Prospective Scenarios on Coverage of Deaths in Brazil

Chapter
Part of the The Springer Series on Demographic Methods and Population Analysis book series (PSDE, volume 46)

Abstract

Vital statistics reflect the health status of a population, which are widely used in the formulation of important demographic indicators. The evolution of vital records in Brazil is marked by political factors and administrative instabilities that have compromised its quality and utility. Due to this commitment, the two main sources of vital records, the Brazilian Institute of Geography and Statistics and the Ministry of Health, do not capture all of these records, mainly in less developed regions such as the Northeast of Brazil with a population of 57 million inhabitants in 2016. Although there have been gradual advances in coverage of deaths in Brazil, the Northeast region has not yet reached full coverage of deaths (100%). Among the nine states that compose this region, coverage of deaths in 2011 ranged from 79% to 94%. In order to estimate the year in which the states of the Northeast will reach the full coverage of death records projections were performed on coverage of deaths for each state. The annual series of death coverage estimated by the Ministry of Health from 1991 to 2011 were used. The projections were made through the mathematical methods of projections: Logistic, Gompertz and Holt’s Exponential Smoothing Model. The Holt’s model, in general, was the best fit to the pattern of the series of coverage of deaths. The states were classified in three intervals of years when they reached 100% of coverage, which varied from 2019 to 2028. It is estimated that for the Northeast the full coverage of deaths will be reached during 2021–2025. It is expected that these scenarios can contribute to the planning strategies and to the evaluation of managers regarding the actions and policies to be implemented on the performance of death statistics in the Northeast and Brazil.

Keywords

Vital statistics Mortality Death coverage Projections Brazil 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Postgraduate Program in Decision Modelling and HealthFederal University of ParaíbaJoão PessoaBrazil
  2. 2.Postgraduate Program in Mathematical and Computational ModellingFederal University of ParaíbaJoão PessoaBrazil

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