Evidence map›Paper›PMID 33950996›Full record

SynthesisMedicine2021

Assessment of basic reproductive number for COVID-19 at global level: A meta-analysis.

Cheng-Jun Yu, Zi-Xiao Wang, Yue Xu, Ming-Xia Hu, Kai Chen, Gang Qin

Abstract readMeta-Analysis
In one paragraph

Synthesis in Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

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

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Refining Reproduction Number Estimates to Account for Unobserved Generations of Infection in Emerging Epidemics.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2022
    Article
  9. Article
  10. Review
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Characteristics of COVID-19 Patients With SARS-CoV-2 Positivity in Feces.Frontiers in cellular and infection microbiology · 2022
    Article
  17. Polymeric Materials as Potential Inhibitors Against SARS-CoV-2.Journal of polymers and the environment · 2022
    Review
  18. Article
  19. Underdetection in a stochastic SIR model for the analysis of the COVID-19 Italian epidemic.Stochastic environmental research and risk assessment : research journal · 2022
    Article
  20. 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

6 authors.

Cheng-Jun YuDepartment of Internal Medicine, Medical School, Nantong University, Nantong, China.
Zi-Xiao WangDepartment of Computer Science, New York Institute of Technology, New York, NY, USA.
Yue XuSchool of Pharmacy, Macau University of Science and Technology, Macau.
Ming-Xia HuDepartment of Internal Medicine, Medical School, Nantong University, Nantong, China.
Kai ChenDepartment of Internal Medicine, Medical School, Nantong University, Nantong, China.
Gang QinDepartment of Epidemiology and Biostatistics, School of Public Health, Nantong University, Nantong, China.

Funding

Jiangsu Provincial Health Committee QNRC2016402 and LGY2017039Nantong Municipal Bureau of Science and Technology HS2016002Nantong Municipal Bureau of Science and Technology XG202009-3
6 · The paper itself

Abstract

backgroundThere are large knowledge gaps regarding how transmission of 2019 novel coronavirus disease (COVID-19) occurred in different settings across the world. This study aims to summarize basic reproduction number (R0) data and provide clues for designing prevention and control measures.

methodsSeveral databases and preprint platforms were retrieved for literature reporting R0 values of COVID-19. The analysis was stratified by the prespecified modeling method to make the R0 values comparable, and by country/region to explore whether R0 estimates differed across the world. The average R0 values were pooled using a random-effects model.

resultsWe identified 185 unique articles, yielding 43 articles for analysis. The selected studies covered 5 countries from Asia, 5 countries from Europe, 12 countries from Africa, and 1 from North America, South America, and Australia each. Exponential growth rate model was most favored by researchers. The pooled global R0 was 4.08 (95% CI, 3.09-5.39). The R0 estimates for new and shifting epicenters were comparable or even higher than that for the original epicenter Wuhan, China.

conclusionsThe high R0 values suggest that an extraordinary combination of control measures is needed for halting COVID-19.

Indexed as

Basic Reproduction NumberGlobal HealthCOVID-19HumansPandemicsPneumonia, ViralSARS-CoV-2

Identifiers

PMID33950996
PMCPMC8104145

What OpenQuestion holds

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Registered trials

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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.