Using forecast and observed weather data to assess performance of forecast products in identifying heat waves and estimating heat wave effects on mortality

Impact of heat on emergency hospital admissions related to kidney diseases in Texas: Uncovering racial disparities

BACKGROUND AND OBJECTIVE

While impact of heat exposure on human health is well-documented, limited research exists on its effect on kidney disease hospital admissions especially in Texas, a state with diverse demographics and a high heat-related death rate. We aimed to explore the link between high temperatures and emergency kidney disease hospital admissions across 12 Texas Metropolitan Statistical Areas (MSAs) from 2004 to 2013, considering causes, age groups, and ethnic populations.

METHODS

To investigate the correlation between high temperatures and emergency hospital admissions, we utilized MSA-level hospital admission and weather data. We employed a Generalized Additive Model to calculate the association specific to each MSA, and then performed a random effects meta-analysis to estimate the overall correlation. Analyses were stratified by age groups, admission causes, and racial/ethnic disparities. Sensitivity analysis involved lag modifications and ozone inclusion in the model.

RESULTS

Our analysis found that each 1 °C increase in temperature was associated with a 1.73 % (95 % CI [1.43, 2.03]) increase in hospital admissions related to all types of kidney diseases. Besides, the effect estimates varied across different age groups and specific types of kidney diseases. We observed statistically significant associations between high temperatures and emergency hospital admissions for Acute Kidney Injury (AKI) (3.34 % (95 % CI [2.86, 3.82])), Kidney Stone (1.76 % (95 % CI [0.94, 2.60])), and Urinary Tract Infections (UTI) (1.06 % (95 % CI [0.61, 1.51])). Our research findings indicate disparities in certain Metropolitan Statistical Areas (MSAs). In Austin, Houston, San Antonio, and Dallas metropolitan areas, the estimated effects are more pronounced for African Americans when compared to the White population. Additionally, in Dallas, Houston, El Paso, and San Antonio, the estimated effects are greater for the Hispanic group compared to the Non-Hispanic group.

CONCLUSIONS

This study finds a strong link between higher temperatures and kidney disease-related hospital admissions in Texas, especially for AKI. Public health actions are necessary to address these temperature-related health risks, including targeted kidney health initiatives. More research is needed to understand the mechanisms and address health disparities among racial/ethnic groups.

Impact of heat on emergency hospital admission in Texas: geographic and racial/ethnic disparities

BACKGROUND

Studies exploring the racial/ethnicity disparity of the impact of heat on hospital admission are notably limited, especially in Texas, a state with a diverse population and consistently ranking among the top ten U.S. states for heat-related deaths per capita from 2018 to 2020.

OBJECTIVE

Our objective is to determine the correlation between elevated temperatures and emergency hospital admissions for various causes and age groups across 12 Metropolitan Statistical Areas(MSAs) in Texas. Additionally, we aim to investigate health inequalities in the five largest MSAs in Texas between 2004 and 2013.

METHODS

We used MSA-level hospital admission and weather data to estimate the relationship between heat and emergency hospital admissions. We applied a Generalized Additive Model and random effects meta-analysis to calculate MSA-specific associations and overall correlation, repeating the analysis for age groups and specific causes of admission. We also investigated health disparities across racial and ethnic groups and performed a sensitivity analysis.

RESULTS

The results showed that a 1 °C increase in temperature was associated with a 0.50% (95% CI [0.38%, 0.63%]) increase in all-cause emergency hospital admissions. Heat's impact on hospital admissions varied among age groups and causes, with children under 6 years showing the highest effect estimate (0.64% (95% CI [0.32%,0.96%])). Statistically significant associations were found for Cardiovascular Diseases (0.27% (95% CI [0.07%,0.47%])), Ischemic Heart Diseases (0.53% (95% CI [0.15%,0.92%])), Pneumonia (0.70% (95% CI [0.25%,1.16%])), and Respiratory Diseases (0.67% (95% CI [0.18%,1.17%])). Health disparities were found among racial and ethnic groups in the five largest MSAs.

