Evidence map›Paper›PMID 34373859›Full record

ArticlemedRxiv : the preprint server for health sciences2021

Investigating the first stage of the COVID-19 pandemic in Ukraine using epidemiological and genomic data.

Yuriy Gankin, Alina Nemira, Vladimir Koniukhovskii, Gerardo Chowell, Thomas A Weppelmann, Pavel Skums, Alexander Kirpich

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2021. 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
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Yuriy Gankin *Quantori, Cambridge, Massachusetts, United States of America.
Alina Nemira *Department of Computer Science, Georgia State University, Atlanta, Georgia, United States of America.
Vladimir Koniukhovskii *EPAM Systems, Saint Petersburg, Russian Federation.
Gerardo ChowellDepartment of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.
Thomas A WeppelmannDepartment of Internal Medicine, University of South Florida, Tampa, Florida, United States.
Pavel Skums *Department of Computer Science, Georgia State University, Atlanta, Georgia, United States of America.
Alexander Kirpich *Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.

Funding

QUBBD: VIRAL EVOLUTION AND SPREAD OF INFECTIOUS DISEASE IN COMPLEX NETWORK: BIG DATA ANALYSIS AND MODELINGR01EB025022 · NIBIB · GEORGIA STATE UNIVERSITY · PI SKUMS, PAVEL, VANNBERG, FREDRIK · 2017 to 2019
$891k
NIBIB NIH HHS R01 EB025022
6 · The paper itself

Abstract

The novel coronavirus SARS-CoV-2 was first detected in China in December 2019 and has rapidly spread around the globe. The World Health Organization declared COVID-19 a pandemic in March 2020 just three months after the introduction of the virus. Individual nations have implemented and enforced a variety of social distancing interventions to slow the virus spread, that had different degrees of success. Understanding the role of non-pharmaceutical interventions (NPIs) on COVID-19 transmission in different settings is highly important. While most such studies have focused on China, neighboring Asian counties, Western Europe, and North America, there is a scarcity of studies for Eastern Europe. The aim of this study is to contribute to filling this gap by analyzing the characteristics of the

Indexed as

agent-basedCOVID-19phylodynamicsphylogeneticsSARS-CoV-2Ukraine

Identifiers

PMID34373859
PMCPMC8351773

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.