Evidence map›Paper›PMID 35576984›Full record

ArticleHealthcare informatics research2022

Lockdowns, Community Mobility Patterns, and COVID-19: A Retrospective Analysis of Data from 16 Countries.

U Venkatesh, Aravind Gandhi P, Tasnim Ara, Md Mahabubur Rahman, Jugal Kishore

Open access · goldAbstract read
In one paragraph

Article in Healthcare informatics research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 42% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

5 authors at 4 institutions in 2 countries.

U VenkateshDepartment of Community Medicine & Family Medicine, All India Institute of Medical Sciences, Gorakhpur, India.
Aravind Gandhi PDepartment of Community Medicine and School of Public Health, Postgraduate Institute of Medical Education and Research, Chandigarh, India.
Tasnim AraInstitute of Statistical Research & Training, University of Dhaka, Dhaka, Bangladesh.
Md Mahabubur RahmanInstitute of Statistical Research & Training, University of Dhaka, Dhaka, Bangladesh.
Jugal KishoreDepartment of Community Medicine, Vardhman Mahavir Medical College & Safdarjung Hospital, New Delhi, India.
University of Dhaka · BDAll India Institute of Medical Sciences · INPost Graduate Institute of Medical Education and Research · INVardhman Mahavir Medical College & Safdarjung Hospital · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesDuring the coronavirus disease 2019 (COVID-19) pandemic, countries around the world framed specific laws and imposed varying degrees of lockdowns to ensure the maintenance of physical distancing. Understanding changes in temporal and spatial mobility patterns may provide insights into the dynamics of this infectious disease. Therefore, we assessed the efficacy of lockdown measures in 16 countries worldwide by analyzing the relationship between community mobility patterns and the doubling time of COVID-19.

methodsWe performed a retrospective record-based analysis of population-level data on the doubling time for COVID-19 and community mobility. The doubling time for COVID-19 was calculated based on the laboratory-confirmed cases reported daily over the study period (from February 15 to May 2, 2020). Principal component analysis (PCA) of six mobility pattern-related variables was conducted. To explain the magnitude of the effect of mobility on the doubling time, a finite linear distributed lag model was fitted. The k-means clustering approach was employed to identify countries with similar patterns in the significant co-efficient of the mobility index, with the optimal number of clusters derived using Elbow's method.

resultsThe countries analyzed had reduced mobility in commercial and social places. Reduced mobility had a significant and favorable association with the doubling time of COVID-19-specifically, the greater the mobility reduction, the longer the time taken for the COVID-19 cases to double.

conclusionsCOVID-19 lockdowns achieved the immediate objective of mobility reduction in countries with a high burden of cases.

Indexed as

COVID-19Geographic Information SystemsInfectious Disease TransmissionInformation TechnologySpatio-Temporal Analysis

Identifiers

PMID35576984
PMCPMC9117801
OpenAlexW4229454536

What OpenQuestion holds

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LicenceCC BY-NC
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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.