Evidence map›Paper›PMID 34852599›Full record

ArticleThe Journal of the Acoustical Society of America2021

Anthropogenic noise variation in Indian cities due to the COVID-19 lockdown during March-to-May 2020.

A Mimani, R Singh

Abstract read
In one paragraph

Article in The Journal of the Acoustical Society of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Sons al Balcó: A Comparative Analysis of WASN-BasedSensors (Basel, Switzerland) · 2024
    Article
  5. Article
  6. FORUM: Remote testing for psychological and physiological acoustics.The Journal of the Acoustical Society of America · 2022
    Article
  7. Review
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

2 authors.

A MimaniDepartment of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur 208 016, Uttar Pradesh, India.
R SinghDepartment of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur 208 016, Uttar Pradesh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper analyzes the impact of a nationwide lockdown enforced during March-to-May 2020 to prevent the widespread transmission of COVID-19 on the local anthropogenic noise level variation in Indian cities. To this end, data obtained from the National Ambient Noise Monitoring Network (NANMN) was used to analyze the long-term daily evolution of average day- and night-time levels at selected locations across seven major cities. The results indicate that when the strict lockdown phase 1 was declared, all industrial (I), commercial (C), and residential (R) zones experienced either a gradual or sudden decrease in noise levels while the silence (S) zone was unaffected. Depending on the zone, the weekly trend graphs reached a minimum either during phase 1 or conditionally relaxed phase 2. Across I, C, and R zones, the average maximum day- and night-time reduction with respect to the pre-lockdown period ranged from 4 to 13.8 dB(A) and 4 to 14.1 dB(A), respectively. As anticipated, with a gradual ease in restrictions from phase 2 onwards, the levels climbed back almost linearly, and during unlocks, the daily variation resembled the pre-lockdown trend. Furthermore, the responses to an online COVID-19 noise perception survey supported the NANMN results and suggested that the lockdown was quieter.

Indexed as

COVID-19CitiesCommunicable Disease ControlEnvironmental MonitoringHumansSARS-CoV-2

Identifiers

PMID34852599
PMCPMC8669881

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.