Evidence map›Paper›PMID 37229295›Full record

ArticleUCL open. Environment2020

How did the 'state of emergency' declaration in Japan due to the COVID-19 pandemic affect the acoustic environment in a rather quiet residential area?

Kimihiro Sakagami

Abstract read
In one paragraph

Article in UCL open. Environment, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. A Smartphone-Based Crowd-Sourced Database for Environmental Noise Assessment.International journal of environmental research and public health · 2021
    Article
  8. Article
  9. Changes in noise levels in the city of Madrid during COVID-19 lockdown in 2020.The Journal of the Acoustical Society of America · 2020
    Article
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

1 author.

Kimihiro SakagamiEnvironmental Acoustics Laboratory, Department of Architecture, Graduate School of Engineering, Kobe University, Rokko, Nada, Kobe 657-8501, Japan.ORCID https://orcid.org/0000-0002-5322-7642

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic caused lockdowns in many countries worldwide. Acousticians have made surveys to monitor how cities became quieter under the lockdown, mainly in central areas in cities. However, there have been few studies on the changes in the acoustic environment due to the pandemic in the usually quieter residential areas. It may be expected to be different from the effect in 'originally noisy' areas. Also, the effect could be different in Japan, because the 'state of emergency' declaration there was different to lockdowns elsewhere. Considering these circumstances, this article reports the results of noise monitoring and makes some observations on the acoustic environment in residential areas far from city centres, to provide an example of how the acoustic environment was affected by the state of emergency declaration due to the COVID-19 pandemic in Japan. The results showed that the reduction of noise levels was somewhat less than that reported in large cities. Also, comparing the results after the cancellation of the state of emergency, the noise level increased again. However, observations of noise sources imply that a possible change in human behaviour may have also affected the acoustic environment.

Indexed as

acoustic environmentbuilt environmentCOVID-19 pandemiclockdownnoise levelresidential areastate of emergency in Japanurban studies

Identifiers

PMID37229295
PMCPMC10208345

What OpenQuestion holds

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LicenceCC BY
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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.