“Google Flu Trends” and Emergency Department Triage Data Predicted the 2009 Pandemic H1N1 Waves in Manitoba

Malik, Mohammad; Gumel, Abba B.; Thompson, Laura H.; Strome, Trevor; Mahmud, Salaheddin M.

doi:10.1007/bf03404053

Cited by 49 publications

(34 citation statements)

References 16 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-st...…”

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%

See 1 more Smart Citation

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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“…Google Flu Trends estimates have been reported to correlate highly with laboratory-confi rmed infl uenza at a provincial and city level. Malik and colleagues 12 reported the correlation between weekly counts of laboratoryconfi rmed H1N1 infl uenza cases in Manitoba, Canada, and Google Flu Trends data during the 2009 infl uenza pandemic (R²=0·69; 2 week lag). Similarly, Google Flu Trends had a high level of congruence with virology data from a Baltimore hospital (adult r=0·88; paediatric r=0·72).…”

Section: Google Flu Trendsmentioning

confidence: 99%

“…The nature of emerging infectious diseases often limits the eff ectiveness of traditional surveillance systems. 12 Digital surveillance could improve both the sensitivity and timeliness of detection of health events. 13 We review recent studies that have exploited internet use and search trends to monitor two acute-onset viral illnesses of worldwide importance that have substantial seasonal and geographic variation: infl uenza and dengue.…”

Section: Introductionmentioning

confidence: 99%

Internet-based surveillance systems for monitoring emerging infectious diseases

Milinovich

Williams

Clements

et al. 2014

The Lancet Infectious Diseases

265

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Emerging infectious diseases present a complex challenge to public health officials and governments; these challenges have been compounded by rapidly shifting patterns of human behaviour and globalisation. The increase in emerging infectious diseases has led to calls for new technologies and approaches for detection, tracking, reporting, and response. Internet-based surveillance systems offer a novel and developing means of monitoring conditions of public health concern, including emerging infectious diseases. We review studies that have exploited internet use and search trends to monitor two such diseases: influenza and dengue. Internet-based surveillance systems have good congruence with traditional surveillance approaches. Additionally, internet-based approaches are logistically and economically appealing. However, they do not have the capacity to replace traditional surveillance systems; they should not be viewed as an alternative, but rather an extension. Future research should focus on using data generated through internet-based surveillance and response systems to bolster the capacity of traditional surveillance systems for emerging infectious diseases.

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“…Scholars have stressed the correlations between Internet search and the triage data, the hospital access, and the need of drugs [35, 36]. …”

Section: Introductionmentioning

confidence: 99%

Infodemiology and Infoveillance of Multiple Sclerosis in Italy

Bragazzi

2013

Multiple Sclerosis International

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Multiple Sclerosis (MS) is a chronic debilitating disease of probable autoimmune inflammatory nature, whose aetiology is not fully understood, despite the many efforts and investigations. In this manuscript, we review the concept of “Multiple Sclerosis 2.0”, that is to say the Internet usage by MS patients, for seeking health and disease-related material for self-care and self-management purposes, and we introduce a Google Trends-based approach for monitoring MS-related Google queries and searches, called MS infodemiology and infoveillance. Google Trends has already proven to be reliable for infectious diseases monitoring, and here we extend its application and potentiality in the field of neurological disorders.

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“Google Flu Trends” and Emergency Department Triage Data Predicted the 2009 Pandemic H1N1 Waves in Manitoba

Cited by 49 publications

References 16 publications

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

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

Internet-based surveillance systems for monitoring emerging infectious diseases

Infodemiology and Infoveillance of Multiple Sclerosis in Italy

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