ED syndromic surveillance for novel H1N1 spring 2009

Bellazzini, Marc A.; Minor, Kyle D.

doi:10.1016/j.ajem.2009.09.009

Cited by 21 publications

(19 citation statements)

References 12 publications

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“…The most frequently used data were chief complaint or ED presentation [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41] and preliminary or discharge diagnosis codes [8], [9], [11], [16], [17], [18], [22], [23], [26], [27], [32], [33], [38], [39], [41], [42]. Other creative data used to capture influenza activity included free text analysis of the entire ED medical record, [37] Google flu trends, [25] calls to teletriage and help lines, [16], [25], [38] ambulance dispatch calls, [19], [20], [21], [30], [31], [32] case reports of H1N1 in the media, [8] ED census/”saturation”/length-of-s...…”

Section: Resultsmentioning

confidence: 99%

“…The observed syndromic cases based on ED data were in some cases linked to objective, confirmatory data, such as culture and other laboratory results, [8], [10], [11], [12], [14], [15], [16], [17], [18], [19], [20], [21], [24], [25], [27], [30], [31], [32], [33], [34], [35], [37], [41] and in some cases to traditional regional and national surveillance databases [9], [13], [16], [17], [22], [25], [26], [27], [29], [40], [43], historic data [44] and pneumonia and influenza weekly mortality data [12], [14].…”

Section: Resultsmentioning

confidence: 99%

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Syndromic Surveillance for Influenza in the Emergency Department–A Systematic Review

et al. 2013

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The science of surveillance is rapidly evolving due to changes in public health information and preparedness as national security issues, new information technologies and health reform. As the Emergency Department has become a much more utilized venue for acute care, it has also become a more attractive data source for disease surveillance. In recent years, influenza surveillance from the Emergency Department has increased in scope and breadth and has resulted in innovative and increasingly accepted methods of surveillance for influenza and influenza-like-illness (ILI). We undertook a systematic review of published Emergency Department-based influenza and ILI syndromic surveillance systems. A PubMed search using the keywords “syndromic”, “surveillance”, “influenza” and “emergency” was performed. Manuscripts were included in the analysis if they described (1) data from an Emergency Department (2) surveillance of influenza or ILI and (3) syndromic or clinical data. Meeting abstracts were excluded. The references of included manuscripts were examined for additional studies. A total of 38 manuscripts met the inclusion criteria, describing 24 discrete syndromic surveillance systems. Emergency Department-based influenza syndromic surveillance has been described worldwide. A wide variety of clinical data was used for surveillance, including chief complaint/presentation, preliminary or discharge diagnosis, free text analysis of the entire medical record, Google flu trends, calls to teletriage and help lines, ambulance dispatch calls, case reports of H1N1 in the media, markers of ED crowding, admission and Left Without Being Seen rates. Syndromes used to capture influenza rates were nearly always related to ILI (i.e. fever +/− a respiratory or constitutional complaint), however, other syndromes used for surveillance included fever alone, “respiratory complaint” and seizure. Two very large surveillance networks, the North American DiSTRIBuTE network and the European Triple S system have collected large-scale Emergency Department-based influenza and ILI syndromic surveillance data. Syndromic surveillance for influenza and ILI from the Emergency Department is becoming more prevalent as a measure of yearly influenza outbreaks.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Syndromic Surveillance for Influenza in the Emergency Department–A Systematic Review

et al. 2013

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“…The accuracy of chief complaint had a good agreement for the syndromes of respiratory infection in reference to discharge diagnosis. 38,51 Syndromic surveillance helped detect the 2009 pandemic infl uenza H1N1 outbreak in the USA 55 and was used in emergency departments in Canada to predict circulating respiratory viral disease such as infl uenza and respiratory syncytial virus. 56 One study compared the Geographic Utilization of Artifi cial Intelligence in Real-time for Disease Identifi cation and Alert Notifi cation (GUARDIAN) system with the Complaint Coder (CoCo) of the Real-time Outbreak Detection System (RODS), the Symptom Coder (SyCo) of RODS, and an electronic medical record (EMR) system.…”

Section: Syndromic Surveillancementioning

confidence: 99%

Surveillance for emerging respiratory viruses

Al‐Tawfiq

Zumla

Gautret

et al. 2014

The Lancet Infectious Diseases

110

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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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“…Retrospectively, the severity of illness from A(H1N1)pdm09 was mild relative to previous influenza seasons, and together with other factors that could affect ED visit volumes, such as the opening of influenza assessment centres, this may contribute to the absence and variability in timing of alerts. As other published results have demonstrated the potential of ED surveillance systems to detect influenza earlier than traditional laboratory-based testing, 3,[18][19][20] further study of ED surveillance systems is warranted.…”

Section: Discussionmentioning

confidence: 99%

Assessing the Relative Timeliness of Ontario’s Syndromic Surveillance Systems for Early Detection of the 2009 Influenza H1N1 Pandemic Waves

Chu

Savage

Whelan

et al. 2013

Can J Public Health

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OBJECTIVES:Building on previous research noting variations in the operation and perceived utility of syndromic surveillance systems in Ontario, the timeliness of these different syndromic systems for detecting the onset of both 2009 H1N1 pandemic (A(H1N1)pdm09) waves relative to laboratory testing data was assessed using a standardized analytic algorithm. METHODS:Syndromic data, specifically local emergency department (ED) visit and school absenteeism data, as well as provincial Telehealth (telephone helpline) and antiviral prescription data, were analyzed retrospectively for the period April 1, 2009 to January 31, 2010. The C2-MEDIUM aberration detection method from the US Centers for Disease Control and Prevention's EARS software was used to detect increases above expected in syndromic data, and compared to laboratory alerts, defined as notice of confirmed A(H1N1)pdm09 cases over two consecutive days, to assess relative timeliness. RESULTS:In Wave 1, provincial-level alerts were detected for antiviral prescriptions and Telehealth respiratory calls before the laboratory alert. In Wave 2, Telehealth respiratory calls similarly alerted in advance of the laboratory, while local alerts from ED visit, antiviral prescription and school absenteeism data varied in timing relative to the laboratory alerts. Alerts from syndromic data were also observed to coincide with external factors such as media releases. CONCLUSIONS:Alerts from syndromic surveillance systems may be influenced by external factors and variation in system operations. Further understanding of both the impact of external factors on surveillance data and standardizing protocols for defining alerts is needed before the use of syndromic surveillance systems can be optimized.

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ED syndromic surveillance for novel H1N1 spring 2009

Cited by 21 publications

References 12 publications

Syndromic Surveillance for Influenza in the Emergency Department–A Systematic Review

Syndromic Surveillance for Influenza in the Emergency Department–A Systematic Review

Surveillance for emerging respiratory viruses

Assessing the Relative Timeliness of Ontario’s Syndromic Surveillance Systems for Early Detection of the 2009 Influenza H1N1 Pandemic Waves

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