Evidence map›Paper›PMID 33903841›Full record

ArticleCureus2021

Mortality Rates of Coronavirus Disease 2019 (COVID-19) Caused by the Novel Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2).

Venkataramana Kandi, Sudhakar Thungaturthi, Sabitha Vadakedath, Rajkumar Gundu, Ranjan K Mohapatra

Abstract read
In one paragraph

Article in Cureus, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

5 authors.

Venkataramana KandiClinical Microbiology, Prathima Institute of Medical Sciences, Karimnagar, IND.
Sudhakar ThungaturthiBiochemistry, Chalmeda Anandrao Institute of Medical Sciences, Karimnagar, IND.
Sabitha VadakedathBiochemistry, Prathima Institute of Medical Sciences, Karimnagar, IND.
Rajkumar GunduBiochemistry, Chalmeda Anandrao Institute of Medical Sciences, Karimnagar, IND.
Ranjan K MohapatraChemistry, Government College of Engineering, Keonjhar, Keonjhar, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background The significance of the global prevalence and incidence of coronavirusdisease 2019 (COVID-19) is a measure of its severity. However, without statistical data, one cannot understand the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic. This study, based on good data, enables us to know how the disease is spreading, what impact the pandemic has on the lives of people around the world, and whether the countermeasures that countries have been taking are successful for controlling and preventing the disease. Therefore, this study is undertaken to estimate the infection fatality rates (IFRs) and case-fatality rates (CFRs) in various countries and regions of the world. Methods COVID-19-related data were collected from various countries belonging to different World Bank categories based on economies (low-income, low-middle income, upper-middle income, and high-income countries) and the World Health Organization's (WHO's) regional classification of countries (the Americas, European, African, South-East Asia, Eastern Mediterranean, and Western Pacific regions). The data were collected from the WHO's dedicated website on COVID-19, and statistical methods like mean, standard deviation, p-value, and percentages were used to calculate the IFR and CFR. Results Mexico (8.94%) reported the highest IFR among all the countries. The low-income countries reported increased IFR (2.46±1.91) as compared to the other groups. The European region (7.3%) and the American region (5.3%) recorded the highest CFRs. The South-East Asian region reported the lowest CFR (1.1%). Conclusions The low-income group countries showed higher rates of IFR and lower CFRs. Lower IFRs and increased CFRs were noted among the high-income group countries and the American and European regions respectively. The varied IFRs and CFRs could be attributed to multiple factors that include climatic conditions, living environments, age, sex, comorbidities, among others.

Indexed as

agecase fatality rate (cfr)comorbiditiescovid-19infection fatality rate (ifr)pandemicsars-cov-2statisticswho regionsworld bank countries

Identifiers

PMID33903841
PMCPMC8063914

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.