Diagnostic accuracy of a SARS-CoV-2 rapid antigen test among military and civilian personnel of an Air Force airport in central Italy

Paola Verde; Cinzia Marcantonio; Angela Costantino; Antonio Martina; Matteo Simeoni; Stefania Taffon; Elena Tritarelli; Carmelo Campanella; Raffaele Cresta; Roberto Bruni; Anna Rita Ciccaglione; Giulio Pisani; Roberto Nisini; Enea Spada

doi:10.1371/journal.pone.0277904

. 2022 Nov 28;17(11):e0277904. doi: 10.1371/journal.pone.0277904

Diagnostic accuracy of a SARS-CoV-2 rapid antigen test among military and civilian personnel of an Air Force airport in central Italy

Paola Verde ¹, Cinzia Marcantonio ^2,^#, Angela Costantino ^2,^#, Antonio Martina ^3,^#, Matteo Simeoni ^3,^#, Stefania Taffon ², Elena Tritarelli ², Carmelo Campanella ⁴, Raffaele Cresta ⁴, Roberto Bruni ², Anna Rita Ciccaglione ², Giulio Pisani ³, Roberto Nisini ², Enea Spada ^2,^*

Editor: Etsuro Ito⁵

PMCID: PMC9704652 PMID: 36441672

Abstract

Background

Most SARS-CoV-2 rapid antigen detection tests (RADTs) validation studies have been performed on specimens from COVID-19 patients and negative controls or from mostly symptomatic individuals. Herein we evaluated the diagnostic accuracy of AFIAS COVID-19 Ag, hereinafter denominated as AFIAS, during a COVID-19 screening program surveillance testing conducted among personnel of an Italian military airport.

Methods

Nasopharyngeal swabs (NPSs) were collected from study participants and were analysed by both AFIAS and RT-PCR assay. A questionnaire collecting demographic and exposure data were administered to all participants. AFIAS accuracy parameters including Cohen’s kappa (K) were determined.

Results

Overall, from November 2020 to April 2021, 1294 (NPSs) were collected from 1183 participants (88.6% males, 11.4% females; mean age were 41.3, median age 42). Forty-nine NPSs (3.78%) were positive by RT-PCR, while 54 NPSs were positive by AFIAS. Overall baseline sensitivity, specificity, positive and negative predictive values were 0.633, 0.981, 0.574, 0.985, respectively and K was 0.585 (moderate). AFIAS sensitivity tended to be higher for NPSs with higher viral load. A higher sensitivity (0.944) compared to the overall baseline sensitivity (0.633) was also found for NPSs from participants with COVID-19 compatible symptoms, for which K was 0.891 (almost perfect). Instead, AFIAS sensitivity was quite poor for NPSs from asymptomatic participants. Most false negative NPSs in this group had moderate viral load.

Conclusion

Overall, AFIAS showed high specificity but only moderate sensitivity, mainly because of the high proportion of asymptomatic participants. However, AFIAS showed good sensitivity for NPSs with high viral load and nearly optimal accuracy parameters for NPSs from participants with COVID-19 compatible symptoms. Thus, taking into consideration its performance features, this test can be useful for COVID-19 case identification and management as well as for infection control.

Introduction

The availability of diagnostic assays for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enabling the identification and effective isolation of COVID-19 cases and the systematic tracing of their close contacts has been critical to mitigate the spread of SARS-CoV-2 infection during the still ongoing pandemic [1, 2].

Nucleic acid amplification techniques (NAATs), like Reverse Transcriptase Real Time Polymerase Chain Reaction (RT-PCR) on nasopharyngeal swabs (NPSs) currently represent the gold standard for SARS-CoV-2 infection diagnosis [3–5]. Unfortunately, performing RT-PCR takes about 3–4 hours and requires special equipment, instruments and skilled laboratory personnel [6]. Furthermore, RT-PCR is costly and subject to reagent and material shortages [7].

Numerous Rapid Antigen Detection Tests (RADTs) have been also developed to diagnose SARS-CoV-2 infection. RADTS have proved particularly suitable as point of care tests (POCT), since they are economical, not requiring the use of particularly complex instrumentation, and have shorter turnaround time (less than 30 minutes). RADTs are primarily lateral flow immunochromatographic assays that detect viral antigen in NPSs by means of a device coated with anti-SARS-CoV-2 antibody [6–17].

Nevertheless, RADTs have demonstrated lower sensitivity for the detection of SARS-CoV-2 in NPSs compared to NAATs. According to a recent systematic review, the average sensitivity and specificity of RADTs were 0.562 and 0.995, respectively [13]. In general, RADTs perform well in NPSs with high viral load or with low cycle threshold (Ct) in RT-PCR for SARS-CoV-2 tests [6–17]. The Ct refers to the number of cycles needed to amplify a fragment of viral genome to reach a threshold level. Ct value provides an indicative measure of viral quantity in the specimen and it is inversely correlated to the original concentration of viral genome in sample tested by RT-PCR. According to the expectations of the European Center of Disease Prevention and Control (ECDC) the implementation of RADTs can serve for the prompt clinical management of cases with COVID-19-compatible symptoms at admission, early detection and isolation of cases and contact tracing [18–20]. In agreement with ECDC and World Health Organization (WHO) [21], Italy has started considering RADTs for diagnosis of symptomatic cases up to five days from symptom onset and, in case of negative result, confirmation with either RADT or molecular tests [22]. According to ECDC, RADTs are also used for case definition, in addition to NAATs [19–21].

The rapid AFIAS COVID-19 Ag (Boditech Med Inc., Chuncheon-si, Gang-won-do, Republic of Korea), hereinafter denominated as AFIAS, is a fluorescence immunoassay designed to detect SARS-CoV-2 antigen in human NPSs within 20 minutes. Thus, although the test requires a fluorescence reader, the running time from sample to result is comparable to traditional RADTs; however, it provides the added value that the result is not subject to the operator’s interpretation. In fact, the positive/negative output of the fluorescence reader is automatic, based on an algorithm comparing the fluorescence obtained from the sample to a cut-off value; in the traditional RADTs, the operator can see more or less well a faint colored band of positivity. This assay has been already included in the Health Security Committee (HSC) Technical Working Group (TWG) common list of antigenic tests, whose results are mutually recognized by European States for public health measures, including issuing European Union (EU) Digital COVID certificate [18, 23].

The aim of this study is to assess the diagnostic accuracy of the AFIAS in comparison to the RT-PCR for detection of SARS-CoV-2 infection in NPSs obtained from military and civilian personnel of a military airport in the metropolitan area of Rome. Differently from similar studies evaluating the performance of RADTs, the study population was unselected and mostly asymptomatic.

Methods

Study population

From November 2020 to April 2021, the military and civilian personnel of the “Mario De Bernardi” military airport, located in the metropolitan area of Rome, underwent a screening program to control transmission of SARS-CoV-2 infection in the workplace. The study was part of the public health response to control as soon as possible any outbreak occurring in the military airport (as reported in the Scientific Collaboration Protocol signed by the Experimental Flight Center, Italian Air Force Logistic Command and Istituto Superiore di Sanità on 30 November 2020), with simultaneous evaluation of the RADT used for the screening. According to the national legislation [24–26], testing was performed locally by a first-line rapid antigen test, then positive and negative NPSs were sent to the Istituto Superiore di Sanità (ISS) for confirmation of positive results by NAAT and evaluation of antigen test performance. To assess the accuracy of AFIAS, NPSs were collected from study participants were analysed by both rapid antigen test and RT-PCR assay. All participants were also asked to fill a questionnaire including demographic data, symptoms (if any) and potential exposure to infection (previous COVID-19, contact with proven COVID-19 cases or contact with persons who tested positive to SARS-CoV-2 by molecular or antigenic tests. These data were collected with the aim to characterize the study population and to assess AFIAS accuracy according to presence of symptoms suggestive of COVID-19 and infection exposure. The study protocol was approved and signed by the Scientific Collaboration Partners (i.e. Experimental Flight Center, Italian Air Force Logistic Command and Istituto Superiore di Sanità) on 30 November 2020. Personal data were collected and processed in compliance with EU and Italia legislation [27–29]. Written informed consent was obtained from all participants or the legally authorized representative. Testing, data collection and evaluation of antigen test performance were carried out as public health activities to improve tracing of infected individuals and contacts, with the aim of reducing viral transmission among personnel attending the military airport base.

