The potential health impacts of climate variability and change for the United States: executive summary of the report of the health sector of the U.S. National Assessment

First Isolation and Genome Sequence Analysis of West Nile Virus in Mosquitoes in Brazil

West Nile virus is a flavivirus transmitted by mosquitoes, mainly of the genus Culex. In Brazil, serological studies have already indicated the circulation of the virus since 2003, with the first human case detected in 2014. The objective of the present paper is to report the first isolation of WNV in a Culex (Melanoconion) mosquito. Arthropods were collected by protected human attraction and CDC light bait, and taxonomically identified and analyzed by viral isolation, complement fixation and genomic sequencing tests. WNV was isolated from samples of Culex (Melanoconion) mosquitoes, and the sequencing analysis demonstrated that the isolated strain belonged to lineage 1a. The finding of the present study presents the first evidence of the isolation and genome sequencing of WNV in arthropods in Brazil.

Human Health and Well-being in a Warming World

Policy Points After decades of scientific progress and growth in academic literature, there is a recognition that climate change poses a substantial threat to the health and well-being of individuals and communities both in the United States and globally. Solutions to mitigate and adapt to climate change can have important health cobenefits. A vital component of these policy solutions is that they must also take into consideration historic issues of environmental justice and racism, and implementation of these policies must have a strong equity lens.

Temporal variation in the association between temperature and cause-specific mortality in 15 German cities

BACKGROUND

There is limited evidence of temporal changes in the association between air temperature and the risk of cause-specific cardiovascular [CVD] and respiratory [RD] mortality.

METHOD

We explored temporal variations in the association between short-term exposures to air temperature and non-accidental and cause-specific CVD and RD mortality in the 15 largest German cities over 24 years (1993-2016) using time-stratified time series analysis. We applied location-specific confounder-adjusted Poisson regression with distributed lag non-linear models with a lag period of 14 days to estimate the temperature-mortality associations. We then pooled the estimates by a multivariate meta-analytical model. We analysed the whole study period and the periods 1993-2004 and 2005-16, separately. We also carried out age- and sex-stratified analysis. Cold and heat effects are reported as relative risk [RR] at the 1st and the 99th temperature percentile, relative to the 25th and the 75th percentile, respectively.

RESULT

We analysed a total of 3,159,292 non-accidental, 1,063,198 CVD and 183,027 RD deaths. Cold-related RR for CVD mortality was seen to rise consistently over time from 1.04 (95% confidence interval [95% CI] 1.02, 1.06) in the period 1993-2004 to 1.10 (95% CI 1.09, 1.11) in the period 2005-16. A similar increase in cold-related RR was also observed for RD mortality with risk increasing from 0.99 (95% CI 0.96, 1.03) to 1.07 (95% CI 1.03, 1.10). Cold-related ischemic, cerebrovascular, and heart failure mortality risk were seen to be increasing over time. Similarly, COPD, the commonly speculated driver of heat-related RD mortality was found to have a constant heat-related risk over time. Males were increasingly vulnerable to cold with time for all causes of death. Females showed increasing sensitivity to cold for CVD mortality. Our results indicated a significant increased cold and heat vulnerability of the youngest age-groups (<64) to non-accidental and RD mortality, respectively. Similarly, the older age group (>65) were found to have significantly increased susceptibility to cold for CVD mortality.

CONCLUSION

We found evidence of rising population susceptibility to both heat- and cold-related CVD and RD mortality risk from 1993 to 2016. Climate change mitigation and targeted adaptation strategies might help to reduce the number of temperature-related deaths in the future.

Climate Change and Health in Urban Areas with a Mediterranean Climate: A Conceptual Framework with a Social and Climate Justice Approach

The consequences of climate change are becoming increasingly evident and highlight the important interdependence between the well-being of people and ecosystems. Although climate change is a global phenomenon, its causes and consequences vary dramatically across territories and population groups. Among settings particularly susceptible to health impacts from climate change are cities with a Mediterranean climate. Here, impacts will put additional pressure on already-stressed ecosystems and vulnerable economies and societies, increasing health inequalities. Therefore, this article presents and discusses a conceptual framework for understanding the complex relationship between climate change and health in the context of cities with Mediterranean climate from a social and climate justice approach. The different elements that integrate the conceptual framework are: (1) the determinants of climate change; (2) its environmental and social consequences; (3) its direct and indirect impacts on health; and (4) the role of mitigation and adaptation policies. The model places special emphasis on the associated social and health inequalities through (1) the recognition of the role of systems of privilege and oppression; (2) the distinction between structural and intermediate determinants of climate change at the root of health inequalities; (3) the role of individual and collective vulnerability in mediating the effects of climate change on health; and (4) the need to act from a climate justice perspective to reverse health inequities.

Weather integrated malaria prediction system using Bayesian structural time series model for northeast states of India

Malaria is an endemic disease in India and targeted to eliminate by the year 2030. The present study is aimed at understanding the epidemiological patterns of malaria transmission dynamics in Assam and Arunachal Pradesh followed by the development of a malaria prediction model using monthly climate factors. A total of 144,055 cases in Assam during 2011-2018 and 42,970 cases in Arunachal Pradesh were reported during the 2011-2019 period observed, and Plasmodium falciparum (74.5%) was the most predominant parasite in Assam, whereas Plasmodium vivax (66%) in Arunachal Pradesh. Malaria transmission showed a strong seasonal variation where most of the cases were reported during the monsoon period (Assam, 51.9%, and Arunachal Pradesh, 53.6%). Similarly, the malaria incidence was highest in the male population in both states (Asam, 55.75%, and Arunachal Pradesh, 51.43%), and the disease risk is also higher among the > 15 years age group (Assam, 61.7%, and Arunachal Pradesh, 67.9%). To predict the malaria incidence, Bayesian structural time series (BSTS) and Seasonal Auto-Regressive Integrated Moving Average with eXogenous factors (SARIMAX) models were implemented. A statistically significant association between malaria cases and climate variables was observed. The most influencing climate factors are found to be maximum and mean temperature with a 6-month lag, and it showed a negative association with malaria incidence. The BSTS model has shown superior performance on the optimal auto-correlated dataset (OAD) which contains auto-correlated malaria cases, cross-correlated climate variables besides malaria cases in both Assam (RMSE, 0.106; MAE, 0.089; and SMAPE, 19.2%) and Arunachal Pradesh (RMSE, 0.128; MAE, 0.122; and SMAPE, 22.6%) than the SARIMAX model. The findings suggest that the predictive performance of the BSTS model is outperformed, and it may be helpful for ongoing intervention strategies by governmental and nongovernmental agencies in the northeast region to combat the disease effectively.

Human Health, Environmental Quality and Governance Quality: Novel Findings and Implications From Human Health Perspective

Human health and wellbeing are intimately linked to the state of the environment. The current study emphasizes the role of environmental quality, government policies, and human health. This paper provides a detailed literature review of existing findings regarding our key variables of interest. The results argue that the implications of poor government policies and environmental pollution for rising economic development have led to poor environmental quality and health issues for humans. Based on earlier investigations, the present study reviewed the state-of-the-art review and determined innovative insights for outdoor and indoor environment difficulties. This study provides a detailed review of human health, environmental quality, and governance quality. In addition, the study conducts an empirical analysis using the annual data of low-income countries from 1996 to 2020. Government actions and health systems must be modified immediately to address these rising concerns successfully. The report offers policy recommendations for addressing health, governance, and environmental change mitigation issues, all of which are directly or indirectly related to the study. This article presents an overview of environmental change's health impacts and explores how health hazards may be reduced or eliminated through effective adaptation strategies.

