title: Natural attack rate of influenza in unvaccinated children and adults: a meta-regression analysis.
abstract: BACKGROUND
  The natural (i.e. unvaccinated population) attack rate of an infectious disease is an important parameter required for understanding disease transmission. As such, it is an input parameter in infectious disease mathematical models. Influenza is an infectious disease that poses a major health concern worldwide and the natural attack rate of this disease is crucial in determining the effectiveness and cost-effectiveness of public health interventions and informing surveillance program design. We estimated age-stratified, strain-specific natural attack rates of laboratory-confirmed influenza in unvaccinated individuals.
  
  
  METHODS
  Utilizing an existing systematic review, we calculated the attack rates in the trial placebo arms using a random effects model and a meta-regression analysis (GSK study identifier: 117102).
  
  
  RESULTS
  This post-hoc analysis included 34 RCTs (Randomized Control Trials) contributing to 47 influenza seasons from 1970 to 2009. Meta-regression analyses showed that age and type of influenza were important covariates. The attack rates (95% CI (Confidence Interval)) in adults for all influenza, type A and type B were 3.50% (2.30%, 4.60%), 2.32% (1.47%, 3.17%) and 0.59% (0.28%, 0.91%) respectively. For children, they were 15.20% (11.40%, 18.90%), 12.27% (8.56%, 15.97%) and 5.50% (3.49%, 7.51%) respectively.
  
  
  CONCLUSIONS
  This analysis demonstrated that unvaccinated children have considerably higher exposure risk than adults and influenza A can cause more disease than influenza B. Moreover, a higher ratio of influenza B:A in children than adults was observed. This study provides a new, stratified and up to-date natural attack rates that can be used in influenza infectious disease models and are consistent with previous published work in the field.
authors.affiliation: GSK Inc, 7333 Mississauga Road North, Mississauga, ON, L5N 6L4, Canada. kavisha.s.jayasundara@gsk.com.
authors.forename: Kavisha
authors.initials: K
authors.lastname: Jayasundara
authors.affiliation: Li Ka Shing Knowledge Institute of St. Michael's Hospital, 30 Bond Street, Toronto, ON, M5B 1W8, Canada. SoobiahC@smh.ca.
authors.forename: Charlene
authors.initials: C
authors.lastname: Soobiah
authors.affiliation: GSK Inc, 7333 Mississauga Road North, Mississauga, ON, L5N 6L4, Canada. edward.w.thommes@gsk.com.|Department of Mathematics & Statistics, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada. edward.w.thommes@gsk.com.
authors.forename: Edward
authors.initials: E
authors.lastname: Thommes
authors.affiliation: Li Ka Shing Knowledge Institute of St. Michael's Hospital, 30 Bond Street, Toronto, ON, M5B 1W8, Canada. TriccoA@smh.ca.|Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, 155 College St, Toronto, ON, M5T 3M7, Canada. TriccoA@smh.ca.
authors.forename: Andrea C
authors.initials: AC
authors.lastname: Tricco
authors.affiliation: GSK Inc, 7333 Mississauga Road North, Mississauga, ON, L5N 6L4, Canada. aymanchit@gmail.com.|Present address: Sanofi Pasteur, 1755 Steeles Avenue West, Toronto, ON, M2R 3T4, Canada. aymanchit@gmail.com.
authors.forename: Ayman
authors.initials: A
authors.lastname: Chit
mesh_terms: D000328:Adult; D000367:Age Factors; D002648:Child; D003362:Cost-Benefit Analysis; D005260:Female; D006801:Humans; D015994:Incidence; D009980:Influenza A virus; D009981:Influenza B virus; D007251:Influenza, Human / Q000453:epidemiology* / Q000821:virology; D008297:Male; D012044:Regression Analysis; D012307:Risk Factors; D012621:Seasons