Evidence map›Paper›PMID 35602211›Full record

ArticleCommunications medicine2021

SARS-CoV-2 transmission dynamics in Belarus in 2020 revealed by genomic and incidence data analysis.

Alina Nemira, Ayotomiwa Ezekiel Adeniyi, Elena L Gasich, Kirill Y Bulda, Leonid N Valentovich, Anatoly G Krasko, Olga Glebova, Alexander Kirpich, Pavel Skums

Open access · goldAbstract read
In one paragraph

Article in Communications medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-weighted citation impact, top 26% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 2 countries.

Alina NemiraDepartment of Computer Science, Georgia State University, Atlanta, GA USA.ORCID 0000-0003-3876-2134
Ayotomiwa Ezekiel AdeniyiDepartment of Computer Science, Georgia State University, Atlanta, GA USA.ORCID 0000-0002-0673-0026
Elena L GasichRepublican Research and Practical Center for Epidemiology and Microbiology, Minsk, Belarus.
Kirill Y BuldaRepublican Research and Practical Center for Epidemiology and Microbiology, Minsk, Belarus.
Leonid N ValentovichInstitute of Microbiology, National Academy of Sciences of Belarus, Minsk, Belarus.ORCID 0000-0001-7329-743X
Anatoly G KraskoRepublican Research and Practical Center for Epidemiology and Microbiology, Minsk, Belarus.
Olga GlebovaDepartment of Computer Science, Georgia State University, Atlanta, GA USA.
Alexander Kirpich *Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA USA.
Pavel Skums *Department of Computer Science, Georgia State University, Atlanta, GA USA.ORCID 0000-0003-4007-5624
Georgia State University · USRepublican Research and Practical Center for Epidemiology and Microbiology · BYNational Academy of Sciences of Belarus · BY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Non-pharmaceutical interventions (NPIs) have been implemented worldwide to curb COVID-19 spread. Belarus is a rare case of a country with a relatively modern healthcare system, where highly limited NPIs have been enacted. Thus, investigation of Belarusian COVID-19 dynamics is essential for the local and global assessment of the impact of NPI strategies. Methods: We integrate genomic epidemiology and surveillance methods to investigate the spread of SARS-CoV-2 in Belarus in 2020. We utilize phylodynamics, phylogeography, and probabilistic bias inference to study the virus import and export routes, the dynamics of the effective reproduction number, and the incidence of SARS-CoV-2 infection. Results: Here we show that the estimated cumulative number of infections by June 2020 exceeds the confirmed case number by a factor of ~4 (95% confidence interval (2; 9)). Intra-country SARS-CoV-2 genomic diversity originates from at least 18 introductions from different regions, with a high proportion of regional transmissions. Phylodynamic analysis indicates a moderate reduction of the effective reproductive number after the introduction of limited NPIs, but its magnitude is lower than for developed countries with large-scale NPIs. On the other hand, the effective reproduction number estimate is comparable with that for the neighboring Ukraine, where NPIs were broader. Conclusions: The example of Belarus demonstrates how countries with relatively low outward population mobility continue to be integral parts of the global epidemiological environment. Comparison of the effective reproduction number dynamics for Belarus and other countries reveals the effect of different NPI strategies but also emphasizes the role of regional Eastern European sociodemographic factors in the virus spread.

Indexed as

EpidemiologyHigh-throughput screening

Identifiers

PMID35602211
PMCPMC9053244
OpenAlexW4206780891

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.