IMPACT STATEMENT

Studies exploring the impact of heat on hospital admission in Texas are notably limited. Our research provided a comprehensive examination of the connection between heat and emergency hospital admissions throughout Texas. Furthermore, we are the first to examine racial/ethnic disparities, identifying African American and Hispanic groups as disproportionately affected. These insights provide valuable insights for policymakers to allocate resources and implement strategies to mitigate the negative consequences of rising temperatures.

Greening is a promising but likely insufficient adaptation strategy to limit the health impacts of extreme heat

BACKGROUND

Adapting the urban environment to heat is a public health priority in the context of climate change. Cities are now considering interventions on specific urban characteristics known to contribute to the urban heat island (UHI) such as vegetation and imperviousness.

OBJECTIVES

To explore how these urban characteristics influence the temperature-mortality relationship in the Paris region.

METHODS

We modeled the temperature-mortality relationship for the 1300 municipalities of the region from 1990 to 2015, while including an interaction with indicators that summarize the municipalities' main urban characteristics. Four indicators were tested: lack of green spaces, lack of trees, proportion of impervious surface, and overexposed population to a potential night UHI.

RESULTS

The shape of the temperature-mortality relationship was similar across all municipalities, but with a higher slope at the highest temperatures in municipalities with less green spaces, less trees, and more impervious soil. For instance, in Paris and its close suburbs, the relative risk associated with a temperature in the 99th percentile of the temperature distribution (compared to the 50th percentile) was 2.17 [IC95% 1.98:2.38] in municipalities with 40% of their surface covered by trees compared to 2.57 [IC 95% 2.47:2.68] in municipalities with only 3% of their surface covered by trees.

DISCUSSION

A lack of vegetation and a high degree of imperviousness were associated with a higher risk of heat-related mortality in the Paris region. Therefore, we can assume that interventions targeting these characteristics could reduce the health impacts of extreme heat. Such interventions should be coupled with other initiatives such as protecting the most vulnerable and promoting appropriate behaviors.

Heatwave Damage Prediction Using Random Forest Model in Korea

Climate change increases the frequency and intensity of heatwaves, causing significant human and material losses every year. Big data, whose volumes are rapidly increasing, are expected to be used for preemptive responses. However, human cognitive abilities are limited, which can lead to ineffective decision making during disaster responses when artificial intelligence-based analysis models are not employed. Existing prediction models have limitations with regard to their validation, and most models focus only on heat-associated deaths. In this study, a random forest model was developed for the weekly prediction of heat-related damages on the basis of four years (2015–2018) of statistical, meteorological, and floating population data from South Korea. The model was evaluated through comparisons with other traditional regression models in terms of mean absolute error, root mean squared error, root mean squared logarithmic error, and coefficient of determination (R2). In a comparative analysis with observed values, the proposed model showed an R2 value of 0.804. The results show that the proposed model outperforms existing models. They also show that the floating population variable collected from mobile global positioning systems contributes more to predictions than the aggregate population variable.

Intensity-duration-frequency relationship of WBGT extremes using regional frequency analysis in South Korea

The risk levels of heat-related extreme events need to be estimated for prediction and real-time monitoring to mitigate their impacts on air quality, public health, the ecosystem, and critical infrastructure. Many countries have adopted meteorological variable base thresholds for assessing the risk level of heat-related extreme events. These thresholds provide an approximate risk level for a specific event but do not consider its intensity and duration in the risk assessment. The current study provides a statistical tool to assess the risk of heat-related extreme events while concurrently considering their intensities and durations based on the wet-bulb globe temperature (WBGT). To this end, the intensity-duration-frequency (IDF) relationship of the extreme WBGT in South Korea was derived. Regional frequency analysis was employed to understand the IDF relationship. Return levels of heat-related extreme events in South Korea were calculated and their characteristics were investigated based on the annual maximum WBGT observations. The results showed that the IDF relationship could provide the risks of heat-related extreme events while concurrently considering their intensities and durations. The extreme WBGT in South Korea was used to categorize two regions such as coastal and inland based on their statistical characteristics. The return levels of the annual maximum WBGT events were found to vary largely by location. The return levels corresponding to 32 °C with 3-h duration for stations in the coastal and inland regions ranged from 1- to 100-years and 3- to 1000-years, respectively. Mean values of return levels for heatwave events in Seoul, Incheon, Daejon, Gwangju, Daegu, and Busan were 2.8-, 8.4-, 15.3-, 2.8-, 1.6-, and 2.2-years, respectively. The return levels of heatwaves for the warmer cities are smaller than those for cooler cities. The return levels of the heatwave events in South Korea showed a significant increasing trend in several cities, supporting the notion that the impact of heatwave events on South Korea might become more severe in the future.

