Evidence map›Paper›PMID 38620724›Full record

ArticleIFAC-PapersOnLine2020

Prediction of the COVID-19 spread in Russia based on SIR and SEIR models of epidemics.

Dmitry A Tomchin, Alexander L Fradkov

Abstract read
In one paragraph

Article in IFAC-PapersOnLine, 2020. 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
–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

2 citing papers in PubMed.

  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

2 authors.

Dmitry A TomchinInstitute for Problems of Mechanical Engineering, Russian Academy of Sciences, Bolshoy Ave 61, Vasilievsky Ostrov, St. Petersburg, 199178, Russia.
Alexander L FradkovInstitute for Problems of Mechanical Engineering, Russian Academy of Sciences, Bolshoy Ave 61, Vasilievsky Ostrov, St. Petersburg, 199178, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An attempt is made to use the simplest epidemic models: SIR and SEIR to predict the spread of COVID-19 in Russia. Simplicity and a small number of parameters are very significant advantages of SIR and SEIR models in conditions of a lack of numerical initial data and structural incompleteness of models. The forecast of distribution of COVID-19 in Russia is carried out according to public data sets from March 10 to April 20, 2020. Comparison of forecast results by SIR and SEIR models are given. In both cases, the peak number of infected persons while maintaining the current level of quarantine measures is forecasted at the end of May 2020.

Identifiers

PMID38620724
PMCPMC8153197

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.