Antigen assay for SARS-CoV-2

AFIAS (Boditech Med., Chuncheon-si, Gang-won-do, Republic of Korea) is an immunochromatographic, fluorescence-based rapid antigen test designed to detect the nucleocapsidprotein of SARS-CoV-2 in NP swab specimens. The assay includes an anti-SARS-CoV-2 monoclonal antibody that binds to the viral nucleocapsid protein.

The test was performed according to the manufacturers’ instructions. The antigen-antibody interaction leads to a fluorescence signal. Results were interpreted according to the cut-off index (COI), in particular COI <1.0 was interpreted as negative and COI ≥1.0 as positive.

SARS-CoV-2 molecular detection

The COVID-19 laboratory diagnosis was based on a RT-PCR test (RealStar® SARS-CoV-2 RT-PCR Kit 1.0, Altona Diagnostics) performed on RNA extracts to detect viral RNA. The kit contains all components to enable reverse transcription, PCR-mediated amplification and simultaneous detection of the B-βCoV specific RNA (target E gene) and the SARS-CoV-2 specific RNA (target S gene) as well as the internal control in a single reaction

RNA was extracted from 200μl of NPSs collected in Virus Transport Medium (VTM, Noble Bio, Hwaseong-si, Gyeonggi-do, Republic of Korea) using the QIAamp® MinElute® Virus Spin Kit (QIAGEN, Hilden, Germany).

Every sample was spiked with five μL of RNA Internal Extraction Control (RealStar® SARS-CoV-2 RT-PCR Kit 1.0, Altona Diagnostics) added to the AVL lysis buffer at the first extraction step as a control of nucleic acid extraction step and possible inhibition of RT-PCR. The second part of the nucleic acid purification was performed on the QIAcube instrument (QIAGEN Biotechnology & Life Science).

The extracted RNA was amplified by RT-PCR technology on the Rotor-Gene® instrument (QIAGEN, Hilden, Germany). NPSs with a detectable signal for at least one gene were considered SARS-CoV-2 positive. NPSs with no detectable signal for both genes were considered negative. NPSs with no detectable signal for both target genes and internal control were considered as inconclusive. When we assessed AFIAS accuracy for NPSs from the overall population as well as from the different subgroups of participants, we took also into account the overall median Ct value of both target genes of RT-PCR positive samples. This procedure aimed at assessing AFIAS performance parameters according to different Ct levels (i.e. above or below that median Ct value), has also been suggested by others authors [6, 30–33]. Furthermore, in our accuracy assessment we also considered the definitions for viral load present in the document from the TWG of the EU HSC [18]: very high (Ct≤25), high (Ct 26–30), moderate (Ct >30–36) and low viral load (Ct >36).

Statistical analysis

Continuous variables were expressed as median and range or as mean ± standard deviation (SD) and differences were compared using the Mann Whitney U test or t-test. Categorical variables were expressed as numbers and percentages and were compared using X² or Fisher’s exact test. A p value < 0.05 was considered significant. Agreement beyond the chance between AFIAS and RT-PCR results was evaluated calculating Cohn’s kappa index (K) interpreted according Landis & Koch [34]: <0, no agreement; 0–0.21, slight; 0.21–0.40, fair; 0.41–0.60, moderate; 0.61–0.80, substantial; 0.81–1.0, almost perfect. AFIAS sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+) and negative likelihood ratio (LR-) for NPSs from all study population and for those from the different population subgroups were calculated on contingency tables containing the numbers of each outcome. The confidence intervals (CI) were calculated using the Wilson-Brown method. All analyses were carried out using STATA version 15.0 (College Station, TX, USA)

Results

Overall diagnostic accuracy of AFIAS COVID-19 Ag

A total of 1294 NPSs were collected from 1183 individuals. Of them, 88.6% males, 11.4% females. Median and mean age were 42 (range 5–92) and 41.3 (± 10.8), respectively. However, 99.1% of the NPSs were from working age people (18–66 years). One hundred and 11 of the 1183 participants were tested twice and thrice in different occasions, respectively.

Of the 1294 NPSs assayed, 49 (75.5% males; mean age, 42.85 ± 13.8) were positive by RT-PCR assay indicating a SARS-CoV-2 prevalence of 3.78%. Fifty-four NPSs (4.17%) were positive by AFIAS, while 31 NPSs (2.39%) resulted positive by both these tests (true-positive) (Table 1). Eighteen and 23 NPSs resulted false-negative (RT-PCR+/AFIAS-) and false-positive (RT-PCR-/AFIAS+), respectively. The number of true-negative NPSs (RT-PCR-/AFIAS-) was 1222. Overall, AFIAS showed a good SP and NPV but a moderate SS and PPV. Percent agreement between the results of the AFIAS results and those of the reference test was nearly 0.97, but K was 0.585 (Table 1).

Table 1. Diagnostic accuracy of AFIAS COVID-19 Ag test assessed against RT-PCR assay.

				Prevalence %	3.78 (2.88–4.97)
	RT-PCR +	RT-PCR -	Total	SS	0.633 (0.493–0.753)
AFIAS +	31	23	54	SP	0.981 (0.972–0.987)
AFIAS -	18	1222	1240	PPV	0.574 (0.441–0.696)
Total	49	1245	1294	NPV	0.985 (0.972–0.990)
				LR+	34 (22–54)
				LR-	0.37 (0.26–0.54)
				% Agreement	0.969
				Cohen’s kappa	0.585 (0.470–0.701)
					(Moderate)

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AFIAS+, AFIAS COVID-19 Ag positive; AFIAS-, AFIAS COVID-19 Ag negative; COI, Cut Off Index, LR+, positive likelihood ratio; LR-, negative likelihood ratio; NPV, negative predictive value; PPV, positive predictive value; RT-PCR+, Real-time RT-PCR positive; RT-PCR-, Real-time RT-PCR negative; SS, sensitivity; SP, specificity.

Analysing in depth the comparison between the two tests (Table 2) − taking also into account the overall median Ct value of both target genes of RT-PCR positive NPSs (i.e., 22.34)–it was evident that positive NPSs with Ct ≤22.34 were detected by AFIAS with higher sensitivity compared to NPSs with Ct >22.34 (Ct ≤22.34, SS = 22/25 = 0.880 vs. Ct > 22.34, SS = 9/24 = 0.375; p = 0.00001).

Table 2. AFIAS COVID-19 Ag test sensitivity according to the median RT-PCR Ct value (22.34).

		≤22.34	>22.34
	RT-PCR +	RT-PCR +		RT-PCR -	Total
AFIAS +	31	22	9	23	54
AFIAS -	18	3	15	1222	1240
Total	49	25	24	1245	1294

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RT-PCR+ 49 NPSs (97 S and E gene positive amplifications); median Ct, 22.34; range Ct, 12.12–37.76

Ct ≤22.34: 22 NPSs RT-PCR+/AFIAS+; 3 NPSs RT-PCR+/AFIAS- SS = 22/25 = 0.880

Ct >22.34: 9 NPSs RT-PCR+/AFIAS+; 15 NPSs RT-PCR+/AFIAS- SS = 9/24 = 0.375

AFIAS +, AFIAS COVID-19 Ag positive; AFIAS -, AFIAS COVID-19 Ag negative; COI, Cut Off Index, LR+, positive likelihood ratio; LR-, negative likelihood ratio; NPV, negative predictive value; NPSs, Nasopharyngeal swabs; PPV, positive predictive value; RT-PCR+, Real-time RT-PCR positive; RT-PCR-, Real-time RT-PCR negative; SS, sensitivity; SP, specificity.

In agreement with this latter finding, Fig 1 shows as the Ct values for each of the two PCR target genes were significantly higher among NPSs with false-negative results than among NPSs with true-positive Ag results (S gene Ct/AFIAS Ag- vs S gene Ct/AFIAS Ag+, p = 0.00026; E gene Ct/AFIAS Ag- vs E gene Ct/AFIAS Ag+, p<0.00001).

