating this methodology would bring benefits associated with a reduction in attributable mortality and improved effectiveness of public health interventions.

A Geographical Analysis of Emergency Medical Service Calls and Extreme Heat in King County, WA, USA (2007-2012)

This research analyzed the relationship between extreme heat and Emergency Medical Service (EMS) calls in King County, WA, USA between 2007 and 2012, including the effect of community-level characteristics. Extreme heat thresholds for the Basic Life Support (BLS) data and the Advanced Life Support (ALS) data were found using a piecewise generalized linear model with Akaike Information Criterion (AIC). The association between heat exposure and EMS call rates was investigated using a generalized estimating equations with Poisson mean model, while adjusting for community-level indicators of poverty, impervious surface, and elderly population (65+). In addition, we examined the effect modifications of these community-level factors. Extreme-heat thresholds of 31.1 °C and 33.5 °C humidex were determined for the BLS and ALS data, respectively. After adjusting for other variables in the model, increased BLS call volume was significantly associated with occurring on a heat day (relative rate (RR) = 1.080, p < 0.001), as well as in locations with higher percent poverty (RR = 1.066, p < 0.001). No significant effect modification was identified for the BLS data on a heat day. Controlling for other variables, higher ALS call volume was found to be significantly associated with a heat day (RR = 1.067, p < 0.001), as well as in locations with higher percent impervious surface (RR = 1.015, p = 0.039), higher percent of the population 65 years or older (RR = 1.057, p = 0.005), and higher percent poverty (RR = 1.041, p = 0.016). Furthermore, percent poverty and impervious surface were found to significantly modify the relative rate of ALS call volumes between a heat day and non-heat day. We conclude that EMS call volume increases significantly on a heat day compared to non-heat day for both call types. While this study shows that there is some effect modification between the community-level variables and call volume on a heat day, further research is necessary. Our findings also suggest that with adequate power, spatially refined analyses may not be necessary to accurately estimate the extreme-heat effect on health.

Hospitalizations for heat-stress illness varies between rural and urban areas: an analysis of Illinois data, 1987-2014

BACKGROUND

The disease burden due to heat-stress illness (HSI), which can result in significant morbidity and mortality, is expected to increase as the climate continues to warm. In the United States (U.S.) much of what is known about HSI epidemiology is from analyses of urban heat waves. There is limited research addressing whether HSI hospitalization risk varies between urban and rural areas, nor is much known about additional diagnoses of patients hospitalized for HSI.

METHODS

Hospitalizations in Illinois for HSI (ICD-9-CM codes 992.x or E900) in the months of May through September from 1987 to 2014 (n = 8667) were examined. Age-adjusted mean monthly hospitalization rates were calculated for each county using U.S. Census population data. Counties were categorized into five urban-rural strata using Rural Urban Continuum Codes (RUCC) (RUCC1, most urbanized to RUCC5, thinly populated). Average maximum monthly temperature (°C) was calculated for each county using daily data. Multi-level linear regression models were used, with county as the fixed effect and temperature as random effect, to model monthly hospitalization rates, adjusting for the percent of county population below the poverty line, percent of population that is Non-Hispanic Black, and percent of the population that is Hispanic. All analyses were stratified by county RUCC. Additional diagnoses of patients hospitalized for HSI and charges for hospitalization were summarized.

RESULTS

Highest rates of HSI hospitalizations were seen in the most rural, thinly populated stratum (mean annual summer hospitalization rate of 1.16 hospitalizations per 100,000 population in the thinly populated strata vs. 0.45 per 100,000 in the metropolitan urban strata). A one-degree Celsius increase in maximum monthly average temperature was associated with a 0.34 increase in HSI hospitalization rate per 100,000 population in the thinly populated counties compared with 0.02 per 100,000 in highly urbanized counties. The most common additional diagnoses of patients hospitalized with HSI were dehydration, electrolyte abnormalities, and acute renal disorders. Total and mean hospital charges for HSI cases were $167.7 million and $20,500 (in 2014 US dollars).

