TY - JOUR
T1 - Estimating the measles effective reproduction number in Australia from routine notification data
AU - Chiew, May
AU - Gidding, Heather F.
AU - Dey, Aditi
AU - Wood, James
AU - Martin, Nicolee
AU - Davis, Stephanie
AU - McIntyre, Peter
PY - 2014/3
Y1 - 2014/3
N2 - Objective To estimate the measles effective reproduction number (R) in Australia by modelling routinely collected notification data. Methods R was estimated for 2009-2011 by means of three methods, using data from Australia's National Notifiable Disease Surveillance System. Method 1 estimated R as 1 - P, where P equals the proportion of cases that were imported, as determined from data on place of acquisition. The other methods estimated R by fitting a subcritical branching process that modelled the spread of an infection with a given R to the observed distributions of outbreak sizes (method 2) and generations of spread (method 3). Stata version 12 was used for method 2 and Matlab version R2012 was used for method 3. For all methods, calculation of 95% confidence intervals (CIs) was performed using a normal approximation based on estimated standard errors. Findings During 2009-2011, 367 notifiable measles cases occurred in Australia (mean annual rate: 5.5 cases per million population). Data were 100% complete for importation status but 77% complete for outbreak reference number. R was estimated as < 1 for all years and data types, with values of 0.65 (95% CI: 0.60-0.70) obtained by method 1, 0.64 (95% CI: 0.56-0.72) by method 2 and 0.47 (95% CI: 0.38-0.57) by method 3. Conclusion The fact that consistent estimates of R were obtained from all three methods enhances confidence in the validity of these methods for determining R.
AB - Objective To estimate the measles effective reproduction number (R) in Australia by modelling routinely collected notification data. Methods R was estimated for 2009-2011 by means of three methods, using data from Australia's National Notifiable Disease Surveillance System. Method 1 estimated R as 1 - P, where P equals the proportion of cases that were imported, as determined from data on place of acquisition. The other methods estimated R by fitting a subcritical branching process that modelled the spread of an infection with a given R to the observed distributions of outbreak sizes (method 2) and generations of spread (method 3). Stata version 12 was used for method 2 and Matlab version R2012 was used for method 3. For all methods, calculation of 95% confidence intervals (CIs) was performed using a normal approximation based on estimated standard errors. Findings During 2009-2011, 367 notifiable measles cases occurred in Australia (mean annual rate: 5.5 cases per million population). Data were 100% complete for importation status but 77% complete for outbreak reference number. R was estimated as < 1 for all years and data types, with values of 0.65 (95% CI: 0.60-0.70) obtained by method 1, 0.64 (95% CI: 0.56-0.72) by method 2 and 0.47 (95% CI: 0.38-0.57) by method 3. Conclusion The fact that consistent estimates of R were obtained from all three methods enhances confidence in the validity of these methods for determining R.
UR - http://www.scopus.com/inward/record.url?scp=84896839139&partnerID=8YFLogxK
U2 - 10.2471/BLT.13.125724
DO - 10.2471/BLT.13.125724
M3 - Article
SN - 0042-9686
VL - 92
SP - 171
EP - 177
JO - Bulletin of the World Health Organization
JF - Bulletin of the World Health Organization
IS - 3
ER -