Table 3 shows the distribution of the 49 RT-PCR positive NPSs, according to HSC TWG viral load cut-off and AFIAS results (i.e. true-positive or false-negative).

Table 3. RT-PCR positve NPSs according to HSC TWG Ct and AFIAS result.

Ct	Viral load	NPSs Ct range	N° RT-PCR +	N° TP	N° FN
≤25	Very high	12.12–24.86	32	26	6
26–30	High	25.07–29.90	5	3	2
>30–36	Moderate	30.02–34.10	11	2	9
>36	Low	37.62	1	0	1

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AFIAS, AFIAS COVID-19 Ag assay, NPSs, Nasopharingeal samples; N°, numero of samples

RT-PCR+, Real-time RT-PCR positive; FN, false-negative; TP, true-positive.

Diagnostic accuracy of AFIAS COVID-19 Ag according to presence or absence of symptoms suggestive of COVID-19

Apart from 73 NPSs taken from participants with symptoms suggestive of COVID-19 at the time of testing, the remaining 1221 NPSs were from asymptomatic participants

The diagnostic accuracy parameters for NPSs from symptomatic and asymptomatic participants are shown in Table 4.

Table 4. Diagnostic accuracy of AFIAS COVID-19 Ag test according to presence or absence of COVID-19 symptoms.

	NPSs from participants with symptoms suggestive of COVID-19					NPSs from participants without symptoms suggestive of COVID-19
		≤18.08^a	>18.08				≤26.00^b	>26.00
	RT-PCR+	RT-PCR+	RT-PCR+	RT-PCR-	Total	RT-PCR+	RT-PCR+	RT-PCR+	RT-PCR-	Total
AFIAS +	17	10	7	2	19	14	11	3	21	35
AFIAS -	1	0	1	53	54	17	5	12	1169	1186
Total	18	10	8	55	73	31	16	15	1190	1221
		95% CI					95% CI
Prevalence	24.66	16.20–35.64				2.54	1.79–3.58
SS	0.944	0.724–0.990				0.452	0.292–0.622
SP	0.964	0.877–0.990				0.982	0.973–0988
PPV	0.895	0.686–0.971				0.400	0.255–0.564
NPV	0.981	0.923–0.997				0.986	0.977–9.991
LR+	26	6.63–102				26	14–45
LR-	0.06	0.01–0.39				0.56	0.41–077
% Agreement	0.959	0.886–0.986				0.969	0.958–0.977
Cohen’s Kappa	0.891	0.771–1.000		Almost perfect		0.408	0.256–0.561		Moderate

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AFIAS +, AFIAS COVID-19 Ag positive; AFIAS -, AFIAS COVID-19 Ag negative; COI, Cut Off Index, LR+, positive likelihood ratio; LR-, negative likelihood ratio; NPSs, nasopharyngeal swabs, NPV, negative predictive value; PPV, positive predictive value; RT-PCR+, Real-time RT-PCR positive; RT-PCR-, Real-time RT-PCR negative; SS, sensitivity; SP, specificity.

^amedian Ct value for NPSs from RT-PCR positive participants with symptoms suggestive of COVID-19.

^bmedian Ct value for NPSs from RT-PCR positive participants without symptoms suggestive of COVID-19.

In this table, RT-PCR positive NPSs from both asymptomatic and symptomatic participants were further stratified in two sub-groups according to the overall median Ct value of both target genes.

As expected, the prevalence of positive RT-PCR results in NPSs from symptomatic participants was nearly tenfold higher than in NPSs from asymptomatic participants (p<0.0001) and, again as expected, median Ct value for both RT-PCR target genes was significantly lower in NPSs from symptomatic participants than in NPSs from asymptomatic ones (18.08 vs. 26.00; p<0.00001). Optimal accuracy parameter values were found for NPSs from symptomatic participants, also showing an almost perfect agreement beyond the chance (K = 0.891) (Table 3). On the contrary, among NPSs from asymptomatic participants, despite specificity and NPV were good, sensitivity and PPV were quite low and a barely moderate K (0.408) was found. The low PPV found for NPSs from asymptomatic participants, also considering the high specificity (0.986) shown by the AFIAS, indicated that it was clearly influenced by the low prevalence among them of RT-PCR positive results (nearly tenfold lower than in NPSs from symptomatic participants; p<0.0001).

Fig 2A shows the Ct value distribution for S and E genes in RT-PCR positive NPSs from participants with and without symptoms suggestive of COVID-19 at time of testing. From Fig 2A it is evident that the difference in sensitivity (Table 3: 0.944 vs. 0.452) between these two groups of NPSs was clearly linked to the different distribution of Ct values in the two groups. Median Ct values in NPSs from symptomatic participants were significantly lower than in NPSs from asymptomatic participants for both the S and E genes (S gene: 18.52 vs. 25.43; E gene: 18.09 vs. 26.00).

Fig 2B and Table 3 allow to analyse in more detail the difference in sensitivity and other accuracy parameters of the AFIAS between NPSs from symptomatic and asymptomatic participants. Among the 18 RT-PCR positive NPSs from symptomatic participants, only one of them (1/18) was false-negative and, not surprisingly, all the 18 RT-PCR positive NPSs had very high viral load, including the only false-negative sample (Fig 2B). On the contrary, among the 31 RT-PCR positive NPSs from asymptomatic participants more than half (17/31) were false-negative, and, importantly, nearly 60% of them (10/17) had Ct>30 (i.e. moderate/low viral load).

Diagnostic accuracy of AFIAS COVID-19 Ag test in specimens from participants more likely to test positive for COVID-19

Among all collected NPSs, 57 were from participants reporting a previous positive SARS-CoV-2 RT-PCR test (A), 94 from those who had had contact with an ascertained COVID-19 case (confirmed by RT-PCR) (B) and 150 from participants who had had contact with people reporting a positive for SARS-CoV-2 test (not specified if molecular or antigenic) (C).

Diagnostic accuracy parameters for the above subgroups (hereafter referred to as A, B, C) are shown in Table 5. The prevalence of RT-PCR positive NPSs was higher among subgroup A respect to the other two groups, but the differences were not statistically significant. However, NPSs from subgroup A showed the lowest sensitivity and NPV, with a relevant proportion of false-negative results (8/13). As expected, false negative results were more frequent in NPSs with a Ct value higher than the median Ct (29.60).

Table 5. Diagnostic accuracy of AFIAS COVID-19 Ag test in participants with previous positive molecular test or high-risk contact.

	(A) NPSs from participants with previous positive SARS-CoV-2 PCR test					(B) NPSs from participants reporting contact with COVID-19 case^a					(C) NPSs from participants reporting contact with people tested positive for SARS-CoV-2^a
		≤29.60^b	>29.60				≤22.06^c	>22.06				≤20.30^d	>20.30
	RT-PCR+	RT-PCR+	RT-PCR+	RT-PCR-	Total	RT-PCR+	RT-PCR+	RT-PCR+	RT-PCR-	Total	RT-PCR+	RT-PCR+	RT-PCR+	RT-PCR-	Total
AFIAS +	5	4	1	2	7	10	7	3	2	12	12	10	2	2	14
AFIAS -	8	3	5	42	50	3	0	3	79	82	6	1	5	130	136
	13	7	6	44	57	13	7	6	81	94	18	11	7	132	150
		95% CI					95% CI					95% CI
Prevalence	22.81	13.84–35.21				13.82	8.26–22.24				12.0	77.3–18.2
SS	0.385	0.117–0.6645				0.769	0.497–0.918				0.667	0.437–0.837
SP	0.954	0.849–0.987				0.975	0.914–0.993				0.985	0.946–0.996
PPV	0.714	0359–918				0.833	0.552–0.953				0.857	0.600–0.960
NPV	0.840	0.715–0.917				0.963	0.898–0.987				0.956	0.907–0.980
LR+	8.46	11.85–39				31	7.68–126				44	11–181
LR-	0.64	0.42–1.00				0.24	0.09–0.64				0.34	0.18–0.65
% Agreement	0.824	0.706–0.902				0.946	0.881–0.977				0.946	0.898–0.973
Cohen’s Kappa	0.405	0.113–0697		Moderate		0.769	0.576–0.963		Substantial		0.761	0.538–0.903		Substantial

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AFIAS +, AFIAS COVID-19 Ag positive; AFIAS -, AFIAS COVID-19 Ag negative; COI, Cut Off Index, LR+, positive likelihood ratio; LR-, negative likelihood ratio; NPSs, nasopharyngeal swabs; NPV, negative predictive value; PPV, positive predictive value; RT-PCR +, Real-time RT-PCR positive; RT-PCR-, Real-time RT-PCR negative; SS, sensitivity; SP, specificity.

