Incorporation of hierarchical structure into estimation and projection package fitting with examples of estimating subnational HIV/AIDS dynamics

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Abstract

Objectives:

The article aims to give Spectrum/estimation and projection package (EPP) users and the scientific community a basic understanding of the underlying statistical model used to incorporate hierarchical structure in HIV subnational estimation, and to show how it has been implemented in the Spectrum/EPP interface for improving subepidemic estimation. The article also provides recommended default settings for this new model.

Methods:

We apply a generalized linear mixed-effects model on antenatal clinics prevalence data to get area-specific prevalence and uncertainty estimates, and transform those estimates to auxiliary data. We then fit the EPP model to both the observed data and auxiliary data.

Results:

We apply the proposed methods to four countries with different levels of data availability. We compare the out-of-sample prediction accuracy of the proposed method with varying auxiliary sample sizes and EPP without auxiliary data.

Conclusion:

We find that borrowing information from data-rich areas to data-sparse areas using our proposed method improves EPP fit in data-sparse areas. We recommend using the sample size estimated from generalized linear mixed-effects model as the default auxiliary sample size.

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