Current state of Diagnostic, Screening and Surveillance Testing Methods for COVID-19
      from an Analytical Chemistry Point of View

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Abstract

Since December 2019, we have been in the battlefield with a new threat to the humanity known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this review, we describe the four main methods used for diagnosis, screening and/or surveillance of SARS-CoV-2: Real-time reverse transcription polymerase chain reaction (RT-PCR); chest computed tomography (CT); and different complementary alternatives developed in order to obtain rapid results, antigen and antibody detection. All of them compare the highlighting advantages and disadvantages from an analytical point of view. The gold standard method in terms of sensitivity and specificity is the RT-PCR. The different modifications propose to make it more rapid and applicable at point of care (POC) are also presented and discussed. CT images are limited to central hospitals. However, being combined with RT-PCR is the most robust and accurate way to confirm COVID-19 infection. Antibody tests, although unable to provide reliable results on the status of the infection, are suitable for carrying out maximum screening of the population in order to know the immune capacity. More recently, antigen tests, less sensitive than RT-PCR, have been authorized to determine in a quicker way whether the patient is infected at the time of analysis and without the need of specific instruments.

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Deep learning.

Yann LeCun, Yoshua Bengio, Geoffrey E Hinton (2015)

Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Deep learning discovers intricate structure in large data sets by using the backpropagation algorithm to indicate how a machine should change its internal parameters that are used to compute the representation in each layer from the representation in the previous layer. Deep convolutional nets have brought about breakthroughs in processing images, video, speech and audio, whereas recurrent nets have shone light on sequential data such as text and speech.

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Aerosol and Surface Stability of SARS-CoV-2 as Compared with SARS-CoV-1

Neeltje van Doremalen, Trenton Bushmaker, Dylan H Morris … (2021)

To the Editor: A novel human coronavirus that is now named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (formerly called HCoV-19) emerged in Wuhan, China, in late 2019 and is now causing a pandemic. 1 We analyzed the aerosol and surface stability of SARS-CoV-2 and compared it with SARS-CoV-1, the most closely related human coronavirus. 2 We evaluated the stability of SARS-CoV-2 and SARS-CoV-1 in aerosols and on various surfaces and estimated their decay rates using a Bayesian regression model (see the Methods section in the Supplementary Appendix, available with the full text of this letter at NEJM.org). SARS-CoV-2 nCoV-WA1-2020 (MN985325.1) and SARS-CoV-1 Tor2 (AY274119.3) were the strains used. Aerosols (<5 μm) containing SARS-CoV-2 (105.25 50% tissue-culture infectious dose [TCID50] per milliliter) or SARS-CoV-1 (106.75-7.00 TCID50 per milliliter) were generated with the use of a three-jet Collison nebulizer and fed into a Goldberg drum to create an aerosolized environment. The inoculum resulted in cycle-threshold values between 20 and 22, similar to those observed in samples obtained from the upper and lower respiratory tract in humans. Our data consisted of 10 experimental conditions involving two viruses (SARS-CoV-2 and SARS-CoV-1) in five environmental conditions (aerosols, plastic, stainless steel, copper, and cardboard). All experimental measurements are reported as means across three replicates. SARS-CoV-2 remained viable in aerosols throughout the duration of our experiment (3 hours), with a reduction in infectious titer from 103.5 to 102.7 TCID50 per liter of air. This reduction was similar to that observed with SARS-CoV-1, from 104.3 to 103.5 TCID50 per milliliter (Figure 1A). SARS-CoV-2 was more stable on plastic and stainless steel than on copper and cardboard, and viable virus was detected up to 72 hours after application to these surfaces (Figure 1A), although the virus titer was greatly reduced (from 103.7 to 100.6 TCID50 per milliliter of medium after 72 hours on plastic and from 103.7 to 100.6 TCID50 per milliliter after 48 hours on stainless steel). The stability kinetics of SARS-CoV-1 were similar (from 103.4 to 100.7 TCID50 per milliliter after 72 hours on plastic and from 103.6 to 100.6 TCID50 per milliliter after 48 hours on stainless steel). On copper, no viable SARS-CoV-2 was measured after 4 hours and no viable SARS-CoV-1 was measured after 8 hours. On cardboard, no viable SARS-CoV-2 was measured after 24 hours and no viable SARS-CoV-1 was measured after 8 hours (Figure 1A). Both viruses had an exponential decay in virus titer across all experimental conditions, as indicated by a linear decrease in the log10TCID50 per liter of air or milliliter of medium over time (Figure 1B). The half-lives of SARS-CoV-2 and SARS-CoV-1 were similar in aerosols, with median estimates of approximately 1.1 to 1.2 hours and 95% credible intervals of 0.64 to 2.64 for SARS-CoV-2 and 0.78 to 2.43 for SARS-CoV-1 (Figure 1C, and Table S1 in the Supplementary Appendix). The half-lives of the two viruses were also similar on copper. On cardboard, the half-life of SARS-CoV-2 was longer than that of SARS-CoV-1. The longest viability of both viruses was on stainless steel and plastic; the estimated median half-life of SARS-CoV-2 was approximately 5.6 hours on stainless steel and 6.8 hours on plastic (Figure 1C). Estimated differences in the half-lives of the two viruses were small except for those on cardboard (Figure 1C). Individual replicate data were noticeably “noisier” (i.e., there was more variation in the experiment, resulting in a larger standard error) for cardboard than for other surfaces (Fig. S1 through S5), so we advise caution in interpreting this result. We found that the stability of SARS-CoV-2 was similar to that of SARS-CoV-1 under the experimental circumstances tested. This indicates that differences in the epidemiologic characteristics of these viruses probably arise from other factors, including high viral loads in the upper respiratory tract and the potential for persons infected with SARS-CoV-2 to shed and transmit the virus while asymptomatic. 3,4 Our results indicate that aerosol and fomite transmission of SARS-CoV-2 is plausible, since the virus can remain viable and infectious in aerosols for hours and on surfaces up to days (depending on the inoculum shed). These findings echo those with SARS-CoV-1, in which these forms of transmission were associated with nosocomial spread and super-spreading events, 5 and they provide information for pandemic mitigation efforts.

