title: Understanding estimated worker absenteeism rates during an influenza pandemic.
abstract: OBJECTIVE
  Published employee absenteeism estimates during an influenza pandemic range from 10 to 40 percent. The purpose of this study was to estimate daily employee absenteeism through the duration of an influenza pandemic and to determine the relative impact of key variables used to derive the estimates.
  
  
  METHODS
  Using the Centers for Disease Control and Prevention's FluWorkLoss program, the authors estimated the number of absent employees on any given day over the course of a simulated 8-week pandemic wave by using varying attack rates. Employee data from a university with a large academic health system were used. Sensitivity of the program outputs to variation in predictor (inputs) values was assessed. Finally, the authors examined and documented the algorithmic sequence of the program.
  
  
  RESULTS
  Using a 35 percent attack rate, a total of 47,270 workdays (or 3.4 percent of all available workdays) would be lost over the course of an 8-week pandemic among a population of 35,026 employees. The highest (peak) daily absenteeism estimate was 5.8 percent (minimum 4.8 percent; maximum 7.4 percent). Sensitivity analysis revealed that varying days missed for nonhospitalized illness had the greatest potential effect on peak absence rate (3.1 to 17.2 percent). Peak absence with 15 and 25 percent attack rates were 2.5 percent and 4.2 percent, respectively.
  
  
  CONCLUSIONS
  The impact of an influenza pandemic on employee availability may be less than originally thought, even with a high attack rate. These data are generalizable and are not specific to institutions of higher education or medical centers. Thus, these findings provide realistic and useful estimates for influenza pandemic planning for most organizations.
authors.affiliation: Department of Emergency Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
authors.forename: Meridith H
authors.initials: MH
authors.lastname: Thanner
authors.forename: Jonathan M
authors.initials: JM
authors.lastname: Links
authors.forename: Martin I
authors.initials: MI
authors.lastname: Meltzer
authors.forename: James J
authors.initials: JJ
authors.lastname: Scheulen
authors.forename: Gabor D
authors.initials: GD
authors.lastname: Kelen
mesh_terms: D000041:Absenteeism; D015142:Baltimore / Q000453:epidemiology; D002487:Centers for Disease Control and Prevention, U.S.; D004651:Employment / Q000191:economics; D005260:Female; D006801:Humans; D007251:Influenza, Human / Q000191:economics / Q000453:epidemiology*; D008297:Male; D015233:Models, Statistical; D058873:Pandemics / Q000191:economics; D010564:Personnel, Hospital; D014481:United States / Q000453:epidemiology; D014495:Universities