Environmental Health

Cyanotoxins are unregulated, emerging contaminants that have been associated with adverse health effects, including gastroenteritis, when consumed at high levels1,2. In May and June of 2018 cyanotoxins were detected in the public drinking water system for Salem, OR at levels above Environmental Protection Agency (EPA) health advisory levels for sensitive groups3. Sensitive groups were defined as children under 6, elderly adults, pregnant women, nursing mothers, people with compromised immune systems, people receiving dialysis, people with pre-existing liver conditions, and pets. Several health advisories were issued, and there was substantial media coverage of the event. The Oregon Health Authority (OHA) organized an Incident Management Team (IMT), which coordinated activities with other state and local agencies. Oregon ESSENCE staff used syndromic surveillance to monitor the population for health effects and healthcare seeking behavior.

Objective: Examine healthcare seeking behavior in a population exposed to low levels of cyanotoxins in the public drinking water supply and quantify how publicity of the event may have affected perceptions of risk in the affected population.

In 2002, the United States (US) Centers for Disease Control and Prevention (CDC) launched the National Environmental Public Health Tracking Program (Tracking Program) to address the challenges in environmental health surveillance described by the Pew Environmental Commission (1). The report cited gaps in our understanding of how the environment affects our health and attributed these gaps to a dearth of surveillance data for environmental hazards, human exposures, and health effects. The Tracking Program's mission is to provide information from a nationwide network of integrated health and environmental data that drives actions to improve the health of communities. Accomplishing this mission requires a range of expertise from environmental health scientists to programmers to communicators employing the best practices and latest technical advances of their disciplines. Critical to this mission, the Tracking Program must identify and prioritize what data are needed, address any gaps found, and integrate the data into the network for ongoing surveillance.

Objective: To increase the availability and accessibility of standardized environmental health data for public health surveillance and decision-making.

Leptospirosis is a zoonotic disease caused by the pathogenic Leptospira bacteria and is ubiquitously distributed in tropical and subtropical regions. Leptospirosis transmission driven by complex factors include climatic, environmental and local social conditions [1]. Each year, there are about 1 million cases of human leptospirosis reported globally and it causes approximately 60,000 people lost their lives due to infection [2]. Yunnan Province and Sichuan Province are two of highly endemic areas in the southwest China that had contributed for 47% of the total national reported cases during 2005-2015 [3]. Factors underlying local leptospirosis transmission in these two areas is far from clear and thus hinder the efficacy of control strategies. Hence, it is essential to assess and identify local key drivers associated with persistent leptospirosis transmission in that areas to lay foundation for the development of early-warning systems. Currently, remote sensing technology provides broad range of physical environment data at various spatial and temporal scales [4], which can be used to understand the leptospirosis epidemiology. Utilizing satellite-based environmental data combined with locally-acquired weather data may potentially enhance existing surveillance programs in China so that the burden of leptospirosis could be reduced.

Objective: To quantify the effects of climate variability, selected remotely-sensed environmental factors on human leptospirosis in the high-risk counties in China.

Public health surveillance relies on surveys and/or self-reported data collection, both of which require manpower, time commitment, and financial resources from public health agencies and participants. The survey results can quickly become outdated due to fast-paced changes in our society. The health habits of Canadians have rapidly evolved with technology and research indicates we are becoming a sedentary society, thus the levels of physical activity (PA) are very important population level health indicators. We will present a novel method to gather data at a granular level in near real-time, with minimal effort from participants. Simple thermostats are found in nearly every house in Canada, and smart thermostats enable efficient temperature adjustment, saving energy costs by adjusting according to human activity. Thermostats are ubiquitous in Canadian homes and the current expansion of smart thermostats make them an ideal data source over traditional methods. Utilizing technology that can be deployed at a population level will enable vast granular data collection beyond capabilities of traditional surveys. In this project UbiLab1 is exploring the use of the zero-effort technology using sensor data collected by smart thermostats and other associated sensors to develop an innovative health surveillance platform and monitor an individual's health at the household level as well as health indicators at population level. Utilizing the smart wi-fi thermostat, we able to report on PA, sedentary behaviour, and sleep patterns at the household level. The thermostat and remote sensors (RS) contain temperature and motion sensors, which can be used to monitor activity in the home (i.e. lack of travel indicates sedentary behaviour), as well as sleep characteristics. This is beneficial as no action is required from participants, allowing individuals to go about their lives unperturbed. This powerful system will be able to deliver real-time health insights to public health professionals.

Objective: The objective of this study is to explore individual, household and population-level health indicators collected in the home via smart thermostats. The study's approach is to (a) identify if it is possible to isolate specific user behaviours using the motion and thermostat sensor data, and (b) develop Remote Monitoring of healthy behaviours at population level. Furthermore, this study is interested in identifying if observed patterns will suffer variations. As a result, it will be possible to understand human behaviours and consequently understand lifestyle habits of a person or a group of people.

Enteric fever (EF) is a grave systemic infection, which has been controlled quite effectively in developed countries, but continues to be a grave public health concern for India. Environmental drivers such as rainfall, temperature, relative humidity and El Niño-Southern Oscillations (ENSO) are known to influence the transmission of Salmonella typhi and paratyphi. India possesses the largest population burden of EF, yet very few studies have explored its climatic associations.

Objective: This study is an attempt to explore the relationship of EF incidence with climate variables and ENSO events in the seventh most populous city in India.

Although rare in the US, the CDC reports 13-14 drinking-water-related disease outbreaks per year, affecting an average of about 1000 people. The US EPA has determined that the distribution system is the most vulnerable component of a drinking water system. Recognizing this vulnerability, water utilities are increasingly measuring disinfectant levels and other parameters in their distribution systems. The US EPA is sponsoring an initiative to fuse this distribution system water quality data with health data to improve surveillance by providing an assessment of the likelihood of the occurrence of a waterborne disease outbreak. This fused analysis capability will be available via a prototype water security module within a population-based public health syndromic surveillance system.

Objective

The objective of this paper is to illustrate a technique for combining water quality and population-based health data to monitor for water-borne disease outbreaks.

In July 2006, an important heat wave occurred in France, and generated alarm of all the public health services. In Gironde, a department in region Aquitaine, the level of "warning and actions" of the Heat Health Watch Warning System, based on an analysis of weather-mortality relationship, was activated from the 16th and the 27th of July, when the limits of biometeorological indicators were reached [1].

Objective

To assess health impact of heat wave occurred in July 2006 through data from emergency activity and mortality from syndromic surveillance systems in Gironde, a department in south-western France.

Under a grant from the Centers for Disease Control and Prevention (CDC), the DC DOH established the Environmental Public Health Tracking Program (EPHTP) to monitor specific environmental and public health indicators and to investigate any potential links for the purpose of guiding policy development, resource allocation, and decision-making on disease prevention and treatment activities. This information improves understanding of the immediate and short-term effects of airborne pollutants on health care usage. In a collaborative project between JHU/APL and DC DOH, investigators explored and quantified correlations between ambient air quality measurements from five DC stations between October 2001 and March 2004 and DC hospital pediatric emergency department (ED) visits for asthma exacerbations. 

Objective

The study objective was to provide the CDC results from the EPHTP on quantifying the relationship between air quality and pediatric ED visits for asthma among DC residents over a 3 year period. This effort also explored novel uses of traditional data to understand background disease patterns so that unexpected fluctuations could be better detected in community disease trends and thereby identify early disease outbreaks.