Final assessment of the COVID-19 pandemic impact between the different social and economic strata population of the city of Buenos Aires

Background

During the pandemic, epidemiological communications reported an estimation of excess deaths. However, the final calculation requires a detailed analysis. The study aim was to ascertain the number and distribution of COVID-19 fatalities among various socio-economic strata in a large, moderate to low-income city.

Study design

Observational time series analysis in a large city, treated as a natural experiment.

Methods

Analysis of death certificates, demographic data, and health system records of positive RT-PCR COVID-19 tests from 2015 to 2021, categorizing by age, sex, and place of residence. The study measured the pandemic's impact on mortality, including COVID and non-COVID deaths, using corrected Poisson regression models for different demographics and assessing socio-economic status impact via ecological community-level analysis.

Results

Compared to the pre-pandemic period (2015–2019, IRR = 1.00), the sex- and age-adjusted rate of all-cause death increased significantly during the pandemic (2020–2021) IRR = 1.109 [1.054–1.167], p < 0.0001. This was observed in both males (IRR = 1.158 [1.1–1.219], p < 0.0001) and females (IRR = 1.068 [1.016–1.124], p = 0.01). There was no observed effect of the pandemic on the historical trend in the progressive reduction of mortality in people under 35 years of age. The increase in deaths was at the expense of COVID (+11,175 deaths) and cardiovascular causes (IRR = 1.114 [1.020–1.217] p = 0.017). During the pandemic, there was a significant increase in deaths at home (IRR = 1.219 [1197–1.242], p < 0.0001), especially in people dying of cardiovascular causes (IRR = 1.391 [1.360–1.422], p < 0.0001). The increase in the adjusted mortality rate during the pandemic was socially conditioned.

Conclusions

The pandemic not only led to increased COVID-19 mortality but also heightened fatalities from non-COVID causes, reflecting a potential bias in healthcare resource allocation towards SARS-CoV-2 at the expense of chronic pathologies care.