Serology characteristics of SARS-CoV-2 infection after exposure and post-symptom onset.

BACKGROUND: Timely diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a prerequisite for treatment and prevention. The serology characteristics and complement diagnosis value of the antibody test to RNA test need to be demonstrated.
METHOD: Serial sera of 80 patients with PCR-confirmed coronavirus disease 2019 (COVID-19) were collected at the First Affiliated Hospital of Zhejiang University, Hangzhou, China. Total antibody (Ab), IgM and IgG antibodies against SARS-CoV-2 were detected, and the antibody dynamics during the infection were described.
RESULTS: The seroconversion rates for Ab, IgM and IgG were 98.8%, 93.8% and 93.8%, respectively. The first detectible serology marker was Ab, followed by IgM and IgG, with a median seroconversion time of 15, 18 and 20 days post exposure (d.p.e.) or 9, 10 and 12 days post onset (d.p.o.), respectively. The antibody levels increased rapidly beginning at 6 d.p.o. and were accompanied by a decline in viral load. For patients in the early stage of illness (0-7 d.p.o), Ab showed the highest sensitivity (64.1%) compared with IgM and IgG (33.3% for both; p<0.001). The sensitivities of Ab, IgM and IgG increased to 100%, 96.7% and 93.3%, respectively, 2 weeks later. When the same antibody type was detected, no significant difference was observed between enzyme-linked immunosorbent assays and other forms of immunoassays.
CONCLUSIONS: A typical acute antibody response is induced during SARS-CoV-2 infection. Serology testing provides an important complement to RNA testing in the later stages of illness for pathogenic-specific diagnosis and helpful information to evaluate the adapted immunity status of patients.

Introduction

In early December 2019, a novel coronavirus (SARS-CoV-2) was first reported to cause lethal pneumonia in humans, and person-to-person transmission was demonstrated soon in Wuhan, the capital city of Hubei Province, China [1]. The virus rapidly spread through China and then many other countries globally. Through May 6, 2020, the virus resulted in over 3.5 million laboratory-confirmed cases of coronavirus disease 2019 (COVID-19) and more than 243 000 deaths in 215 countries [2]. The World Health Organization (WHO) has declared COVID-19 a public health emergency of international concern and given a “very high” risk assessment on a global level [3]. A recent report from China showed that the median incubation period of COVID-19 infection was 4 days (interquartile range, 2 to 7) [4]. Fever, cough and fatigue are the most common symptoms [1]. Severe cases could rapidly progress to acute respiratory distress syndrome (ARDS) and septic shock. Abnormalities on chest computed tomography, particularly ground-glass opacity and bilateral patchy shadowing, were found in over 80% of patients [5]. Over 80% of patients had lymphopenia, and approximately 60% of patients had elevated C-reactive protein [6]. However, the clinical and laboratory findings of COVID-19 infection are not distinguishable from pneumonia caused by infection of some common respiratory tract pathogens, such as influenza virus, Streptococcus pneumoniae and Mycoplasma pneumoniae [7]. Hence, the timely diagnosis of SARS-CoV-2 infection is important for providing appropriate medical support and for preventing the spread by quarantining.

Currently, the diagnosis of SARS-CoV-2 infection almost solely depends on the detection of viral RNA using polymerase chain reaction (PCR)-based techniques [8]. Unfortunately, the sensitivity of the RNA test in the real world is not satisfactory, particularly when samples collected from the upper respiratory tract are used [9-12]. In Wuhan, the overall positive rate of RNA testing is estimated to be approximately 30–50% in patients with COVID-19 when they come to the hospital [13]. Furthermore, the overall throughput of available RNA tests is highly limited by their nature of requiring high workload, needing skilful operators for testing and sample collection, and needing costly instruments and special operation places [14]. As a result, convenient serological detection is expected to be helpful. However, current knowledge of the antibody response to SAR-CoV-2 infection is very limited. The diagnostic value of the antibody test remains to be clearly demonstrated. How many patients would raise an antibody response, and how long will it take for the antibody to convert to positive since the exposure? Are there any meaningful differences between patients with short and long incubation periods? What are the sensitivities of antibody detection for patients in different illness stages? Is there any temporal association between the antibody response and the decline in viral load? To answer some of these questions, we investigated the characteristics of antibody responses in 80 patients with COVID-19 during their hospitalisation periods by detecting total antibodies, IgM and IgG using immunoassays.