^acontact within the last 14 days

^bmedian Ct value for NPSs from RT-PCR positive participants with previous positive SARS-CoV-2 PCR test

^cmedian Ct value for NPSs from RT-PCR positive participants reporting contact with COVID-19 case (confirmed by RT-PCR)

^dmedian Ct value for NPSs from RT-PCR positive participants reporting contact with people tested positive for COVID-19 by molecular or rapid antigen test.

The NPSs included in subgroup A had a significant higher median Ct value compared to specimens from subgroup B and C (p = 0.0029 and p = 0.0048, respectively). Diagnostic accuracy parameters were better for these two latter subgroups as also demonstrated by their K indicating a substantial agreement beyond the chance.

Discussion

Prompt and accurate testing is key for identification and clinical management of COVID-19 cases and for surveillance, control and prevention of SARS-CoV-2 infection [1, 2].

Since December 2020, the EU case definition for COVID-19 includes the detection of antigens in the clinical specimens and therefore the use of RADTs as a diagnostic method [19, 20]. Currently available RADTs show a variable but lower sensitivity compared to RT-PCR test, while their specificity is generally high [6–17]. It is worthy of note that RADTs are sensitive enough to detect cases with a high viral load [i.e. pre-symptomatic and early symptomatic cases (up to five days from symptom onset); or low RT-PCR Ct value (≤25)]. Such cases likely account for a significant proportion of SARS-CoV-2 transmission events [20].

Most of RADTs validation studies were performed in cohorts of symptomatic participants, while a limited number of these studies were performed in asymptomatic or predominantly asymptomatic individuals [35–39], to support the use of these tests in mass screening and epidemiological surveillance.

According to a more recent systematic review [40], the average SS in 37 studies carried out in symptomatic individuals was 0.720 [95% Confidence Interval (CI) 0.637–0.790] while that in 12 studies in asymptomatic individuals was 0.581 (95% CI, 0.402–0.701).

Overall, in our study, in which SARS-CoV-2 infection prevalence was 3.8%, AFIAS showed a good specificity (0.981) but a moderate sensitivity (0.633). However, we observed a quite good sensitivity (0.880) for RT-PCR positive NPSs with a Ct value lower than the overall median Ct value of both target genes (Ct≤22.34, i.e. corresponding to a “very high viral load” level) (Tables 2 and 3). An increased sensitivity with higher viral load was also found when results were analysed according to the presence of symptoms (0.944, Table 4). Sensitivity and specificity figures reported in a systematic revision for rapid antigen immune-fluorescent assays were higher than those found in our work for AFIAS [13, 41–43]. However, this is not at odds with the overall results of our study because the respiratory samples tested in the studies considered in that systematic revision were from individuals with fever or with respiratory symptoms suggestive of COVID-19 [41], or from suspected COVID-19 cases [42, 43]. The overall moderate AFIAS’s sensitivity in our study could undoubtedly be influenced by the larger proportion of NPSs from asymptomatic participants, which accounted for 94.3% of the total NPSs and 63% of the RT-PCR positive NPSs. In fact, NPSs from the asymptomatic participants showed both a higher median Ct value and a wider range of Ct than NPSs from the symptomatic participants, ultimately resulting in a significant greater proportion of false-negative results (17/31, 54.8% vs. 1/18, 5.6%; p = 0.0005) (Table 3).

As regards the other accuracy parameters in NPSs from symptomatic participants, the AFIAS showed very good performance parameters (SP 0.964, PPV 0.895, NPV 0.981) and K was 0.891. As expected, in this subgroup the SARS-CoV-2 prevalence was very high (24.7%), while among NPSs from asymptomatic participants the prevalence was about ten-fold lower, leading to a lower PPV than in symptomatic participants’ NPSs (0.400 vs 0.895).

For NPSs from participants with previous positive SARS-CoV-2 PCR test, for which the infection prevalence was similar (22.8%) to that found for NPSs from symptomatic participants (24.7%), AFIAS sensitivity was very low (0.385) with a barely moderate K. These findings indicated that most NPSs from this group were indeed from non-recent infections, according to the observed relatively low viral load (median Ct: 29.60), leading to high proportion of false-negative results (8/13, 61.5%).

The link between viral load and sensitivity was further confirmed when the findings obtained for NPSs from participants with a previous positive SARS-CoV-2 PCR test (prevalence, 22.80%) were compared to those found for NPSs from participants reporting a contact with a COVID-19 case (prevalence, 13.82%) and or a contact with people tested positive for SARS-CoV-2 within the previous 14 days (prevalence, 12.00%) (Table 4, subgroups A, B and C). In fact, in both these latter subgroups of participants, sensitivity was higher (with a substantial K) than in participants with a previous positive SARS-CoV-2 PCR test. Indeed, in both these groups the median viral load (inversely related to the median Ct value) was higher, likely indicating a more recent infection.

Comparison of the PPV from the three above-mentioned groups shows that the expected influence of prevalence on PPV is counterbalanced by the viral load: in fact, despite the prevalence decreases (22.81%, 13.82% and 12.00%), the PPV increases (71.4%, 83.3% and 85.7%), with a minor role of specificity (95.4%, 97.5% and 98.5%) (see Table 4).

Other studies have previously assessed the diagnostic accuracy of AFIAS [10, 11, 14]. A Korean study performed on clinical specimens from 38 adult COVID-19 and 122 non-COVID-19 patients showed an excellent SP (0.987–0.989), but the sensitivity was good only for NPSs with high viral load (0.913–1.00 in NPSs with Ct <25) [10]. In the present study, the sensitivity was 0.813 (26/32) in NPSs with Ct ≤25. This difference might be due to different distribution of Ct values in NPSs with Ct ≤25 between the two studies, but this hypothesis could not be verified as detailed information was not reported in the Korean study. Another study assessed the accuracy of AFIAS COVID-19 Ag in a mass screening carried out among unselected paediatric patients. Overall sensitivity and specificty were 86.4% and 98.3%, respectively [11]. Also in that study, information about distribution of Ct values as well as presence of symptoms were not reported, precluding any detailed comparison with results of the present study. Finally, another Italian study evaluating the performance of three different RADTs, assessed the accuracy of AFIAS by testing 81 known SARS-COV-2 positive and negative respiratory samples. Sensitivity and specificity found in this study were 0.375 a 0.100 respectively [14].

Our study had some limitations. Precise information on the time to onset of symptoms was not available. Similarly, participants were asked if they had had contact with cases or people with previous positive tests within 14 days earlier, but precise information on contact time point was not collected.

In conclusion, AFIAS COVID Ag, as many other RADTs, showed an overall high specificity, a good sensitivity for NPSs with high viral load and nearly optimal accuracy parameters for participants with COVID-19 compatible symptoms. Hence, taking into consideration its performance features, in high prevalence settings/population this test might be used for COVID-19 case identification and management, as well as for infection control.

Supporting information

S1 Data

(XLSX)

Click here for additional data file.^{(101.9KB, xlsx)}

Data Availability

All relevant data are within the paper and its Supporting Information file.

Funding Statement

The study was supported in part by the institutional funds of the Istituto Superiore di Sanità, (Fascicolo BA17). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0277904.r001

Decision Letter 0

Luisa Gregori

22 Jul 2022

PONE-D-22-13832Diagnostic accuracy of a SARS-CoV-2 rapid antigen test among military and civilian personnel of an Air Force airport in central ItalyPLOS ONE

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Reviewer #1: The authors tested from November 2020 to April 2021, 1294 nasopharyngeal swab samples from 1183 participants with the rapid antigen test AFIAS COVID-19 Ag, a fluorescence-based rapid antigen test. This is a not wide-spread rapid antigen test, not easy to work with as the development of the final reaction is fluorescence and a little instrumentation is required for reaction reading. Results were compared with standard RT-PCR (gene E and N, by Altona) according to the presence of symptoms and the level of viral load as expressed by the Ct value as a proxy. Testing was performed within the military and civilian personnel of a military airport, located in the metropolitan area of Rome, who underwent a screening program to control transmission of SARS-CoV-2 infection, Prevalence rate of Covid-19 in the studied population: 3.78%.