Short-term changes in meteorological conditions and suicide: A systematic review and meta-analysis

BACKGROUND

Suicide is a leading cause of death, particularly for young adults. Suicidal behaviours are influenced by a wide-range of personal, social, and cultural factors. Emerging evidence suggests that daily changes in meteorological conditions, including temperature, increases the risk of suicide.

METHODS

We conducted a systematic review and meta-analysis of studies that examined associations between either daily, or weekly, variations for eight meteorological variables and suicide outcomes (attempts, or deaths). Meta-analytic methods were applied to derive summary measures of association using random effect models. We assessed the heterogeneity in these associations by region and biological sex.

RESULTS

We identified 29 studies of suicide. Of these, 26 reported associations between temperature, while fewer studies reported on rain (n = 4), solar radiation (n = 4), humidity (n = 3), sunshine (n = 3), atmospheric pressure (n = 2), wind (n = 2) and cloud cover (n = 2). The overall relative risk for suicide deaths/attempts per 1 °C increase in ambient temperature was 1.016 (95% CI: 1.013-1.019). Subgroup analysis of temperature found stronger associations with suicide when using the maximum rather than the mean daily temperature, among men, and for completed suicides relative to attempts. Regionally, the strongest associations were found in the East Asia and Pacific region. While associations were found for solar radiation and cloud coverage and suicide, we did not undertake a meta-analysis for these exposures as it was not possible to standardize measures of association across studies. Statistically significant associations were not observed for other identified meteorological variables.

CONCLUSIONS

Our findings suggest that daily increases in temperature increase the risk of suicide, particularly, among men and in the East Asia and Pacific region.

Norovirus Genogroup II Epidemics and the Potential Effect of Climate Change on Norovirus Transmission in Taiwan

The activity of norovirus varies from season to season, and the effect of climate change on the incidence of norovirus outbreaks is a widely recognized yet poorly understood phenomenon. Investigation of the possible association between climatic factors and the incidence of norovirus is key to a better understanding of the epidemiology of norovirus and early prediction of norovirus outbreaks. In this study, clinical stool samples from acute gastroenteritis outbreaks were collected from January 2015 to June 2019 in Taiwan. Data analysis from our study indicated that more than half of the cases were reported in the winter and spring seasons, including those caused by norovirus of genotypes GII (genogroup II).2, GII.3, GII.6, and GII.17, and 45.1% of the patients who tested positive for norovirus were infected by the GII.4 norovirus in autumn. However, GII.6 norovirus accounted for a higher proportion of the cases reported in summer than any other strain. Temperature is a crucial factor influencing patterns of epidemic outbreaks caused by distinct genotypes of norovirus. The results of this study may help experts predict and issue early public warnings of norovirus transmission and understand the effect of climate change on norovirus outbreaks caused by different genotypes and occurring in different locations.

Mapping Heat Vulnerability Index Based on Different Urbanization Levels in Nebraska, USA

Heatwaves cause excess mortality and physiological impacts on humans throughout the world, and climate change will intensify and increase the frequency of heat events. Many adaptation and mitigation studies use spatial distribution of highly vulnerable local populations to inform heat reduction and response plans. However, most available heat vulnerability studies focus on urban areas with high heat intensification by Urban Heat Islands (UHIs). Rural areas encompass different environmental and socioeconomic issues that require alternate analyses of vulnerability. We categorized Nebraska census tracts into four urbanization levels, then conducted factor analyses on each group and captured different patterns of socioeconomic vulnerabilities among resultant Heat Vulnerability Indices (HVIs). While disability is the major component of HVI in two urbanized classes, lower education, and races other than white have higher contributions in HVI for the two rural classes. To account for environmental vulnerability of HVI, we considered different land type combinations for each urban class based on their percentage areas and their differences in heat intensifications. Our results demonstrate different combinations of initial variables in heat vulnerability among urban classes of Nebraska and clustering of high and low heat vulnerable areas within the highest urbanized sections. Less urbanized areas show no spatial clustering of HVI. More studies with separation on urbanization level of residence can give insights into different socioeconomic vulnerability patterns in rural and urban areas, while also identifying changes in environmental variables that better capture heat intensification in rural settings.

#Climate Change on TikTok: A Content Analysis of Videos

Current day youth have an important role in climate activism, as the decisions and policies made now will have long lasting impacts on the climate and sustainability. Climate change is becoming an increasing concern for younger generations. As such, the purpose of this study was to describe content related to climate change on TikTok. This study included 100 English-language videos related to climate change featured on TikTok. The hashtag #climatechange was chosen because it had the most views of any related hashtag at the time of the study. The number of views, comments, and likes were recorded for each video. Each video was also observed for the presence of predetermined content characteristics. The 100 videos sampled collectively received 205,551,200 views, 40, 203,400 likes, and 666,089 comments. Only eight of the 100 videos included information from a reputable source. Only three of the characteristics were featured in a majority (> 50) of the videos. These were, presents climate change as real (93), affected populations (76), and climate anxiety/frustration (57). Videos mentioning natural disasters garnered 63,453,100 (30.87%) views, 14,245,200 (35.43%) likes, and 236,493 (35.50%) comments. In all, 73 of the 100 videos mentioned at least one environmental impact. Videos including this theme earned 156,677,200 (76.22%) views, 32,000,700 (79.60%) likes, and 563,195 (84.55%) comments. Social media platforms such as TikTok are important tools for understanding popular opinion regarding public health issues such as global climate change. However, the presence of credible professionals is essential on platforms such as TikTok to increase the chances that messaging is as comprehensive as time allows, while also being scientifically sound.

Home measures against low air humidity which may alleviate health problems

Objective

Humidity and temperature are fundamental for the balance in the life cycle of living beings and, consequently, for maintaining the well-being of the human population and reducing the prevalence of infectious diseases. Thus, in order to mitigate the impact of climate change, especially in the period when humidity is not the ideal, it is necessary to adopt some assistance measures. The present experimental study aims to elucidate what would be the recommended option to improve the quality of life of the human being and to clarify which resources (air humidifier, bucket of water or wet towel) will be effective to improve the humidity of the air in times of drought and low moisture.

Methods

The experimental study was carried out with INKBIRD hygrometers allowing the analysis of the variation of air humidity throughout the day. Three forms of treatment were established: humidifier, wet towel and bucket of water. In each room, two hygrometers were placed equidistant from the occupant of the room and their respective treatment that varied between 1m and 2m away from the headboard indoor each room. In addition, two environments were used as controls, one being an external environment and the other an internal closed environment, totaling five rooms for the study. The rooms were monitored between the end of July and the end of August 2019 in Goiania (GO).

Results

Although assistance measures are used to significantly improve air pollution in times of extreme drought, there was a significant difference between them. The humidifier and a wet towel had 7.50% and 5.71% more humidity in the external relation (external control), respectively, more efficient. The volume of water, however, did not show significant difference (p>0.05) and, therefore, there was no variation.

