» Articles » PMID: 32966344

City Size and the Spreading of COVID-19 in Brazil

Overview
Journal PLoS One
Date 2020 Sep 23
PMID 32966344
Citations 38
Authors
Affiliations
Soon will be listed here.
Abstract

The current outbreak of the coronavirus disease 2019 (COVID-19) is an unprecedented example of how fast an infectious disease can spread around the globe (especially in urban areas) and the enormous impact it causes on public health and socio-economic activities. Despite the recent surge of investigations about different aspects of the COVID-19 pandemic, we still know little about the effects of city size on the propagation of this disease in urban areas. Here we investigate how the number of cases and deaths by COVID-19 scale with the population of Brazilian cities. Our results indicate small towns are proportionally more affected by COVID-19 during the initial spread of the disease, such that the cumulative numbers of cases and deaths per capita initially decrease with population size. However, during the long-term course of the pandemic, this urban advantage vanishes and large cities start to exhibit higher incidence of cases and deaths, such that every 1% rise in population is associated with a 0.14% increase in the number of fatalities per capita after about four months since the first two daily deaths. We argue that these patterns may be related to the existence of proportionally more health infrastructure in the largest cities and a lower proportion of older adults in large urban areas. We also find the initial growth rate of cases and deaths to be higher in large cities; however, these growth rates tend to decrease in large cities and to increase in small ones over time.

Citing Articles

Impact of inter-city interactions on disease scaling.

Loureiro N, Neto C, Sutton J, Perc M, Ribeiro H Sci Rep. 2025; 15(1):498.

PMID: 39748086 PMC: 11696764. DOI: 10.1038/s41598-024-84252-z.


Urban-rural disparities in COVID-19 hospitalisations and mortality: A population-based study on national surveillance data from Germany and Italy.

Assche S, Ferraccioli F, Riccetti N, Gomez-Ramirez J, Ghio D, Stilianakis N PLoS One. 2024; 19(5):e0301325.

PMID: 38696525 PMC: 11065260. DOI: 10.1371/journal.pone.0301325.


Complexity of the COVID-19 pandemic in Maringá.

Sunahara A, Pessa A, Perc M, Ribeiro H Sci Rep. 2023; 13(1):12695.

PMID: 37542059 PMC: 10403588. DOI: 10.1038/s41598-023-39815-x.


Unveiling the paths of COVID-19 in a large city based on public transportation data.

Araujo J, Oliveira E, Lima Neto A, Andrade Jr J, Furtado V Sci Rep. 2023; 13(1):5761.

PMID: 37031258 PMC: 10082688. DOI: 10.1038/s41598-023-32786-z.


STG-Net: A COVID-19 prediction network based on multivariate spatio-temporal information.

Song Y, Chen H, Song X, Liao Z, Zhang Y Biomed Signal Process Control. 2023; 84:104735.

PMID: 36875288 PMC: 9969838. DOI: 10.1016/j.bspc.2023.104735.


References
1.
Jones K, Patel N, Levy M, Storeygard A, Balk D, Gittleman J . Global trends in emerging infectious diseases. Nature. 2008; 451(7181):990-3. PMC: 5960580. DOI: 10.1038/nature06536. View

2.
Schlapfer M, Bettencourt L, Grauwin S, Raschke M, Claxton R, Smoreda Z . The scaling of human interactions with city size. J R Soc Interface. 2014; 11(98):20130789. PMC: 4233681. DOI: 10.1098/rsif.2013.0789. View

3.
Bettencourt L, Lobo J, Helbing D, Kuhnert C, West G . Growth, innovation, scaling, and the pace of life in cities. Proc Natl Acad Sci U S A. 2007; 104(17):7301-6. PMC: 1852329. DOI: 10.1073/pnas.0610172104. View

4.
Dowd J, Andriano L, Brazel D, Rotondi V, Block P, Ding X . Demographic science aids in understanding the spread and fatality rates of COVID-19. Proc Natl Acad Sci U S A. 2020; 117(18):9696-9698. PMC: 7211934. DOI: 10.1073/pnas.2004911117. View

5.
Melo H, Moreira A, Batista E, Makse H, Andrade J . Statistical signs of social influence on suicides. Sci Rep. 2014; 4:6239. PMC: 4150102. DOI: 10.1038/srep06239. View