Forty-nine samples (3.78%) were positive by RT-PCR (32 of them with a high viral load: Ct range 12.12-24.86), while 54 samples were positive by AFIAS COVID-19 Ag; 18 samples were false negative by AFIAS and 23 were false positive. AFIAS overall sensitivity, specificity, positive and negative predictive values were 0.633, 0.981, 0.574, 0.985, respectively with only a moderate level of concordance with RT-PCR. These figures increased when comparison was made in samples with a high viral load (Ct ≤22). Similar results were achived if AFIAS COVID-19 Ag was compared with RT-PCR results in symptomatic patients and this is certainly a results of higher viral loads in these patients. Instead, and as expected by the scientific literature, test sensitivity was poor for samples from asymptomatic participants and for viral load CT >30.

In conclusion, the authors stated that AFIAS COVID Ag showed high specificity but only moderate sensitivity in the screened population where the prevalence of COVID-19 was, by the way, low. However, and again as expected, the assay showed good sensitivity for samples with high viral load and in participants with COVID-19 compatible symptoms. Thus, in high prevalence setting this test can be useful for COVID-19 case identification and management at a point-of-care level.

The work is in line with many other papers on rapid antigen testing in COVID-19 pandemic showing that the sensitivity of these type of tests is higher in symptomatic than in asymptomatic patients and that using the Ct value as a proxy for viral load, the sensitivity increases with the increasing of viral loads. All these data have already been acknowledged by the scientific and medical community, the only reason to ask a re-submission from the authors is that there are not so many data on the type of rapid antigen test used by them, e.g. AFIAS COVID-19 Ag and it would be certainly usefull to add more data to the existing ones. The good correlation with RT-PCR is only for Ct <22, which means that the technique of this rapid test e.g. fluorescence, is not as sensitive as the one of other rapid test working with fluorescence in the same context (Dinnes J, Deeks JJ, Adriano A, Berhane S, Davenport C, Dittrich S, et al. Rapid, point-of-care antigen and molecular-based tests for diagnosis of SARS-CoV-2 infection. Cochrane Database Syst Rev. 2020 Aug 26;8(8). There are no comments by the authors on this important issues.

Therefore, my suggestion is to re-write it as short report, making the study more synthetic, technical and readable, cutting down the number of tables to the essential (just one as the overall evaluation and one more according to the Ct level). The Ct level chosen for statistical analysis should be the same across all the study (e.g. abstract ct<25, table Ct< 22.34, text Ct <22), as there are only 49 positive samples by RT-PCR, 18 of them negative by the antigen test (the authors are working on 31 positive concordant samples, which is not that much). Therefore, there is no clue in making several subsets of positive samples/patients (and each one corresponds to a table!) since they are just few positive samples by the gold standard RT-PCR. This gives the work a strong reading difficulty and hard to follow the analysis. Moreover, it is not clear if the statistical analysis is run on sample or patients (1294 vs 1183, text vs. tables).

Reviewer #2: The authors evaluated a SARS-CoV-2 rapid antigen detection test (RADT) while using RT-PCR as the gold standard. The works were scientifically sound. However, mistakes and confusions were found and I have several queries for the current version of the manuscript. I hope the authors will find them useful to revise it so that the quality could be improved.

- the research gap was not well defined:

(1) lines 95-100: the authors have to explain the reasons for choosing ‘military and civilian personnel of a military airport in the metropolitan area of Rome’ as the subjects

(2) lines 69, 87-88, 114-121: the authors stated that RADTs are easy to use since equipment was not required, however, the authors employed the fluorescence based RADT in the study. This test requires an equipment to read the test results. It seems that the introduction was discordant to the method used.

- line 172: you have to mention the meaning of the cut-off value Ct 22.34, readers will not know that unless they went through the table 1b

- lines 220-221, 272-273, table 3, footnote a: you have to define group B and group C clearly. I still do not know the differences between groups B and C after going through these explanations. I only know that participants in groups B and C had contact history with COVID-19 patients within the last 14 days. Participants in groups B will be more likely to be detected by RADT than those in group C. If I understand correctly, groups B participants had contact history with COVID-19 patients tested positive by RADT while groups C participants had contact history with COVID-19 patients tested positive by RT-PCR. Please confirm my speculation.

- the authors analyzed the RADT results according to the four different parameters: (1) EU HSC (2) RT-PCR results (3) presence of symptoms (4) contact history with COVID-19 cases. It means that many different cut-offs were used:

(1) EU HSC cut-offs: <25, 26-30, 30-36, >36 (lines 141-142)

(2) median RT-PCR: 22.34

(3) symptomatic patients: 18.08

(4) asymptomatic patients: 26.00

For (1), a table is preferred rather than just describing the results in text only (lines 179-182).

Minor comments:

- avoid creating unnecessary abbreviations if the fluency is not improved, it is not inconvenient to spell the terms SS (line 73) and SP (line 75) in full as sensitivity and specificity respectively. I cannot see those terms will either save the word counts or make the manuscript more neat and tidy. In addition, these two terms are not commonly used by other research groups. Readers have to memorize them throughout the manuscript. It is easy to create confusion. On the other hand, the term ‘N’ referring nucleocapsid protein created (line 117) has not been used in subsequent texts. All these kinds of arrangements make this manuscript quite unprofessional.

- there were only two different assays, RT-PCR and RADT, it is not necessary to create another term, index test in lines 34, 41, 44, 49, 169, 200, 211, 254, 260. As you define RADT at the beginning, you can either use this term throughout the manuscript or make a short form for the RADT that your performed in your study, ‘AFIAS’ to refer ‘AFIAS COVID-19 Ag’.

Reviewer #3: In this manuscript, Authors report the results of a screening program to control transmission of SARS-CoV-2 infection in the workplace. The study was conducted from November 2020 to April 2021 on the personnel of a military airport in Rome. Tests were performed with immunochromatographic fluorescence-based rapid antigen test designed to detect the nucleocapsid protein (N) of SARS-CoV-2 in nasopharyngeal swab specimens.

The study was conducted appropriately. Nevertheless, an important limitation is that the study was carried out almost a year and a half ago: the epidemiological situation and the variants circulating today are different. Moreover, the topic of the article appears to be of limited interest since it has been extensively covered in similar published works regarding the same rapid antigen test and others similar. In addition to the two studies already mentioned in the manuscript’s discussion, some other examples are reported below:

- Baccani I, Morecchiato F, Chilleri C, Cervini C, Gori E, Matarrese D, Bassetti A, Bonizzoli M, Mencarini J, Antonelli A, Rossolini GM. Evaluation of Three Immunoassays for the Rapid Detection of SARS-CoV-2 antigens. Diagn Microbiol Infect Dis. 2021 Oct;101(2):115434. doi: 10.1016/j.diagmicrobio.2021.115434. Epub 2021 May 21. PMID: 34174523; PMCID: PMC8137375.

- Parvu, V.; Gary, D.S.; Mann, J.; Lin, Y.C.; Mills, D.; Cooper, L.; Andrews, J.C.; Manabe, Y.C.; Pekosz, A.; Cooper, C.K. Factors that influence the reported sensitivity of rapid antigen testing for SARS-CoV-2. Front. Microbiol. 2021, 12, 714242.

- Filchakova, O.; Dossym, D.; Ilyas, A.; Kuanysheva, T.; Abdizhamil, A.; Bukasov, R. Review of COVID-19 testing and diagnostic methods. Talanta 2022, 244, 123409.

- Bruzzone, B.; De Pace, V.; Caligiuri, P.; Ricucci, V.; Guarona, G.; Pennati, B.M.; Boccotti, S.; Orsi, A.; Domnich, A.; Da Rin,G.; et al. Comparative diagnostic performance of rapid antigen detection tests for COVID-19 in a hospital setting. Int. J. Infect.Dis. 2021, 107, 215-218.

