Evidence map›Paper›PMID 34270185›Full record

SynthesisJournal of epidemiology and global health2021

Factors Associated with the Incidence and Mortality of Coronavirus Disease 2019 (COVID-19) after 126-million Cases: A Meta-analysis.

Jeerath Phannajit, Kullaya Takkavatakarn, Pisut Katavetin, Thanin Asawavichienjinda, Kriang Tungsanga, Kearkiat Praditpornsilpa, Somchai Eiam-Ong, Paweena Susantitaphong

Abstract readMeta-Analysis
In one paragraph

Synthesis in Journal of epidemiology and global health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Review
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

8 authors.

Jeerath PhannajitDivision of Nephrology, Department of Medicine, King Chulalongkorn Memorial Hospital, Faculty of Medicine, Chulalongkorn University, 1873 RAMA IV, Bangkok, Thailand.ORCID 0000-0002-3524-6292
Kullaya TakkavatakarnDivision of Nephrology, Department of Medicine, King Chulalongkorn Memorial Hospital, Faculty of Medicine, Chulalongkorn University, 1873 RAMA IV, Bangkok, Thailand.
Pisut KatavetinDivision of Nephrology, Department of Medicine, King Chulalongkorn Memorial Hospital, Faculty of Medicine, Chulalongkorn University, 1873 RAMA IV, Bangkok, Thailand.
Thanin AsawavichienjindaDivision Clinical Epidemiology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.ORCID 0000-0002-3119-2610
Kriang TungsangaDivision of Nephrology, Department of Medicine, King Chulalongkorn Memorial Hospital, Faculty of Medicine, Chulalongkorn University, 1873 RAMA IV, Bangkok, Thailand.ORCID 0000-0003-4990-9306
Kearkiat PraditpornsilpaDivision of Nephrology, Department of Medicine, King Chulalongkorn Memorial Hospital, Faculty of Medicine, Chulalongkorn University, 1873 RAMA IV, Bangkok, Thailand.
Somchai Eiam-OngDivision of Nephrology, Department of Medicine, King Chulalongkorn Memorial Hospital, Faculty of Medicine, Chulalongkorn University, 1873 RAMA IV, Bangkok, Thailand.
Paweena SusantitaphongDivision of Nephrology, Department of Medicine, King Chulalongkorn Memorial Hospital, Faculty of Medicine, Chulalongkorn University, 1873 RAMA IV, Bangkok, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis meta-analysis was conducted to investigate the current global incidence and mortality of COVID-19 and also explored the associated factors including geographic variations, transmission scenarios, country economic status, and healthcare performance.

methodsThe search was conducted in online databases based on reports from national authorities by March 28, 2021. Random-effects model meta-analyses and meta-regression analyses were used to generate summary estimates and explored sources of heterogeneity.

resultsThe cumulative number of confirmed COVID-19 cases was 125,704,789 reported by 216 countries. The pooled Daily Cumulative Index (DCI) was 1423.87 cases/day which was highest in South America (2759.15 cases/day) followed by North America (2252.49 cases/day), Europe (1858.44 cases/day), Asia (1484.84 cases/day), Africa (193.09 cases/day), and Australia/Oceania (18.55 cases/day). The overall pooled mortality rate of COVID-19 was 1.53%. Higher income countries and countries with community transmission had higher DCI. By meta-regression, country total health expenditure per capita, percentage of universal health coverage, and total number of tests were associated with higher DCI. On the contrary, country Gross Domestic Product (GDP) per capita were negatively correlated with mortality rate.

conclusionTo date, 216 countries around the world are affected by COVID-19. Higher income, GDP, and countries' investments on heath are associated with higher DCI while higher GDP correlates with lower mortality. Community transmission route have more impact on the incidence and mortality of COVID-19.

Indexed as

COVID-19AustraliaEuropeHumansIncidenceSARS-CoV-2Coronavirus disease-19epidemiologyhealth systemincidencemortalitypandemics

Identifiers

PMID34270185
PMCPMC8435869

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.