Evidence map›Paper›PMID 34558879›Full record

ArticleJournal of public health research2021

Simulation of COVID-19 outbreaks via Graphical User Interface (GUI).

Norazaliza Mohd Jamil, Norhayati Rosli, Noryanti Muhammad

Open access · goldAbstract read
In one paragraph

Article in Journal of public health research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 40% 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

0 citing papers in PubMed, 5 citations in OpenAlex.

No citing paper in PubMed yet.

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 1 institution in 1 country.

Norazaliza Mohd JamilCentre for Mathematical Sciences, College of Computing and Applied Sciences, Universiti Malaysia Pahang, Gambang. norazaliza@ump.edu.my.
Norhayati RosliCentre for Mathematical Sciences, College of Computing and Applied Sciences, Universiti Malaysia Pahang, Gambang. norhayati@ump.edu.my.
Noryanti MuhammadCentre for Mathematical Sciences, College of Computing and Applied Sciences, Universiti Malaysia Pahang, Gambang. noryanti@ump.edu.my.
Universiti Malaysia Pahang Al-Sultan Abdullah · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis research aimed to model the outbreak of COVID-19 in Malaysia and develop a GUI-based model. DESIGN AND

methodsThe model is an improvement of the susceptible, infected, recovery, and death (SIRD) compartmental model.  The epidemiological parameters of the infection, recovery, and death rates were formulated as time dependent piecewise functions by incorporating the control measures of lockdown, social distancing, quarantine, lockdown lifting time and the percentage of people who abide by the rules. An improved SIRD model was solved via the 4th order Runge-Kutta (RK4) method and 14 unknown parameters were estimated by using Nelder-Mead algorithm and pattern-search technique. The publicly available data for COVID-19 outbreak in Malaysia was used to validate the performance of the model. The GUI-based SIRD model was developed to simulate the number of active cases of COVID-19 over time by considering movement control order (MCO) lifted date and the percentage of people who abide the rules.

resultsThe simulator showed that the improved SIRD model adequately fitted Malaysia COVID-19 data indicated by low values of root mean square error (RMSE) as compared to other existing models. The higher the percentage of people following the SOP, the lower the spread of disease. Another key point is that the later the lifting time after the lockdown, the lower the spread of disease.

conclusionsThese findings highlight the importance of the society to obey the intervention measures in preventing the spread of the COVID-19 disease.

Identifiers

PMID34558879
PMCPMC8859730
OpenAlexW3200421000

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

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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.