Chiew May, Gidding Heather F, Dey Aditi, Wood James, Martin Nicolee, Davis Stephanie, McIntyre Peter
National Centre for Immunisation Research and Surveillance of Vaccine Preventable Diseases, The Children's Hospital Westmead, Sydney, Australia .
School of Public Health and Community Medicine, University of New South Wales, Samuels Bldg, Botany St, Randwick, Sydney 2052, Australia .
Bull World Health Organ. 2014 Mar 1;92(3):171-7. doi: 10.2471/BLT.13.125724. Epub 2013 Dec 9.
To estimate the measles effective reproduction number (R) in Australia by modelling routinely collected notification data.
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.
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.
The fact that consistent estimates of R were obtained from all three methods enhances confidence in the validity of these methods for determining R.
通过对常规收集的通报数据进行建模,估算澳大利亚麻疹的有效繁殖数(R)。
利用澳大利亚国家法定传染病监测系统的数据,通过三种方法对2009 - 2011年的R进行估算。方法1将R估算为1 - P,其中P等于根据感染地点数据确定的输入病例比例。其他方法通过将模拟给定R值感染传播的亚临界分支过程拟合到观察到的疫情规模分布(方法2)和传播代数(方法3)来估算R。方法2使用Stata 12版本,方法3使用Matlab R2012版本。对于所有方法,基于估计的标准误差,使用正态近似计算95%置信区间(CI)。
2009 - 2011年期间,澳大利亚共发生367例法定报告麻疹病例(年均发病率:每百万人口5.5例)。输入状态数据的完整性为100%,但疫情参考编号数据的完整性为77%。所有年份和数据类型的R估计值均<1,方法1得到的值为0.65(95% CI:0.60 - 0.70),方法2为0.64(95% CI:0.56 - 0.72),方法3为0.47(95% CI:0.38 - 0.57)。
从所有三种方法获得的R的一致估计值这一事实增强了对这些确定R的方法有效性的信心。