B1897
Title: Bayesian methods to estimate the completeness of death registration
Authors: Jairo Fuquene - UC Davis (United States) [presenting]
Abstract: Civil registration and vital statistics (CRVS) systems should be the primary source of mortality data for governments. Accurate and timely measurement of the completeness of death registration helps inform interventions to improve CRVS systems and generate reliable mortality indicators. The use of Bayesian models is proposed to estimate the completeness of death registration at global, national and subnational levels. Suitable Markov chain Monte Carlo algorithms are proposed to measure the uncertainty of the predictive completeness at the different levels and study the theoretical properties of the Bayesian models. The use of the approach can allow institutions to improve the model parameter estimates and prediction of completeness of death registration. The new models are based on a dataset updated based on 120 countries and 2,748 country-years. To illustrate the effectiveness of the proposal at national and subnational levels, the completeness of death registration is considered in a low-income country as the comparator dataset.