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Virological assessment of hospitalized patients with COVID-2019

Roman Wölfel, Victor M Corman, Wolfgang Guggemos … (2020)

Coronavirus disease 2019 (COVID-19) is an acute infection of the respiratory tract that emerged in late 20191,2. Initial outbreaks in China involved 13.8% of cases with severe courses, and 6.1% of cases with critical courses3. This severe presentation may result from the virus using a virus receptor that is expressed predominantly in the lung2,4; the same receptor tropism is thought to have determined the pathogenicity-but also aided in the control-of severe acute respiratory syndrome (SARS) in 20035. However, there are reports of cases of COVID-19 in which the patient shows mild upper respiratory tract symptoms, which suggests the potential for pre- or oligosymptomatic transmission6-8. There is an urgent need for information on virus replication, immunity and infectivity in specific sites of the body. Here we report a detailed virological analysis of nine cases of COVID-19 that provides proof of active virus replication in tissues of the upper respiratory tract. Pharyngeal virus shedding was very high during the first week of symptoms, with a peak at 7.11 × 108 RNA copies per throat swab on day 4. Infectious virus was readily isolated from samples derived from the throat or lung, but not from stool samples-in spite of high concentrations of virus RNA. Blood and urine samples never yielded virus. Active replication in the throat was confirmed by the presence of viral replicative RNA intermediates in the throat samples. We consistently detected sequence-distinct virus populations in throat and lung samples from one patient, proving independent replication. The shedding of viral RNA from sputum outlasted the end of symptoms. Seroconversion occurred after 7 days in 50% of patients (and by day 14 in all patients), but was not followed by a rapid decline in viral load. COVID-19 can present as a mild illness of the upper respiratory tract. The confirmation of active virus replication in the upper respiratory tract has implications for the containment of COVID-19.

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Author and article information

Journal

Journal ID (nlm-ta): Microchem J

Journal ID (iso-abbrev): Microchem J

Title: Microchemical Journal

Publisher: Elsevier B.V.

ISSN (Print): 0026-265X

ISSN (Electronic): 1095-9149

Publication date PMC-release: 19 April 2021

Publication date (Electronic): 19 April 2021

Electronic Location Identifier: 106305

Affiliations

[a ]Departamento de Química Analítica, Escuela Politécnica Superior, Universidad de Sevilla, C/ Virgen de África 7, Sevilla, E-41011, España

[b ]Departamento de Química Analítica, Facultad de Farmacia, Universidad de Sevilla, Prof. García González, 2, Sevilla, 41012, España

Author notes

[* ]Corresponding author.

