Evidence map›Paper›PMID 39043801›Full record

ArticleScientific reports2024

Risk analysis and assessment method for infectious diseases based on information entropy theory.

Tilei Gao, Tiebing Li, Peng Xu

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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

3 authors.

Tilei GaoYunnan University of Finance and Economics, Kunming, 650221, China. gtllei@ynufe.edu.cn.ORCID 0000-0002-3707-5060
Tiebing LiYunnan University of Finance and Economics, Kunming, 650221, China. tiebing1973@163.com.ORCID 0009-0003-8130-1074
Peng XuYunnan University of Finance and Economics, Kunming, 650221, China.ORCID 0009-0001-9439-1211

Funding

Foundation of Yunnan Key Laboratory of Service Computing YNSC23110National Natural Science Foundation of China 72261033Yunnan Fundamental Research Projects 202201AT070142
6 · The paper itself

Abstract

Infectious diseases risk is directly related to human life safety. After the COVID-19 pandemic, people have paid unprecedented attention to the risk of infectious diseases. Compared with treatment after the outbreak of the epidemic, identifying the influencing factors of infectious disease risk and quantitatively analyzing and assessing infectious disease risk before the outbreak of the epidemic plays an equally important role. This article focuses on the risk of irregular outbreaks of infectious diseases. On the one hand, a method based on information gain is proposed to calculate the weight of environmental factors directly related to infectious disease risk, to clarify the correlation between environmental factors and infectious disease risk. On the other hand, the risk calculation method based on risk weight number is proposed to calculate the risk level of different infectious diseases under the influence of specific environmental factors. Finally, the effectiveness and feasibility of the proposed method are verified through case analysis and discussion. By comparing it with other risk assessment methods, the advantages and disadvantages of the proposed method are demonstrated.

Indexed as

Communicable DiseasesCOVID-19EntropyDisease OutbreaksHumansPandemicsRisk AssessmentSARS-CoV-2Environment factors and infectious disease riskInformation entropyRisk assessmentRisk weight number

Identifiers

PMID39043801
PMCPMC11266543

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.