Evidence map›Paper›PMID 33083402›Full record

ArticleWorld journal of clinical cases2020

Global analysis of daily new COVID-19 cases reveals many static-phase countries including the United States potentially with unstoppable epidemic.

Cheng Long, Xin-Miao Fu, Zhi-Fu Fu

Abstract read
In one paragraph

Article in World journal of clinical cases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Cheng LongDepartment of Orthopaedics, Sichuan University West China Hospital, Chengdu 610041, Sichuan Province, China.
Xin-Miao FuCollege of Life Sciences, Fujian Normal University, Fuzhou 350117, Fujian Province, China.
Zhi-Fu FuAnxi AIER Eye Hospital (AIER EYE Hospital Group), Anxi 362400, Fujian Province, China. fu_zhifu@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe coronavirus disease 2019 (COVID-19) pandemic is hitting many countries. It is hypothesized the epidemic is differentially progressing in different countries.

aimTo investigate how the COVID-19 epidemic is going on in different countries by analyzing representative countries.

methodsThe status of COVID-19 epidemic in over 60 most affected countries was characterized. The data of daily new cases of each country were collected from Worldometer. The data of daily tests for the United States, Italy, and South Korea were collected from the Website of One World Data. Levels of daily positive COVID-19 tests in the two most affected states of the United States (New York and New Jersey) were collected from the website of the COVID Tracking Project. Statistics were analyzed using Microcal Origin software with ANOVA algorithm, and significance level was set at a

resultsThe COVID-19 epidemic was differentially progressing in different countries. Comparative analyses of daily new cases as of April 19, 2020 revealed that 61 most affected countries can be classified into four types: Downward (22), upward (20), static-phase (12), and uncertain ones (7). In particular, the 12 static-phase countries including the United States were characterized by largely constant numbers of daily new cases in the past over 14 d. Furthermore, these static-phase countries were overall significantly lower in testing density (

conclusionIncreasing the testing capacity and/or reducing the COVID-19 transmission are urgently needed to stop the potentially unstoppable, severing crisis in static-phase countries.

Indexed as

CoronavirusCOVID-19PandemicSARS-CoV-2Testing density

Identifiers

PMID33083402
PMCPMC7559691

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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.