Here below, Authors can find a list of revisions that need to be addressed in order to improve the quality of the manuscript.

Abstract

- line 38: median age is missing from results

- line 41-44: it is not so clear what concept the authors want to express

Methods

- the method of enlistment is not specified (they were volunteers?)

- It is not specified how was determined the number of people to be enlisted (only time criteria?)

- line 104-106: we suggested to specify the use that will be made of the data contained in the questionnaires

- viral variants circulating at the time of the study are never mentioned in the study. Therefore, data on their detection capabilities for the test under consideration are missing.

- line 139-140: it would be helpful to specify the number of samples with inconclusive results found, whether they were included in the study and the AFIAS COVID-19 test result, if any

- line 140-142: this section reports viral load cut-offs that are not met in subsequent sections

Results

- Table 1b reported a classification of analyzed samples that does not meet the content of Methods section; moreover, there is no explanation of how and why Authors selected and calculated the cut-off and to which of target gene it refers (E or S or both target genes of molecular assay)

- Table 1a: an asterisk is reported near the values of prevalence, but there is no explanation of its meaning

- Table 1a: the number of negative samples is too high compared with PCR positives

- line 185-188: the population appears disproportionate between symptomatic and asymptomatic participants

- Table 2: Same considerations of Table 1b

- Table 3: Same considerations of Table 1b

**********

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Reviewer #1: No

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Reviewer #3: Yes: Andrea Orsi

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PLoS One. 2022 Nov 28;17(11):e0277904. doi: 10.1371/journal.pone.0277904.r002

Author response to Decision Letter 0

20 Oct 2022

Point-by-point response to Reviewers and Academic Editor

Reviewer #1

Reviewer comment:

The reviewer in summarizing our work states:”… with the rapid antigen test AFIAS COVID-19 Ag, a fluorescence-based rapid antigen test. This is a not wide-spread rapid antigen test, not easy to work with as the development of the final reaction is fluorescence and a little instrumentation is required for reaction reading”

Response:

In reading what the reviewer writes, we realize that we have used a wrong wording in describing the characteristics of RADTs (i.e.“not requiring special equipment”). With "special equipment" (line 69 of the first manuscript version) we wanted to refer to a complex equipment to use, which required a particular laboratory training or particular technical skills. Furthermore, we also wanted to refer to the instrumentation footprint. Indeed, AFIAS COVID-19 Ag is very easy to work. The instrumentation for reading the test’s final reaction is of small dimension. Also, this test does not require a particular training of the laboratory personnel and the turnaround time is less than 20 minutes. For all these reasons, we state that AFIAS COVID-19 Ag is particularly suitable as a point of care test (https://www.youtube.com/watch?v=Up-ywSfpr9c ).

Reviewer comment:

Response:

We agree with the reviewer when she/he states that the results of our manuscript are in line with those of various other studies which have shown that the sensitivity of RADTs is generally higher in symptomatic than in asymptomatic subjects. However, we disagree with the reviewer when she/he says that the only reason for resubmitting our work would be the few data available on AFIAS. Unfortunately, the reviewer does not seem to take into account that in our study we also assessed the diagnostic accuracy of AFIAS based on the presence or absence of symptoms and on the level of exposure to SARS-COV-2.. The are very important aspects regarding the control of COVID-19, that is, the diagnosis and epidemiological surveillance (e.g. contact tracing) of the infection. These are very important aspects regarding the control of COVID-19, that is, the diagnosis and epidemiological surveillance (e.g. contact tracing) of the infection. Furthermore, the reviewer does not even take into account the particular type of study population that we considered in our study: a sample of the general population (i.e. mostly asymptomatic individuals) in a particular workplace, involving different infection exposures, subjected to SARS-COV-2 surveillance screening.

Reviewer comment:

The good correlation with RT-PCR is only for Ct <22, which means that the technique of this rapid test e.g. fluorescence, is not as sensitive as the one of other rapid test working with fluorescence in the same context (Dinnes J, Deeks JJ, Adriano A, Berhane S, Davenport C, Dittrich S, et al. Rapid, point-of-care antigen and molecular-based tests for diagnosis of SARS-CoV-2 infection. Cochrane Database Syst Rev. 2020 Aug 26;8(8). There are no comments by the authors on this important issues.

Response:

The reviewer is right. Sensitivity and specificity data found for antigen immune-fluorescent assays considered in the systematic revision by Dinnes J (Cochrane Database Syst Rev, 2020) are higher than those found in our work for AFIAS. However, this is not at odds with the overall results of our study because the respiratory samples tested in the studies considered in that meta-analysis were from individuals with fever or with respiratory symptoms suggestive of COVID-19 (Weizel, 2020), or from suspected COVID-19 cases (Diao Clin Microbiol Infect 2021, 2021; Porte, Int J Infect Dis. 2020). Also in our study sensitivity was higher if analysis was restricted to samples from individuals with symptoms. It is important to note (as we have already stated om the discussion session of the first version of our manuscript) that in our study the larger proportion of NPSs was from asymptomatic participants, which accounted for 94.3% of the total NPSs and 63% of the RT-PCR positive. We have added a brief sentence in the discussion section to comment this issue.

Reviewer comment:

“Therefore, my suggestion is to re-write it as short report, making the study more synthetic, technical and readable, cutting down the number of tables to the essential (just one as the overall evaluation and one more according to the Ct level)”.

Response:

We prefer to maintain the current “long” format of the manuscript because re-writing it as a short report and especially cutting down the number of tables, as suggested by the reviewer (“just one as the overall evaluation and one more according to the Ct level”) would prevent us to correlate AFIAS accuracy with both presence or absence of COVID-19 symptoms and infection exposure, thus causing a loss of meaning and value in our work.

Reviewer comment:

The Ct level chosen for statistical analysis should be the same across all the study (e.g. abstract ct<25, table Ct< 22.34, text Ct <22), as there are only 49 positive samples by RT-PCR, 18 of them negative by the antigen test (the authors are working on 31 positive concordant samples, which is not that much). Therefore, there is no clue in making several subsets of positive samples/patients (and each one corresponds to a table!) since they are just few positive samples by the gold standard RT-PCR. This gives the work a strong reading difficulty and hard to follow the analysis.

Response:

We think that the fact that there are only 49 RT-PCR positive NPSs is not a sufficient and valid reason to adopt a single level of Ct for all statistical analysis in our work. This is because these 49 samples are not the same as regards clinical characteristics (presence of symptoms) and epidemiological characteristics (e.g. type and time of exposure to the virus) of the individuals from which they were collected. Studies investigating these aspects are important to support the use of RADTs in mass screening and epidemiological surveillance. In our opinion, the use of the median Ct for both PCR gene for each analysis is much more correct than the use of a unique cut-off for all analysis, and this approach has been used by other authors (Singh, Cereus 2021; Mak, J Clin Virol 2020; Ristic, PlosOne 2021; Singh, JMID 2021, Van der Moeren, Plos One2021). If we did not adopt the average median Ct levels specific for each type of sample subgroup, we would not be able to assess the influence of symptoms or exposure on the performance of theAFIAS. RT-PCR assays Ct values are relative, not absolute numbers. Ct values of the same RT-PCR assay varies between different labs. Furthermore, Ct values can vary up to two to three logs from test to test (Pritt, et al, 2020; https://www.publichealthontario.ca/-/media/documents/ncov/main/2020/09/cycle-threshold-values-sars-cov2-pcr.pdf?la=en; https://perkinelmer-appliedgenomics.com/2021/03/04/covid-19-rt-pcr-ct-values/

Reviewer comment:

Moreover, it is not clear if the statistical analysis is run on sample or patients (1294 vs 1183, text vs. tables).

Response

We analyzed 1294 samples belonging to 1183 participants (line 158 and line 162 of the first manuscript version). To avoid further misunderstandings, in revising the manuscript, we used the term “nasopharyngeal swabs (NPSs)” instead of the generic term "samples".

Reviewer #2

The authors evaluated a SARS-CoV-2 rapid antigen detection test (RADT) while using RT-PCR as the gold standard. The works were scientifically sound. However, mistakes and confusions were found and I have several queries for the current version of the manuscript. I hope the authors will find them useful to revise it so that the quality could be improved.

