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Real-Time

Description

The resources available in most public health departments are limited. Access to trained technical personnel and stateof-the-art computing resources are also lacking. Customizable off-the-shelf systems contribute only to creation of information silos, are expensive, and not affordable by the limited budget available to the departments of health (only growing worse with the recession). The one thing that has increased is the need for surveillance in more areas, from diseases to environmental exposures to unexpected disasters. One solution would be an adaptable system able to cope with changing requirements while reusing or eliminating infrastructure from both computing hardware and technical personnel.2 We report in this paper an instance of such system as used to perform disease surveillance across the Harris County school system. The system is designed to be customizable for surveillance of any disease, while simultaneously accommodating other use cases like disaster response and registries.

Objective

This paper describes use of semantic technologies in combination with Services Oriented Architecture (SOA) to construct dynamic public health surveillance systems1 used for just-in-time monitoring of emerging infectious disease outbreaks. The system was used for surveillance of schools in the third largest population center, Harris County.

Submitted by Magou on
Description

Unfortunately, confirmation and notification of all A/H1N1 (2009) patients in Japan was ceased on 24 July when the cumulative number of patients was about 5000. After that, as all suspected patients are not necessarily confirmed or reported, the only official surveillance was the sentinel surveillance for influenza-like-illness (ILI) patients from 5000 clinics accounting for almost 10% of all clinics and hospitals in Japan. However, because the surveillance results are reported weekly, it tends to lack timeliness. To collect and analyze the information in more timely manner, we, Infectious Disease Surveillance Center, National Institute of Infectious Diseases, developed a full automatic daily reporting system of ILI patients. Using this information, we had estimated Rv and predict its course in every week.

Objective

This paper summarized our effort for real-time estimation of pandemic influenza A/H1N1pdm in Japan.

Submitted by uysz on
Description

During March-May 2013, 14 overdose deaths occurred in RI that were caused by acetyl fentanyl, a novel synthetic opioid about five times more potent than heroin1. Ten of these deaths were clustered in March, causing a significant increase over baseline of monthly illicit drug overdose deaths in RI1. Overdose deaths are well described in RI by forensic toxicology testing results. However, the overall number of ED visits associated with this event was unknown. We used RODS data retrospectively to characterize overdose related ED visits in RI and to analyze trends.

Objective

Determine if the Rhode Island (RI) Real-time Outbreak and Disease Surveillance (RODS) system (a syndromic surveillance system) identified an increase in overdoses during a known cluster of illicit drug overdose deaths in RI and characterize emergency department (ED) overdose visits during the 15 month period prior to and including the known cluster.

Submitted by elamb on
Description

Currently Scotland has a number of influenza surveillance schemes, including âflu-spotter’ practices, and enhanced surveillance general practices that submit clinical samples for virological testing (SERVIS practices). This information feeds annually into the European Influenza Surveillance Scheme1. Information from the systems is seasonal, and limited geographically covering 6% and 3% of the population respectively. The utilisation by Scottish community physicians (general practitioners, GP’s) of the same administration system in over 80% of settings - the General Practice Administration System for Scotland (GPASS) - offers an alternative approach to influenza surveillance with some additional benefits.

Objective

To develop and pilot an enhanced primary care surveillance system of influenza-like illness in Scotland, record influenza vaccine uptake and estimate vaccine effectiveness in season in real time.

 

Submitted by elamb on
Description

Air pollution is well documented to cause adverse health effects in the population. Epidemiological/toxicological studies have demonstrated that air pollution is associated with various adverse health outcomes, ranging from mortality to subclinical respiratory symptoms. Classical epidemiological studies of the health effects of air pollution are typically retrospective. In order to assess the effectiveness of any public health messages or interventions in a timely manner there is a need to be able to systematically detect any health effects occurring in real-time. The UK syndromic surveillance systems are coordinated by Public Health England (PHE) and are used to monitor infectious diseases in real-time. This study is the first in the UK to explore whether syndromic surveillance systems can detect public health impacts associated with air pollution events.

Objective: This study examined whether the current UK real-time syndromic surveillance systems can detect public health impacts associated with air pollution events such as fires and ambient air pollution episodes.

Submitted by knowledge_repo… on
Description

Wetter and stormier weather is predicted in the UK as global temperatures rise. It is likely there will be increases in river and coastal flooding. The known short and medium term health effects of flooding are drowning, injury, acute asthma, skin rashes and outbreaks of gastrointestinal and respiratory disease. Longer term health effects of flooding are thought to be psychological stress and increased rates of mental illness. Reacher et al. conducted a retrospective study of illness in a population affected by flooding in Lewes, South-East England during 2000 [1]. They found a significant raised risk of earache (RR=2.2) and gastroenteritis (RR=1.7) for flooded households. More striking was the higher level of psychological distress experienced by these residents (RR=4.1), which may have also explained some of the excess physical illness.