Methods

Study design and participants

A confirmed COVID-19 case was defined based on the New Coronavirus Pneumonia Prevention and Control Program (6th edition) published by the National Health Commission of China [15]. Briefly, a confirmed case should meet three criteria: 1) fever and/or respiratory symptoms; 2) abnormal lung imaging findings; and 3) positive result of the nucleic acid of SARS-CoV-2. The degree of severity of the patient was categorised as critical if any of the following clinical findings appeared: 1) ARDS or oxygen saturation <93% and requiring mechanical ventilation either invasively or noninvasively; 2) shock; and 3) complications of organ functional failure and requiring intensive care unit support. A COVID-19 patient who did not meet the above criteria was defined as a non-critical case.

This study enrolled a total of 80 cases of COVID-19, where all patients were admitted to the hospital between Jan 19 and Feb 9, 2020, and were willing to donate their blood samples. All enrolled cases were confirmed to be infected by SARS-CoV-2 through quantitative real-time RT-PCR (qRT-PCR) testing. The date of illness onset, clinical classification, RNA testing results during the hospitalisation period, and personal demographic information were obtained from the clinical records. A total of 300 healthy people were enrolled from the local community during the circulation of the virus. All the controls had not reported close contact with any confirmed COVID-19 patient. This study was reviewed and approved by the Medical Ethics Committee of the First Affiliated Hospital of Zhejiang University (approval number 2020-IIT-47). Written informed consent was obtained from each enrolled subject.

Laboratory confirmation of COVID-19 by reverse-transcription polymerase chain reactions

For each patient, sputum specimen was collected preferentially. While sputum was not produced, saliva after deep cough was collected as previously reported [16]. The sputum was first treated with equal volume of protease K solution (0.4 mg·mL−1) at room temperature for 20 min. 200 μL of treated sputum or saliva was subjected to total nucleic acid extraction by MagNA Pure LC 2.0 (Roche, Basel, Switzerland), and each sample obtained 50 μL elution. A commercial 1-step real-time reverse transcription polymerase chain reaction (RT-PCR) assay (Bio-Germ, Shanghai, China) targeting the nucleocapsid gene and open reading frame 1ab gene was performed with 5 μL of total nucleic acid according to the manufacturer's instructions.

Antibody measurement

The total antibody (Ab), IgM antibody and IgG antibody against SARS-CoV-2 in plasma samples were tested using three enzyme-linked immunosorbent assays (ELISA-Ab, ELISA-IgM and ELISA-IgG), three colloidal-gold lateral-flow immunoassays (LFIA-Ab, LFIA-IgM and LFIA-IgG) and two chemiluminescence microparticle immunoassays (CMIA-Ab and CMIA-IgM). The ELISA reagents and LFIA reagents were supplied by Beijing Wantai Biological Pharmacy Enterprise Co., Ltd., China (Beijing, China), and the CMIA reagents were supplied by Xiamen InnoDx Biotech Co., Ltd., China (Xiamen, China). Total antibody detection was based on a double-antigen sandwich immunoassay, and IgM antibody detection was based on a μ-chain capture immunoassay. Mammalian cell-expressed recombinant antigens containing the receptor binding domain (RBD) of the SARS-CoV-2 spike protein were used to develop total antibody and IgM antibody assays. Meanwhile, the IgG antibody kits were indirect immunoassays, and a recombinant nucleoprotein of SARS-CoV-2 expressed in Escherichia coli was used as the coating antigen. The antigens used in these assay were in-house prepared by Beijing Wantai Biological Pharmacy Enterprise Co., Ltd., and the same antigen or antigen pairs were used for ELISA, CMIA and LFIA assays.

The measurement processes of ELISA and CMIA were conducted with an automatic ELISA analyser HB-300E (Jiaxing CRED Medical Equipment Co. Ltd., China) and automatic CMIA analyser Caris 200 (Xiamen UMIC Medical Instrument Co. Ltd., China) according to the manufacturer's instructions, respectively. The details of the procedures were described in the supplementary materials. When LFIA-Ab and LFIA-IgM were performed, 10 μL of sample was pipetted onto the sample receiving zone followed by adding two drops of sample buffer. For LFIA-IgG, the sample was diluted 1000-fold with sample buffer, and then 80 μL of dilution was added onto the sample receiving area. 15 min after the sample was added, the LFIA results were observed by eye and recorded. It takes 75 min, 29 min and 15 min to get the results back for ELISA, CMIA and LFIA assays, respectively.

Statistical analysis

The incubation period was defined as the interval between the earliest date of SARS-CoV-2 exposure and the earliest date of symptom onset. Non-normally distributed continuous data were described as the median with interquartile range (IQR) and compared by the Wilcoxon test. Categorical data were summarised as counts and percentages. The 95% confidence intervals of sensitivity and specificity were estimated by binomial exact test. Categorical data were compared using the χ2 test or Fisher's exact test for unpaired proportions and McNemar's test for paired proportions. Cumulative seroconversion rates were calculated by the Kaplan-Meier method. All statistical analyses were conducted using SAS 9.4 (SAS Institute, Cary, NC, USA).