Reviewer comment:

- the research gap was not well defined:

(1) lines 95-100: the authors have to explain the reasons for choosing ‘military and civilian personnel of a military airport in the metropolitan area of Rome’ as the subjects

Response:

(1) The study was part of the public health response to control as soon as possible any outbreak occurring in the military airport (as reported in the Scientific Collaboration Protocol signed by the Experimental Flight Center, Italian Air Force Logistic Command and Istituto Superiore di Sanità on 30 November 2020), with simultaneous evaluation of the RADT used for the screening.

(2) In reading this comment, we realize that we have used a wrong wording in describing the characteristics of RADTs (i.e.“not requiring special equipment”). With "special equipment" (line 69 of the first manuscript version) we wanted to refer to a complex equipment to use, which required a particular laboratory training or particular technical skills. Indeed, AFIAS COVID-19 Ag is very easy to work with. The instrumentation for reading the test’s final reaction is of small dimension. Also, this test does not require a particular training of the laboratory personnel and the turnaround time is less than 20 minutes. For all these reasons we state that AFIAS COVID-19 Ag is particularly suitable as a point of care test (https://www.youtube.com/watch?v=Up-ywSfpr9c).

Reviewer comment:

line 172: you have to mention the meaning of the cut-off value Ct 22.34, readers will not know

that unless they went through the table 1b

Response:

The reviewer is right. In the revised version of the manuscript we have clarified the meaning of the cut-off value Ct 22.34.

Reviewer comment:

lines 220-221, 272-273, table 3, footnote a: you have to define group B and group C clearly. I still do not know the differences between groups B and C after going through these explanations. I only know that participants in groups B and C had contact history with COVID-19 patients within the last 14 days. Participants in groups B will be more likely to be detected by RADT than those in group C. If I understand correctly, groups B participants had contact history with COVID-19 patients tested positive by RADT while groups C participants had contact history with COVID-19 patients tested positive by RT-PCR. Please confirm my speculation.

Response:

We apologize to the reviewer. We actually failed to define groups B and C clearly enough. Let's try to do that now: group B participants had contact history with COVID-19 case confirmed by RT-PCR; group C participants had contact history with individual tested positive for SARS-CoV-2 by a molecular or an antigenic test (by answering the question in the questionnaire, participants were unable to specify whether the test was antigenic or molecular). In the revised version of the manuscript we defined more clearly the groups B and C.

Reviewer comment:

the authors analyzed the RADT results according to the four different parameters: (1) EU HSC (2) RT-PCR results (3) presence of symptoms (4) contact history with COVID-19 cases. It means that many different cut-offs were used:

(1) EU HSC cut-offs: <25, 26-30, 30-36, >36 (lines 141-142)

(2) median RT-PCR: 22.34

(3) symptomatic patients: 18.08

(4) asymptomatic patients: 26.00

For (1), a table is preferred rather than just describing the results in text only (lines 179-182).

Response:

We think that the use of the median Ct for both PCR is the most correct procedure to analyse AFIAS accuracy in each subgroup of our study population. This is because the 49 RT- PCR positive participants in our study are different as regards clinical characteristics (presence of symptoms) and epidemiological characteristics (type and time of exposure to the virus). If we did not adopt the average median Ct levels specific for each type of population subgroup, we would not be able to assess the influence of symptoms or exposure on the performance of the test. The median Ct for both PCR gene as cut-off for accuracy analysis has also been adopted by other authors. (e.g. Singh, Cereus 2021; Mak, J Clin Virol 2020; Ristic, PlosOne 2021; Singh, JMID 2021, Van der Moeren, Plos One2021). However, RT-PCR assays Ct values are relative, not absolute numbers. Ct values of the same RT-PCR assay varies between different labs. Furthermore, Ct values can vary up to two to three logs from test to test (Pritt, et al, 2020; https://www.publichealthontario.ca/-/media/documents/ncov/main/2020/09/cycle-threshold-values-sars-cov2-pcr.pdf?la=en; https://perkinelmer-appliedgenomics.com/2021/03/04/covid-19-rt-pcr-ct-values/)

Anyway, we added a new Table (Table 2) for the EU HSC cut-offs.

Reviewer comment:

Minor comments:

Response:

The reviewer is right. In the revised manuscript version, we have deleted the abbreviation for nucleocapsid protein (N) and we have spelled in full sensitivity and specificity. Also, after the first citation we have used AFIAS’ to refer ‘AFIAS COVID-19 Ag throughout the manuscript.

Reviewer #3

Reviewer comment:

Response:

The impact of variability of nucleocapsid region in circulating variants on performance of RADT test is carefully monitored in the world. To date, in our knowledge, no evidence has been reported about changes significantly influencing the sensitivity of RADTs.

Reviewer comment:

Moreover, the topic of the article appears to be of limited interest since it has been extensively covered in similar published works regarding the same rapid antigen test and others similar. In addition to the two studies already mentioned in the manuscript’s discussion, some other examples are reported below:

- Filchakova, O.; Dossym, D.; Ilyas, A.; Kuanysheva, T.; Abdizhamil, A.; Bukasov, R. Review of COVID-19 testing and diagnostic methods. Talanta 2022, 244, 123409.

Response:

We are aware that the topic of our study has been covered in many other similar studies. In the study by Baccani et al. who also used AFIAS COVID-19 Ag, only 81 samples, collected from known positive and negative COVID-19 patients, were tested. The very small study sample was the reason because we did not cite that work. The other studies cited by the reviewer were also conducted on known positive and negative SARS-CoV-2. We would like to stress that our study is one of the not numerous (at all) accuracy studies in which the study population consists of general people, therefore largely asymptomatic. We think studies like ours can be useful to support the use of these tests in mass screening and epidemiological surveillance.

In the revised version of the manuscript, we have added the studies cited by the reviewer

Reviewer comments:

Here below, Authors can find a list of revisions that need to be addressed in order to improve the quality of the manuscript.

Abstract

- line 38: median age is missing from results

Response:

Median age was 42 years. We have added this data.

- line 41-44: it is not so clear what concept the authors want to express

Response:

The reviewer is right. The sentence is misspelled. In the revised version of the manuscript we rewrote that sentence as follows: “AFIAS sensitivity tended to be higher for NPSs with higher viral load. A higher sensitivity (0.944) compared to the overall baseline sensitivity (0.633) was also found for NPSs from participants with COVID-19 compatible symptoms, for which K was 0.891 (almost perfect).

Reviewer comment:

Table 1b reported a classification of analyzed samples that does not meet the content of

Methods section;

Response: The reviewer is right. In the Methods section of the revised version of the manuscript we have added some sentences which clarify what is reported in table 1b.

Reviewer comment:

Methods

- the method of enlistment is not specified (they were volunteers?)

Response: They were not enlisted on a voluntary basis. The study was part of the public health response to control as soon as possible any outbreak occurring in the military airport with simultaneous evaluation of the RADT used for the screening. This information is included in Methods and Ethical Approval Statement

- It is not specified how was determined the number of people to be enlisted (only time criteria?)

Response: The study population included people screened from November 2020 to April 2021, to control the transmission in the workplace.

Reviewer comment:

- line 104-106: we suggested to specify the use that will be made of the data contained in the questionnaires

Response:

We have specified the use of the data collected through the questionnaire.

Reviewer comment:

- viral variants circulating at the time of the study are never mentioned in the study. Therefore, data on their detection capabilities for the test under consideration are missing.

Response: The impact of variability of nucleocapsid region in circulating variants on performance of RADT test is carefully monitored in the world. To date, in our knowledge, no evidence has been reported about changes significantly influencing the sensitivity of RADTs.

Reviewer comment:

- line 139-140: it would be helpful to specify the number of samples with inconclusive results found, whether they were included in the study and the AFIAS COVID-19 test result, if any

Response: Actually, no sample with inconclusive result (no detectable signal for both target genes and internal control) was observed.

Reviewer comment:

- line 140-142: this section reports viral load cut-offs that are not met in subsequent sections

Response

In the revised version of the manuscript these viral load Ct cut-offs were included in the new table 2.