Objective

This paper describes the results of prospective real time syndromic surveillance conducted during a national flooding incident during 2007 in the UK.

Submitted by elamb on
Description

Prehospital  EMS  data  is  rarely  mentioned  in  discus-sions  surrounding  syndromic  surveillance  for  covert  bio-terrorism  attacks  or  for  the  monitoring  of  syn-dromic  illness  such  as  bird  flu.    However,  EMS  dis-patch data may serve as the very first marker in such an event.  EMS dispatch data has many useful advan-tages  in  syndromic  surveillance.    These  include  the  ability to monitor across wide areas of geography and a  single  data  collection  source.    Additionally,  EMS  dispatchers  are  a  medically  trained  core  group  of  in-dividuals that use a single standardized set of interro-gation  questions  and  methods  with  specific  dispatch  codes  regarding  patient  conditions.    This  data  would  arguably be a more reliable source of data than mul-tiple  different  inputs  from  multiple  individuals  at  various clinics and hospitals emergency departments.  EMS  data  is  also  able  to  look  at  a  much  broader  group  of  individuals  both  by  volume  of  calls  and  by  geography,  since  they  are  instantaneously  able  to  capture  the  location  of  the  callers  when  dialing  911. EMS  dispatch  is  also  able  to  monitor  patient  move-ment to different accepting facilities.

Objective

This paper describes how the surveillance of actual EMS real time events occurring during normal operations were analyzed using a syndromic surveillance system and how these events can be used as surrogate markers for how a bio-surveillance system would act if an actual covert or overt terrorist event or pandemic illness were to occur

Submitted by elamb on
Description

Real-time disease surveillance is critical for early detection of the covert release of a biological threat agent (BTA). Numerous software applications have been developed to detect emerging disease clusters resulting from either naturally occurring phenomena or from occult acts of bioterrorism. However, these do not focus adequately on the diagnosis of BTA infection in proportion to the potential risk to public health.

GUARDIAN is a real-time, scalable, extensible, automated, knowledge-based BTA detection and diagnosis system.  GUARDIAN conducts real-time analysis of multiple pre-diagnostic parameters from records already being collected within an emergency department (ED).  The goal of this system is to assist clinicians in detecting potential BTAs as quickly and effectively as possible in order to better respond to and mitigate the effects of a large-scale outbreak.  

GUARDIAN improves the diagnostic process by moving away from simple trend anomaly detection and towards the development of a BTA-specific infectious disease expert system [1].  Through the capture and automated application of specific clinical expertise, GUARDIAN provides the focus and accuracy necessary for effective BTA infection diagnosis.  The continuity of this process improves the efficiency by which diagnoses of BTA infections can be made.

 

Submitted by elamb on
Description

Influenza epidemics occur seasonally, impose a high economic burden on the health care system, and are responsible for substantial morbidity and mortality (1). The past century has seen three influenza A pandemics with variable severity. The recent outbreaks of avian influenza involving different virus strains in Asia, North America and the Netherlands, indicates the increasing potential of a new influenza pandemic (2). Public and political awareness needs to be strengthened while public health surveillance strategies need significant improvements if we are to mitigate such a potentially devastating worldwide pandemic, and provide the healthcare system with as much early warning as possible to enhance preparedness. Telehealth Ontario is a provincial telephone helpline for health information staffed by nurses that, if monitored on a real-time basis, has the potential to identify increases in seasonal respiratory infection rates. A recent study suggested that Telehealth Ontario respiratory calls reflect the seasonality of diagnosed respiratory illnesses in emergency departments (van Dijk et al., unpublished data), but an estimation of how respiratory pathogens contribute to Telehealth Ontario’s respiratory complaint calls has not been studied.

Objective:

This paper will explore the possibility and utility of monitoring Telehealth Ontario respiratory calls as an efficient public health influenza strategy for early warning by comparing this data source to provincial viral lab data.

Submitted by elamb on
Description

Since July 2004 the BioSense program at the Centers for Disease Control and Prevention (CDC) has received data from DoD military and VA outpatient clinics (not in real time). In January 2006 real-time hospital data (e.g. chief complaints and diagnoses) was added. Various diagnoses from all sources are binned into one or more of 11 syndrome categories.

Objective

This paper'­s objective is to compare syndromic categorization of newly acquired real-time civilian hospital data with existing BioSense data sources.

Submitted by elamb on