Patient and public involvement

No patients were involved in setting the research question or the outcome measures, nor were they involved in the design and implementation of the study.

Dissemination declaration

Dissemination to these groups is not possible/applicable.

Results

Characteristics of enrolled patients with COVID-19

Among 81 cases of COVID-19 patients admitted to the hospital (before Feb 9, 2020), 80 (99%) patients were enrolled in the study (table 1). The median age of the patients was 55 years (IQR, 45–64 years), and 38.7% were females. The critical patients were significantly older than the non-critical patients (p<0.001). The time of SARS-CoV-2 exposure before onset in 45 patients (15 were critical cases) was determined according to unambiguous close contact with confirmed patients with COVID-19 through epidemiological inspection upon admission to the hospital. The incubation period ranged from 0 to 23 days with a median of 5 days (IQR, 2–10 days). By February 15, a total of 32 patients (40%, all were non-critical cases) were recovered and discharged from the hospital, and none died.

TABLE 1

Demographics and clinical characteristics of enrolled patients with COVID-19

	Total	Non-critical	Critical	P value
Number	80	54	26	-
Sex, n (%)
Female	31 (38.7)	24 (44.4)	7 (26.9)	0.132
Male	49 (61.3)	30 (55.6)	19 (73.1)
Age, median (IQR)	55 (45, 64)	51 (38,39)	65 (52,74)	<0.001
Clinical outcome, n (%)
Recovery	26 (32.5)	26 (48.1)	0 (0.0)	<0.001
Still in hospital	54 (67.5)	28 (51.9)	26 (100.0)
Incubation period, median (IQR)#	5 (2, 10)	4 (2,12)	7 (1,10)	1.000
Illness day of the first positive SARA-CoV-2 RNA finding, median (IQR)	4 (1,6)	4 (2,6)	3 (1,6)	0.179
Illness days when the first antibody testing sample were collected, median (IQR)	8 (6, 10)	7 (5, 10)	8 (7,10)	0.215
No. of tested samples for antibodies for each case, median (IQR)	4 (3,5)	4 (3,4)	4 (3,5)	0.888
Total number of plasma samples	305	205	100	-

#For patients who had not travel history to Wuhan but had close contact with a confirmed COVID-19 patient (index patient) within 14 days before the symptoms onset, the exposure time was defined as the first day of close contact date with the index patient. The time of SARS-CoV-2 exposure before onset in 45 patients was determined through epidemiological inspection; among them, 15 were critical cases. IQR: interquartile range.

The performance of 2019-nCoV antibody detection kits

A total of 80 patients with COVID-19 and 100 to 300 healthy people were tested for antibodies against SARS-CoV-2 using different immunoassays. The seroconversion rates for Ab, IgM and IgG in patients were 98.8% (79/80), 93.8% (75/80) and 93.8% (75/80), respectively (table 2, combined sensitivity of three methods). The last blood sample of the only patient who had not seroconverted was collected at 7 days post onset (d.p.o). For the Ab, IgM and IgG tests, the performance of ELISAs seems to be the best, although the differences are generally not significant. Therefore, the following serological analyses were all based on the results of ELISAs unless specifically noted.

TABLE 2

Sensitivity and specificity of different immunoassays to detect antibodies against SARS-CoV-2

Type of immunoassay#	Sensitivity			Specificity¶
	No. patient	n(+)	% (95% CI）	No. uninfected person	n(-)	% (95% CI）
Total antibody
ELISA-Ab	80	78	97.5 (91.3, 99.7)	300	300	100.0 (98.8, 100.0)
CMIA-Ab	80	77	96.3 (89.4, 99.2)	300	298	99.3 (97.6, 99.9)
LFIA-Ab	80	78	97.5 (91.3, 99.7)	209	199	95.2 (91.4, 97.7)
Combined	80	79	98.8 (93.2, 100.0)	209	197	94.3 (90.2, 97.0)
IgM
ELISA-IgM	80	74	92.5 (84.4, 97.2)	300	300	100 (98.8, 100)
CMIA-IgM	80	69	86.3 (76.7, 92.9)	300	298	99.3 (97.6, 99.9)
LFIA-IgM	80	71	88.8 (79.7, 94.7)	209	205	98.1 (95.2, 99.5)
Combined	80	75	93.8 (86.0, 97.9)	209	203	97.1 (93.9, 98.9)
IgG
ELISA-IgG	80	71	88.8 (79.7, 94.7)	100	100	100.0 (96.4, 100.0)
LFIA-IgG	80	69	86.3 (76.7, 92.9)	209	208	99.5 (97.4, 100.0)
Combined	80	75	93.8 (86.0, 97.9)	100	99	99.0 (94.6, 100)

#ELISA: enzyme-linked immunosorbent assay; CMIA: chemiluminescence immunoassay; LFIA: lateral flow immunoassay. The combined sensitivities were calculated based on positive findings by any of the assays, and the combined specificities were calculated based on negative findings for all assays.

