Evidence map›Paper›PMID 37104371›Full record

ArticlePloS one2023

Effect of total population, population density and weighted population density on the spread of Covid-19 in Malaysia.

Hui Shan Wong, Md Zobaer Hasan, Omar Sharif, Azizur Rahman

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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  3. Review
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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.

Hui Shan WongSchool of Science, Monash University Malaysia, Jalan Lagoon Selatan, Bandar Sunway, Selangor D. E., Malaysia.
Md Zobaer HasanSchool of Science, Monash University Malaysia, Jalan Lagoon Selatan, Bandar Sunway, Selangor D. E., Malaysia.ORCID 0000-0002-6378-6333
Omar SharifDepartment of Mathematics and Statistical Science, University of Texas Rio Grande Valley, Edinburg, Texas, United States of America.
Azizur RahmanSchool of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, Australia.ORCID 0000-0002-7670-5192

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since November 2019, most countries across the globe have suffered from the disastrous consequences of the Covid-19 pandemic which redefined every aspect of human life. Given the inevitable spread and transmission of the virus, it is critical to acknowledge the factors that catalyse transmission of the disease. This research investigates the relation of the external demographic parameters such as total population, population density and weighted population density on the spread of Covid-19 in Malaysia. Pearson correlation and simple linear regression were utilized to identify the relation between the population-related variables and the spread of Covid-19 in Malaysia using data from 15th March 2020 to 31st March 2021. As a result, a strong positive significant correlation between the total population and Covid-19 cases was found. However, a weak positive relationship was found between the density variable (population density and weighted population density) and the spread of Covid-19. Our findings suggest that the transmission of Covid-19 during lockdown (Movement Control Order, MCO) in Malaysia was more readily explained by the demographic variable population size, than population density or weighted population density. Thus, this study could be helpful in intervention planning and managing future virus outbreaks in Malaysia.

Indexed as

COVID-19Communicable Disease ControlHumansMalaysiaPandemicsPopulation DensitySARS-CoV-2

Identifiers

PMID37104371
PMCPMC10138265

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.