Evidence map›Paper›PMID 34834990›Full record

ReviewViruses2021

A Review of COVID-19 Modelling Strategies in Three Countries to Develop a Research Framework for Regional Areas.

Azizur Rahman, Md Abdul Kuddus, Ryan H L Ip, Michael Bewong

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Viruses, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Can infectious modelling be applicable globally - lessons from COVID 19.Current opinion in environmental science & health · 2022
    Review
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

4 authors.

Azizur RahmanSchool of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, NSW 2678, Australia.ORCID 0000-0002-7670-5192
Md Abdul KuddusSchool of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, NSW 2678, Australia.ORCID 0000-0003-1569-9523
Ryan H L IpSchool of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, NSW 2678, Australia.ORCID 0000-0001-8636-1891
Michael BewongSchool of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, NSW 2678, Australia.ORCID 0000-0002-5848-7451

Funding

Charles Sturt University 57
6 · The paper itself

Abstract

At the end of December 2019, an outbreak of COVID-19 occurred in Wuhan city, China. Modelling plays a crucial role in developing a strategy to prevent a disease outbreak from spreading around the globe. Models have contributed to the perspicacity of epidemiological variations between and within nations and the planning of desired control strategies. In this paper, a literature review was conducted to summarise knowledge about COVID-19 disease modelling in three countries-China, the UK and Australia-to develop a robust research framework for the regional areas that are urban and rural health districts of New South Wales, Australia. In different aspects of modelling, summarising disease and intervention strategies can help policymakers control the outbreak of COVID-19 and may motivate modelling disease-related research at a finer level of regional geospatial scales in the future.

Indexed as

Epidemiological ModelsChinaCommunicable Disease ControlCOVID-19COVID-19 VaccinesDisease OutbreaksHumansNew South WalesQuarantineTravelUnited KingdomVaccinationCOVID-19 VaccinesCOVID-19different settingsintervention strategiesmodelsNSW

Identifiers

PMID34834990
PMCPMC8623457

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.