Evidence map›Paper›PMID 35941912›Full record

ArticleEngineering reports : open access2022

Epidemic trend analysis of SARS-CoV-2 in South Asian Association for Regional Cooperation countries using modified susceptible-infected-recovered predictive model.

Samrat Kumar Dey, Md Mahbubur Rahman, Kabid Hassan Shibly, Umme Raihan Siddiqi, Arpita Howlader

Open access · goldAbstract read
In one paragraph

Article in Engineering reports : open access, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 41% 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, 4 citations in OpenAlex.

  1. 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

5 authors at 5 institutions in 2 countries.

Samrat Kumar DeySchool of Science and Technology (SST) Bangladesh Open University (BOU) Gazipur Bangladesh.ORCID https://orcid.org/0000-0002-7999-8576
Md Mahbubur RahmanDepartment of Computer Science and Engineering (CSE) Military Institute of Science and Technology (MIST) Dhaka Bangladesh.
Kabid Hassan ShiblyLaboratory for Cyber Resilience Nara Institute of Science and Technology (NAIST) Nara Japan.
Umme Raihan SiddiqiDepartment of Physiology Shaheed Suhrawardy Medical College (ShSMC) Dhaka Bangladesh.
Arpita HowladerDepartment of Computer and Communication Engineering (CCE) Patuakhali Science and Technology University (PSTU) Dumki Patuakhali Bangladesh.
Bangladesh Open University · BDDhaka University of Engineering & Technology · BDNara Institute of Science and Technology · JPPatuakhali Science and Technology University · BDShaheed Suhrawardy Medical College · BD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel coronavirus causing the severe and fatal respiratory syndrome was identified in China, is now producing outbreaks in more than 200 countries around the world, and became pandemic by the time. In this article, a modified version of the well-known mathematical epidemic model susceptible-infected-recovered (SIR) is used to analyze the epidemic's course of COVID-19 in eight different countries of the South Asian Association for Regional Cooperation (SAARC). To achieve this goal, the parameters of the SIR model are identified by using publicly available data for the corresponding countries: Afghanistan, Bangladesh, Bhutan, India, the Maldives, Nepal, Pakistan, and Sri Lanka. Based on the prediction model, we estimated the epidemic trend of COVID-19 outbreak in SAARC countries for 20, 90, and 180 days, respectively. A short-mid-long term prediction model has been designed to understand the early dynamics of the COVID-19 epidemic in the southeast Asian region. The maximum and minimum basic reproduction numbers (

Indexed as

COVID‐19epidemicsmodified susceptible‐infected‐recoveredprediction modelSAARCSARS‐CoV‐2

Identifiers

PMID35941912
PMCPMC9349771
OpenAlexW4285005955

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.