Evidence map›Paper›PMID 32577693›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Meta-analysis of several epidemic characteristics of COVID-19.

Panpan Zhang, Tiandong Wang, Sharon X Xie

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. 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

5 · Who and what money

Authors and funding

3 authors.

Panpan ZhangDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104.
Tiandong WangDepartment of Statistics, Texas A&M University, College Station, TX 77843.
Sharon X XieDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104.

Funding

Efficient statistical methods for assessing dementia risk in Parkinson's diseaseR01NS102324 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI WEINTRAUB, DANIEL, XIE, SHARON XIANGWEN · 2017 to 2020
$1.3M
NINDS NIH HHS R01 NS102324
6 · The paper itself

Abstract

As the COVID-19 pandemic has strongly disrupted people's daily work and life, a great amount of scientific research has been conducted to understand the key characteristics of this new epidemic. In this manuscript, we focus on four crucial epidemic metrics with regard to the COVID-19, namely the basic reproduction number, the incubation period, the serial interval and the epidemic doubling time. We collect relevant studies based on the COVID-19 data in China and conduct a meta-analysis to obtain pooled estimates on the four metrics. From the summary results, we conclude that the COVID-19 has stronger transmissibility than SARS, implying that stringent public health strategies are necessary.

Indexed as

basic reproduction numberepidemic doubling timeincubation periodmeta-analysissensitivity analysisserial interval

Identifiers

PMID32577693
PMCPMC7302302

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.