Age reporting in the Brazilian COVID-19 vaccination database: What can we learn from it?

  1. Cássio M Turra
  2. Fernando Fernandes
  3. Julia Calazans
  4. Marília R. Nepomuceno

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Age is a key variable for sciences and public planning. The demographic consequences of not measuring age correctly are manifold, including errors in mortality rates and population estimates, particularly at older ages. It also affects public programs because target populations depend on reliable population age distributions. In Brazil, the start of the vaccination campaign against COVID-19 marked the collection of new administrative data. Every citizen must be registered and need to show an identity document to get vaccinated. The requirement of proof-of-age documentation provides a unique opportunity for measuring the elderly population using a different database. This article examines the reliability of age distributions of men and women 80 years and older. We calculate various demographic indicators using data from the vaccination registration system and compare them to those from the target population estimates of the National Vaccination Plan, censuses, and population projections for Brazil and countries with high-quality population data. We show that requiring proof-of-age, such as in the vaccination records, increases data quality, mainly through the reduction of age heaping and age exaggeration. However, I.D. cards cannot fully solve wrong birth dates that result from weak historical registration systems. Thus, one should be careful when using estimates of the old age population living in some of the Brazilian regions, particularly the North, Northeast, and Center-West. Also, our analysis reveals a mismatch between the projected population by age, sex, and region, which guided the vaccination plan, and the number of vaccinated at ages 80 and older. The methodology developed to adjust the mortality rates used in the demographic projections is probably the main factor behind the disparities found.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2021.06.27.21259575: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableOur final database consisted of 4,375,174 individuals 80 years and older, 2,711,186 females, and 1,663,988 males.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    However, our analysis is not free of limitations. As with any database, vaccination records may contain both content and coverage errors. Concerning the potential coverage errors, some individuals ages 80 and older may have refused to vaccinate. Yet, we expect older individuals to be more prone to vaccinate because of the higher mortality risk associated with COVID-19. Also, it is unclear to what extent functional limitations and other chronic conditions have hindered some of the 80+ individuals from getting vaccinated. The consolidation of the Brazilian public health system (universal, integral, and decentralized) that resulted in expanding healthcare services and success in earlier vaccination campaigns makes us confident about the high coverage of vaccination records at older ages.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2021.06.27.21259575v1 on medRxiv