Evidence map›Paper›PMID 35140319›Full record

ArticleScientific reports2022

The effects of super spreading events and movement control measures on the COVID-19 pandemic in Malaysia.

Lai Chee Herng, Sarbhan Singh, Bala Murali Sundram, Ahmed Syahmi Syafiq Md Zamri, Tan Cia Vei, Tahir Aris, Hishamshah Ibrahim, Noor Hisham Abdullah, Sarat Chandra Dass, Balvinder Singh Gill

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 11% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
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  12. COVID-19 in Malaysia: Descriptive Epidemiologic Characteristics of the First Wave.International journal of environmental research and public health · 2022
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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

10 authors at 3 institutions in 1 country.

Lai Chee Herng *Institute for Medical Research (IMR), National Institutes of Health (NIH), Ministry of Health Malaysia, 40170, Setia Alam, Malaysia.
Sarbhan Singh *Institute for Medical Research (IMR), National Institutes of Health (NIH), Ministry of Health Malaysia, 40170, Setia Alam, Malaysia. lssarbhan@moh.gov.my.
Bala Murali Sundram *Institute for Medical Research (IMR), National Institutes of Health (NIH), Ministry of Health Malaysia, 40170, Setia Alam, Malaysia.
Ahmed Syahmi Syafiq Md Zamri *Institute for Medical Research (IMR), National Institutes of Health (NIH), Ministry of Health Malaysia, 40170, Setia Alam, Malaysia.
Tan Cia Vei *Institute for Medical Research (IMR), National Institutes of Health (NIH), Ministry of Health Malaysia, 40170, Setia Alam, Malaysia.
Tahir Aris *Institute for Medical Research (IMR), National Institutes of Health (NIH), Ministry of Health Malaysia, 40170, Setia Alam, Malaysia.
Hishamshah Ibrahim *Ministry of Health Malaysia, 62590, Putrajaya, Malaysia.
Noor Hisham Abdullah *Ministry of Health Malaysia, 62590, Putrajaya, Malaysia.
Sarat Chandra Dass *Heriot-Watt University Malaysia, 62200, Putrajaya, Malaysia.
Balvinder Singh Gill *Institute for Medical Research (IMR), National Institutes of Health (NIH), Ministry of Health Malaysia, 40170, Setia Alam, Malaysia.
Ministry of Health · MYInstitute for Medical Research · MYHeriot-Watt University Malaysia · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper aims to develop an automated web application to generate validated daily effective reproduction numbers (Rt) which can be used to examine the effects of super-spreading events due to mass gatherings and the effectiveness of the various Movement Control Order (MCO) stringency levels on the outbreak progression of COVID-19 in Malaysia. The effective reproduction number, Rt, was estimated by adopting and modifying an Rt estimation algorithm using a validated distribution mean of 3.96 and standard deviation of 4.75 with a seven-day sliding window. The Rt values generated were validated using thea moving window SEIR model with a negative binomial likelihood fitted using methods from the Bayesian inferential framework. A Pearson's correlation between the Rt values estimated by the algorithm and the SEIR model was r = 0.70, p < 0.001 and r = 0.81, p < 0.001 during the validation period The Rt increased to reach the highest values at 3.40 (95% CI 1.47, 6.14) and 1.72 (95% CI 1.54, 1.90) due to the Sri Petaling and Sabah electoral process during the second and third waves of COVID-19 respectively. The MCOs was able to reduce the Rt values by 63.2 to 77.1% and 37.0 to 47.0% during the second and third waves of COVID-19, respectively. Mass gathering events were one of the important drivers of the COVID-19 outbreak in Malaysia. However, COVID-19 transmission can be fuelled by noncompliance to Standard Operating Procedure, population mobility, ventilation and environmental factors.

Indexed as

AlgorithmsCOVID-19HumansMalaysiaPandemicsQuarantineSARS-CoV-2Web Browser

Identifiers

PMID35140319
PMCPMC8828893
OpenAlexW4210945479

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.