Conclusion

The humidifier and the towel are treatments considered more efficient, and that there was a significant effect of distance on humidity. Therefore, 1m of distance is more efficient in increasing and/or maintaining air humidity, inducing improvements in the populations’ health.

Modeling the Effects of Future Hydroclimatic Conditions on Microbial Water Quality and Management Practices in Two Agricultural Watersheds

Anticipated future hydroclimatic changes are expected to alter the transport and survival of fecally-sourced waterborne pathogens, presenting an increased risk of recreational water quality impairments. Managing future risk requires an understanding of interactions between fecal sources, hydroclimatic conditions and best management practices (BMPs) at spatial scales relevant to decision makers. In this study we used the Hydrologic Simulation Program FORTRAN to quantify potential fecal coliform (FC - an indicator of the potential presence of pathogens) responses to a range of mid-century climate scenarios and assess different BMP scenarios (based on reduction factors) for reducing the risk of water quality impairment in two, small agricultural watersheds - the Chippewa watershed in Minnesota, and the Tye watershed in Virginia. In each watershed, simulations show a wide range of FC responses, driven largely by variability in projected future precipitation. Wetter future conditions, which drive more transport from non-point sources (e.g. manure application, livestock grazing), show increases in FC loads. Loads typically decrease under drier futures; however, higher mean FC concentrations and more recreational water quality criteria exceedances occur, likely caused by reduced flow during low-flow periods. Median changes across the ensemble generally show increases in FC load. BMPs that focus on key fecal sources (e.g., runoff from pasture, livestock defecation in streams) within a watershed can mitigate the effects of hydroclimatic change on FC loads. However, more extensive BMP implementation or improved BMP efficiency (i.e., higher FC reductions) may be needed to fully offset increases in FC load and meet water quality goals, such as total maximum daily loads and recreational water quality standards. Strategies for managing climate risk should be flexible and to the extent possible include resilient BMPs that function as designed under a range of future conditions.

Generalized additive models: Building evidence of air pollution, climate change and human health

Advances in statistical analysis in the last few decades in the area of linear models enhanced the capability of researchers to study environmental procedures. In relation to general linear models; generalized linear models (GLM) provide greater flexibility in analyzing data related to non-normal distributions. Considering this, the current review explains various applications of the generalized additive model (GAM) to link air pollution, climatic variability with adverse health outcomes. The review examines the application of GAM within the varied field, focusing on the environment and meteorological data. Further, advantages and complications of applying GAM to environmental data are also discussed. Application of GAM allowed for specification for the error pattern and found to be an appropriate fit for the data sets having non-normal distributions; this results in lower and more reliable p-values. Since most environmental data is non-normal, GAM provides a more effective analytical method than traditional linear models. This review highlights on ambient air pollutants, climate change, and health by evaluating studies related to GAM. Additionally, an insight into the application of GAM in R software is provided, which is open source software with the extensive application for any type of dataset.

Predicted temperature-increase-induced global health burden and its regional variability

An increase in the global health burden of temperature was projected for 459 locations in 28 countries worldwide under four representative concentration pathway scenarios until 2099. We determined that the amount of temperature increase for each 100 ppm increase in global CO₂ concentrations is nearly constant, regardless of climate scenarios. The overall average temperature increase during 2010-2099 is largest in Canada (1.16 °C/100 ppm) and Finland (1.14 °C/100 ppm), while it is smallest in Ireland (0.62 °C/100 ppm) and Argentina (0.63 °C/100 ppm). In addition, for each 1 °C temperature increase, the amount of excess mortality is increased largely in tropical countries such as Vietnam (10.34%p/°C) and the Philippines (8.18%p/°C), while it is decreased in Ireland (-0.92%p/°C) and Australia (-0.32%p/°C). To understand the regional variability in temperature increase and mortality, we performed a regression-based modeling. We observed that the projected temperature increase is highly correlated with daily temperature range at the location and vulnerability to temperature increase is affected by health expenditure, and proportions of obese and elderly population.

New ECOSTRESS and MODIS Land Surface Temperature Data Reveal Fine-Scale Heat Vulnerability in Cities: A Case Study for Los Angeles County, California

Rapid 21st century urbanization combined with anthropogenic climate warming are significantly increasing heat-related health threats in cities worldwide. In Los Angeles (LA), increasing trends in extreme heat are expected to intensify and exacerbate the urban heat island effect, leading to greater health risks for vulnerable populations. Partnerships between city policymakers and scientists are becoming more important as the need to provide data-driven recommendations for sustainability and mitigation efforts becomes critical. Here we present a model to produce heat vulnerability index (HVI) maps driven by surface temperature data from National Aeronautics and Space Administration’s (NASA) new Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) thermal infrared sensor. ECOSTRESS was launched in June 2018 with the capability to image fine-scale urban temperatures at a 70 m resolution throughout different times of the day and night. The HVI model further includes information on socio-demographic data, green vegetation abundance, and historical heatwave temperatures from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Aqua spacecraft since 2002. During a period of high heat in July 2018, we identified the five most vulnerable communities at a sub-city block scale in the LA region. The persistence of high HVI throughout the day and night in these areas indicates a clear and urgent need for implementing cooling technologies and green infrastructure to curb future warming.

Waterborne Diseases Arising From Climate Change

As a result of increased frequency and intensity of heat waves, increased floods and droughts, change in climate will affect biological, physical, and chemical components of water through different paths thus enhancing the risk of waterborne diseases. Identifying the role of weather in waterborne infection is a priority public health research issue as climate change is predicted to increase the frequency of extreme precipitation and temperature events. This chapter provides evidence that precipitation and temperature can affect directly or indirectly water quality and consequently affect the health human. This chapter also highlights the complex relationship between precipitation or temperature and transmission of waterborne disease such as diarrheal disease, gastroenteritis, cryptosporidiosis, giardiasis, and cholera.

A REVIEW OF WATER QUALITY RESPONSES TO AIR TEMPERATURE AND PRECIPITATION CHANGES 2: NUTRIENTS, ALGAL BLOOMS, SEDIMENT, PATHOGENS

In this paper we review the published, scientific literature addressing the response of nutrients, sediment, pathogens and cyanobacterial blooms to historical and potential future changes in air temperature and precipitation. The goal is to document how different attributes of water quality are sensitive to these drivers, to characterize future risk, to inform management responses and to identify research needs to fill gaps in our understanding. Results suggest that anticipated future changes present a risk of water quality and ecosystem degradation in many U.S. locations. Understanding responses is, however, complicated by inherent high spatial and temporal variability, interactions with land use and water management, and dependence on uncertain changes in hydrology in response to future climate. Effects on pollutant loading in different watershed settings generally correlate with projected changes in precipitation and runoff. In all regions, increased heavy precipitation events are likely to drive more episodic pollutant loading to water bodies. The risk of algal blooms could increase due to an expanded seasonal window of warm water temperatures and the potential for episodic increases in nutrient loading. Increased air and water temperatures are also likely to affect the survival of waterborne pathogens. Responding to these challenges requires understanding of vulnerabilities, and management strategies to reduce risk.

Maxent estimation of aquatic Escherichia coli stream impairment

BACKGROUND

The leading cause of surface water impairment in United States' rivers and streams is pathogen contamination. Although use of fecal indicators has reduced human health risk, current approaches to identify and reduce exposure can be improved. One important knowledge gap within exposure assessment is characterization of complex fate and transport processes of fecal pollution. Novel modeling processes can inform watershed decision-making to improve exposure assessment.