CONCLUSION

Elevated temperatures appear to have different impacts on HSI hospitalization rates as function of urbanization. The most rural and the most urbanized counties of Illinois had the largest increases in monthly hospitalization rates for HSI per unit increase in the average monthly maximum temperature. This suggests that vulnerability of communities to heat is complex and strategies to reduce HSI may need to be tailored to the degree of urbanization of a county.

Effects of noise on telephone calls to the Madrid Regional Medical Emergency Service (SUMMA 112)

BACKGROUND

Although the effects of noise on population morbidity and mortality have been observed both in the short and long term, the morbidity and mortality indicators used to date have not enabled information on such health effects to be accessed in real time. At an international level, there are relatively few studies, mostly recent, which have considered an alternative indicator, such as the demand for medical attention provided by emergency services, taking into account environmental factors other than noise.

OBJECTIVES

To ascertain the short-term effect of road-traffic noise levels on medical care, broken down by organic, circulatory and respiratory causes, provided by the Madrid Regional Medical Emergency Service (Servicio de Urgencia Médica de Madrid/SUMMA 112).

METHODS

We used an ecological time-series study and fitted Poisson regression models, to analyse the number of daily, cause-specific episodes of care provided in situ by SUMMA 112, via emergency ambulance dispatches, across the period 01/01/2008-31/12/2009. To this end, we considered diurnal (Leqd: 7-23h), nocturnal (Leqn: 23-7h) and daily (Leq24: 24h) noise (in db(A)) as the principal factor, and chemical air pollution (µg/m³) and temperature (°C) as the control variables. We also controlled for trend and seasonalities, the autoregressive nature of the series, and day of the week.

RESULTS

Nocturnal noise exceeded the WHO threshold (55 db(A)) on 100% of nights, despite displaying a downward trend across the study period. For all causes, with the exception of emergency calls due to ischaemic disease, it was nocturnal rather than diurnal noise levels that had a short-term effect (lags 0-1) on SUMMA 112 calls, with this impact being greater for respiratory than for circulatory causes. Hence, for every increase of 1db in Leqn, the relative risks (RRs) were as follows: 1.11 (95% CI 1.09-1.13) for organic causes; 1.14 (95% CI: 1.11-1.18) for respiratory causes; and 1.08 (95% CI: 1.05-1.10) for circulatory causes.

CONCLUSION

SUMMA 112 data give access to real-time information on the health effects associated with increases in noise levels, which cannot be obtained via mortality or hospital-admission data, since these are collected in the longer term. Accordingly, this is something that would be immediately applicable in any future implementation of a syndromic surveillance system focusing on the effects of environmental pollutants on health.

A Case-Crossover Study of Heat Exposure and Injury Risk in Outdoor Agricultural Workers

Background

Recent research suggests that heat exposure may increase the risk of traumatic injuries. Published heat-related epidemiological studies have relied upon exposure data from individual weather stations.

Objective

To evaluate the association between heat exposure and traumatic injuries in outdoor agricultural workers exposed to ambient heat and internal heat generated by physical activity using modeled ambient exposure data.

Methods

A case-crossover study using time-stratified referent selection among 12,213 outdoor agricultural workers with new Washington State Fund workers’ compensation traumatic injury claims between 2000 and 2012 was conducted. Maximum daily Humidex exposures, derived from modeled meteorological data, were assigned to latitudes and longitudes of injury locations on injury and referent dates. Conditional logistic regression was used to estimate odds ratios of injury for a priori daily maximum Humidex categories.

Results

The mean of within-stratum (injury day and corresponding referent days) standard deviations of daily maximum Humidex was 4.8. The traumatic injury odds ratio was 1.14 (95% confidence interval 1.06, 1.22), 1.15 (95% confidence interval 1.06, 1.25), and 1.10 (95% confidence interval 1.01, 1.20) for daily maximum Humidex of 25–29, 30–33, and ≥34, respectively, compared to < 25, adjusted for self-reported duration of employment. Stronger associations were observed during cherry harvest duties in the June and July time period, compared to all duties over the entire study period.

Conclusions

Agricultural workers laboring in warm conditions are at risk for heat-related traumatic injuries. Combined heat-related illness and injury prevention efforts should be considered in high-risk populations exposed to warm ambient conditions in the setting of physical exertion.