Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile-Reference-Cited by-同舟云学术

Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile

Published:2021-05-28 Issue:6545 Volume:372 Page:
ISSN:0036-8075
Container-title:Science
language:en
Short-container-title:Science

Author:

Mena Gonzalo E.¹^ORCID,Martinez Pamela P.²³⁴⁵^ORCID,Mahmud Ayesha S.²⁶^ORCID,Marquet Pablo A.⁷⁸⁹¹⁰¹¹^ORCID,Buckee Caroline O.²,Santillana Mauricio²¹²¹³^ORCID

Affiliation:

1. Department of Statistics, University of Oxford, Oxford, UK.

2. Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

3. Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.

4. Department of Statistics, University of Illinois at Urbana-Champaign, Champaign, IL, USA.

5. Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.

6. Department of Demography, University of California, Berkeley, CA, USA.

7. Departamento de Ecología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago, Chile.

8. Instituto de Ecología y Biodiversidad (IEB), Santiago, Chile.

9. The Santa Fe Institute, Santa Fe, NM, USA.

10. Instituto de Sistema Complejos de Valparaíso (ISCV), Valparaíso, Chile.

11. Centro de Cambio Global UC, Pontificia Universidad Católica de Chile, Santiago, Chile.

12. Computational Health Informatics Program, Boston Children’s Hospital, Boston, MA, USA.

13. Department of Pediatrics, Harvard Medical School, Boston, MA, USA.

Abstract

Urban socioeconomics and mortality Santiago, Chile, is a highly segregated city with distinct zones of affluence and deprivation. This setting offers a window on how social factors propel the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in an economically vulnerable society with high levels of income inequality. Mena et al. analyzed incidence and mortality attributed to SARS-CoV-2 to understand spatial variations in disease burden. Infection fatality rates were higher in lower-income municipalities because of comorbidities and lack of access to health care. Disparities between municipalities in the quality of their health care delivery system became apparent in testing delays and capacity. These indicators explain a large part of the variation in COVID-19 underreporting and deaths and show that these inequalities disproportionately affected younger people. Science , abg5298, this issue p. eabg5298

Funder

National Institutes of Health

National Institute of General Medical Sciences

Teikyo University School of Medicine

Harvard Data Science Initiative

Schmidt futures award

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference62 articles.

1. Mobility network models of COVID-19 explain inequities and inform reopening