The Role of Individual and Small-Area Social and Environmental Factors on Heat Vulnerability to Mortality Within and Outside of the Home in Boston, MA

Climate change is resulting in heatwaves that are more frequent, severe, and longer lasting, which is projected to double-to-triple the heat-related mortality in Boston, MA if adequate climate change mitigation and adaptation strategies are not implemented. A case-only analysis was used to examine subject and small-area neighborhood characteristics that modified the association between hot days and mortality. Deaths of Boston, Massachusetts residents that occurred from 2000–2015 were analyzed in relation to the daily temperature and heat index during the warm season as part of the case-only analysis. The modification by small-area (census tract, CT) social, and environmental (natural and built) factors was assessed. At-home mortality on hot days was driven by both social and environmental factors, differentially across the City of Boston census tracts, with a greater proportion of low-to-no income individuals or those with limited English proficiency being more highly represented among those who died during the study period; but small-area built environment features, like street trees and enhanced energy efficiency, were able to reduce the relative odds of death within and outside the home. At temperatures below current local thresholds used for heat warnings and advisories, there was increased relative odds of death from substance abuse and assault-related altercations. Geographic weighted regression analyses were used to examine these relationships spatially within a subset of at-home deaths with high-resolution temperature and humidity data. This revealed spatially heterogeneous associations between at-home mortality and social and environmental vulnerability factors.

Evaluating the potential public health impacts of the Toronto cold weather program

BACKGROUND

Extreme cold weather alert programs have been implemented in some areas to address the significant health impacts of exposure to cold. One such program is the Toronto Cold Weather Program (TCWP) that was implemented in the City of Toronto since 1996 to protect the public from extreme weather conditions. In this paper, we aim to evaluate the effectiveness of the TCWP in reducing mortality and morbidity outcomes related to cold temperatures.

METHODS

We applied a quasi-experimental study design using the Difference-in-Differences method coupled with propensity-score-matching to determine the effect of the TCMP on daily hospitalizations and deaths due to cardiovascular disease (CVD), coronary heart disease (CHD) or cerebrovascular disease, using two complementary analytical approaches.

RESULTS

Overall, the analysis did not detect an impact on reduced mortality/morbidity in the City of Toronto from the TCMP. For example, we obtained a Risk Difference (RD) of -0.88 (per 1,000,000 people) (95% CI: -3.27 to 1.51) and a Risk Ratio (RR) of 0.98 (95% CI: 0.91 to 1.05) people for CVD hospitalizations.

CONCLUSIONS

The TCWP was not found to be effective in reducing cold related mortality and morbidity which demonstrates the importance of improving existing policies related to cold in Canada and other countries.

The predictability of heat-related mortality in Prague, Czech Republic, during summer 2015-a comparison of selected thermal indices

We compared selected thermal indices in their ability to predict heat-related mortality in Prague, Czech Republic, during the extraordinary summer 2015. Relatively, novel thermal indices-Universal Thermal Climate Index and Excess Heat Factor (EHF)-were compared with more traditional ones (apparent temperature, simplified wet-bulb globe temperature (WBGT), and physiologically equivalent temperature). The relationships between thermal indices and all-cause relative mortality deviations from the baseline (excess mortality) were estimated by generalized additive models for the extended summer season (May-September) during 1994-2014. The resulting models were applied to predict excess mortality in 2015 based on observed meteorology, and the mortality estimates by different indices were compared. Although all predictors showed a clear association between thermal conditions and excess mortality, we found important variability in their performance. The EHF formula performed best in estimating the intensity of heat waves and magnitude of heat-impacts on excess mortality on the most extreme days. Afternoon WBGT, on the other hand, was most precise in the selection of heat-alert days during the extended summer season, mainly due to a relatively small number of "false alerts" compared to other predictors. Since the main purpose of heat warning systems is identification of days with an increased risk of heat-related death rather than prediction of exact magnitude of the excess mortality, WBGT seemed to be a slightly favorable predictor for such a system.

