⭐️ Presented by the Center for the Advancement of Multicultural Perspectives on Science (DEI | OAD)

Jairo Fúquene Patiño

Assistant Professor, Statistics

Bayesian Methods to Estimate the Completeness of Death Registration

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 also generate reliable mortality indicators. In this work, we propose the use of Bayesian models to estimate the completeness of death registration at global, national and subnational levels. We propose suitable Markov chain Monte Carlo algorithms to measure the uncertainty of the predictive completeness at the different levels and study the theoretical properties of the Bayesian models. The use of our approach can allow institutions to improve the model parameter estimates and prediction of completeness of death registration. Our new models are based on a dataset updated based on 120 countries and 2,748 country-years. To illustrate the effectiveness of our proposal at national and subnational levels, we consider the completeness of death registration in a low-income country as our comparator dataset.

This talk is based on joint work with Tim Adair, Melbourne School of Population and Global Health, The University of Melbourne.

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