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Using internet search queries for infectious disease surveillance: screening diseases for suitability
BACKGROUND: Internet-based surveillance systems provide a novel approach to monitoring infectious diseases. Surveillance systems built on internet data are economically, logistically and epidemiologically appealing and have shown significant promise. The potential for these systems has increased wit...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4300155/ https://www.ncbi.nlm.nih.gov/pubmed/25551277 http://dx.doi.org/10.1186/s12879-014-0690-1 |
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author | Milinovich, Gabriel J Avril, Simon M R Clements, Archie C A Brownstein, John S Tong, Shilu Hu, Wenbiao |
author_facet | Milinovich, Gabriel J Avril, Simon M R Clements, Archie C A Brownstein, John S Tong, Shilu Hu, Wenbiao |
author_sort | Milinovich, Gabriel J |
collection | PubMed |
description | BACKGROUND: Internet-based surveillance systems provide a novel approach to monitoring infectious diseases. Surveillance systems built on internet data are economically, logistically and epidemiologically appealing and have shown significant promise. The potential for these systems has increased with increased internet availability and shifts in health-related information seeking behaviour. This approach to monitoring infectious diseases has, however, only been applied to single or small groups of select diseases. This study aims to systematically investigate the potential for developing surveillance and early warning systems using internet search data, for a wide range of infectious diseases. METHODS: Official notifications for 64 infectious diseases in Australia were downloaded and correlated with frequencies for 164 internet search terms for the period 2009–13 using Spearman’s rank correlations. Time series cross correlations were performed to assess the potential for search terms to be used in construction of early warning systems. RESULTS: Notifications for 17 infectious diseases (26.6%) were found to be significantly correlated with a selected search term. The use of internet metrics as a means of surveillance has not previously been described for 12 (70.6%) of these diseases. The majority of diseases identified were vaccine-preventable, vector-borne or sexually transmissible; cross correlations, however, indicated that vector-borne and vaccine preventable diseases are best suited for development of early warning systems. CONCLUSIONS: The findings of this study suggest that internet-based surveillance systems have broader applicability to monitoring infectious diseases than has previously been recognised. Furthermore, internet-based surveillance systems have a potential role in forecasting emerging infectious disease events, especially for vaccine-preventable and vector-borne diseases. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12879-014-0690-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4300155 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43001552015-01-21 Using internet search queries for infectious disease surveillance: screening diseases for suitability Milinovich, Gabriel J Avril, Simon M R Clements, Archie C A Brownstein, John S Tong, Shilu Hu, Wenbiao BMC Infect Dis Research Article BACKGROUND: Internet-based surveillance systems provide a novel approach to monitoring infectious diseases. Surveillance systems built on internet data are economically, logistically and epidemiologically appealing and have shown significant promise. The potential for these systems has increased with increased internet availability and shifts in health-related information seeking behaviour. This approach to monitoring infectious diseases has, however, only been applied to single or small groups of select diseases. This study aims to systematically investigate the potential for developing surveillance and early warning systems using internet search data, for a wide range of infectious diseases. METHODS: Official notifications for 64 infectious diseases in Australia were downloaded and correlated with frequencies for 164 internet search terms for the period 2009–13 using Spearman’s rank correlations. Time series cross correlations were performed to assess the potential for search terms to be used in construction of early warning systems. RESULTS: Notifications for 17 infectious diseases (26.6%) were found to be significantly correlated with a selected search term. The use of internet metrics as a means of surveillance has not previously been described for 12 (70.6%) of these diseases. The majority of diseases identified were vaccine-preventable, vector-borne or sexually transmissible; cross correlations, however, indicated that vector-borne and vaccine preventable diseases are best suited for development of early warning systems. CONCLUSIONS: The findings of this study suggest that internet-based surveillance systems have broader applicability to monitoring infectious diseases than has previously been recognised. Furthermore, internet-based surveillance systems have a potential role in forecasting emerging infectious disease events, especially for vaccine-preventable and vector-borne diseases. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12879-014-0690-1) contains supplementary material, which is available to authorized users. BioMed Central 2014-12-31 /pmc/articles/PMC4300155/ /pubmed/25551277 http://dx.doi.org/10.1186/s12879-014-0690-1 Text en © Milinovich et al.; licensee BioMed Central. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Milinovich, Gabriel J Avril, Simon M R Clements, Archie C A Brownstein, John S Tong, Shilu Hu, Wenbiao Using internet search queries for infectious disease surveillance: screening diseases for suitability |
title | Using internet search queries for infectious disease surveillance: screening diseases for suitability |
title_full | Using internet search queries for infectious disease surveillance: screening diseases for suitability |
title_fullStr | Using internet search queries for infectious disease surveillance: screening diseases for suitability |
title_full_unstemmed | Using internet search queries for infectious disease surveillance: screening diseases for suitability |
title_short | Using internet search queries for infectious disease surveillance: screening diseases for suitability |
title_sort | using internet search queries for infectious disease surveillance: screening diseases for suitability |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4300155/ https://www.ncbi.nlm.nih.gov/pubmed/25551277 http://dx.doi.org/10.1186/s12879-014-0690-1 |
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