Please use this identifier to cite or link to this item:
doi:10.22028/D291-33449
Title: | A Comprehensive Review of Detection Methods for SARS-CoV-2 |
Author(s): | Eftekhari, Aziz Alipour, Mahdieh Chodari, Leila Maleki Dizaj, Solmaz Ardalan, Mohammadreza Samiei, Mohammad Sharifi, Simin Zununi Vahed, Sepideh Huseynova, Irada Khalilov, Rovshan Ahmadian, Elham Cucchiarini, Magali |
Language: | English |
Title: | Microorganisms |
Volume: | 9 |
Issue: | 2 |
Publisher/Platform: | MDPI |
Year of Publication: | 2021 |
Free key words: | COVID-19 coronavirus detection epidemic nanotechnology |
DDC notations: | 610 Medicine and health |
Publikation type: | Journal Article |
Abstract: | Recently, the outbreak of the coronavirus disease 2019 (COVID-19), caused by the SARSCoV-2 virus, in China and its subsequent spread across the world has caused numerous infections and deaths and disrupted normal social activity. Presently, various techniques are used for the diagnosis of SARS-CoV-2 infection, with various advantages and weaknesses to each. In this paper, we summarize promising methods, such as reverse transcription-polymerase chain reaction (RT-PCR), serological testing, point-of-care testing, smartphone surveillance of infectious diseases, nanotechnology-based approaches, biosensors, amplicon-based metagenomic sequencing, smartphone, and wastewaterbased epidemiology (WBE) that can also be utilized for the detection of SARS-CoV-2. In addition, we discuss principles, advantages, and disadvantages of these detection methods, and highlight the potential methods for the development of additional techniques and products for early and fast detection of SARS-CoV-2. |
DOI of the first publication: | 10.3390/microorganisms9020232 |
Link to this record: | urn:nbn:de:bsz:291--ds-334491 hdl:20.500.11880/30755 http://dx.doi.org/10.22028/D291-33449 |
ISSN: | 2076-2607 |
Date of registration: | 1-Mar-2021 |
Faculty: | M - Medizinische Fakultät |
Department: | M - Orthopädie |
Professorship: | M - Prof. Dr. Henning Madry |
Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
Files for this record:
File | Description | Size | Format | |
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microorganisms-09-00232-v2.pdf | 1,58 MB | Adobe PDF | View/Open |
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