Comparison: Flu prescription sales data from a retail pharmacy in the US with Google Flu trends and US ILINet (CDC) data as flu activity indicator.

The potential threat of bioterrorism along with the emergence of new or existing drug resistant strains of influenza virus, added to expanded global travel, have increased vulnerability to epidemics or pandemics and their aftermath. The same factors have also precipitated urgency for having better,...

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Autores principales:	Avinash Patwardhan, Robert Bilkovski
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/399f1ed1e18948e6a64660e41fecde01
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spelling	oai:doaj.org-article:399f1ed1e18948e6a64660e41fecde012021-11-18T07:07:04ZComparison: Flu prescription sales data from a retail pharmacy in the US with Google Flu trends and US ILINet (CDC) data as flu activity indicator.1932-620310.1371/journal.pone.0043611https://doaj.org/article/399f1ed1e18948e6a64660e41fecde012012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22952719/?tool=EBIhttps://doaj.org/toc/1932-6203The potential threat of bioterrorism along with the emergence of new or existing drug resistant strains of influenza virus, added to expanded global travel, have increased vulnerability to epidemics or pandemics and their aftermath. The same factors have also precipitated urgency for having better, faster, sensitive, and reliable syndromic surveillance systems. Prescription sales data can provide surrogate information about the development of infectious diseases and therefore serve as a useful tool in syndromic surveillance. This study compared prescription sales data from a large drug retailing pharmacy chain in the United States with Google Flu trends surveillance system data as a flu activity indicator. It was found that the two were highly correlated. The correlation coefficient (Pearson 'r') for five years' aggregate data (2007-2011) was 0.92 (95% CI, 0.90-0.94). The correlation coefficients for each of the five years between 2007 and 2011 were 0.85, 0.92, 0.91, 0.88, and 0.87 respectively. Additionally, prescription sales data from the same large drug retailing pharmacy chain in the United States were also compared with US Outpatient Influenza-like Illness Surveillance Network (ILINet) data for 2007 by Centers for Disease Control and Prevention (CDC). The correlation coefficient (Pearson 'r') was 0.97 (95% CI, 0.95-0.98).Avinash PatwardhanRobert BilkovskiPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 8, p e43611 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Avinash Patwardhan Robert Bilkovski Comparison: Flu prescription sales data from a retail pharmacy in the US with Google Flu trends and US ILINet (CDC) data as flu activity indicator.
description	The potential threat of bioterrorism along with the emergence of new or existing drug resistant strains of influenza virus, added to expanded global travel, have increased vulnerability to epidemics or pandemics and their aftermath. The same factors have also precipitated urgency for having better, faster, sensitive, and reliable syndromic surveillance systems. Prescription sales data can provide surrogate information about the development of infectious diseases and therefore serve as a useful tool in syndromic surveillance. This study compared prescription sales data from a large drug retailing pharmacy chain in the United States with Google Flu trends surveillance system data as a flu activity indicator. It was found that the two were highly correlated. The correlation coefficient (Pearson 'r') for five years' aggregate data (2007-2011) was 0.92 (95% CI, 0.90-0.94). The correlation coefficients for each of the five years between 2007 and 2011 were 0.85, 0.92, 0.91, 0.88, and 0.87 respectively. Additionally, prescription sales data from the same large drug retailing pharmacy chain in the United States were also compared with US Outpatient Influenza-like Illness Surveillance Network (ILINet) data for 2007 by Centers for Disease Control and Prevention (CDC). The correlation coefficient (Pearson 'r') was 0.97 (95% CI, 0.95-0.98).
format	article
author	Avinash Patwardhan Robert Bilkovski
author_facet	Avinash Patwardhan Robert Bilkovski
author_sort	Avinash Patwardhan
title	Comparison: Flu prescription sales data from a retail pharmacy in the US with Google Flu trends and US ILINet (CDC) data as flu activity indicator.
title_short	Comparison: Flu prescription sales data from a retail pharmacy in the US with Google Flu trends and US ILINet (CDC) data as flu activity indicator.
title_full	Comparison: Flu prescription sales data from a retail pharmacy in the US with Google Flu trends and US ILINet (CDC) data as flu activity indicator.
title_fullStr	Comparison: Flu prescription sales data from a retail pharmacy in the US with Google Flu trends and US ILINet (CDC) data as flu activity indicator.
title_full_unstemmed	Comparison: Flu prescription sales data from a retail pharmacy in the US with Google Flu trends and US ILINet (CDC) data as flu activity indicator.
title_sort	comparison: flu prescription sales data from a retail pharmacy in the us with google flu trends and us ilinet (cdc) data as flu activity indicator.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/399f1ed1e18948e6a64660e41fecde01
work_keys_str_mv	AT avinashpatwardhan comparisonfluprescriptionsalesdatafromaretailpharmacyintheuswithgoogleflutrendsandusilinetcdcdataasfluactivityindicator AT robertbilkovski comparisonfluprescriptionsalesdatafromaretailpharmacyintheuswithgoogleflutrendsandusilinetcdcdataasfluactivityindicator
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Comparison: Flu prescription sales data from a retail pharmacy in the US with Google Flu trends and US ILINet (CDC) data as flu activity indicator.

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