Comparison of health risks by heat wave definition: Applicability of wet-bulb globe temperature for heat wave criteria

Despite the active applications of thermal comfort indices for heat wave definitions, there is lack of evaluation for the impact of extended days of high temperature on health outcomes using many of the indices. This study compared the impact of heat waves on health outcomes among different heat wave definitions based on thermal comfort and air temperature. We compared heat waves in South Korea (cities and provinces) for the warm season for 2011-2014, using air temperature, heat index (HI), and web-bulb globe temperature (WBGT). Heat waves were defined as days with daily maximum values of each index at a specified threshold (literature-based, the 90th and 95th percentiles) or above. Distributed lag non-linear models and meta-analysis were used to estimate risk of mortality and hospitalization for all-causes, cardiovascular causes, respiratory causes and heat disorders during heat wave days compared to non-heat wave days. WBGT identified 1.15 times longer maximum heat wave duration for the study periods than air temperature when the thresholds were based on 90th and 95th percentiles. Over the study period, for heat waves defined by WBGT and HI, the Southwestern region showed the highest total number of heat wave days, whereas for air temperature the longest heat wave days were identified in the southeastern region. The highest and most significant impact of heat waves were found by WBGT for hospitalization from heat disorders (Relative risk = 2.959, 95% CI: 1.566-5.594). In sensitivity analyses using different structure of lags and temperature metrics (e.g., daily mean and minimum), the impacts of heat waves on most health outcomes substantially increased by using WBGT for heat wave definitions. As a result, WBGT and its thresholds can be used to relate heat waves and heat-related diseases to improve the prevention effectiveness of heat wave warnings and give informative health guidelines according to the range of WBGT thresholds.

Effectiveness of National Weather Service heat alerts in preventing mortality in 20 US cities

BACKGROUND

Extreme heat is a well-documented public health threat. The US National Weather Service (NWS) issues heat advisories and warnings (collectively, "heat alerts") in advance of forecast extreme heat events. The effectiveness of these alerts in preventing deaths remains largely unknown.

OBJECTIVES

To quantify the change in mortality rates associated with heat alerts in 20 US cities between 2001 and 2006.

METHODS

Because NWS heat alerts are issued based on forecast weather and these forecasts are imperfect, in any given location there exists a set of days of similar observed heat index in which heat alerts have been issued for some days but not others. We used a case-crossover design and conditional logistic regression to compare mortality rates on days with versus without heat alerts among such eligible days, adjusting for maximum daily heat index and temporal factors. We combined city-specific estimates into a summary measure using standard random-effects meta-analytic techniques.

RESULTS

Overall, NWS heat alerts were not associated with lower mortality rates (percent change in rate: -0.5% [95% CI: -2.8, 1.9]). In Philadelphia, heat alerts were associated with a 4.4% (95% CI: -8.3, -0.3) lower mortality rate or an estimated 45.1 (95% empirical CI: 3.1, 84.1) deaths averted per year if this association is assumed to be causal. No statistically significant beneficial association was observed in other individual cities.

CONCLUSIONS

Our results suggest that between 2001 and 2006, NWS heat alerts were not associated with lower mortality in most cities studied, potentially missing a valuable opportunity to avert a substantial number of heat-related deaths. These results highlight the need to better link alerts to effective communication and intervention strategies to reduce heat-related mortality.

