Article Text

Excess deaths reveal unequal impact of COVID-19 in Ecuador
  1. Leticia Cuéllar1,
  2. Irene Torres2,
  3. Ethan Romero-Severson1,
  4. Riya Mahesh1,
  5. Nathaniel Ortega1,
  6. Sarah Pungitore1,
  7. Ruian Ke1,
  8. Nicolas Hengartner1
  1. 1Los Alamos National Laboratory, Los Alamos, New Mexico, USA
  2. 2Fundacion Octaedro, Quito, Ecuador
  1. Correspondence to Dr Leticia Cuéllar; leticia{at}lanl.gov

Abstract

Latin America has struggled to control the transmission of COVID-19. Comparison of excess death (ED) rates during the pandemic reveals that Ecuador is among the highest impacted countries. In this analysis, we update our previous findings with the most complete all-cause mortality records available for 2020, disaggregated by sex, age, ethnicity and geography. Our study shows that in 2020, Ecuador had a 64% ED rate (95% CI 63% to 65%) or 64% more deaths than expected. Men had a higher ED rate, 75% (95% CI 73% to 76%), than women’s 51% (95% CI 49% to 52%), and this pattern of higher EDs for men than women held for most age groups. The only exception was the 20–29 age group, where women had 19% more deaths, compared to 10% more deaths for men, but that difference is not statistically significant. The analysis provides striking evidence of the lack of COVID-19 diagnostic testing in Ecuador: the confirmed COVID-19 deaths in 2020 accounted for only 21% of total EDs. Our significant finding is that indigenous populations, who typically account for about 5% of the deaths, show almost four times the ED rate of the majority mestizo group. Indigenous women in each age group have higher ED rates than the general population and, in ages between 20 and 49 years, they have higher ED rates than indigenous men. Indigenous women in the age group 20–29 years had an ED rate of 141%, which is commensurate to the ED rate of indigenous women older than 40 years.

  • COVID-19
  • epidemiology
  • public health

Data availability statement

Data may be obtained from a third party and are not publicly available.

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This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Data availability statement

Data may be obtained from a third party and are not publicly available.

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Footnotes

  • Handling editor Seye Abimbola

  • Twitter @lairene1

  • Contributors Conceptualisation: LC and IT; data acquisition: IT; data processing: LC, RM, NO, SP, ER-S; methodology and formal analysis: LC and NH; visualisation and writing: IT, LC, NH, ER-S and RK.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.