Environmental Health

CO poisoning is a leading cause of mortality and morbidity in disaster and post-disaster situations, when widespread power outages most likely occur (1, 2). The NYSDOH Syndromic Surveillance System receives daily ED visit chief complaint data from 140 NYS (excluding New York City) hospitals. Daily power outage data are available from the NYS Department of Public Service (NYSDPS). These data can be used to estimate the risk of CO-EDs and provide useful information for public health situational awareness and emergency response management during disaster events.

Objective

1) To identify carbon monoxide (CO) poisoning in three most affected New York State (NYS) counties (Nassau, Suffolk, and Westchester) during and immediately after Hurricane Sandy with hospital emergency department (ED) chief complaint data reported daily to the New York State Department of Health (NYSDOH). 2) To explore the relationship between power outage and the numbers of CO-related ED visits (CO-EDs).

Chagas’ disease, caused by the protozoan Trypanosoma cruzi, is spread mostly by Triatominae bugs. High carbon dioxide emission and strong infra-red (IR) radiation are indicative of their presence. Periods of low atmospheric water saturation favor their dispersal, when the bugs’ IR perception is high.

The Fast Subset Scan (FSScan) is very efficient for the detection of the most likely geographic cluster. Covariate studies associating the presence of regular clusters with environmental factors are routinely done using the Circular Scan, the simplest version of the Spatial Scan statistic. However, if the study employs irregular clusters instead, accurate results depend on the generation of a rich family of variants of the primary cluster.

Objective

We employ climate information to assess the possible spatial dependence on the occurrence of Chagas’ disease irregular clusters in Central Brazil, using a variant of the Spatial Scan Statistic, the Geo-Dynamic Scan (GDScan).

Hurricane ‘Superstorm’ Sandy struck New Jersey on October 29, 2012, causing harm to the health of New Jersey residents and billions of dollars of damage to businesses, transportation, and infrastructure. Monitoring health outcomes for increased illness and injury due to a severe weather event is important in measuring the severity of conditions and the efficacy of state response, as well as in emergency response preparations for future severe weather events. Following the experience with Hurricane Sandy and the foreseeable need to be prepared for future severe weather events, NJDOH initiated a project to develop a suite of 20 indicators in EpiCenter, an online system which collects emergency department chief complaint data in realtime, to perform syndromic surveillance of extreme weather–related conditions.

Objective

To introduce and describe methods for evaluating and refining custom classifier keyword lists for syndromic surveillance of several post-severe weather event conditions and to report findings from New Jersey’s syndromic surveillance of selected conditions in the aftermath of Hurricane Sandy.

Healthcare seeking behavior is important to understand when interpreting public health surveillance data, planning for healthcare utilization, or attempting to estimate or model consequences of an adverse event, such as widespread water contamination. Although there is evidence that factors such as perceived susceptibility and benefits affect healthcare seeking behavior, it is difficult to develop accurate assumptions due to a lack of published research on this topic. Current conceptual behavior models, such as the health belief model, are not easily translated into quantifiable terms.

Objective

This paper describes analyses of health seeking behaviors from two surveillance datastreams: Poison Control Center (PCC) calls and Emergency Department (ED) visit records. These analyses were conducted in order to quantify behaviors following the development of symptoms after water contamination exposure and to understand the motivation, decision-making and timing behind healthcare seeking behaviors.

Geographic Information System (GIS) applications are increasingly being used for public health purposes. GIS technology provides visual tools – through the creation of computerized maps, graphs, and tables of geographic data – that can assist with problem solving and inform decision-making. PHIMS aims to enable visualization and spatial analysis of environmental data with underlying population based indicators. PHIMS displays many layers of environmental information across Ontario, and users can view maps demonstrating environmental or demographic data as they apply to specific geographic areas. This is useful for observing where environmental events are occurring, detecting potential emergency situations, and identifying areas with vulnerable populations. By displaying available, real-time, environmental data from multiple partners through PHIMS, public health events can be identified earlier to better prevent, prepare for, and respond to emergencies.

Objective

To describe how the Public Health Information Management System (PHIMS) tool is used by KFL&A Public Health to enhance real-time situational awareness and assist with evidence informed decision-making to help protect the health of the population.

The impact of poor air quality (AQ) on human health is a global issue, with periods of poor AQ known to occur in multiple locations, across different countries at, or around the same time. The Public Health England (PHE) Emergency Department Syndromic Surveillance System (EDSSS) is a public health legacy of the London 2012 Olympic and Paralympic Games, monitoring anonymised daily attendance data in near real-time from a sentinel network of up to 38 EDs across England and Northern Ireland during 2014. The Organisation de la Surveillance COordonnée des URgences (OSCOUR®) is a similar ED system coordinated by Santé publique France and has been running in France since 2004, established following a major heatwave in 2003 to improve real-time public health surveillance capabilities. This truly national network included around 540 EDs in 2014.

Objective

To assess the impact on human health observed in association with periods of poor air quality which extended across international borders, affecting both London (UK) and Paris (France). In particular to quantify increased levels of emergency department (ED) attendances for asthma and wheeze/ difficulty breathing, and how different age groups were affected. Here, using ED syndromic surveillance from England and France, we aimed to identify and describe the acute impact of periods of particularly poor air quality during 2014 on human health in both London and Paris.

Technology that combines traditional manipulations with databases and complete visualization of geographic (spatial) analysis employing maps has been developed in order to explore the possibilities for Geographical Information Systems (GIS) to be used in sanitary and epidemiological surveillance system based on the analysis of morbidity and identification of influence of hazardous chemical environmental factors on human health.