Evidence map›Paper›PMID 35103090›Full record

ArticleProcedia computer science2022

On intelligent agent-based simulation of COVID-19 epidemic process in Ukraine.

Dmytro Chumachenko, Ievgen Meniailov, Kseniia Bazilevych, Tetyana Chumachenko, Sergiy Yakovlev

Abstract read
In one paragraph

Article in Procedia computer science, 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
–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

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.

Dmytro ChumachenkoNational Aerospace University "Kharkiv Aviation Institute", Mathematical Modelling and Artificial Intelligence department, Chkalow str., 17, Kharkiv, 61072, Ukraine.
Ievgen MeniailovNational Aerospace University "Kharkiv Aviation Institute", Mathematical Modelling and Artificial Intelligence department, Chkalow str., 17, Kharkiv, 61072, Ukraine.
Kseniia BazilevychNational Aerospace University "Kharkiv Aviation Institute", Mathematical Modelling and Artificial Intelligence department, Chkalow str., 17, Kharkiv, 61072, Ukraine.
Tetyana ChumachenkoKharkiv National Medical University, Epidemiology department, Nauky ave., 4, Kharkiv, 61001, Ukraine.
Sergiy YakovlevNational Aerospace University "Kharkiv Aviation Institute", Mathematical Modelling and Artificial Intelligence department, Chkalow str., 17, Kharkiv, 61072, Ukraine.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 has impacted all areas of human activity around the world. Modern society has not faced such a challenge. Affordable travel and flights between continents allowed the virus to rapidly spread to all corners of the world. An effective tool for the development of anti-epidemic measures is mathematical modeling. The paper proposes a simulation model of COVID-19 propagation based on an agent-based approach. The case of the spread of the epidemic process before vaccination is considered. To verify the model, we used the data of official statistics on the incidence of COVID-19 in Ukraine, provided by the Center for Public Health of the Ministry of Health of Ukraine. The constructed model makes it possible to identify the factors influencing the development of the COVID-19 epidemic in a certain area.

Indexed as

Agent-based simulationcompartement modelCOVID-19epidemic modelepidemic process

Identifiers

PMID35103090
PMCPMC8790955

What OpenQuestion holds

Textmetadata
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.