Evidence map›Paper›PMID 33906968›Full record

ArticleScience (New York, N.Y.)2021

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

Gonzalo E Mena, Pamela P Martinez, Ayesha S Mahmud, Pablo A Marquet, Caroline O Buckee, Mauricio Santillana

Open access · hybridAbstract read
In one paragraph

Article in Science (New York, N.Y.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 250 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
250citing papers in PubMed, 3 pooled it
37.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

250 citing papers in PubMed, 3 syntheses or guidelines pooled it, 456 citations in OpenAlex.

  1. Incorporating Social Determinants of Health in Infectious Disease Models: A Systematic Review of Guidelines.Medical decision making : an international journal of the Society for Medical Decision Making · 2024
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190 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 3 countries.

Gonzalo E Mena *Department of Statistics, University of Oxford, Oxford, UK. gonzalo.mena@stats.ox.ac.uk pamelapm@illinois.edu.ORCID 0000-0003-4432-9679
Pamela P Martinez *Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. gonzalo.mena@stats.ox.ac.uk pamelapm@illinois.edu.ORCID 0000-0002-3607-0938
Ayesha S MahmudCenter for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID 0000-0002-2282-8613
Pablo A MarquetDepartamento de Ecología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago, Chile.ORCID 0000-0001-6369-9339
Caroline O Buckee *Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Mauricio Santillana *Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID 0000-0002-4206-418X
Center for Disease Dynamics, Economics & Policy · USBoston Children's Hospital · USSanta Fe Institute · USUniversity of Oxford · GB

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIPSITCH, MARC · 2009 to 2018
$26.4M
Epidemiology of Infectious Diseases and BiodefenseT32AI007535 · NIAID · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI GRAD, YONATAN H, MURRAY, MEGAN B · 1998 to 2025
$4.8M
Dev-Core-001P2CHD073964 · NICHD · UNIVERSITY OF CALIFORNIA BERKELEY · PI JOSHUA R. GOLDSTEIN · 2019 to 2026
$2.9M
Development of an Open-Source and Data-Driven Modeling Platform to Monitor and Forecast Disease ActivityR01GM130668 · NIGMS · NORTHEASTERN UNIVERSITY · PI SANTILLANA, MAURICIO · 2018 to 2022
$1.9M
NIAID NIH HHS T32 AI007535NICHD NIH HHS P2C HD073964NIGMS NIH HHS R01 GM130668NIGMS NIH HHS U54 GM088558
6 · The paper itself

Abstract

The COVID-19 pandemic has affected cities particularly hard. Here, we provide an in-depth characterization of disease incidence and mortality and their dependence on demographic and socioeconomic strata in Santiago, a highly segregated city and the capital of Chile. Our analyses show a strong association between socioeconomic status and both COVID-19 outcomes and public health capacity. People living in municipalities with low socioeconomic status did not reduce their mobility during lockdowns as much as those in more affluent municipalities. Testing volumes may have been insufficient early in the pandemic in those places, and both test positivity rates and testing delays were much higher. We find a strong association between socioeconomic status and mortality, measured by either COVID-19-attributed deaths or excess deaths. Finally, we show that infection fatality rates in young people are higher in low-income municipalities. Together, these results highlight the critical consequences of socioeconomic inequalities on health outcomes.

Indexed as

Social ClassSocioeconomic FactorsAdultAgedAge FactorsChileCitiesCOVID-19COVID-19 Nucleic Acid TestingHumansIncidenceMiddle AgedMortalityPhysical DistancingPovertyUrban Health

Identifiers

PMID33906968
PMCPMC8158961
OpenAlexW3157070895

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.