Evidence map›Paper›PMID 32867133›Full record

ReviewInternational journal of environmental research and public health2020

The Prediction of Infectious Diseases: A Bibliometric Analysis.

Wenting Yang, Jiantong Zhang, Ruolin Ma

Open access · goldAbstract readReview
In one paragraph

Review in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 2 pooled it
2.2field-weighted citation impact, top 8% of its field
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

30 citing papers in PubMed, 2 syntheses or guidelines pooled it, 87 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  6. Review
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  11. Article
  12. A Bibliometric Analysis of Literature on Prenatal Exposure to Air Pollution: 1994-2022.International journal of environmental research and public health · 2023
    Review
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  15. Review
  16. Article
  17. Review
  18. Article
  19. Article
  20. A Bibliometric Analysis of Leprosy during 2000-2021 from Web of Science Database.International journal of environmental research and public health · 2022
    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 at 2 institutions in 2 countries.

Wenting YangSchool of Economics and Management, Tongji University, Shanghai 200092, China.
Jiantong ZhangSchool of Economics and Management, Tongji University, Shanghai 200092, China.ORCID 0000-0003-1890-1117
Ruolin MaEli Broad College of Business, Michigan State University, Michigan, MI 48824, USA.
Tongji University · CNMichigan State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe outbreak of infectious diseases has a negative influence on public health and the economy. The prediction of infectious diseases can effectively control large-scale outbreaks and reduce transmission of epidemics in rapid response to serious public health events. Therefore, experts and scholars are increasingly concerned with the prediction of infectious diseases. However, a knowledge mapping analysis of literature regarding the prediction of infectious diseases using rigorous bibliometric tools, which are supposed to offer further knowledge structure and distribution, has been conducted infrequently. Therefore, we implement a bibliometric analysis about the prediction of infectious diseases to objectively analyze the current status and research hotspots, in order to provide a reference for related researchers.

methodsWe viewed "infectious disease*" and "prediction" or "forecasting" as search theme in the core collection of Web of Science from inception to 1 May 2020. We used two effective bibliometric tools, i.e., CiteSpace (Drexel University, Philadelphia, PA, USA) and VOSviewer (Leiden University, Leiden, The Netherlands) to objectively analyze the data of the prediction of infectious disease domain based on related publications, which can be downloaded from the core collection of Web of Science. Then, the leading publications of the prediction of infectious diseases were identified to detect the historical progress based on collaboration analysis, co-citation analysis, and co-occurrence analysis.

results1880 documents that met the inclusion criteria were extracted from Web of Science in this study. The number of documents exhibited a growing trend, which can be expressed an increasing number of experts and scholars paying attention to the field year by year. These publications were published in 427 different journals with 11 different document types, and the most frequently studied types were articles 1618 (83%). In addition, as the most productive country, the United States has provided a lot of scientific research achievements in the field of infectious diseases.

conclusionOur study provides a systematic and objective view of the field, which can be useful for readers to evaluate the characteristics of publications involving the prediction of infectious diseases and for policymakers to take timely scientific responses.

Indexed as

BibliometricsCommunicable DiseasesDisease OutbreaksPublicationsEfficiencyForecastingHumansNetherlandsPhiladelphiabibliometric analysisinfectious diseasesprediction

Identifiers

PMID32867133
PMCPMC7504049
OpenAlexW3081244446

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.