Evidence map›Paper›PMID 35712301›Full record

ArticleFrontiers in public health2022

Empirical Analysis of the Dynamics of the COVID-19 Epidemic in Urban Embedded Social Networks.

Zihao Wang, Yue Zhuang, Chao Fan

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. 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
0.3field-weighted citation impact, top 53% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

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

3 authors at 1 institution in 1 country.

Zihao WangSchool of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan, China.
Yue ZhuangSchool of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan, China.
Chao FanSchool of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan, China.
Wuhan University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Due to the continual recurrence of COVID-19 in urban areas, it is important to know more about the evolution of the epidemic within this setting to mitigate the risk of the situation getting worse. As the virus spreads through human society, the social networks of confirmed cases can provide us with crucial new insights on this question. Methods: Based on the epidemiological reports of 235 COVID-19 cases in Nanjing, we constructed a social contact network for the epidemic. By analyzing the structure of this network, we explored the transmission characteristics of the epidemic, to provide evidence-based explanations for its transmission. Results: In our constructed transmission network, more than half (95/165, 57.58%) of patients were found not to have transmitted the infection, with only 15 (9.10%) source patients accounting for more than a third of the contagion (60, 36.36%), suggesting that the transmission of COVID-19 varies per individuals. Patients in the 31 to 50 age group were the main source of infectious clusters, with females playing a more active role in passing on the infection. Network component analysis identified nine components with disproportionate concentrations of influential patients, accounting for 49.09% (81) of the patients and 59.09% (78) of epidemiological network contacts. Family aggregation may favor disease transmission, and parenthood is the relationship with the highest infection risk within the family cluster. In addition, some specific public places, such as chess and card parlors, were found to be notable hotspots for community infection. Conclusion: This study presents the evolution of the urban epidemic from the perspective of individual-level and socially interactive processes. This real-world evidence can help to increase public awareness of the epidemic, formulate countermeasures, and allocate limited public health resources for urban management.

Indexed as

COVID-19EpidemicsContact TracingFemaleHumansPublic HealthSocial Networkingcontact tracing dataCOVID-19Nanjingsocial networkurban epidemic

Identifiers

PMID35712301
PMCPMC9195001
OpenAlexW4282002626

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.