Katz J, Yoon S S, Brendel K, West K P
Department of International Health, Johns Hopkins School of Hygiene and Public Health, Baltimore, MD 21205-2103, USA.
Int J Epidemiol. 1997 Oct;26(5):1041-8. doi: 10.1093/ije/26.5.1041.
The purpose of this study was to estimate the bias and design effects associated with the Expanded Program on Immunization's (EPI) sampling design when estimating xerophthalmia prevalence, and to estimate the savings associated with EPI in terms of distance travelled within selected clusters.
Computer simulation of the EPI sampling strategy was done using maps from a xerophthalmia survey of 40 wards in Sarlahi district, Nepal. Samples of fixed cluster sizes of 7, 10, 15, 20 and 25 were compared. The estimated prevalence using the EPI design was compared with the true prevalence in the 40 wards to estimate the bias. The design effect was estimated by taking the ratio of the variance under EPI sampling to that of stratified random sampling (SRS) with fixed cluster sizes. The EPI was also modified by increasing the distance between selected houses from nearest neighbour to skipping 1-4 houses between selected ones. The difference between the distance travelled within clusters using SRS compared with EPI was weighed against the bias and increased variance.
The prevalence of xerophthalmia was 2.8%. The EPI design overestimated xerophthalmia prevalence by between 0.27% and 1.16%. The design effects of EPI cluster sampling within wards varied between 0.73 and 1.35. Neither the bias nor the design effect was related to distance between households or cluster size. Distance travelled within wards was always less for EPI designs with cluster sizes of 7 or 10. There was no saving in terms of distance travelled for designs with cluster sizes from 15 to 25 if there were two or more houses between selected ones. For fixed cluster sizes of 15 or fewer, the EPI sampling design using nearest or next nearest neighbours is a better choice than SRS in terms of minimizing the distance travelled and the mean square error.
The choice of an optimum method would need to account for the density of clusters and difficulty of travel between clusters, as well as the costs of travel within clusters. Based on certain assumptions, EPI with 15 children per cluster would be favoured over examining all children in selected wards unless the travel time between wards was more than 2 days.
本研究的目的是在估计干眼病患病率时，评估与扩大免疫规划（EPI）抽样设计相关的偏差和设计效应，并估算在选定群组内EPI在行程距离方面的节省情况。
利用尼泊尔萨拉希县40个行政区干眼病调查的地图，对EPI抽样策略进行计算机模拟。比较了固定群组大小为7、10、15、20和25的样本。将使用EPI设计估计的患病率与40个行政区的真实患病率进行比较，以评估偏差。通过计算EPI抽样方差与固定群组大小的分层随机抽样（SRS）方差之比来估计设计效应。还对EPI进行了修改，将选定房屋之间的距离从最近邻增加到跳过1至4间房屋。将使用SRS与EPI在群组内行程距离的差异与偏差和方差增加进行权衡。
干眼病患病率为2.8%。EPI设计将干眼病患病率高估了0.27%至1.16%。行政区内EPI群组抽样的设计效应在0.73至1.35之间。偏差和设计效应均与家庭间距离或群组大小无关。对于群组大小为7或10的EPI设计，行政区内的行程距离总是较短。如果选定房屋之间有两间或更多房屋，则对于群组大小为15至25的设计，在行程距离方面没有节省。对于固定群组大小为15或更少的情况，就最小化行程距离和均方误差而言，使用最近邻或次近邻的EPI抽样设计比SRS更好。
选择最佳方法需要考虑群组密度、群组间出行难度以及群组内出行成本。基于某些假设，除非行政区之间的出行时间超过2天，否则每群组15名儿童的EPI比检查选定行政区内的所有儿童更可取。
