scholarly journals Influenza-like illness-related emergency department visits: Christmas and New Year holiday peaks and relationships with laboratory-confirmed respiratory virus detections, Edmonton, Alberta, 2004-2014

2016 ◽  
Vol 11 (1) ◽  
pp. 33-40 ◽  
Author(s):  
Leah J. Martin ◽  
Cindy Im ◽  
Huiru Dong ◽  
Bonita E. Lee ◽  
James Talbot ◽  
...  
PEDIATRICS ◽  
2006 ◽  
Vol 118 (1) ◽  
pp. e1-e8 ◽  
Author(s):  
F. T. Bourgeois ◽  
C. Valim ◽  
J. C. Wei ◽  
A. J. McAdam ◽  
K. D. Mandl

2020 ◽  
Vol 39 (8) ◽  
pp. e176-e182
Author(s):  
Namrata Prasad ◽  
Adrian A. Trenholme ◽  
Q. Sue Huang ◽  
Jazmin Duque ◽  
Cameron C. Grant ◽  
...  

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
Jennifer Nguyen ◽  
Wan Yang ◽  
Kazuhiko Ito ◽  
Thomas Matte ◽  
Jeffrey L Shaman ◽  
...  

Introduction: In temperate regions, cardiovascular deaths and influenza epidemics peak with regularity during the winter months. Hypothesis: We assessed the hypothesis that population increases in seasonal influenza infections are associated with a rise in mortality due to cardiovascular causes, and that influenza incidence can be used to predict cardiovascular mortality rates during the influenza season. Methods: We used time series regression models, adjusted for season and time trend, to quantify the temporal association between influenza incidence and cardiovascular mortality during the influenza season in New York City. Mortality data on date of death, age, and underlying cause of death were obtained from the New York City Office of Vital Statistics. Daily mortality counts from 2006 to 2012 were aggregated for all cardiovascular causes (International Classification of Diseases, Revision 10 (ICD-10) codes I00-I99), ischemic heart disease (ICD-10 codes I20-I25), and myocardial infarction (ICD-10 code I21). Influenza incidence was represented using four different measures: emergency department visits for influenza-like illness, grouped by age ≥ 0 and age ≥ 65 years, and these same measures scaled by laboratory surveillance data for viral types/sub-types. The 2009 H1N1 pandemic period was excluded from temporal analyses and reserved for out-of-sample prediction. Results: There were 73,384 cardiovascular deaths among adults age ≥ 65 years during the influenza seasons between 2006 and 2012, excluding the 2009 H1N1 pandemic period. Interquartile range increases of the four indicators of influenza incidence in the previous 21 days were associated with increases in cardiovascular mortality of between 2.3% (95% confidence interval (CI): 0.7%, 3.9%) and 6.3% (95% CI: 3.6%, 8.9%), and increases in ischemic heart disease mortality of between 2.4% (95% CI: 1.1%, 3.7%) and 7.0% (95% CI: 4.1%, 10.0%). Associations were most acute and strongest for myocardial infarction mortality, with interquartile range increases for the four influenza indicators during the previous 14 days associated with mortality increases between 5.9% (95% CI: 2.7%, 9.2%) and 12.8% (95% CI: 5.1%, 20.6%). Out-of-sample prediction of cardiovascular mortality among adults age ≥ 65 years during the 2009-2010 influenza season yielded average estimates with 94.4% accuracy. Conclusions: Emergency department visits for influenza-like illness are associated with and predictive of cardiovascular disease mortality in New York City. Retrospective estimation of influenza-attributable cardiovascular mortality burden, combined with accurate and reliable influenza forecasts, could predict the timing and burden of seasonal increases in cardiovascular mortality.


2012 ◽  
Vol 19 (6) ◽  
pp. 1075-1081 ◽  
Author(s):  
Taha A Kass-Hout ◽  
Zhiheng Xu ◽  
Paul McMurray ◽  
Soyoun Park ◽  
David L Buckeridge ◽  
...  

2019 ◽  
Vol 147 ◽  
Author(s):  
L. J. Martin ◽  
H. Dong ◽  
Q. Liu ◽  
J. Talbot ◽  
W. Qiu ◽  
...  

Abstract Predicting the magnitude of the annual seasonal peak in influenza-like illness (ILI)-related emergency department (ED) visit volumes can inform the decision to open influenza care clinics (ICCs), which can mitigate pressure at the ED. Using ILI-related ED visit data from the Alberta Real Time Syndromic Surveillance Net for Edmonton, Alberta, Canada, we developed (training data, 1 August 2004–31 July 2008) and tested (testing data, 1 August 2008–19 February 2014) spatio-temporal statistical prediction models of daily ILI-related ED visits to estimate high visit volumes 3 days in advance. Our Main Model, based on a generalised linear mixed model with random intercept, incorporated prediction residuals over 14 days and captured increases in observed volume ahead of peaks. During seasonal influenza periods, our Main Model predicted volumes within ±30% of observed volumes for 67%–82% of high-volume days and within 0.3%–21% of observed seasonal peak volumes. Model predictions were not as successful during the 2009 H1N1 pandemic. Our model can provide early warning of increases in ILI-related ED visit volumes during seasonal influenza periods of differing intensities. These predictions may be used to support public health decisions, such as if and when to open ICCs, during seasonal influenza epidemics.


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