Evidence map›Paper›PMID 35474915›Full record

ArticleAdvances in continuous and discrete models2022

Dynamical analysis of a stochastic delayed SIR epidemic model with vertical transmission and vaccination.

Xiaolei Zhang, Maoxing Liu

Abstract read
In one paragraph

Article in Advances in continuous and discrete models, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Xiaolei ZhangDepartment of Mathematics, North University of China, Taiyuan, Shanxi 030051 P.R. China.
Maoxing LiuDepartment of Mathematics, North University of China, Taiyuan, Shanxi 030051 P.R. China.ORCID 0000-0002-3342-7209

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to describe the dynamic process of epidemic transmission with vertical transmission and vaccination in more detail and to better track the factors that lead to the occurrence of epidemics, we construct a stochastic delayed model with a specific functional response to describe its epidemic dynamics. We first prove the existence and uniqueness of the positive solution of the model. Moreover, we analyze the sufficient conditions for the extinction and persistence of the model. Finally, numerical simulations are presented to illustrate our mathematical findings.

Indexed as

ExtinctionPersistenceStochastic delayed SIR epidemic modelTemporary immunityThresholdVaccination

Identifiers

PMID35474915
PMCPMC9024298

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Registered trials

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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.