Reviewer comment:

Results

Response:

The reviewer is right. In the Methods section of the revised version of the manuscript, information on classification of the different sample groups (study population’s paragraph) and on the cut-of calculation (SARS-CoV-2 Molecular Detection paragraph) have been given.

Reviewer comment:

Table 1a: an asterisk is reported near the values of prevalence, but there is no explanation of its meaning

Response:

The reviewer is right. It was a typo that escaped later checks.

Reviewer comment:

- Table 1a: the number of negative samples is too high compared with PCR positives.

Response:

We think this is normal in a population like the one that was tested in our study. The prevalence of positive RT-PCR samples was 3.8%, which is perfectly in line with that recorded throughout Italy in that period. We must reiterate that our study population consisted of the general population and about 94% of the participants were asymptomatic.

Reviewer comment:

- Table 2: Same considerations of Table 1b

- Table 3: Same considerations of Table 1b

Response:

The reviewer is right. In the Methods section of the revised version of the manuscript we have added some sentences which clarify what is reported in table 1b.

Response to Academic Editor

Editor comment:

Response

We are aware that the topic of our study has been covered in many other similar studies. However, we would like to stress that our study is one of the not numerous (at all) accuracy studies in which the study population consists of general people, therefore largely asymptomatic. Besides, our study was carried out in a particular workplace, involving different infection exposures, subjected to SARS-COV-2 surveillance screening. We think studies like ours can be useful to support the use of these tests in mass screening and epidemiological surveillance.

As regards the response to the reviewers, we think that all of the requests and suggestions of both Reviewer #2 and Reviewer #3 have been met. Regarding Reviewer #1, while trying to answer point by point to his comments, we regret to say that we disagree with either his overall judgment of the study or the suggestion to rewrite it as a short report and cutting down the number of tables to the essential (“just one as the overall evaluation and one more according to the Ct level”). Following this reviewer's suggestion would prevent us to assess AFIAS accuracy according both presence or absence of COVID-19 symptoms and infection exposure, thus causing a loss of meaning and value in our work. We think the analysis of these aspects are crucial to support the use of RADTs in mass screening and epidemiological surveillance.

We replaced the previous information in Funding source and Financial disclosure with the following statement: “The study was supported by the institutional fund of the Italian National Institute of Health (Istituto Superiore di Sanità) in the frame of its institutional role in public health activities for the COVID-19 emergency (internal code for administrative management: Fascicolo BA17).”

Resubmitting the manuscript, we uploaded our minimal underlying data set as Supporting Information files.

Attachment

Submitted filename: Point-by-point response.docx

Click here for additional data file.^{(43.4KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0277904.r003

Decision Letter 1

Etsuro Ito

31 Oct 2022

PONE-D-22-13832R1Diagnostic accuracy of a SARS-CoV-2 rapid antigen test among military and civilian personnel of an Air Force airport in central ItalyPLOS ONE

Dear Dr. Spada,

Please submit your revised manuscript by Dec 15 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Etsuro Ito

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #2: The authors addressed all of my queries, the revised version is better than the previous one. I went through the reviewer 1 and reviewer 3 comments and I shared similar views for some of them. I have the following three comments, the quality of the manuscript can be improved further.

1. The authors should elaborate more about the background of the study by copy and paste your response ‘The study was part of the public health response to control as soon as possible any outbreak occurring in the military airport (as reported in the Scientific Collaboration Protocol signed by the Experimental Flight Center, Italian Air Force Logistic Command and Istituto Superiore di Sanità on 30 November 2020), with simultaneous evaluation of the RADT used for the screening.’ into line 95, after the sentence ‘………….transmission of SARS-CoV-2 infection in the workplace.’

2. Reviewer 1 and I shared similar concerns of using fluorescence based RADT in your study, it is worthwhile to justify the reasons for selecting this RADT instead of traditional RADT without using fluorescence instrument.

3. Both reviewers 1 and 3 raised the concerns of similar studies have been published between 2020 and 2022. I also shared this view when I reviewed the first version, however, the PLOS journal did not focus on the novelty of the research. As I am not the new reviewer in PLOS, that’s why I did not raise this out. I suggest you should go through your manuscript thoroughly, try to write more about the background and the reasons to launch this study. The above comments 1 and 2 are aimed at filling this gap.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

**********

PLoS One. 2022 Nov 28;17(11):e0277904. doi: 10.1371/journal.pone.0277904.r004

Author response to Decision Letter 1

3 Nov 2022

Point-by-point response to Reviewers

We thank Reviewer #2 for her/his further requests: they allowed us to improve further the manuscript.

Reviewer #2

Reviewer comment 1:

Response:

The sentence was copy-pasted in the manuscript (line 95, Methods - Study population section) as suggested by the reviewer (line 100 in the revised version)

Reviewer comment 2:

Response:

Although the test requires a fluorescence reader, the running time from sample to result is comparable to traditional RADTs; however, it provides the added value that the result is not subject to the operator's interpretation. In fact, the positive/negative output of the fluorescence reader is automatic, based on an algorithm comparing the fluorescence obtained from the sample to a cut-off value; in the traditional RADTs, the operator can see more or less well a faint colored band of positivity

We included this explanation in the “Introduction” section of the manuscript (line 84, after “… in human NPSs within 20 minutes.”)

Reviewer comment 3:

Response:

The manuscript was revised and modified in the “Introduction” and “Methods” section, according to the reviewer comments 1 and 2; in particular, we stressed that:

- the use of a fluorescence reader makes results less dependent from the operator interpretation than traditional tests

- the study population is unselected and mostly asymptomatic

- the study was carried out in the frame of a public health response, with simultaneous evaluation of the RADT used for screening

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(27.3KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0277904.r005

Decision Letter 2

Etsuro Ito

6 Nov 2022

Diagnostic accuracy of a SARS-CoV-2 rapid antigen test among military and civilian personnel of an Air Force airport in central Italy

PONE-D-22-13832R2

Dear Dr. Spada,

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PLOS ONE

PLoS One. doi: 10.1371/journal.pone.0277904.r006

Acceptance letter

Etsuro Ito

15 Nov 2022

PONE-D-22-13832R2

Diagnostic accuracy of a SARS-CoV-2 rapid antigen test among military and civilian personnel of an Air Force airport in central Italy

Dear Dr. Spada:

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PERMALINK

Diagnostic accuracy of a SARS-CoV-2 rapid antigen test among military and civilian personnel of an Air Force airport in central Italy

Paola Verde

Cinzia Marcantonio

Angela Costantino

Antonio Martina

Matteo Simeoni

Stefania Taffon

Elena Tritarelli

Carmelo Campanella

Raffaele Cresta

Roberto Bruni

Anna Rita Ciccaglione

Giulio Pisani

Roberto Nisini

Enea Spada

Roles

Abstract

Background

Methods

Results

Conclusion

Introduction

Methods

Study population

Antigen assay for SARS-CoV-2

SARS-CoV-2 molecular detection

Statistical analysis

Results

Overall diagnostic accuracy of AFIAS COVID-19 Ag

Table 1. Diagnostic accuracy of AFIAS COVID-19 Ag test assessed against RT-PCR assay.

Table 2. AFIAS COVID-19 Ag test sensitivity according to the median RT-PCR Ct value (22.34).

Fig 1. Box-plot distribution of Ct values obtained by RT-PCR targeted to the viral S gene and E gene from NP swab NPSs, broken down according to the result obtained by AFIAS COVID-19 Ag rapid test.

Table 3. RT-PCR positve NPSs according to HSC TWG Ct and AFIAS result.

Diagnostic accuracy of AFIAS COVID-19 Ag according to presence or absence of symptoms suggestive of COVID-19

Table 4. Diagnostic accuracy of AFIAS COVID-19 Ag test according to presence or absence of COVID-19 symptoms.

Fig 2.

Diagnostic accuracy of AFIAS COVID-19 Ag test in specimens from participants more likely to test positive for COVID-19

Table 5. Diagnostic accuracy of AFIAS COVID-19 Ag test in participants with previous positive molecular test or high-risk contact.

Discussion

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Luisa Gregori

Roles

Author response to Decision Letter 0

Decision Letter 1

Etsuro Ito

Roles

Author response to Decision Letter 1

Decision Letter 2

Etsuro Ito

Roles

Acceptance letter

Etsuro Ito

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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