Evidence map›Paper›PMID 32921865›Full record

ArticleCities (London, England)2020

Study of COVID-19 pandemic in London (UK) from urban context.

Aritra Ghosh, Srijita Nundy, Sumedha Ghosh, Tapas K Mallick

Abstract read
In one paragraph

Article in Cities (London, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

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

  1. Pooled it
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  5. Local travel behaviour under continuing COVID-19 waves- A proxy for pandemic fatigue?Transportation research interdisciplinary perspectives · 2023
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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

4 authors.

Aritra GhoshEnvironment and Sustainability Institute, University of Exeter, Penryn Campus, Cornwall TR10 9FE, UK.
Srijita NundySchool of advanced materials science and engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea.
Sumedha GhoshIndian Institute of Technology, Bombay, Maharashtra, India.
Tapas K MallickEnvironment and Sustainability Institute, University of Exeter, Penryn Campus, Cornwall TR10 9FE, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 transmission in London city was discussed in this work from an urban context. The association between COVID-19 cases and climate indicators in London, UK were analysed statistically employing published data from national health services, UK and Time and Date AS based weather data. The climatic indicators included in the study were the daily averages of maximum and minimum temperatures, humidity, and wind speed. Pearson, Kendall, and Spearman rank correlation tests were selected for data analysis. The data was considered up to two different dates to study the climatic effect (10th May in the first study and then updated up to 16th of July in the next study when the rest of the data was available). The results were contradictory in the two studies and it can be concluded that climatic parameters cannot solely determine the changes in the number of cases in the pandemic. Distance from London to four other cities (Birmingham, Leeds, Manchester, and Sheffield) showed that as the distance from the epicentre of the UK (London) increases, the number of COVID-19 cases decrease. What should be the necessary measure to be taken to control the transmission in cities have been discussed.

Indexed as

CityCoronavirusCOVID-19HumidityLock downLondonTemperatureTransmissionTransportUrban context

Identifiers

PMID32921865
PMCPMC7480337

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.