Relationship among environmental quality variables, housing variables, and residential needs: a secondary analysis of the relationship among indoor, outdoor, and personal air (RIOPA) concentrations database

Retrospective descriptive secondary analyses of data from relationships of indoor, outdoor, and personal air (RIOPA) study homes (in Houston, Texas; Los Angeles County, California; and, Elizabeth, New Jersey May 1999-February 2001) were conducted. Data included air exchange rates, associations between indoor and outdoor temperature and humidity, and calculated apparent temperature and humidex. Analyses examined if study homes provided optimum thermal comfort for residents during both heating and cooling seasons when compared to current American Society of Heating, Refrigerating and Air Conditioning Engineers (ASHRAE) Standards 62/62.1 and 55. Results suggested outdoor temperature, humidex, and apparent temperature during the cooling season potentially served as indicators of indoor personal exposure to parameters of thermal comfort. Outdoor temperatures, humidex, and apparent temperature during the cooling season had statistically significant predictive abilities in predicting indoor temperature. During the heating season, only humidex in Texas and combined data across study states were statistically significant, but with weaker to moderate predicative ability. The high degree of correlation between outdoor and indoor environmental variables provided support for the validity of epidemiologic studies of weather relying on temporal comparisons. Results indicated most RIOPA study residents experienced thermal comfort; however, many values indicated how several residents may have experienced some discomfort depending on clothing and indoor activities. With climate change, increases in temperature are expected, with more days of extreme heat and humidity and, potentially harsher, longer winters. Homes being built or modernized should be created with the appropriate guidelines to provide comfort for residents daily and in extreme weather events.

Spatiotemporal analysis of heat and heat wave effects on elderly mortality in Texas, 2006-2011

BACKGROUND

Heat and heat waves have been linked to the increased risk of deaths, hospital admissions, and emergency visits.

OBJECTIVES

This study presents a spatiotemporal analysis of heat and heat wave effects on elderly mortality (≥65years) in Texas.

METHODS

We compiled a six-year daily weather and mortality counts dataset from 254 counties in Texas during 2006-2011. Heat index (HI), a combination of temperature and relative humidity, was used as the exposure metric in this study. Associations between daily all-cause elderly mortality and daily maximum HI and heat waves (≥2days of county-specific daily maximum HI>95th percentiles) were examined using a quasi-Poisson regression. A Markov random field smoother was included in the model to account for spatial autocorrelations and spatial heterogeneity. The model also controlled for long-term trend and seasonality in mortality, and the effects of day of the week.

DISCUSSION

On average, the lag effect of heat on elderly mortality risk lasted up to 10days, and the cumulative heat effects started to increase rapidly when daily maximum HI exceeded the 90th percentile in Texas. Elderly living in Northwest Texas and parts of West Texas were at greater risk of elderly mortality attributable to heat waves, and the highest relative risk for elderly mortality occurred in El Paso County (4.70, 95% Confidence Interval=4.33, 5.10).

CONCLUSIONS

Our study indicates strong geographical variations of heat wave effects on elderly mortality risk in Texas.

Heat effects among migrant and seasonal farmworkers: a case study in Colorado

BACKGROUND

Although migrant and seasonal farmworkers are highly vulnerable to ambient heat because of their working conditions, heat effects in this population have been rarely studied.

OBJECTIVES

We estimated effects of heat on mean daily counts of clinic visits among migrant and seasonal farmworkers by taking advantage of a unique longitudinal medical records database in the USA.

METHODS

We compiled a daily weather and clinic visit data set based on data from a health centre in Colorado for the summer of 2013. A total of 14 481 patients were included in our analysis, including 150 migrant farmworkers and 231 seasonal farmworkers with an average of 3 and 4 visits per day. We used Poisson regression to estimate the associations between heat and daily all-cause or cardiovascular-specific clinic visits among migrant or seasonal farmworkers or other stratified patients. We defined heat effects as the percentage difference in average daily counts of clinic visits, comparing 90-50th centiles of daily mean apparent temperature, a composite index accounting for both temperature and humidity. We conducted a sensitivity analysis to evaluate the impact of adjustment for ozone levels and different heat definitions.

RESULTS

Estimates of heat effects on average daily clinic visits among migrant farmworkers were positive (88.0%, 95% CI: 26.2% to 180.0%). We did not observe statistically significant associations between heat and clinic visits among other stratified groups.

