Evidence map›Paper›PMID 34676263›Full record

ArticleBioMed research international2021

Extended Epidemiological Models for Weak Economic Region: Case Studies of the Spreading of COVID-19 in the South Asian Subcontinental Countries.

Shafayat Bin Shabbir Mugdha, Mahtab Uddin, Md Toriqul Islam

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 43% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Shafayat Bin Shabbir MugdhaDepartment of Computer Science & Engineering, United International University, Dhaka 1212, Bangladesh.ORCID https://orcid.org/0000-0002-9379-6823
Mahtab UddinInstitute of Natural Sciences, United International University, Dhaka 1212, Bangladesh.ORCID https://orcid.org/0000-0002-6526-9276
Md Toriqul IslamDepartment of Mathematics, Bangladesh University of Engineering & Technology, Dhaka 1000, Bangladesh.ORCID https://orcid.org/0000-0002-3696-5109
Bangladesh University of Engineering and Technology · BDDhaka International University · BD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ascendancy of coronavirus has become widespread all around the world. For the prevention of viral transmission, the pattern of disease is explored. Epidemiological modeling is a vital component of the research. These models assist in studying various aspects of infectious diseases, such as death, recovery, and infection rates. Coronavirus trends across several countries may analyze sufficiently using SIR, SEIR, and SIQR models. Across this study, we propose two modified versions of the SEIRD method for evaluating the transmission of this infectious disease in the South Asian countries, more precisely, in the south Asian subcontinent. The SEIRD model is updated further by fusing some new factors, namely, isolation for the suspected people and recovery and death of the people who are not under the coverage of healthcare schemes or reluctant to receive treatment for various catastrophes. We will investigate the influences of those ingredients on public health-related issues. Finally, we will predict and display the infection scenario and relevant elements with the concluding remarks through the statistical analysis.

Indexed as

Models, TheoreticalAsiaBangladeshCOVID-19Developing CountriesHumansInfection ControlPhysical DistancingPublic Health

Identifiers

PMID34676263
PMCPMC8526245
OpenAlexW3207121435

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.