Background: Environmental health research employs a variety of metrics to measure heat exposure, both to directly study the health effects of outdoor temperature and to control for temperature in s

Methods to Calculate the Heat Index as an Exposure Metric in Environmental Health Research

Background: A deeper understanding of how heat wave definition affects the relationship between heat exposure and health, especially as a function of rurality, will be useful in developing effectiv...

Heat Waves and Health Outcomes in Alabama (USA): The Importance of Heat Wave Definition

Reducing the health effects of hot weather and heat extremes: from personal cooling strategies to green cities.

Summary Several new viral respiratory tract infectious diseases with epidemic potential that threaten global health security have emerged in the past 15 years. In 2003, WHO issued a worldwide alert for an unknown emerging illness, later named severe acute respiratory syndrome (SARS). The disease caused by a novel coronavirus (SARS-CoV) rapidly spread worldwide, causing more than 8000 cases and 800 deaths in more than 30 countries with a substantial economic impact. Since then, we have witnessed the emergence of several other viral respiratory pathogens including influenza viruses (avian influenza H5N1, H7N9, and H10N8; variant influenza A H3N2 virus), human adenovirus-14, and Middle East respiratory syndrome coronavirus (MERS-CoV). In response, various surveillance systems have been developed to monitor the emergence of respiratory-tract infections. These include systems based on identification of syndromes, web-based systems, systems that gather health data from health facilities (such as emergency departments and family doctors), and systems that rely on self-reporting by patients. More effective national, regional, and international surveillance systems are required to enable rapid identification of emerging respiratory epidemics, diseases with epidemic potential, their specific microbial cause, origin, mode of acquisition, and transmission dynamics.

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Surveillance for emerging respiratory viruses

Extreme heat events have occurred more frequently in China in recent years, leading to serious impacts on human life and the health care system. To identify the characteristics of individuals with heat-related illnesses in China during the summer of 2013, we collected the data from the Heat-related Illness Surveillance System in Chinese Center for Disease Control and Prevention (China CDC). A total of 5758 cases were reported in the summer of 2013, mostly concentrated in urban areas around the middle and lower reaches of the Yangtze River. We found a difference in age distribution of percentage of deaths from heat-related illness between males and females. Severe cases in males mostly occurred in the age group 45–74 years but in females mostly in the age group over 75. A distributed lag non-linear model had been used to identify population vulnerabilities in Ningbo and Chongqing. The results show that there was a clear positive relationship between maximum temperature and heat-related illness, and the heat effect was nonlinear and could last for 3 days. The elderly and males in the range of 45–64 years old might be the most vulnerable people of heat-related illness in China. We also highlighted some deficiencies of the surveillance system, such that the reported data were not accurate, comprehensive, or timely enough at this stage.

Heat-related illness in China, summer of 2013

This paper compares syndromic surveillance and predictive weather-based models for estimating emergency department (ED) visits for Heat-Related Illness (HRI). A retrospective time-series analysis of weather station observations and ICD-coded HRI ED visits to ten hospitals in south eastern Ontario, Canada, was performed from April 2003 to December 2008 using hospital data from the National Ambulatory Care Reporting System (NACRS) database, ED patient chief complaint data collected by a syndromic surveillance system, and weather data from Environment Canada. Poisson regression and Fast Orthogonal Search (FOS), a nonlinear time series modeling technique, were used to construct models for the expected number of HRI ED visits using weather predictor variables (temperature, humidity, and wind speed). Estimates of HRI visits from regression models using both weather variables and visit counts captured by syndromic surveillance as predictors were slightly more highly correlated with NACRS HRI ED visits than either regression models using only weather predictors or syndromic surveillance counts.

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Modeling and Syndromic Surveillance for Estimating Weather-Induced Heat-Related Illness

Private water supplies, which are the primary source of drinking water for rural communities in developed countries, are at risk of becoming fecally contaminated. It is important to identify the source of contamination in order to better understand and address this human health risk. Microbial source tracking methods using human, bovine and general Bacteroidales markers were performed on 716 well water samples from southeastern Ontario, which had previously tested positive for Escherichia coli. The results were then geospatially analyzed in order to elucidate contamination patterns. Markers for human feces were found in nearly half (49%) of all samples tested, and a statistically significant spatial cluster was observed. A quarter of the samples tested positive for only general Bacteroidales markers (25.7%) and relatively few bovine specific marker positives (12.6%) were found. These findings are fundamental to the understanding of pathogen dynamics and risk in the context of drinking well water and will inform future research regarding host-specific pathogens in private well water samples.

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Microbial source tracking and spatial analysis of E. coli contaminated private well waters in southeastern Ontario.

Research to date has provided limited insight into the complexity of water-borne pathogen transmission. Private well water supplies have been identified as a significant pathway in infectious disease transmission in both the industri- alised and the developing world. Using over 90,000 private well water submission records representing approximately 30,000 unique well locations in south-eastern Ontario, Canada, a spatial analysis was performed in order to delineate clus- ters with elevated risk of E. coli contamination using 5 years of data (2008-2012). Analyses were performed for all years independently and subsequently compared to each other. Numerous statistically significant clusters were identified and both geographic stability and variation over time were examined. Through the identification of spatial and temporal pat- terns, this study provides the basis for future investigations into the underlying causes of bacterial groundwater contami- nation, while identifying geographic regions that merit particular attention to public health interventions and improvement of water quality.

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A spatial analysis of private well water Escherichia coli contamination in southern Ontario.

BACKGROUND: Seasonal outbreaks of winter respiratory viruses are responsible for increases in morbidity and mortality in the community. Previous studies have used hospitalizations, intensive care unit and emergency department (ED) visits as indicators of seasonal influenza incidence.

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Geoffrey Hall

Papers

Modeling and Syndromic Surveillance for Estimating Weather-Induced Heat-Related Illness

Microbial source tracking and spatial analysis of E. coli contaminated private well waters in southeastern Ontario.

A spatial analysis of private well water Escherichia coli contamination in southern Ontario.

Emergency department surveillance as a proxy for the prediction of circulating respiratory viral disease in Eastern Ontario.

Effects of different substrates in the mitigation of algae-induced high pH wastewaters in a pilot-scale free water surface wetland system.