Article

Publisher Item ID: S0026-265X(21)00389-1 Publisher ID: 106305

DOI: 10.1016/j.microc.2021.106305

PMC ID: 8054532

PubMed ID: 33897053

SO-VID: 0ceaed1e-4710-4ee4-b84f-7c80004eff70

License:

Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

History

Date received : 10 February 2021

Date revision received : 12 April 2021

Date accepted : 14 April 2021

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Subject: Article

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Keywords: covid-19, sars-cov-2, rt-pcr, chest computerized tomography, antigen and antibody tests, 2019-ncov, 2019 novel coronavirus, ace2, angiotensin-converting enzyme 2, ai, artificial intelligence, alp, alkaline phosphatase, am, attomolar, asos, antisense oligonucleotides, aunis, gold nanoislands, aunps, gold nanoparticles, bsl, biosecurity level, cap, college of american pathologists, cas, crispr associate protein, ccd, charge-coupled device, cg, colloidal gold, cgia, colloidal gold immunochromatographic assay, china cdc, chinese center for disease control and prevention, clia, chemiluminescence enzyme immunoassay, clia, clinical laboratory improvement amendments, covid-19, coronavirus disease-19, crispr, clustered regularly interspaced short palindromic repeats, ct, chest computed tomography, ct, cycle threshold, detectr, sars-cov-2 dna endonuclease-targeted crispr trans reporter, dna, dexosyrosyribonucleic acid, dntps, nucleotides, ddpcr, droplet digital pcr, dpcr, digital pcr, e, envelope protein, elisa, enzyme linked immunosorbent assay, ema, european medicines agency, eua, emergence use authorization, fda, food and drug administration, fet, field-effect transistor, fm, femtomolar, genebank, genetic sequence data base of the national institute of health, gisaid, global initiative on sharing all influenza data, ictv, international committee on taxonomy of viruses, iga, immunoglobulins a, igg, immunoglobulins g, igm, immunoglobulins m, iomt, internet of medical things, iot, internet of things, lfia, lateral flow immunochromatographic assays, loc, lab-on-a-chip, lod, limit of detection, lspr, localized surface plasmon resonance, m, membrane protein, mers-cov, middle east respiratory syndrome coronavirus, mnp, magnetic nanoparticle, m-rna, messenger ribonucleic acid, ms, mass spectrometry, n, nucleocapsid protein, ner, naked eye readout, net, neural network, ngm, next generation molecular, ngs, next generation sequencing, nih, national institute of health, nm, nanomolar, nsps, nonstructural proteins, orf, open reading frame, osn, one step single-tube nested, pdms, polydimethylsiloxane, pfu, plaque-forming unit, pm, picomolar, poc, point of care, ppt, plasmonic photothermal, qd, quantum dot, rbd, receptor-binding domain, rdrp, rna-dependent rna polymerase, rn, recombinant nucleocapsid protein antigen, rna, ribonucleic acid, rnaseh, ribonuclease h, rs, recombinant spike protein antigen, r0, basic reproductive number, rt, reverse transcriptase, rt-lamp, reverse transcription loop-mediated isothermal amplification, rt-pcr, real-time reverse transcription polymerase chain reaction, s, spike protein, sars-cov-2, severe acute respiratory syndrome coronavirus 2, sers, surface enhanced raman spectroscopy, sherlock, specific high sensitivity enzymatic reporter unlocking, sio2@ag, complete silver nanoparticle shell coated on silica core, ssrna, single-stranded positive-sense rna, stopcovid, sherlock testing on one pot, svm, support vector machine, us cdc, us centers for disease control and prevention, voc, variant of concern, vtm, viral transport medium, wgs, whole genome sequencing, who, world health organization

Current state of Diagnostic, Screening and Surveillance Testing Methods for COVID-19 from an Analytical Chemistry Point of View

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Novel Coronavirus Disease COVID-19

Most cited references 160

Deep learning.

Aerosol and Surface Stability of SARS-CoV-2 as Compared with SARS-CoV-1

Virological assessment of hospitalized patients with COVID-2019

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