Use of excess mortality associated with the COVID-19 epidemic as an epidemiological surveillance strategy - preliminary results of the evaluation of six Brazilian capitals

  1. André Ricardo Ribas Freitas
  2. Nicole Montenegro de Medeiros
  3. Livia Carla Vinhal Frutuoso
  4. Otto Albuquerque Beckedorff
  5. Lucas Mariscal Alves de Martin
  6. Marcela Montenegro de Medeiros Coelho
  7. Giovanna Gimenez Souza de Freitas
  8. Daniele Rocha Queiróz Lemos
  9. Luciano Pamplona de Góes Cavalcanti

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

In early 2020, the World Health Organization (WHO) recognized the pandemic situation of the new coronavirus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2), which causes Coronavirus Disease-2019 (COVID-19). In Brazil by the end of April 2020, another 110 thousand cases and 5,000 deaths had been confirmed. The scarcity of laboratory resources and overload of the care network, added to the broad clinical spectrum of the disease, can make it difficult to capture all mortality from this disease through epidemiological surveillance based on individual notification of cases. The aim of this study was to evaluate the excess of deaths in Brazilian capitals with the highest incidence of COVID-19, as a way of validating the method, we also evaluated a capital with low incidence.

We assessed weekly mortality from all causes during the year 2020, up to the epidemiological week 17, compared with the previous year. The data were obtained through the National Civil Registry Information Center (CNIRC, acronym in Portuguese). We estimate the expected mortality and the 95% confidence interval by projecting the observed mortality in 2019 for the population of 2020.

In the five capitals with the highest incidences it was possible to identify excess deaths in the pandemic period, the age group most affected were those over 60 years old, 31% of the excess deaths occurred in the population between 20 and 59 years old. There was a strong correlation (r = 0.94) between the excess of deaths in each city and the number of deaths confirmed by epidemiological surveillance. There was no excess of deaths in the capital with the lowest incidence, nor among the population under 20 years old. We estimate that epidemiological surveillance managed to capture only 52% of all mortality associated with the COVID-19 pandemic in the cities studied.

Considering the simplicity of the method, its low cost and reliability for assessing the real burden of the disease, we believe that the assessment of excess mortality associated with the COVID-19 pandemic should be widely used as a complementary tool to regular epidemiological surveillance and its use should be encouraged by WHO.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.05.08.20093617: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Demographic data were collected on the Brazilian Institute of Geography and Statistics (IBGE, acronym in Portuguese) website, which estimates the population of Brazilian capitals by age group on a quarterly basis through the Continuous National Household Sample Survey (PNADc, acronym in Portuguese)[12].
    Portuguese
    suggested: None

    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:
    The present study has some limitations, many of which are a consequence of the fact that the assessment is made at the moment when the epidemic is still in its beginning, so some data may still be incomplete. In addition, death records were obtained from the registry information system instead of the SIM (Mortality Information System), which check the consistency of the diagnosis and follow the recommendations of the World Health Organization for the classification of the basic cause of death.. This choice was due to the fact that the SIM takes at least 6 months to consolidate the information and free access for consultations. We emphasize that this limitation is restricted to the analysis of the excess of deaths from respiratory causes, since the cause of death does not interfere in the assessment of mortality from all causes. Another limitation related to the use of data from the registry offices is that in this system only data are available for the years 2019 and 2020, therefore, it was not possible to use an average mortality rate of several years as would be the most appropriate [14,15]. Even with these limitations, the results were quite consistent, showing the most affected ages and there was a strong correlation between the mortality found in the official surveillance system and excess mortality, in addition, the period of increase in mortality was coincident with the pandemic. In addition, no excess deaths were identified in the city with a low incidence of COVID-19...

    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.

    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 10.1101/2020.05.08.20093617v1 on medRxiv
  3. Version published to 10.1590/0037-8682-0558-2020