CONCLUSIONS

Our study appears to be the first to link heat effects with clinic data among migrant and seasonal farmworkers. This research suggests possible significant impact of heat on migrant farmworkers and provides justifications for further studies.

The Effects of Climate Change on Patients With Chronic Lung Disease. A Systematic Literature Review

BACKGROUND

Ever since higher overall mortality rates due to heat stress were reported during the European heat waves of 2003 and 2006, the relation between heat waves and disease-specific events has been an object of scientific study. The effects of heat waves on the morbidity and mortality of persons with chronic lung disease remain unclear.

METHODS

We conducted a systematic search using PubMed, the Cochrane Library, and Google Advanced Search to identify relevant studies published between 1990 and 2015. The reference lists of the primarily included articles were searched for further pertinent articles. All articles were selected according to the PRISMA guidelines. The heat-wave-related relative excess mortality was descriptively expressed as a mean daily rate ratio ([incidence 1]/[incidence 2]), and the cumulative excess risk (CER) was expressed in percent.

RESULTS

33 studies with evaluable raw data concerning the effect of heat waves on patients with chronic lung disease (chronic obstructive pulmonary disease, bronchial asthma, pulmonary arterial hypertension, and idiopathic pulmonary fibrosis) were analyzed in this review. By deriving statistics from the overall data set, we arrived at the conclusion that future heat waves will-with at least 90% probability-result in a mean daily excess mortality (expressed as a rate ratio) of at least 1.018, and-with 50% probability-in a mean daily excess mortality of at least 1.028. These figures correspond, respectively, to 1.8% and 2.8% rises in the daily risk of death.

CONCLUSION

Heat waves significantly increase morbidity and mortality in patients with chronic lung disease. The argument that the excess mortality during heat waves is compensated for by a decrease in mortality in the subsequent weeks/months (mortality displacement) should not be used as an excuse for delay in implementing adaptive strategies to protect lung patients from this risk to their health.

Geographical variation in relative risks associated with heat: Update of Spain's Heat Wave Prevention Plan

A decade after the implementation of prevention plans designed to minimise the impact of high temperatures on health, some countries have decided to update these plans in order to improve the weakness detected in these ten years of operation. In the case of Spain, this update has fundamentally consisted of changing the so-called "threshold" or "trigger" temperatures used to activate the plan, by switching from temperature values based on climatological criteria to others obtained by epidemiological studies conducted on a provincial scale. This study reports the results of these "trigger" temperatures for each of Spain's 52 provincial capitals, as well as the impact of heat on mortality by reference to the relative risks (RRs) and attributable risks (ARs) calculated for natural as well as circulatory and respiratory causes. The results obtained for threshold temperatures and RRs show a more uniform behaviour pattern than those obtained using temperature values based on climatological criteria; plus a clear decrease in RRs of heat-associated mortality due to the three causes considered, at both a provincial and regional level as well as for Spain as a whole. The updating of prevention plans is regarded as crucial for optimising the operation of these plans in terms of reducing the effect of high temperatures on population health.

Heat waves and morbidity: current knowledge and further direction-a comprehensive literature review

In the past few decades, several devastating heat wave events have significantly challenged public health. As these events are projected to increase in both severity and frequency in the future, it is important to assess the relationship between heat waves and the health indicators that can be used in the early warning systems to guide the public health response. Yet there is a knowledge gap in the impact of heat waves on morbidity. In this study, a comprehensive review was conducted to assess the relationship between heat waves and different morbidity indicators, and to identify the vulnerable populations. The PubMed and ScienceDirect database were used to retrieve published literature in English from 1985 to 2014 on the relationship between heat waves and morbidity, and the following MeSH terms and keywords were used: heat wave, heat wave, morbidity, hospital admission, hospitalization, emergency call, emergency medical services, and outpatient visit. Thirty-three studies were included in the final analysis. Most studies found a short-term negative health impact of heat waves on morbidity. The elderly, children, and males were more vulnerable during heat waves, and the medical care demand increased for those with existing chronic diseases. Some social factors, such as lower socioeconomic status, can contribute to heat-susceptibility. In terms of study methods and heat wave definitions, there remain inconsistencies and uncertainties. Relevant policies and guidelines need to be developed to protect vulnerable populations. Morbidity indicators should be adopted in heat wave early warning systems in order to guide the effective implementation of public health actions.

