Using web search query data to monitor dengue epidemics: a new model for neglected tropical disease surveillance.
Background A variety of obstacles including bureaucracy and lack of resources have interfered with timely detection and reporting of dengue cases in many endemic countries. Surveillance efforts have turned to modern data sources, such as Internet search queries, which have been shown to be effective...
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ftdoajarticles:oai:doaj.org/article:74bc6afa9f864d98a92c65ce92718f9f 2023-05-15T15:15:58+02:00 Using web search query data to monitor dengue epidemics: a new model for neglected tropical disease surveillance. Emily H Chan Vikram Sahai Corrie Conrad John S Brownstein 2011-05-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0001206 https://doaj.org/article/74bc6afa9f864d98a92c65ce92718f9f EN eng Public Library of Science (PLoS) https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21647308/?tool=EBI https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0001206 https://doaj.org/article/74bc6afa9f864d98a92c65ce92718f9f PLoS Neglected Tropical Diseases, Vol 5, Iss 5, p e1206 (2011) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2011 ftdoajarticles https://doi.org/10.1371/journal.pntd.0001206 2022-12-31T05:45:34Z Background A variety of obstacles including bureaucracy and lack of resources have interfered with timely detection and reporting of dengue cases in many endemic countries. Surveillance efforts have turned to modern data sources, such as Internet search queries, which have been shown to be effective for monitoring influenza-like illnesses. However, few have evaluated the utility of web search query data for other diseases, especially those of high morbidity and mortality or where a vaccine may not exist. In this study, we aimed to assess whether web search queries are a viable data source for the early detection and monitoring of dengue epidemics. Methodology/principal findings Bolivia, Brazil, India, Indonesia and Singapore were chosen for analysis based on available data and adequate search volume. For each country, a univariate linear model was then built by fitting a time series of the fraction of Google search query volume for specific dengue-related queries from that country against a time series of official dengue case counts for a time-frame within 2003-2010. The specific combination of queries used was chosen to maximize model fit. Spurious spikes in the data were also removed prior to model fitting. The final models, fit using a training subset of the data, were cross-validated against both the overall dataset and a holdout subset of the data. All models were found to fit the data quite well, with validation correlations ranging from 0.82 to 0.99. Conclusions/significance Web search query data were found to be capable of tracking dengue activity in Bolivia, Brazil, India, Indonesia and Singapore. Whereas traditional dengue data from official sources are often not available until after some substantial delay, web search query data are available in near real-time. These data represent valuable complement to assist with traditional dengue surveillance. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLoS Neglected Tropical Diseases 5 5 e1206 |
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Directory of Open Access Journals: DOAJ Articles |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Emily H Chan Vikram Sahai Corrie Conrad John S Brownstein Using web search query data to monitor dengue epidemics: a new model for neglected tropical disease surveillance. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
Background A variety of obstacles including bureaucracy and lack of resources have interfered with timely detection and reporting of dengue cases in many endemic countries. Surveillance efforts have turned to modern data sources, such as Internet search queries, which have been shown to be effective for monitoring influenza-like illnesses. However, few have evaluated the utility of web search query data for other diseases, especially those of high morbidity and mortality or where a vaccine may not exist. In this study, we aimed to assess whether web search queries are a viable data source for the early detection and monitoring of dengue epidemics. Methodology/principal findings Bolivia, Brazil, India, Indonesia and Singapore were chosen for analysis based on available data and adequate search volume. For each country, a univariate linear model was then built by fitting a time series of the fraction of Google search query volume for specific dengue-related queries from that country against a time series of official dengue case counts for a time-frame within 2003-2010. The specific combination of queries used was chosen to maximize model fit. Spurious spikes in the data were also removed prior to model fitting. The final models, fit using a training subset of the data, were cross-validated against both the overall dataset and a holdout subset of the data. All models were found to fit the data quite well, with validation correlations ranging from 0.82 to 0.99. Conclusions/significance Web search query data were found to be capable of tracking dengue activity in Bolivia, Brazil, India, Indonesia and Singapore. Whereas traditional dengue data from official sources are often not available until after some substantial delay, web search query data are available in near real-time. These data represent valuable complement to assist with traditional dengue surveillance. |
format |
Article in Journal/Newspaper |
author |
Emily H Chan Vikram Sahai Corrie Conrad John S Brownstein |
author_facet |
Emily H Chan Vikram Sahai Corrie Conrad John S Brownstein |
author_sort |
Emily H Chan |
title |
Using web search query data to monitor dengue epidemics: a new model for neglected tropical disease surveillance. |
title_short |
Using web search query data to monitor dengue epidemics: a new model for neglected tropical disease surveillance. |
title_full |
Using web search query data to monitor dengue epidemics: a new model for neglected tropical disease surveillance. |
title_fullStr |
Using web search query data to monitor dengue epidemics: a new model for neglected tropical disease surveillance. |
title_full_unstemmed |
Using web search query data to monitor dengue epidemics: a new model for neglected tropical disease surveillance. |
title_sort |
using web search query data to monitor dengue epidemics: a new model for neglected tropical disease surveillance. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2011 |
url |
https://doi.org/10.1371/journal.pntd.0001206 https://doaj.org/article/74bc6afa9f864d98a92c65ce92718f9f |
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Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 5, Iss 5, p e1206 (2011) |
op_relation |
https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21647308/?tool=EBI https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0001206 https://doaj.org/article/74bc6afa9f864d98a92c65ce92718f9f |
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https://doi.org/10.1371/journal.pntd.0001206 |
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