County-level socio-economic disparities in COVID-19 mortality in the USA
Author(s) -
Denys Dukhovnov,
Magali Barbiéri
Publication year - 2021
Publication title -
international journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.406
H-Index - 208
eISSN - 1464-3685
pISSN - 0300-5771
DOI - 10.1093/ije/dyab267
Subject(s) - life expectancy , disadvantaged , demography , mortality rate , covid-19 , public health , pandemic , geography , socioeconomic status , medicine , years of potential life lost , socioeconomics , gerontology , population , disease , economic growth , infectious disease (medical specialty) , sociology , economics , pathology , nursing
Background Preliminary studies have suggested a link between socio-economic characteristics and COVID-19 mortality. Such studies have been carried out on particular geographies within the USA or selective data that do not represent the complete experience for 2020. Methods We estimated COVID-19 mortality rates, number of years of life lost to SARS-CoV-2 and reduction in life expectancy during each of the three pandemic waves in 2020 for 3144 US counties grouped into five socio-economic status categories, using daily death data from the Johns Hopkins University of Medicine and weekly mortality age structure from the Centers for Disease Control. Results During March–May 2020, COVID-19 mortality was highest in the most socio-economically advantaged quintile of counties and lowest in the two most-disadvantaged quintiles. The pattern reversed during June–August and widened by September–December, such that COVID-19 mortality rates were 2.58 times higher in the bottom than in the top quintile of counties. Differences in the number of years of life lost followed a similar pattern, ultimately resulting in 1.002 (1.000, 1.004) million years in the middle quintile to 1.381 (1.378, 1.384) million years of life lost in the first (most-disadvantaged) quintile during the whole year. Conclusions Diverging trajectories of COVID-19 mortality among the poor and affluent counties indicated a progressively higher rate of loss of life among socio-economically disadvantaged communities. Accounting for socio-economic disparities when allocating resources to control the spread of the infection and to reinforce local public health infrastructure would reduce inequities in the mortality burden of the disease.
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