METHODS

We used the ecological model, Maxent, and the fecal indicator bacterium Escherichia coli to identify environmental factors associated with surface water impairment. Samples were collected August, November, February, and May for 8 years on Sinking Creek in Northeast Tennessee and analyzed for 10 water quality parameters and E. coli concentrations. Univariate and multivariate models estimated probability of impairment given the water quality parameters. Model performance was assessed using area under the receiving operating characteristic (AUC) and prediction accuracy, defined as the model's ability to predict both true positives (impairment) and true negatives (compliance). Univariate models generated action values, or environmental thresholds, to indicate potential E. coli impairment based on a single parameter. Multivariate models predicted probability of impairment given a suite of environmental variables, and jack-knife sensitivity analysis removed unresponsive variables to elicit a set of the most responsive parameters.

RESULTS

Water temperature univariate models performed best as indicated by AUC, but alkalinity models were the most accurate at correctly classifying impairment. Sensitivity analysis revealed that models were most sensitive to removal of specific conductance. Other sensitive variables included water temperature, dissolved oxygen, discharge, and NO3. The removal of dissolved oxygen improved model performance based on testing AUC, justifying development of two optimized multivariate models; a 5-variable model including all sensitive parameters, and a 4-variable model that excluded dissolved oxygen.

DISCUSSION

Results suggest that E. coli impairment in Sinking Creek is influenced by seasonality and agricultural run-off, stressing the need for multi-month sampling along a stream continuum. Although discharge was not predictive of E. coli impairment alone, its interactive effect stresses the importance of both flow dependent and independent processes associated with E. coli impairment. This research also highlights the interactions between nutrient and fecal pollution, a key consideration for watersheds with multiple synergistic impairments. Although one indicator cannot mimic theplethora of existing pathogens in water, incorporating modeling can fine tune an indicator's utility, providing information concerning fate, transport, and source of fecal pollution while prioritizing resources and increasing confidence in decision making.

Dependence of future mortality changes on global CO2 concentrations: A review

The heterogeneity among previous studies of future mortality projections due to climate change has often hindered comparisons and syntheses of resulting impacts. To address this challenge, the present study introduced a novel method to normalize the results from projection studies according to different baseline and projection periods and climate scenarios, thereby facilitating comparison and synthesis. This study reviewed the 15 previous studies involving projected climate change-related mortality under Representative Concentration Pathways. To synthesize their results, we first reviewed the important study design elements that affected the reported results in previous studies. Then, we normalized the reported results by CO₂ concentration in order to eliminate the effects of the baseline period, projection period, and climate scenario choices. For twenty-five locations worldwide, the normalized percentage changes in temperature-attributable mortality per 100 ppm increase in global CO₂ concentrations ranged between 41.9% and 330%, whereas those of total mortality ranged between 0.3% and 4.8%. The normalization methods presented in this work will guide future studies to provide their results in a normalized format and facilitate research synthesis to reinforce our understanding on the risk of climate change.

Effects of climatic and social factors on dengue incidence in Mexican municipalities in the state of Veracruz

Objective:

To assess links between the social variables and longer-term El Niño-Southern Oscillation (ENSO) related weather conditions as they relate to the week-to-week changes in dengue incidence at a regional level.

Materials and methods:

We collected data from 10 municipalities of the Olmeca region in México, over a 10 year period (January 1995 to December 2005). Negative binomial models with distributed lags were adjusted to look for associations between changes in the weekly incidence rate of dengue fever and climate variability.

Results:

Our results show that it takes approximately six weeks for sea surface temperatures (SST -34) to affect dengue incidence adjusted by weather and social variables.

Conclusion:

Such models could be used as early as two months in advance to provide information to decision makers about potential epidemics. Elucidating the effect of climatic variability and social variables, could assist in the development of accurate early warning systems for epidemics like dengue, Chikungunya and Zika.

A Review of Heat Stress Policies in the Context of Climate Change and Its Impacts on Outdoor Workers

Record-breaking summer heat events are increasing in frequency in Zimbabwe and 2016 was a particularly hot year with the country experiencing its worst heat wave event in decades. Currently, Zimbabwe has no coordinated public health response to deal with heat wave events and no specific data on heat-related morbidity and mortality. The country has no legislation for protecting workers against environmental heat exposure, particularly those most vulnerable who are employed in the informal sector. These workers are also at risk due to their outdoor work environments. The article outlines the state of climate and heat stresses in Zimbabwe, as benchmarked against other African countries and France. It further summarizes outdoor workers' susceptibility to heat exposure and the need for the Zimbabwean Government to develop policies to ensure the health and safety of an increasing population of outdoor workers in Zimbabwe.

The Heat Exposure Integrated Deprivation Index (HEIDI): A data-driven approach to quantifying neighborhood risk during extreme hot weather

Mortality attributable to extreme hot weather is a growing concern in many urban environments, and spatial heat vulnerability indexes are often used to identify areas at relatively higher and lower risk. Three indexes were developed for greater Vancouver, Canada using a pool of 20 potentially predictive variables categorized to reflect social vulnerability, population density, temperature exposure, and urban form. One variable was chosen from each category: an existing deprivation index, senior population density, apparent temperature, and road density, respectively. The three indexes were constructed from these variables using (1) unweighted, (2) weighted, and (3) data-driven Heat Exposure Integrated Deprivation Index (HEIDI) approaches. The performance of each index was assessed using mortality data from 1998-2014, and the maps were compared with respect to spatial patterns identified. The population-weighted spatial correlation between the three indexes ranged from 0.68-0.89. The HEIDI approach produced a graduated map of vulnerability, whereas the other approaches primarily identified areas of highest risk. All indexes performed best under extreme temperatures, but HEIDI was more useful at lower thresholds. Each of the indexes in isolation provides valuable information for public health protection, but combining the HEIDI approach with unweighted and weighted methods provides richer information about areas most vulnerable to heat.

Potential Impacts of Future Warming and Land Use Changes on Intra-Urban Heat Exposure in Houston, Texas

Extreme heat events in the United States are projected to become more frequent and intense as a result of climate change. We investigated the individual and combined effects of land use and warming on the spatial and temporal distribution of daily minimum temperature (T_min) and daily maximum heat index (HI_max) during summer in Houston, Texas. Present-day (2010) and near-future (2040) parcel-level land use scenarios were embedded within 1-km resolution land surface model (LSM) simulations. For each land use scenario, LSM simulations were conducted for climatic scenarios representative of both the present-day and near-future periods. LSM simulations assuming present-day climate but 2040 land use patterns led to spatially heterogeneous temperature changes characterized by warmer conditions over most areas, with summer average increases of up to 1.5°C (T_min) and 7.3°C (HI_max) in some newly developed suburban areas compared to simulations using 2010 land use patterns. LSM simulations assuming present-day land use but a 1°C temperature increase above the urban canopy (consistent with warming projections for 2040) yielded more spatially homogeneous metropolitan-wide average increases of about 1°C (T_min) and 2.5°C (HI_max), respectively. LSM simulations assuming both land use and warming for 2040 led to summer average increases of up to 2.5°C (T_min) and 8.3°C (HI_max), with the largest increases in areas projected to be converted to residential, industrial and mixed-use types. Our results suggest that urbanization and climate change may significantly increase the average number of summer days that exceed current threshold temperatures for initiating a heat advisory for metropolitan Houston, potentially increasing population exposure to extreme heat.

