Evidence map›Paper›PMID 33643779›Full record

ReviewZeitschrift fur Gesundheitswissenschaften = Journal of public health2022

Incubation period for COVID-19: a systematic review and meta-analysis.

Balram Rai, Anandi Shukla, Laxmi Kant Dwivedi

Abstract readReview
In one paragraph

Review in Zeitschrift fur Gesundheitswissenschaften = Journal of public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

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

  1. Pooled it
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  13. COVID-19 in one region of New Zealand: a descriptive epidemiological study.Australian and New Zealand journal of public health · 2022
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  15. Utility of NO and HNitric oxide : biology and chemistry · 2022
    Review
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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

3 authors.

Balram RaiDepartment of Mathematical Demography and Statistics, International Institute for Population Sciences, Mumbai, 400088 India.ORCID 0000-0002-3987-2557
Anandi ShuklaDepartment of Mathematical Demography and Statistics, International Institute for Population Sciences, Mumbai, 400088 India.
Laxmi Kant DwivediDepartment of Mathematical Demography and Statistics, International Institute for Population Sciences, Mumbai, 400088 India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: This study aims to conduct a review of the existing literature about incubation period for COVID-19, which can provide insights to the transmission dynamics of the disease. Methods: A systematic review followed by meta-analysis was performed for the studies providing estimates for the incubation period of COVID-19. The heterogeneity and bias in the included studies were tested by various statistical measures, including I Results: Fifteen studies with 16 estimates of the incubation period were selected after implementing the inclusion and exclusion criteria. The pooled estimate of the incubation period is 5.74 (5.18, 6.30) from the random effects model. The heterogeneity in the selected studies was found to be 95.2% from the I Conclusion: This review provides sufficient evidence for the incubation period of COVID-19 through various studies, which can be helpful in planning preventive and control measures for the disease. The pooled estimate from the meta-analysis is a valid and reliable estimate of the incubation period for COVID-19.

Indexed as

COVID-19EpidemiologyIncubation periodInfectious diseaseMeta-analysisSystematic review

Identifiers

PMID33643779
PMCPMC7901514

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.