Evidence map›Paper›PMID 35782716›Full record

ArticleIEEE transactions on molecular, biological, and multi-scale communications2021

Molecular Communication Theoretical Modeling and Analysis of SARS-CoV2 Transmission in Human Respiratory System.

Caglar Koca, Meltem Civas, Selin Merve Sahin, Onder Ergonul, Ozgur B Akan

Abstract read
In one paragraph

Article in IEEE transactions on molecular, biological, and multi-scale communications, 2021. 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
–field-weighted citation impact
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.

  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

5 authors.

Caglar KocaInternet of Everything Group, Electrical Engineering DivisionDepartment of EngineeringUniversity of Cambridge Cambridge CB2 1PZ U.K.ORCID https://orcid.org/0000-0002-8592-0943
Meltem CivasNext-Generation and Wireless Communications LaboratoryDepartment of Electrical and Electronics EngineeringKoç University 34450 Istanbul Turkey.ORCID https://orcid.org/0000-0001-6248-773X
Selin Merve SahinSchool of MedicineKoç University 34450 Istanbul Turkey.ORCID https://orcid.org/0000-0002-2282-5527
Onder ErgonulSchool of MedicineDepartment of Infectious Diseases and Clinical MicrobiologyKoç University 34450 Istanbul Turkey.
Ozgur B AkanResearch Centre for Infectious DiseasesKoç University 34450 Istanbul Turkey.ORCID https://orcid.org/0000-0003-2523-3858

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Severe Acute Respiratory Syndrome-CoronaVirus 2 (SARS-CoV2) caused the ongoing pandemic. This pandemic devastated the world by killing more than a million people, as of October 2020. It is imperative to understand the transmission dynamics of SARS-CoV2 so that novel and interdisciplinary prevention, diagnostic, and therapeutic techniques could be developed. In this work, we model and analyze the transmission of SARS-CoV2 through the human respiratory tract from a molecular communication perspective. We consider that virus diffusion occurs in the mucus layer so that the shape of the tract does not have a significant effect on the transmission. Hence, this model reduces the inherent complexity of the human respiratory system. We further provide the impulse response of SARS-CoV2-ACE2 receptor binding event to determine the proportion of the virus population reaching different regions of the respiratory tract. Our findings confirm the results in the experimental literature on higher mucus flow rate causing virus migration to the lower respiratory tract. These results are especially important to understand the effect of SARS-CoV2 on the different human populations at different ages who have different mucus flow rates and ACE2 receptor concentrations in the different regions of the respiratory tract.

Indexed as

2019-n-Covmolecular communicationSARS-CoV2

Identifiers

PMID35782716
PMCPMC8544952

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.