The impact of meteorology on the occurrence of waterborne outbreaks of vero cytotoxin-producing Escherichia coli (VTEC): a logistic regression approach

This study analyses the relationship between meteorological phenomena and outbreaks of waterborne-transmitted vero cytotoxin-producing Escherichia coli (VTEC) in the Republic of Ireland over an 8-year period (2005-2012). Data pertaining to the notification of waterborne VTEC outbreaks were extracted from the Computerised Infectious Disease Reporting system, which is administered through the national Health Protection Surveillance Centre as part of the Health Service Executive. Rainfall and temperature data were obtained from the national meteorological office and categorised as cumulative rainfall, heavy rainfall events in the previous 7 days, and mean temperature. Regression analysis was performed using logistic regression (LR) analysis. The LR model was significant (p < 0.001), with all independent variables: cumulative rainfall, heavy rainfall and mean temperature making a statistically significant contribution to the model. The study has found that rainfall, particularly heavy rainfall in the preceding 7 days of an outbreak, is a strong statistical indicator of a waterborne outbreak and that temperature also impacts waterborne VTEC outbreak occurrence.

Impact of Climate and Environmental Factors on West Nile Virus Circulation in Iran

BACKGROUND

Geographic distribution of West Nile virus (WNV) is heterogeneous in Iran by a high circulation in the southern-western areas. The objective of our study was to determine environmental and climatic factors associated with the risk of WNV equine seropositivity in Iran.

METHODS

Serological data were obtained from a serosurvey conducted in equine population in 260 districts in Iran. The climate and environmental parameters included in the models were distance to the nearest wetland area, type of stable, Normalized Difference Vegetation Index (NDVI), annual mean temperature, humidity and precipitation.

RESULTS

The important risk factors included annual mean temperature, distance to wetlands, local and seasonal NDVI differences. The effect of local NDVI differences in spring was particularly notable. This was a normalized difference of average NDVI between two areas: a 5 km radius area centered on the stable and the 5-10 km surrounding area.

CONCLUSION

The model indicated that local NDVI's contrast during spring is a major risk factor of the transmission of West-Nile virus in Iran. This so-called oasis effect consistent with the seasonal production of vegetation in spring, and is associated to the attractiveness of the local NDVI environment for WNV vectors and hosts.

The emerging threats of climate change on tropical coastal ecosystem services, public health, local economies and livelihood sustainability of small islands: Cumulative impacts and synergies

Climate change has significantly impacted tropical ecosystems critical for sustaining local economies and community livelihoods at global scales. Coastal ecosystems have largely declined, threatening the principal source of protein, building materials, tourism-based revenue, and the first line of defense against storm swells and sea level rise (SLR) for small tropical islands. Climate change has also impacted public health (i.e., altered distribution and increased prevalence of allergies, water-borne, and vector-borne diseases). Rapid human population growth has exacerbated pressure over coupled social-ecological systems, with concomitant non-sustainable impacts on natural resources, water availability, food security and sovereignty, public health, and quality of life, which should increase vulnerability and erode adaptation and mitigation capacity. This paper examines cumulative and synergistic impacts of climate change in the challenging context of highly vulnerable small tropical islands. Multiple adaptive strategies of coupled social-ecological ecosystems are discussed. Multi-level, multi-sectorial responses are necessary for adaptation to be successful.

Challenges and Opportunities for Advancing Work on Climate Change and Public Health

Climate change poses a major threat to public health. Strategies that address climate change have considerable potential to benefit health and decrease health inequities, yet public health engagement at the intersection of public health, equity, and climate change has been limited. This research seeks to understand the barriers to and opportunities for advancing work at this nexus. We conducted semi-structured in-depth interviews (N = 113) with public health and climate change professionals and thematic analysis. Barriers to public health engagement in addressing climate change include individual perceptions that climate change is not urgent or solvable and insufficient understanding of climate change's health impacts and programmatic connections. Institutional barriers include a lack of public health capacity, authority, and leadership; a narrow framework for public health practice that limits work on the root causes of climate change and health; and compartmentalization within and across sectors. Opportunities include integrating climate change into current public health practice; providing inter-sectoral support for climate solutions with health co-benefits; and using a health frame to engage and mobilize communities. Efforts to increase public health sector engagement should focus on education and communications, building leadership and funding, and increasing work on the shared root causes of climate change and health inequities.

Temporal Variation in Heat-Mortality Associations: A Multicountry Study

BACKGROUND

Recent investigations have reported a decline in the heat-related mortality risk during the last decades. However, these studies are frequently based on modeling approaches that do not fully characterize the complex temperature-mortality relationship, and are limited to single cities or countries.

OBJECTIVES

We assessed the temporal variation in heat-mortality associations in a multi-country data set using flexible modelling techniques.

METHODS

We collected data for 272 locations in Australia, Canada, Japan, South Korea, Spain, the United Kingdom, and the United States, with a total 20,203,690 deaths occurring in summer months between 1985 and 2012. The analysis was based on two-stage time-series models. The temporal variation in heat-mortality relationships was estimated in each location with time-varying distributed lag nonlinear models, expressed through an interaction between the transformed temperature variables and time. The estimates were pooled by country through multivariate meta-analysis.

RESULTS

Mortality risk due to heat appeared to decrease over time in several countries, with relative risks associated to high temperatures significantly lower in 2006 compared with 1993 in the United States, Japan, and Spain, and a nonsignificant decrease in Canada. Temporal changes are difficult to assess in Australia and South Korea due to low statistical power, and we found little evidence of variation in the United Kingdom. In the United States, the risk seems to be completely abated in 2006 for summer temperatures below their 99th percentile, but some significant excess persists for higher temperatures in all the countries.

CONCLUSIONS

We estimated a statistically significant decrease in the relative risk for heat-related mortality in 2006 compared with 1993 in the majority of countries included in the analysis.

CITATION

Gasparrini A, Guo Y, Hashizume M, Kinney PL, Petkova EP, Lavigne E, Zanobetti A, Schwartz JD, Tobias A, Leone M, Tong S, Honda Y, Kim H, Armstrong BG. 2015. Temporal variation in heat-mortality associations: a multicountry study. Environ Health Perspect 123:1200-1207; http://dx.doi.org/10.1289/ehp.1409070.

A Heat Vulnerability Index and Adaptation Solutions for Pittsburgh, Pennsylvania

With increasing evidence of global warming, many cities have focused attention on response plans to address their populations' vulnerabilities. Despite expected increased frequency and intensity of heat waves, the health impacts of such events in urban areas can be minimized with careful policy and economic investments. We focus on Pittsburgh, Pennsylvania and ask two questions. First, what are the top factors contributing to heat vulnerability and how do these characteristics manifest geospatially throughout Pittsburgh? Second, assuming the City wishes to deploy additional cooling centers, what placement will optimally address the vulnerability of the at risk populations? We use national census data, ArcGIS geospatial modeling, and statistical analysis to determine a range of heat vulnerability indices and optimal cooling center placement. We find that while different studies use different data and statistical calculations, all methods tested locate additional cooling centers at the confluence of the three rivers (Downtown), the northeast side of Pittsburgh (Shadyside/Highland Park), and the southeast side of Pittsburgh (Squirrel Hill). This suggests that for Pittsburgh, a researcher could apply the same factor analysis procedure to compare data sets for different locations and times; factor analyses for heat vulnerability are more robust than previously thought.

