Evidence map›Paper›PMID 37711145›Full record

ArticleRoyal Society open science2023

Understanding community level influences on the prevalence of SARS-CoV-2 infection in England: new insights from comparison over time and space.

Chaitanya Joshi, Arif Ali, Thomas ÓConnor, Li Chen, Kaveh Jahanshahi

Abstract read
In one paragraph

Article in Royal Society open science, 2023. 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
–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

0 citing papers in PubMed.

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

5 authors.

Chaitanya JoshiData Science Campus, Office for National Statistics, Newport, UK.ORCID 0000-0002-7628-1481
Arif AliData Science Campus, Office for National Statistics, Newport, UK.
Thomas ÓConnorData Science Campus, Office for National Statistics, Newport, UK.
Li ChenData Science Campus, Office for National Statistics, Newport, UK.
Kaveh JahanshahiData Science Campus, Office for National Statistics, Newport, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding and monitoring the major influences on SARS-CoV-2 prevalence is essential to inform policy making and devise appropriate packages of non-pharmaceutical interventions. Through evaluating community level influences on the prevalence of SARS-CoV-2 infection and their spatio-temporal variations in England, this study aims to provide some insights into the most important risk parameters. We used spatial clusters developed in Jahanshahi and Jin (2021

Indexed as

communityCOVID-19Englandinfluenceslevelprevalences

Identifiers

PMID37711145
PMCPMC10498042

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.