Evidence map›Paper›PMID 38829889›Full record

ArticlePloS one2024

First year of COVID-19 in Brazil: Factors associated with the spread of COVID-19 in small and large cities.

Alexandre Augusto de Paula da Silva, Rodrigo Siqueira Reis, Franciele Iachecen, Fábio Duarte, Cristina Pellegrino Baena, Adriano Akira Ferreira Hino

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Alexandre Augusto de Paula da SilvaSchool of Medicine, Graduate Program in Health Sciences, Pontifícia Universidade Católica do Paraná, Curitiba, Paraná, Brazil.ORCID 0000-0003-0442-4938
Rodrigo Siqueira ReisResearch Group of Physical Activity and Quality of Life, Pontifícia Universidade Católica do Paraná, Curitiba, Paraná, Brazil.
Franciele IachecenGraduate Program in Health Technology, Polytechnic School, Pontifícia Universidade Católica do Paraná, Curitiba, Paraná, Brazil.
Fábio DuarteDepartment of Urban Studies and Planning, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
Cristina Pellegrino BaenaSchool of Medicine, Graduate Program in Health Sciences, Pontifícia Universidade Católica do Paraná, Curitiba, Paraná, Brazil.
Adriano Akira Ferreira HinoSchool of Medicine, Graduate Program in Health Sciences, Pontifícia Universidade Católica do Paraná, Curitiba, Paraná, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo test the association between sociodemographic and social characteristics with COVID-19 cases and deaths in small and large Brazilian cities.

methodsThis ecological study included COVID-19 data available in State Health Secretaries (managed by brasil.io API) and three national databases (IBGE, DATASUS and Embrapa). Temporal spread of COVID-19 in Brazil during the first year considered as outcome: a) days until 1st case in each city since 1st in the country; b) days until 1,000 cases/100,000 inhabitants since 1st case in each city; c) days until 1st death until 50 deaths/100,000 inhabitants. Covariates included geographic region, city social and environmental characteristics, housing conditions, job characteristics, socioeconomic and inequalities characteristics, and health services and coverage. The analysis were stratified by city size into small (<100,000 inhabitants) and large cities (≥100,00 inhabitants). Multiple linear regressions were performed to test associations of all covariates to adjust to potential confounders.

resultsIn small cities, the first cases were reported after 82.2 days and 1,000 cases/100,000 were reported after 117.8 days, whereas in large cities these milestones were reported after 32.1 and 127.7 days, respectively. For first death, small and large cities took 121.6 and 36.0 days, respectively. However, small cities were associated with more vulnerability factors to first case arrival in 1,000 cases/100,000 inhabitants, first death and 50 deaths/100,000 inhabitants. North and Northeast regions positively associated with faster COVID-19 incidence, whereas South and Southeast were least.

conclusionSocial and built environment characteristics and inequalities were associated with COVID-19 cases spread and mortality incidence in Brazilian cities.

Indexed as

CitiesCOVID-19BrazilHumansSARS-CoV-2Socioeconomic Factors

Identifiers

PMID38829889
PMCPMC11146709

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.