Isolated and synergistic effects of PM10 and average temperature on cardiovascular and respiratory mortality

OBJECTIVE

To analyze the effect of air pollution and temperature on mortality due to cardiovascular and respiratory diseases.

METHODS

We evaluated the isolated and synergistic effects of temperature and particulate matter with aerodynamic diameter < 10 µm (PM₁₀) on the mortality of individuals > 40 years old due to cardiovascular disease and that of individuals > 60 years old due to respiratory diseases in Sao Paulo, SP, Southeastern Brazil, between 1998 and 2008. Three methodologies were used to evaluate the isolated association: time-series analysis using Poisson regression model, bidirectional case-crossover analysis matched by period, and case-crossover analysis matched by the confounding factor, i.e., average temperature or pollutant concentration. The graphical representation of the response surface, generated by the interaction term between these factors added to the Poisson regression model, was interpreted to evaluate the synergistic effect of the risk factors.

RESULTS

No differences were observed between the results of the case-crossover and time-series analyses. The percentage change in the relative risk of cardiovascular and respiratory mortality was 0.85% (0.45;1.25) and 1.60% (0.74;2.46), respectively, due to an increase of 10 μg/m³ in the PM₁₀ concentration. The pattern of correlation of the temperature with cardiovascular mortality was U-shaped and that with respiratory mortality was J-shaped, indicating an increased relative risk at high temperatures. The values for the interaction term indicated a higher relative risk for cardiovascular and respiratory mortalities at low temperatures and high temperatures, respectively, when the pollution levels reached approximately 60 μg/m³.

CONCLUSIONS

The positive association standardized in the Poisson regression model for pollutant concentration is not confounded by temperature, and the effect of temperature is not confounded by the pollutant levels in the time-series analysis. The simultaneous exposure to different levels of environmental factors can create synergistic effects that are as disturbing as those caused by extreme concentrations.

A scalable climate health justice assessment model

This paper introduces a scalable "climate health justice" model for assessing and projecting incidence, treatment costs, and sociospatial disparities for diseases with well-documented climate change linkages. The model is designed to employ low-cost secondary data, and it is rooted in a perspective that merges normative environmental justice concerns with theoretical grounding in health inequalities. Since the model employs International Classification of Diseases, Ninth Revision Clinical Modification (ICD-9-CM) disease codes, it is transferable to other contexts, appropriate for use across spatial scales, and suitable for comparative analyses. We demonstrate the utility of the model through analysis of 2008-2010 hospitalization discharge data at state and county levels in Texas (USA). We identified several disease categories (i.e., cardiovascular, gastrointestinal, heat-related, and respiratory) associated with climate change, and then selected corresponding ICD-9 codes with the highest hospitalization counts for further analyses. Selected diseases include ischemic heart disease, diarrhea, heat exhaustion/cramps/stroke/syncope, and asthma. Cardiovascular disease ranked first among the general categories of diseases for age-adjusted hospital admission rate (5286.37 per 100,000). In terms of specific selected diseases (per 100,000 population), asthma ranked first (517.51), followed by ischemic heart disease (195.20), diarrhea (75.35), and heat exhaustion/cramps/stroke/syncope (7.81). Charges associated with the selected diseases over the 3-year period amounted to US$5.6 billion. Blacks were disproportionately burdened by the selected diseases in comparison to non-Hispanic whites, while Hispanics were not. Spatial distributions of the selected disease rates revealed geographic zones of disproportionate risk. Based upon a downscaled regional climate-change projection model, we estimate a >5% increase in the incidence and treatment costs of asthma attributable to climate change between the baseline and 2040-2050 in Texas. Additionally, the inequalities described here will be accentuated, with blacks facing amplified health disparities in the future. These predicted trends raise both intergenerational and distributional climate health justice concerns.

Seasonal variation of fecal contamination in drinking water sources in developing countries: a systematic review

Accounting for fecal contamination of drinking water sources is an important step in improving monitoring of global access to safe drinking water. Fecal contamination varies with time while its monitoring is often infrequent. We sought to understand seasonal trends in fecal contamination to guide best practices to capture seasonal variation and ascertain the extent to which the results of a single sample may overestimate compliance with health guidelines. The findings from 22 studies from developing countries written in English and identified through a systematic review were analyzed. Fecal contamination in improved drinking water sources was shown to follow a statistically significant seasonal trend of greater contamination during the wet season (p<0.001). This trend was consistent across fecal indicator bacteria, five source types, twelve Köppen-Geiger climate zones, and across both rural and urban areas. Guidance on seasonally representative water quality monitoring by the World Health Organization and national water quality agencies could lead to improved assessments of access to safe drinking water.

A health impact assessment framework for assessing vulnerability and adaptation planning for climate change

This paper presents a detailed description of an approach designed to investigate the application of the Health Impact Assessment (HIA) framework to assess the potential health impacts of climate change. A HIA framework has been combined with key climate change terminology and concepts. The fundamental premise of this framework is an understanding of the interactions between people, the environment and climate. The diversity and complexity of these interactions can hinder much needed action on the critical health issue of climate change. The objectives of the framework are to improve the methodology for understanding and assessing the risks associated with potential health impacts of climate change, and to provide decision-makers with information that can facilitate the development of effective adaptation plans. While the process presented here provides guidance with respect to this task it is not intended to be prescriptive. As such, aspects of the process can be amended to suit the scope and available resources of each project. A series of working tables has been developed to assist in the collation of evidence throughout the process. The framework has been tested in a number of locations including Western Australia, Solomon Islands, Vanuatu and Nauru.

Climate change: challenges and opportunities for global health

IMPORTANCE

Health is inextricably linked to climate change. It is important for clinicians to understand this relationship in order to discuss associated health risks with their patients and to inform public policy.

OBJECTIVES

To provide new US-based temperature projections from downscaled climate modeling and to review recent studies on health risks related to climate change and the cobenefits of efforts to mitigate greenhouse gas emissions.

DATA SOURCES, STUDY SELECTION, AND DATA SYNTHESIS

We searched PubMed and Google Scholar from 2009 to 2014 for articles related to climate change and health, focused on governmental reports, predictive models, and empirical epidemiological studies. Of the more than 250 abstracts reviewed, 56 articles were selected. In addition, we analyzed climate data averaged over 13 climate models and based future projections on downscaled probability distributions of the daily maximum temperature for 2046-2065. We also compared maximum daily 8-hour average ozone with air temperature data taken from the National Oceanic and Atmospheric Administration, National Climate Data Center.

