Event-based internet biosurveillance: relation to epidemiological observation
<p>Abstract</p> <p>Background</p> <p>The World Health Organization (WHO) collects and publishes surveillance data and statistics for select diseases, but traditional methods of gathering such data are time and labor intensive. Event-based biosurveillance, which utilizes...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2012-06-01
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| Series: | Emerging Themes in Epidemiology |
| Subjects: | |
| Online Access: | http://www.ete-online.com/content/9/1/4 |
| _version_ | 1818213618333777920 |
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| author | Nelson Noele P Yang Li Reilly Aimee R Hardin Jessica E Hartley David M |
| author_facet | Nelson Noele P Yang Li Reilly Aimee R Hardin Jessica E Hartley David M |
| author_sort | Nelson Noele P |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>The World Health Organization (WHO) collects and publishes surveillance data and statistics for select diseases, but traditional methods of gathering such data are time and labor intensive. Event-based biosurveillance, which utilizes a variety of Internet sources, complements traditional surveillance. In this study we assess the reliability of Internet biosurveillance and evaluate disease-specific alert criteria against epidemiological data.</p> <p>Methods</p> <p>We reviewed and compared WHO epidemiological data and Argus biosurveillance system data for pandemic (H1N1) 2009 (April 2009 – January 2010) from 8 regions and 122 countries to: identify reliable alert criteria among 15 Argus-defined categories; determine the degree of data correlation for disease progression; and assess timeliness of Internet information.</p> <p>Results</p> <p>Argus generated a total of 1,580 unique alerts; 5 alert categories generated statistically significant (p < 0.05) correlations with WHO case count data; the sum of these 5 categories was highly correlated with WHO case data (r = 0.81, p < 0.0001), with expected differences observed among the 8 regions. Argus reported first confirmed cases on the same day as WHO for 21 of the first 64 countries reporting cases, and 1 to 16 days (average 1.5 days) ahead of WHO for 42 of those countries.</p> <p>Conclusion</p> <p>Confirmed pandemic (H1N1) 2009 cases collected by Argus and WHO methods returned consistent results and confirmed the reliability and timeliness of Internet information. Disease-specific alert criteria provide situational awareness and may serve as proxy indicators to event progression and escalation in lieu of traditional surveillance data; alerts may identify early-warning indicators to another pandemic, preparing the public health community for disease events.</p> |
| first_indexed | 2024-12-12T06:07:09Z |
| format | Article |
| id | doaj.art-8cd5c7e8e8dd4e16b03e5d7a712e51e7 |
| institution | Directory Open Access Journal |
| issn | 1742-7622 |
| language | English |
| last_indexed | 2024-12-12T06:07:09Z |
| publishDate | 2012-06-01 |
| publisher | BMC |
| record_format | Article |
| series | Emerging Themes in Epidemiology |
| spelling | doaj.art-8cd5c7e8e8dd4e16b03e5d7a712e51e72022-12-22T00:35:16ZengBMCEmerging Themes in Epidemiology1742-76222012-06-0191410.1186/1742-7622-9-4Event-based internet biosurveillance: relation to epidemiological observationNelson Noele PYang LiReilly Aimee RHardin Jessica EHartley David M<p>Abstract</p> <p>Background</p> <p>The World Health Organization (WHO) collects and publishes surveillance data and statistics for select diseases, but traditional methods of gathering such data are time and labor intensive. Event-based biosurveillance, which utilizes a variety of Internet sources, complements traditional surveillance. In this study we assess the reliability of Internet biosurveillance and evaluate disease-specific alert criteria against epidemiological data.</p> <p>Methods</p> <p>We reviewed and compared WHO epidemiological data and Argus biosurveillance system data for pandemic (H1N1) 2009 (April 2009 – January 2010) from 8 regions and 122 countries to: identify reliable alert criteria among 15 Argus-defined categories; determine the degree of data correlation for disease progression; and assess timeliness of Internet information.</p> <p>Results</p> <p>Argus generated a total of 1,580 unique alerts; 5 alert categories generated statistically significant (p < 0.05) correlations with WHO case count data; the sum of these 5 categories was highly correlated with WHO case data (r = 0.81, p < 0.0001), with expected differences observed among the 8 regions. Argus reported first confirmed cases on the same day as WHO for 21 of the first 64 countries reporting cases, and 1 to 16 days (average 1.5 days) ahead of WHO for 42 of those countries.</p> <p>Conclusion</p> <p>Confirmed pandemic (H1N1) 2009 cases collected by Argus and WHO methods returned consistent results and confirmed the reliability and timeliness of Internet information. Disease-specific alert criteria provide situational awareness and may serve as proxy indicators to event progression and escalation in lieu of traditional surveillance data; alerts may identify early-warning indicators to another pandemic, preparing the public health community for disease events.</p>http://www.ete-online.com/content/9/1/4BiosurveillanceInfectious diseaseEpidemiologyDisease-specific alertsInternet mediaEarly warningPandemic (H1N1) 2009Situational awarenessOutbreak detection |
| spellingShingle | Nelson Noele P Yang Li Reilly Aimee R Hardin Jessica E Hartley David M Event-based internet biosurveillance: relation to epidemiological observation Emerging Themes in Epidemiology Biosurveillance Infectious disease Epidemiology Disease-specific alerts Internet media Early warning Pandemic (H1N1) 2009 Situational awareness Outbreak detection |
| title | Event-based internet biosurveillance: relation to epidemiological observation |
| title_full | Event-based internet biosurveillance: relation to epidemiological observation |
| title_fullStr | Event-based internet biosurveillance: relation to epidemiological observation |
| title_full_unstemmed | Event-based internet biosurveillance: relation to epidemiological observation |
| title_short | Event-based internet biosurveillance: relation to epidemiological observation |
| title_sort | event based internet biosurveillance relation to epidemiological observation |
| topic | Biosurveillance Infectious disease Epidemiology Disease-specific alerts Internet media Early warning Pandemic (H1N1) 2009 Situational awareness Outbreak detection |
| url | http://www.ete-online.com/content/9/1/4 |
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