Victora Cesar G, Barros Aluisio J D, Malpica-Llanos Tanya, Walker Neff
BMC Public Health. 2013;13 Suppl 3(Suppl 3):S24. doi: 10.1186/1471-2458-13-S3-S24. Epub 2013 Sep 17.
Lives-saved estimates calculated by LiST include the implicit assumptions that there are no inequalities among different socioeconomic groups, and also that the likelihood of a mother or child receiving a given intervention is independent from the probability of receiving any other interventions. It is reasonable to assume that, as a consequence of these assumptions, LiST estimates may exaggerate the numbers of lives saved in a population, by ignoring the fact that coverage is likely to be lower and mortality higher among the poor than the rich, and also by failing to take into account that coverage with different interventions may be clustered at individual mothers and children--a phenomenon described as co-coverage. We used data from 127 DHS surveys to estimate how much these two assumptions may bias estimates produced by LiST, and conclude that under real-life conditions bias occurred in both directions, with LiST results either over or underestimating the more complex estimates. With few exceptions, bias tended to be small (less than 10% in either direction).
由LiST计算得出的挽救生命估计数包含一些隐含假设，即不同社会经济群体之间不存在不平等现象，而且母亲或儿童接受特定干预措施的可能性与接受任何其他干预措施的概率无关。由于这些假设，LiST估计数可能会夸大某一人群中挽救生命的数量，这是合理的，因为它忽略了穷人的覆盖率可能低于富人且死亡率高于富人这一事实，还没有考虑到不同干预措施的覆盖率可能集中在个别母亲和儿童身上——这种现象被称为共同覆盖率。我们使用了来自127项 DHS 调查的数据来估计这两个假设可能会使LiST产生的估计数出现多大偏差，并得出结论：在现实生活条件下，偏差出现在两个方向，LiST的结果要么高估要么低估了更复杂的估计数。除了少数例外情况，偏差往往较小（任何一个方向都小于10%）。
