Evidence map›Paper›PMID 34900606›Full record

ArticleMaterials today. Proceedings2022

A mathematical model of COVID-19 transmission.

R Jayatilaka, R Patel, M Brar, Y Tang, N M Jisrawi, F Chishtie, J Drozd, S R Valluri

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Materials today. Proceedings, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

2 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
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

8 authors at 2 institutions in 1 country.

R JayatilakaDepartment of Physics and Astronomy, University of Western Ontario, 1151 Richmond Street, London N6A 3K7, Canada.
R PatelDepartment of Physics and Astronomy, University of Western Ontario, 1151 Richmond Street, London N6A 3K7, Canada.
M BrarDepartment of Physics and Astronomy, University of Western Ontario, 1151 Richmond Street, London N6A 3K7, Canada.
Y TangDepartment of Physics and Astronomy, University of Western Ontario, 1151 Richmond Street, London N6A 3K7, Canada.
N M JisrawiDepartment of Physics and Astronomy, University of Western Ontario, 1151 Richmond Street, London N6A 3K7, Canada.
F ChishtieDepartment of Applied Mathematics, University of Western Ontario, Canada.
J DrozdMathematics Department, Huron University College, UWO, London N6G 1H3, Canada.
S R ValluriDepartment of Physics and Astronomy, University of Western Ontario, 1151 Richmond Street, London N6A 3K7, Canada.
Western University · CAKing's University College · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Disease transmission is studied through disciplines like epidemiology, applied mathematics, and statistics. Mathematical simulation models for transmission have implications in solving public and personal health challenges. The SIR model uses a compartmental approach including dynamic and nonlinear behavior of transmission through three factors: susceptible, infected, and removed (recovered and deceased) individuals. Using the Lambert W Function, we propose a framework to study solutions of the SIR model. This demonstrates the applications of COVID-19 transmission data to model the spread of a real-world disease. Different models of disease including the SIR, SIRmp and SEIRρqr model are compared with respect to their ability to predict disease spread. Physical distancing impacts and personal protection equipment use are discussed with relevance to the COVID-19 spread.

Indexed as

Disease transmissionLambert W functionNonlinear differential equationsSEIRρqr modelSIR model

Identifiers

PMID34900606
PMCPMC8642156
OpenAlexW4206733432

What OpenQuestion holds

Textmetadata
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.