Evidence map›Paper›PMID 33396519›Full record

ReviewBiosensors2020

Survey of Saliva Components and Virus Sensors for Prevention of COVID-19 and Infectious Diseases.

Priya Kishor Dave, Roberto Rojas-Cessa, Ziqian Dong, Vatcharapan Umpaichitra

Open access · goldAbstract readReview
In one paragraph

Review in Biosensors, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.5field-weighted citation impact, top 20% 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

9 citing papers in PubMed, 33 citations in OpenAlex.

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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

4 authors at 3 institutions in 1 country.

Priya Kishor DaveNetworking Research Laboratory, Department of Electrical and Computer Engineering, New Jersey Institute of Technology, NJ 07102, USA.ORCID 0000-0001-8355-150X
Roberto Rojas-CessaNetworking Research Laboratory, Department of Electrical and Computer Engineering, New Jersey Institute of Technology, NJ 07102, USA.ORCID 0000-0001-6075-9869
Ziqian DongDepartment of Electrical and Computer Engineering, New York Institute of Technology, New York, NY 10023, USA.ORCID 0000-0003-3937-1311
Vatcharapan UmpaichitraDepartment of Pediatrics, State University of New York (SUNY) Downstate Health Sciences University, Brooklyn, NY 11203, USA.ORCID 0000-0002-2754-8215
New Jersey Institute of Technology · USNew York Institute of Technology · USState University of New York · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The United States Centers for Disease Control and Prevention considers saliva contact the lead transmission means of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease 2019 (COVID-19). Saliva droplets or aerosols expelled by heavy breathing, talking, sneezing, and coughing may carry this virus. People in close distance may be exposed directly or indirectly to these droplets, especially those droplets that fall on surrounding surfaces and people may end up contracting COVID-19 after touching the mucosa tissue on their faces. It is of great interest to quickly and effectively detect the presence of SARS-CoV-2 in an environment, but the existing methods only work in laboratory settings, to the best of our knowledge. However, it may be possible to detect the presence of saliva in the environment and proceed with prevention measures. However, detecting saliva itself has not been documented in the literature. On the other hand, many sensors that detect different organic components in saliva to monitor a person's health and diagnose different diseases that range from diabetes to dental health have been proposed and they may be used to detect the presence of saliva. This paper surveys sensors that detect organic and inorganic components of human saliva. Humidity sensors are also considered in the detection of saliva because a large portion of saliva is water. Moreover, sensors that detect infectious viruses are also included as they may also be embedded into saliva sensors for a confirmation of the virus' presence. A classification of sensors by their working principle and the substance they detect is presented. This comparison lists their specifications, sample size, and sensitivity. Indications of which sensors are portable and suitable for field application are presented. This paper also discusses future research and challenges that must be resolved to realize practical saliva sensors. Such sensors may help minimize the spread of not only COVID-19 but also other infectious diseases.

Indexed as

Biological MonitoringCommunicable DiseasesCOVID-19HumansInfluenza A Virus, H1N1 SubtypeSalivaSARS-CoV-2VirusesCOVID-19droplet detectionhuman salivahumidity sensormulti-modal saliva detectionsaliva sensorSARS-CoV-2 detectionvirus detectionvirus sensor

Identifiers

PMID33396519
PMCPMC7824170
OpenAlexW3116116376

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.