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Triggering Interventions for Flu: The ALERT Algorithm Nicholas G Reich Department of Biostatistics and Epidemiology University of Massachusetts - Amherst 10 Dec 2015 :: ISDS :: Denver, CO @reichlab http://reichlab.github.io

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Anecdote: triggering the ResPECT Study intervention period in 2012-2013

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The ResPECT Study Cluster-randomized clinical trial comparing N95 respirators vs. surgical masks at preventing respiratory infections in healthcare workers.

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How to decide when to start the ResPECT study each season? 12 week “active” study period, ideally covering the peak flu season

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0 20 40 60 80 100 120 ODEïFRQILrPHG)OX$FDVHV 200 300 ILrPHG)OX$FDVHV Johns Hopkins Hospital &KLOGUHQ·V+RVSLWDO&RORUDGR 0 20 40 60 80 100 120 ODEïFRQILrPHG)OX$FDVHV 0 100 200 300 ODEïFRQILrPHG)OX$FDVHV 2002 2003 2004 2005 2006 2007 2008 2009 2010 Johns Hopkins Hospital &KLOGUHQ·V+RVSLWDO&RORUDGR Data from one ResPECT site: Johns Hopkins

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Johns Hopkins Hospital lab-confirmed Influenza A cases

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the “ALERT threshold” based on past data, set to 3 cases

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week ending Nov 3 has 3 cases (we receive data on Nov 6)

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Recommended start date: Nov 19

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More generally: how to predict when flu season is starting? Literally, a $75,000 question, according to the CDC.

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Why predict the flu? • For clinical trials, to time interventions.
 • In hospitals, to 
 - start target screening for flu antiviral use,
 - limit patient visitation, 
 - increase mandatory PPE usage.
 • For public health agencies, to determine the best timing for seasonal risk communication. “Predictions that give rise to actionable items that would not otherwise occur are important.” - Jay Varma, NYC DOHMH

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The Above Local Elevated Respiratory illness Threshold Algorithm Reich et al, Clinical Infectious Diseases, 2015. http://tiny.cc/alertapp

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Data Results Choice of threshold 0 20 40 60 80 100 120 ODEïFRQILrPHG)OX$FDVHV 0 100 200 300 ODEïFRQILrPHG)OX$FDVHV 2002 2003 2004 2005 2006 2007 2008 2009 2010 Johns Hopkins Hospital &KLOGUHQ·V+RVSLWDO&RORUDGR How ALERT works

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Data Results Choice of threshold How ALERT works Median   dura*on Percent  of  cases  captured Peaks  captured Mean  weeks       <  threshold Mean  dura*on   difference Threshold median min max % %  +/-­‐  2   1 18 96.9 0 99.8 70 70 3.7 3.7 2 18 97.4 61.3 99.4 90 90 2.9 5.1 3 15.5 95.6 58 98.7 90 90 1.8 1.8 4 14.5 94 57.3 98.7 90 80 2 0.8 5 13 91.8 57.3 96.3 90 80 2.2 -­‐0.3 6 12.5 90.3 57.3 96.2 90 80 2.6 -­‐0.9 7 12 86.4 47.7 94.9 80 80 2.7 -­‐1.4 8 11 82.6 47.7 94.9 80 80 3 -­‐2.1 9 10.5 82.6 0 94.9 80 60 2.2 -­‐2.44 10 9 76.8 0 94.9 70 60 2.2 -­‐3.11

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Data Results Choice of threshold How ALERT works Median   dura*on Percent  of  cases  captured Peaks  captured Mean  weeks       <  threshold Mean  dura*on   difference Threshold median minimu m maximu m % %  +/-­‐  2   1 18 96.9 0 99.8 70 70 3.7 3.7 2 18 97.4 61.3 99.4 90 90 2.9 5.1 3 15.5 95.6 58 98.7 90 90 1.8 1.8 4 14.5 94 57.3 98.7 90 80 2 0.8 5 13 91.8 57.3 96.3 90 80 2.2 -­‐0.3 6 12.5 90.3 57.3 96.2 90 80 2.6 -­‐0.9 7 12 86.4 47.7 94.9 80 80 2.7 -­‐1.4 8 11 82.6 47.7 94.9 80 80 3 -­‐2.1 9 10.5 82.6 0 94.9 80 60 2.2 -­‐2.44 10 9 76.8 0 94.9 70 60 2.2 -­‐3.11

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Data Results Choice of threshold How ALERT works apply ALERT threshold to real-time data

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What ALERT is • Threshold-based algorithm for surveillance data to give early warning signal for epidemic onset. • Simple method with cross-validated performance assessment. • A free online tool for hospital epidemiologists and public health officials. • Open-source, “beta” software (R package).

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What ALERT is not • A statistical prediction model. (not yet…) • Generalizable for non-seasonal data. • A method for detecting outbreaks of emerging pathogens.

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– statistical proverb “The plural of anecdote is not data.”

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Region (CDC #) ResPECT Site ALERT Threshold start date/ season % of Flu A cases captured in 12 weeks Northeast (2) NYC VA 19 12/3/2012 94% 12/16/2013 76% 12/15/2014 90% Mid-Atlantic (3) JHU/DC VA 3 11/19/2012 91% 12/30/2013 90% 12/8/2014 95% Southwest (8) CHCO/DH 3 12/3/2012 87% 12/2/2013 93% 12/1/2014 97% South (6) Houston VA 5 11/11/2013 90% Data and Results

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The future of ALERT [statistics] 
 Incorporate non-parametric prediction model. [epidemiology] 
 Apply ALERT to other seasonal diseases. [software] 
 Continue development and support of web applet and open-source R package.

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Stephen A Lauer The ResPECT Study team Acknowledgments Alexandria C Brown Data collection teams/labs CHCO, NYC DOHMH, JHH, Houston

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Thanks! ! http://tiny.cc/alertapp