The network survival method for estimating adult mortality: Evidence from a survey experiment in Rwanda

TL;DR

The paper introduces the network survival method, a new approach for estimating adult mortality rates in countries lacking vital registration, demonstrating its accuracy and efficiency through a Rwanda survey experiment.

Contribution

It develops a novel, unbiased, and consistent estimation method for adult mortality that requires smaller samples and no external data pooling.

Findings

Network survival estimates align with existing methods.

Method performs well with smaller samples.

Applicable in countries lacking vital registration systems.

Abstract

Adult death rates are a critical indicator of population health and wellbeing. 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 paper, we introduce the network survival method, a new approach for estimating adult death rates. We derive the precise conditions under which it produces estimates that are consistent and unbiased. 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 it can be used in countries where reliable estimates of adult death rates are sorely needed.