Evidence map›Paper›PMID 36429433›Full record

ArticleInternational journal of environmental research and public health2022

Study of the Deep Processes of COVID-19 in Russia: Finding Ways to Identify Preventive Measures.

Alexander P Anyutin, Tatiana M Khodykina, Ekaterina I Akimova, Elena V Belova, Ekaterina A Shashina, Denis V Shcherbakov, Valentina V Makarova, Nadezhda N Zabroda, Anna A Klimova, Nina A Ermakova and 4 more

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. 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
0.1field-weighted citation impact, top 58% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

14 authors at 3 institutions in 1 country.

Alexander P AnyutinInstitute of Radio Engineering and Electronics of the Russian Academy of Sciences, Fryazino Branch, 141190 Fryazino, Russia.
Tatiana M KhodykinaDepartment of General Hygiene, F. Erismann Institute of Public Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia.ORCID 0000-0002-9646-5595
Ekaterina I AkimovaDepartment of General Hygiene, F. Erismann Institute of Public Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia.
Elena V BelovaDepartment of General Hygiene, F. Erismann Institute of Public Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia.
Ekaterina A ShashinaDepartment of General Hygiene, F. Erismann Institute of Public Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia.ORCID 0000-0002-5294-6813
Denis V ShcherbakovDepartment of General Hygiene, F. Erismann Institute of Public Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia.
Valentina V MakarovaDepartment of General Hygiene, F. Erismann Institute of Public Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia.ORCID 0000-0002-7213-4265
Nadezhda N ZabrodaDepartment of General Hygiene, F. Erismann Institute of Public Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia.
Anna A KlimovaDepartment of General Hygiene, F. Erismann Institute of Public Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia.
Nina A ErmakovaDepartment of General Hygiene, F. Erismann Institute of Public Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia.ORCID 0000-0002-9745-4265
Tatiana S Isiutina-FedotkovaDepartment of General Hygiene, F. Erismann Institute of Public Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia.ORCID 0000-0001-8423-9243
Yury V ZhernovDepartment of General Hygiene, F. Erismann Institute of Public Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia.ORCID 0000-0001-8734-5527
Roman V PolibinDepartment of Epidemiology and Evidence-based Medicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia.ORCID 0000-0003-4146-4787
Oleg V MitrokhinDepartment of General Hygiene, F. Erismann Institute of Public Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia.ORCID 0000-0002-6403-0423
Sechenov University · RUInstitute of Radio-Engineering and Electronics · RURussian Academy of Sciences · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The novel coronavirus disease 2019 (COVID-19) pandemic has had a huge impact on all areas of human life. Since the risk of biological threats will persist in the future, it is very important to ensure mobilization readiness for a prompt response to the possible emergence of epidemics of infectious diseases. Therefore, from both a theoretical and practical standpoint, it is currently necessary to conduct a thorough examination of the COVID-19 epidemic. The goal of this research is to investigate the underlying processes that led to the COVID-19 pandemic in Russia and to identify ways to improve preventive measures and ensure mobilization readiness for a quick response to potential COVID-19-like pandemics. This research will analyze the daily dynamics of the number of infection cases and the number of new lethal cases of COVID-19. We analyzed the daily number of new cases of COVID-19 infection N(d), the daily number of new lethal cases L(d), their percentage ratio L(d)/N(d) 100% in Russia for 2 years of the pandemic (from the beginning of the pandemic to 23 March 2022), the rate of increase and decrease of these indicators (dN(d)/dd and dL(d)/dd), as well as their spectra created on the basis of wavelet analysis. Wavelet analysis of the deep structure of the N(d) and L(d) wavelet spectra made it possible to identify the presence of internal cycles, the study of which makes it possible to predict the presence of days with the maximum number of infections and new deaths in a pandemic similar to COVID-19 and outline ways and methods for improving preventive measures and measures to ensure mobilization readiness for a rapid response to the potential emergence of pandemics similar to COVID-19.

Indexed as

COVID-19HumansPandemicsRussiaWavelet AnalysisCOVID-19epidemicmobilization readinessnew coronavirus infectionpandemicpreventive measuresrapid responsewavelet analysis

Identifiers

PMID36429433
PMCPMC9690343
OpenAlexW4308873193

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.