Evidence map›Paper›PMID 36962567›Full record

ArticlePLOS global public health2022

Impact of school closures and reopening on COVID-19 caseload in 6 cities of Pakistan: An Interrupted Time Series Analysis.

Abdul Mueed, Taimoor Ahmad, Mujahid Abdullah, Faisal Sultan, Adnan Ahmad Khan

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Article in PLOS global public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Abdul MueedAkhter Hameed Khan Foundation, Islamabad, Pakistan.ORCID https://orcid.org/0000-0003-2881-9723
Taimoor AhmadAkhter Hameed Khan Foundation, Islamabad, Pakistan.ORCID https://orcid.org/0000-0002-1648-2353
Mujahid AbdullahAkhter Hameed Khan Foundation, Islamabad, Pakistan.ORCID https://orcid.org/0000-0002-2923-0526
Faisal SultanMinistry of National Health Services, Regulation and Coordination, Islamabad, Pakistan.ORCID https://orcid.org/0000-0002-2618-988X
Adnan Ahmad KhanMinistry of National Health Services, Regulation and Coordination, Islamabad, Pakistan.ORCID https://orcid.org/0000-0002-3816-3943

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Schools were closed all over Pakistan on November 26, 2020 to reduce community transmission of COVID-19 and reopened between January 18 and February 1, 2021. However, these closures were associated with significant economic and social costs, prompting a review of effectiveness of school closures to reduce the spread of COVID-19 infections in a developing country like Pakistan. A single-group interrupted time series analysis (ITSA) was used to measure the impact of school closures, as well as reopening schools, on daily new COVID-19 cases in 6 major cities across Pakistan: Lahore, Karachi, Islamabad, Quetta, Peshawar, and Muzaffarabad. However, any benefits were contingent on continued closure of schools, as cases bounced back once schools reopened. School closures are associated with a clear and statistically significant reduction in COVID-19 cases by 0.07 to 0.63 cases per 100,000 population, while reopening schools is associated with a statistically significant increase. Lahore is an exception to the effect of school closures, but it too saw an increase in COVID-19 cases after schools reopened in early 2021. We show that closing schools was a viable policy option, especially before vaccines became available. However, its social and economic costs must also be considered.

Identifiers

PMID36962567
PMCPMC10022346

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read29
identifiers read7
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.