Evidence map›Paper›PMID 35729074›Full record

ArticleJournal of medical virology2022

A highly powerful nonspecific strategy to reduce COVID-19 deaths.

Ji-Ming Chen, Guo-Hui Li, Yu-Fei Ji, Ming-Hui Sun, Huan-Yu Gong, Rui-Xu Chen, Ji-Wang Chen

Open access · hybridAbstract read
In one paragraph

Article in Journal of medical virology, 2022. 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
0.6field-weighted citation impact, top 33% of its field
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, 6 citations in OpenAlex.

  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

7 authors at 1 institution in 2 countries.

Ji-Ming ChenSchool of Life Science and Engineering, Foshan University, Foshan, China.
Guo-Hui LiSchool of Life Science and Engineering, Foshan University, Foshan, China.
Yu-Fei JiSchool of Life Science and Engineering, Foshan University, Foshan, China.
Ming-Hui SunSchool of Life Science and Engineering, Foshan University, Foshan, China.
Huan-Yu GongSchool of Life Science and Engineering, Foshan University, Foshan, China.
Rui-Xu ChenSchool of Life Science and Engineering, Foshan University, Foshan, China.
Ji-Wang ChenDivision of Pulmonary, Critical Care, Sleep, and Allergy, Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA.
Foshan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus disease 2019 (COVID-19) pandemic caused by the coronavirus severe acute respiratory syndrome coronavirus 2 remains risky worldwide. We elucidate here that good IDM (isolation, disinfection, and maintenance of health) is powerful to reduce COVID-19 deaths based on the striking differences in COVID-19 case fatality rates among various scenarios. IDM means keeping COVID-19 cases away from each other and from other people, disinfecting their living environments, and maintaining their health through good nutrition, rest, and treatment of symptoms and pre-existing diseases (not through specific antiviral therapy). Good IDM could reduce COVID-19 deaths by more than 85% in 2020 and more than 99% in 2022. This is consistent with the fact that good IDM can minimize co-infections and maintain body functions and the fact that COVID-19 has become less pathogenic (this fact was supported with three novel data in this report). Although IDM has been frequently implemented worldwide to some degree, IDM has not been highlighted sufficiently. Good IDM is relative, nonspecific, flexible, and feasible in many countries, and can reduce deaths of some other relatively mild infectious diseases. IDM, vaccines, and antivirals aid each other to reduce COVID-19 deaths. The IDM concept and strategy can aid people to improve their health behavior and fight against COVID-19 and future pandemics worldwide.

Indexed as

COVID-19 Drug TreatmentAntiviral AgentsHumansPandemicsSARS-CoV-2Antiviral Agentscase fatality rateco-infectionCOVID-19pandemicSARS-CoV-2strategy

Identifiers

PMID35729074
PMCPMC9349517
OpenAlexW4283257220

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.