RESULTS

By 2050, many US cities may experience more frequent extreme heat days. For example, New York and Milwaukee may have 3 times their current average number of days hotter than 32°C (90°F). High temperatures are also strongly associated with ozone exceedance days, for example, in Chicago, Illinois. The adverse health aspects related to climate change may include heat-related disorders, such as heat stress and economic consequences of reduced work capacity; respiratory disorders, including those exacerbated by air pollution and aeroallergens, such as asthma; infectious diseases, including vectorborne diseases and waterborne diseases, such as childhood gastrointestinal diseases; food insecurity, including reduced crop yields and an increase in plant diseases; and mental health disorders, such as posttraumatic stress disorder and depression, that are associated with natural disasters. Substantial health and economic cobenefits could be associated with reductions in fossil fuel combustion. For example, greenhouse gas emission policies may yield net economic benefit, with health benefits from air quality improvements potentially offsetting the cost of US and international carbon policies.

CONCLUSIONS AND RELEVANCE

Evidence over the past 20 years indicates that climate change can be associated with adverse health outcomes. Health care professionals have an important role in understanding and communicating the related potential health concerns and the cobenefits from policies to reduce greenhouse gas emissions.

The epidemiology of occupational heat exposure in the United States: a review of the literature and assessment of research needs in a changing climate

In recent years, the United States has experienced record-breaking summer heat. Climate change models forecast increasing US temperatures and more frequent heat wave events in the coming years. Exposure to environmental heat is a significant, but overlooked, workplace hazard that has not been well-characterized or studied. The working population is diverse; job function, age, fitness level, and risk factors to heat-related illnesses vary. Yet few studies have examined or characterized the incidence of occupational heat-related morbidity and mortality. There are no federal regulatory standards to protect workers from environmental heat exposure. With climate change as a driver for adaptation and prevention of heat disorders, crafting policy to characterize and prevent occupational heat stress for both indoor and outdoor workers is increasingly sensible, practical, and imperative.

Health consequence scales for use in health impact assessments of climate change

While health impact assessment (HIA) has typically been applied to projects, plans or policies, it has significant potential with regard to strategic considerations of major health issues facing society such as climate change. Given the complexity of climate change, assessing health impacts presents new challenges that may require different approaches compared to traditional applications of HIA. This research focuses on the development of health consequence scales suited to assessing and comparing health effects associated with climate change and applied within a HIA framework. This assists in setting priorities for adaptation plans to minimize the public health impacts of climate change. The scales presented in this paper were initially developed for a HIA of climate change in Perth in 2050, but they can be applied across spatial and temporal scales. The design is based on a health effects pyramid with health measures expressed in orders of magnitude and linked to baseline population and health data. The health consequence measures are combined with a measure of likelihood to determine the level of risk associated with each health potential health impact. In addition, a simple visual framework that can be used to collate, compare and communicate the level of health risks associated with climate change has been developed.

Ambient temperature during gestation and cold-related adult mortality in a Swedish cohort, 1915-2002

For all climatic regions, mortality due to cold exceeds mortality due to heat. A separate line of research indicates that season of birth predicts lifespan after age 50. This and other literature implies the hypothesis that ambient temperature during gestation may influence cold-related adult mortality. We use data on over 13,500 Swedes from the Uppsala Birth Cohort Study to test whether cold-related mortality in adulthood varies positively with unusually benign ambient temperature during gestation. We linked daily thermometer temperatures in Uppsala, Sweden (1915-2002) to subjects beginning at their estimated date of conception and ending at death or the end of follow-up. We specified a Cox proportional hazards model with time-dependent covariates to analyze the two leading causes of cold-related death in adulthood: ischemic heart disease (IHD) and stroke. Over 540,450 person-years, 1313 IHD and 406 stroke deaths occurred. For a one standard deviation increase in our measure of warm temperatures during gestation, we observe an increased hazard ratio of 1.16 for cold-related IHD death (95% confidence interval: 1.03-1.29). We, however, observe no relation for cold-related stroke mortality. Additional analyses show that birthweight percentile and/or gestational age do not mediate discovered findings. The IHD results indicate that ambient temperature during gestation--independent of birth month--modifies the relation between cold and adult mortality. We encourage longitudinal studies of the adult sequelae of ambient temperature during gestation among populations not sufficiently sheltered from heat or cold waves.

Lessons from Hurricane Sandy: a community response in Brooklyn, New York

The frequency and intensity of extreme weather events have increased in recent decades; one example is Hurricane Sandy. If the frequency and severity continue or increase, adaptation and mitigation efforts are needed to protect vulnerable populations and improve daily life under changed weather conditions. This field report examines the devastation due to Hurricane Sandy experienced in Red Hook, Brooklyn, New York, a neighborhood consisting of geographically isolated low-lying commercial and residential units, with a concentration of low-income housing, and disproportionate rates of poverty and poor health outcomes largely experienced by Black and Latino residents. Multiple sources of data were reviewed, including street canvasses, governmental reports, community flyers, and meeting transcripts, as well as firsthand observations by a local nonprofit Red Hook Initiative (RHI) and community members, and social media accounts of the effects of Sandy and the response to daily needs. These data are considered within existing theory, evidence, and practice on protecting public health during extreme weather events. Firsthand observations show that a community-based organization in Red Hook, RHI, was at the center of the response to disaster relief, despite the lack of staff training in response to events such as Hurricane Sandy. Review of these data underscores that adaptation and response to climate change and likely resultant extreme weather is a dynamic process requiring an official coordinated governmental response along with on-the-ground volunteer community responders.

Extreme Weather Events and Mental Health: Tackling the Psychosocial Challenge

Climate change is an emerging challenge to the mental health of entire humanity. Several studies, in recent times, have brought to light the adverse public mental health outcomes of extreme weather events for the suffering communities. The general public and the policy making bodies need to gain awareness about these impacts. Through such awareness, communities and their governments can institutionalize mechanisms to provide psychological support to the populations affected by climate change, before it becomes a massive public health challenge and starts affecting the social and vocational lives of people. There is an urgent need for addressing these impacts. The aim of this paper is to provide an overview of the deleterious effects of climate change related extreme weather events on mental health, the worldwide response of several communities to such events, and preparedness of the public and government to deal with these adverse mental health impacts. Policy imperatives to prevent and mitigate these impacts have been suggested. It is hoped that the psychologists, governments, and communities will act earnestly to prevent the impending harm to human mental health due to climate change.

Identification of heat risk patterns in the U.S. National Capital Region by integrating heat stress and related vulnerability

The increase in the number and severity of weather extremes (including excessive heat) potentially associated with climate change has highlighted the needs for research into risk assessment and risk reduction measures. Extreme heat events, the focus of this paper, have been consistently reported as the leading cause of weather-related mortality in the United States in recent years. In order to fully understand impact potentials and analyze risk in its individual components both the spatially and temporally varying patterns of heat and the multidimensional characteristics of vulnerability have to be considered. In this paper we present a composite index aggregating these factors to assess heat related risk for the U.S. National Capital Region in 2010. The study reveals how risk patterns are in part driven by the geographic variations of vulnerability, generally showing a clear difference between high-risk urban areas and wide areas of low risk in the suburban and rural environments. This pattern is particularly evident for the core center of the study area around the District of Columbia, which is largely characterized by high index values despite not having experienced the peak of the heat stress as compared to other regions in the metropolitan area. The article aims to set a framework for local-level heat stress risk assessment that can provide valuable input and decision support for climate adaptation planning as well as emergency managers aiming at risk reduction and optimization of resource distribution.

