Improving program targeting to combat early-life mortality by identifying high-risk births: an application to India.

ABSTRACT:

Background

It is widely recognized that there are multiple risk factors for early-life mortality. In practice most interventions to curb early-life mortality target births based on a single risk factor, such as poverty. However, most premature deaths are not from the targeted group. Thus interventions target many births that are at not at high risk and miss many births at high risk.

Methods

Using data from the second wave of Demographic and Health Surveys from India and a hierarchical Bayesian model, we estimate infant mortality risk for 73.320 infants in India as a function of 4 risk factors. We show how this information can be used to improve program targeting. We compare our novel approach against common programs that target groups based on a single risk factor.

Result

SUBMITTER: Ramos AP 

PROVIDER: S-EPMC6108144 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature