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Title: Novel use of flu surveillance data: Evaluating potential of sentinel populations for early detection of influenza outbreaks

Abstract

Influenza causes significant morbidity and mortality each year, with 2–8% of weekly outpatient visits around the United States for influenza-like-illness (ILI) during the peak of the season. Effective use of existing flu surveillance data allows officials to understand and predict current flu outbreaks and can contribute to reductions in influenza morbidity and mortality. Previous work used the 2009–2010 influenza season to investigate the possibility of using existing military and civilian surveillance systems to improve early detection of flu outbreaks. Results suggested that civilian surveillance could help predict outbreak trajectory in local military installations. To further test that hypothesis, we compare pairs of civilian and military outbreaks in seven locations between 2000 and 2013. We find no predictive relationship between outbreak peaks or time series of paired outbreaks. This larger study does not find evidence to support the hypothesis that civilian data can be used as sentinel surveillance for military installations. We additionally investigate the effect of modifying the ILI case definition between the standard Department of Defense definition, a more specific definition proposed in literature, and confirmed Influenza A. We find that case definition heavily impacts results. In conclusion, this study thus highlights the importance of careful selection of casemore » definition, and appropriate consideration of case definition in the interpretation of results.« less

Authors:
ORCiD logo [1];  [1];  [1];  [1];  [1];  [2]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Monash Univ., Melbourne, VIC (Australia)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
Defense Threat Reduction Agency (DTRA); USDOE
OSTI Identifier:
1321779
Report Number(s):
LA-UR-16-22898
Journal ID: ISSN 1932-6203
Grant/Contract Number:
AC52-06NA25396
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
PLoS ONE
Additional Journal Information:
Journal Volume: 11; Journal Issue: 7; Journal ID: ISSN 1932-6203
Publisher:
Public Library of Science
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; Biological Science

Citation Formats

Daughton, Ashlynn R., Velappan, Nileena, Abeyta, Esteban, Priedhorsky, Reid, Deshpande, Alina, and Turner, Stephen J.. Novel use of flu surveillance data: Evaluating potential of sentinel populations for early detection of influenza outbreaks. United States: N. p., 2016. Web. doi:10.1371/journal.pone.0158330.
Daughton, Ashlynn R., Velappan, Nileena, Abeyta, Esteban, Priedhorsky, Reid, Deshpande, Alina, & Turner, Stephen J.. Novel use of flu surveillance data: Evaluating potential of sentinel populations for early detection of influenza outbreaks. United States. doi:10.1371/journal.pone.0158330.
Daughton, Ashlynn R., Velappan, Nileena, Abeyta, Esteban, Priedhorsky, Reid, Deshpande, Alina, and Turner, Stephen J.. 2016. "Novel use of flu surveillance data: Evaluating potential of sentinel populations for early detection of influenza outbreaks". United States. doi:10.1371/journal.pone.0158330. https://www.osti.gov/servlets/purl/1321779.
@article{osti_1321779,
title = {Novel use of flu surveillance data: Evaluating potential of sentinel populations for early detection of influenza outbreaks},
author = {Daughton, Ashlynn R. and Velappan, Nileena and Abeyta, Esteban and Priedhorsky, Reid and Deshpande, Alina and Turner, Stephen J.},
abstractNote = {Influenza causes significant morbidity and mortality each year, with 2–8% of weekly outpatient visits around the United States for influenza-like-illness (ILI) during the peak of the season. Effective use of existing flu surveillance data allows officials to understand and predict current flu outbreaks and can contribute to reductions in influenza morbidity and mortality. Previous work used the 2009–2010 influenza season to investigate the possibility of using existing military and civilian surveillance systems to improve early detection of flu outbreaks. Results suggested that civilian surveillance could help predict outbreak trajectory in local military installations. To further test that hypothesis, we compare pairs of civilian and military outbreaks in seven locations between 2000 and 2013. We find no predictive relationship between outbreak peaks or time series of paired outbreaks. This larger study does not find evidence to support the hypothesis that civilian data can be used as sentinel surveillance for military installations. We additionally investigate the effect of modifying the ILI case definition between the standard Department of Defense definition, a more specific definition proposed in literature, and confirmed Influenza A. We find that case definition heavily impacts results. In conclusion, this study thus highlights the importance of careful selection of case definition, and appropriate consideration of case definition in the interpretation of results.},
doi = {10.1371/journal.pone.0158330},
journal = {PLoS ONE},
number = 7,
volume = 11,
place = {United States},
year = 2016,
month = 7
}

Journal Article:
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