Staying cool in a changing climate: Reaching vulnerable populations during heat events

The frequency and intensity of hot weather events are expected to increase globally, threatening human health, especially among the elderly, poor, and chronically ill. Current literature indicates that emergency preparedness plans, heat health warning systems, and related interventions may not be reaching or supporting behavior change among those most vulnerable in heat events. Using a qualitative multiple case study design, we comprehensively examined practices of these populations to stay cool during hot weather ("cooling behaviors") in four U.S. cities with documented racial/ethnic and socio-economic disparities and diverse heat preparedness strategies: Phoenix, Arizona; Detroit, Michigan; New York City, New York; and Philadelphia, Pennsylvania. Based on semi-structured in-depth interviews we conducted with 173 community members and organizational leaders during 2009-2010, we assessed why vulnerable populations do or do not participate in health-promoting behaviors at home or in their community during heat events, inquiring about perceptions of heat-related threats and vulnerability and the role of social support. While vulnerable populations often recognize heat's potential health threats, many overlook or disassociate from risk factors or rely on experiences living in or visiting warmer climates as a protective factor. Many adopt basic cooling behaviors, but unknowingly harmful behaviors such as improper use of fans and heating and cooling systems are also adopted. Decision-making related to commonly promoted behaviors such as air conditioner use and cooling center attendance is complex, and these resources are often inaccessible financially, physically, or culturally. Interviewees expressed how interpersonal, intergenerational relationships are generally but not always protective, where peer relationships are a valuable mechanism for facilitating cooling behaviors among the elderly during heat events. To prevent disparities in heat morbidity and mortality in an increasingly changing climate, we note the implications of local context, and we broadly inform heat preparedness plans, interventions, and messages by sharing the perspectives and words of community members representing vulnerable populations and leaders who work most closely with them.

Health professionals' knowledge and understanding about Listeria monocytogenes indicates a need for improved professional training

Listeria monocytogenes causes listeriosis, an uncommon but potentially fatal disease in immunocompromised persons, with a public health burden of approximately $2 billion annually. Those consumers most at risk are the highly susceptible populations otherwise known as the immunocompromised. Health professionals have a considerable amount of interaction with the immunocompromised and are therefore a valuable resource for providing appropriate safe food handling information. To determine how knowledgeable health professionals are about Listeria monocytogenes, a nationwide Web-based survey was distributed targeting registered nurses (RNs) and registered dietitians (RDs) who work with highly susceptible populations. Responses were received from 499 health professionals. Knowledge and understanding of Listeria monocytogenes was assessed descriptively. Parametric and nonparametric analyses were used to detect differences between RNs and RDs. The major finding is that there are gaps in knowledge and a self-declared lack of understanding by both groups, but especially RNs, about Listeria monocytogenes. RDs were more likely than RNs to provide information about specific foods and food storage behaviors to prevent a Listeria infection. Notably, neither group of health professionals consistently provided Listeria prevention messages to their immunocompromised patients. Pathogens will continue to emerge as food production, climate, water, and waste management systems change. Health professionals, represented by RNs and RDs, need resources and training to ensure that they are providing the most progressive information about various harmful pathogens; in this instance, Listeria monocytogenes.

Influence of variable precipitation on coastal water quality in southern California

OBJECTIVES

To examine the consequences of changing precipitation levels on southern California's recreational coastal water quality, and compare the responses of watersheds with differing levels of urban development.

METHODS

The geo-temporal relationship for six years (2000-2005) of precipitation levels, discharge rates for the ten primary waterways, and coastal water bacteria concentrations at seventy-eight southern California beaches were examined.

RESULTS

Precipitation levels, river-creek discharge rates, and coastal water bacteria concentrations were significantly correlated (p < 0.01) for all ten watersheds investigated. Water bacteria concentrations significantly increased with higher levels of precipitation across 95% of the seventy-eight beaches investigated. A heavily developed watershed had significantly higher median bacteria concentrations (186 cfu) in the adjoining coastal waters compared to an undeveloped watershed (10 cfu) of similar size.

CONCLUSIONS

Precipitation and ensuing runoff strongly control the rate of polluted water delivered to most beaches in southern California. Variable precipitation generates a greater response in coastal water bacteria concentrations in developed watersheds compared to undeveloped areas. Projected declines in regional precipitation as a consequence of climate change may result in less contaminated water delivered to coastal waters, thus decreasing risk of water associated illnesses during winter months.

Causes of death and demographic characteristics of victims of meteorological disasters in Korea from 1990 to 2008

BACKGROUND

Meteorological disasters are an important component when considering climate change issues that impact morbidity and mortality rates. However, there are few epidemiological studies assessing the causes and characteristics of deaths from meteorological disasters. The present study aimed to analyze the causes of death associated with meteorological disasters in Korea, as well as demographic and geographic vulnerabilities and their changing trends, to establish effective measures for the adaptation to meteorological disasters.

METHODS

Deaths associated with meteorological disasters were examined from 2,045 cases in Victim Survey Reports prepared by 16 local governments from 1990 to 2008. Specific causes of death were categorized as drowning, structural collapse, electrocution, lightning, fall, collision, landslide, avalanche, deterioration of disease by disaster, and others. Death rates were analyzed according to the meteorological type, specific causes of death, and demographic and geographic characteristics.

RESULTS

Drowning (60.3%) caused the greatest number of deaths in total, followed by landslide (19.7%) and structural collapse (10.1%). However, the causes of deaths differed between disaster types. The meteorological disaster associated with the greatest number of deaths has changed from flood to typhoon. Factors that raised vulnerability included living in coastal provinces (11.3 times higher than inland metropolitan), male gender (1.9 times higher than female), and older age.

CONCLUSIONS

Epidemiological analyses of the causes of death and vulnerability associated with meteorological disasters can provide the necessary information for establishing future adaptation measures against climate change. A more comprehensive system for assessing disaster epidemiology needs to be established.

Association between rainfall and pediatric emergency department visits for acute gastrointestinal illness

BACKGROUND

Microbial water contamination after periods of heavy rainfall is well described, but its link to acute gastrointestinal illness (AGI) in children is not well known.

OBJECTIVES

We hypothesize an association between rainfall and pediatric emergency department (ED) visits for AGI that may represent an unrecognized, endemic burden of pediatric disease in a major U.S. metropolitan area served by municipal drinking water systems.

METHODS

We conducted a retrospective time series analysis of visits to the Children's Hospital of Wisconsin ED in Wauwatosa, Wisconsin. Daily visit totals of discharge International Classification of Diseases, 9th Revision codes of gastroenteritis or diarrhea were collected along with daily rainfall totals during the study period from 2002 to 2007. We used an autoregressive moving average model, adjusting for confounding variables such as sewage release events and season, to look for an association between daily visits and rainfall after a lag of 1-7 days.

RESULTS

A total of 17,357 AGI visits were identified (mean daily total, 7.9; range, 0-56). Any rainfall 4 days prior was significantly associated with an 11% increase in AGI visits. Expected seasonal effects were also seen, with increased AGI visits in winter months.

CONCLUSIONS

We observed a significant association between rainfall and pediatric ED visits for AGI, suggesting a waterborne component of disease transmission in this population. The observed increase in ED visits for AGI occurred in the absence of any disease outbreaks reported to public health officials in our region, suggesting that rainfall-associated illness may be underestimated. Further study is warranted to better address this association.