Feehan Dennis M, Mahy Mary, Salganik Matthew J
Department of Demography, University of California, Berkeley, Berkeley, CA, USA.
Joint United Nations Programme on HIV/AIDS (UNAIDS), Geneva, Switzerland.
Demography. 2017 Aug;54(4):1503-1528. doi: 10.1007/s13524-017-0594-y.
Adult death rates are a critical indicator of population health and well-being. Wealthy countries have high-quality vital registration systems, but poor countries lack this infrastructure and must rely on estimates that are often problematic. In this article, we introduce the network survival method, a new approach for estimating adult death rates. We derive the precise conditions under which it produces consistent and unbiased estimates. Further, we develop an analytical framework for sensitivity analysis. To assess the performance of the network survival method in a realistic setting, we conducted a nationally representative survey experiment in Rwanda (n = 4,669). Network survival estimates were similar to estimates from other methods, even though the network survival estimates were made with substantially smaller samples and are based entirely on data from Rwanda, with no need for model life tables or pooling of data from other countries. Our analytic results demonstrate that the network survival method has attractive properties, and our empirical results show that this method can be used in countries where reliable estimates of adult death rates are sorely needed.
成人死亡率是衡量人口健康和福祉的关键指标。富裕国家拥有高质量的人口动态登记系统，但贫穷国家缺乏这种基础设施，必须依赖往往存在问题的估计数据。在本文中，我们介绍了网络生存法，这是一种估计成人死亡率的新方法。我们推导出了该方法产生一致且无偏估计的精确条件。此外，我们还开发了一个用于敏感性分析的分析框架。为了在现实环境中评估网络生存法的性能，我们在卢旺达进行了一项具有全国代表性的调查实验（n = 4669）。网络生存估计值与其他方法的估计值相似，尽管网络生存估计是基于小得多的样本得出的，并且完全基于卢旺达的数据，无需模型生命表或汇集其他国家的数据。我们的分析结果表明，网络生存法具有吸引人的特性，我们的实证结果表明，这种方法可用于急需可靠成人死亡率估计值的国家。