Impact of the 2011 heat wave on mortality and emergency department visits in Houston, Texas

BACKGROUND

Heat waves have been linked to increased risk of mortality and morbidity, and are projected to increase in frequency and intensity in a changing climate. Houston and other areas in Texas experienced an exceptional heat wave in the summer of 2011 producing the hottest August on record. This study aims to assess the health-related impact of this heat wave.

METHODS

Distributed lag models were used to estimate associations between the 2011 heat wave and all-cause mortality and emergency department (ED) visits from May 1 through September 30 for the five-year period 2007-2011. The 2011 heat wave is defined as a continuous period from August 2 through 30, 2011 according to the heat advisories issued by the local National Weather Service office, and is included in the models as a dummy variable. We compared the estimated excess risk among the models with and without adjustment of continuous temperature and ozone.

RESULTS

The 2011 heat wave in Houston was associated with a 3.6% excess risk in ED visits (95% CI: 0.6%, 6.6%) and 0.6% increase in mortality risk (95% CI: -5.5%, 7.1%). The elderly over 65 years of age were at the greatest risk in ED visits. These patterns are consistent across different heat-wave definitions, and results are similar when adjusting for continuous temperature and ozone.

CONCLUSIONS

The 2011 heat wave in Houston had a substantial impact on ED visits and no significant impact on mortality. Our findings provide insights into local heat-wave and health preparations and interventions.

Developing a heatwave early warning system for Sweden: evaluating sensitivity of different epidemiological modelling approaches to forecast temperatures

Over the last two decades a number of heatwaves have brought the need for heatwave early warning systems (HEWS) to the attention of many European governments. The HEWS in Europe are operating under the assumption that there is a high correlation between observed and forecasted temperatures. We investigated the sensitivity of different temperature mortality relationships when using forecast temperatures. We modelled mortality in Stockholm using observed temperatures and made predictions using forecast temperatures from the European Centre for Medium-range Weather Forecasts to assess the sensitivity. We found that the forecast will alter the expected future risk differently for different temperature mortality relationships. The more complex models seemed more sensitive to inaccurate forecasts. Despite the difference between models, there was a high agreement between models when identifying risk-days. We find that considerations of the accuracy in temperature forecasts should be part of the design of a HEWS. Currently operating HEWS do evaluate their predictive performance; this information should also be part of the evaluation of the epidemiological models that are the foundation in the HEWS. The most accurate description of the relationship between high temperature and mortality might not be the most suitable or practical when incorporated into a HEWS.

The 2011 heat wave in Greater Houston: Effects of land use on temperature

Effects of land use on temperatures during severe heat waves have been rarely studied. This paper examines land use-temperature associations during the 2011 heat wave in Greater Houston. We obtained high resolution of satellite-derived land use data from the US National Land Cover Database, and temperature observations at 138 weather stations from Weather Underground, Inc (WU) during the August of 2011, which was the hottest month in Houston since 1889. Land use regression and quantile regression methods were applied to the monthly averages of daily maximum/mean/minimum temperatures and 114 land use-related predictors. Although selected variables vary with temperature metric, distance to the coastline consistently appears among all models. Other variables are generally related to high developed intensity, open water or wetlands. In addition, our quantile regression analysis shows that distance to the coastline and high developed intensity areas have larger impacts on daily average temperatures at higher quantiles, and open water area has greater impacts on daily minimum temperatures at lower quantiles. By utilizing both land use regression and quantile regression on a recent heat wave in one of the largest US metropolitan areas, this paper provides a new perspective on the impacts of land use on temperatures. Our models can provide estimates of heat exposures for epidemiological studies, and our findings can be combined with demographic variables, air conditioning and relevant diseases information to identify 'hot spots' of population vulnerability for public health interventions to reduce heat-related health effects during heat waves.