¶All the controls had not reported close contact with any confirmed COVID-19 patient, and individuals who showed positive for any of the antibody tests were tested to be PCR negative with sputum or saliva samples collected later. Considered the very limited local community spread of the virus during the period, and for more rigorous evaluation of assay's specificity, the community controls with positive result in antibody assays were considered as false positive.

Seroconversion sequentially appeared for Ab, IgM and IgG, with median onset times of 9, 10 and 12 days, respectively (fig. 1a). No significant difference of the time of seroconversion was observed between critical and non-critical patients (Supplementary eFigure 1). The seroconversion of Ab was significantly quicker than that of IgM and IgG (p<0.001). The cumulative seroconversion curve showed that the rate for Ab and IgM reached 100% and IgG reached 97.1% on days 16, 21 and 29 post symptom onset, respectively. The antibody levels increased rapidly starting at 6 days post onset (d.p.o) (fig. 1b). The decline in viral load co-occurred with increasing antibody levels. For patients in the early (0–7 d.p.o) stage of illness, the ELISA-Ab showed the highest sensitivity (64.1%) compared to the ELISA-IgM and ELISA-IgG (33.3% for both, p<0.001, table 3). The sensitivities of antibody, IgM and IgG detection increased significantly when the patient entered the later stage and reached 100%, 96.7% and 93.3% 2 weeks later (p<0.05).

FIGURE 1

Cumulative seroconversion rates and the dynamics of antibody levels since the onset of illness in 80 patients with COVID-19. a) The curves of the cumulative seroconversion rates for total antibody, IgM and IgG detected by ELISAs were plotted according to Kaplan-Meier methods. The serological status of patients was assigned to be negative before the time that the first sample was collected. b) The antibody levels were surrogated expressed using the relative binding signals compared to the cutoff value of each assay (S/CO). Four parameter logistic fitting curves were used to mimic the trends of antibody levels.

TABLE 3

Performance of different detection methods in different periods post onset

Days after onset	No. Patients	RNA#		ELISA-Ab		ELISA-IgM		ELISA-IgG
		n(+)	Sensitivity (%)	n(+)	Sensitivity (%)	n(+)	Sensitivity (%)	n(+)	Sensitivity (%)
0–7	39	36¶	100.0	25	64.1	13	33.3	13	33.3
8–14	75	64¶	90.1	74	98.7	65	86.7	57	76.0
15–29	60	41¶	70.7	60	100.0	58	96.7	56	93.3

#RNA was tested using deep sputum samples.

¶There were 36, 71 and 58 patients who underwent RNA testing during the periods between 0–7, 8–14 and 15–29 days post onset, respectively.

The antibody dynamics after exposure to 2019-nCoV

Because of the difficulty of determining the exact infection date for patients with a prolonged exposure, the antibody dynamics after the earliest date of exposure instead of that after infection were investigated among 45 patients whose expose times were determined (fig. 2). Seroconversion sequentially appeared for Ab, IgM and IgG, and the levels increased rapidly, with a median days post exposure (d.p.e) of 15, 18 and 20, respectively (fig. 3). The median seroconverting times post exposure in critical patients were not different from those in non-critical patients (Supplementary eFigure 2). The decline in viral load co-occurred with increasing antibody levels. The cumulative positive rates for Ab, IgM and IgG separately reached 100%, 94.2% and 96.7% at 37 d.p.e. The patients who reported symptoms within 5 days (0–5 d) since the exposure were assigned to the short incubation period group, and the remaining patients were assigned to the long incubation period group (table 4). There was no significant difference in age, viral load in the early stage of illness or the risk of critical status between the groups. However, the median seroconversion time was shorter for the short incubation period group than for the long incubation period group (13 d.p.e versus 21 d.p.e, p<0.001). In contrast, the median seroconversion days post onset was longer for the short incubation period group than the long incubation period group (10 d.p.o versus 7 d.p.o, p<0.05).

FIGURE 2

The total antibody dynamics of 45 patients with determined exposure time. The patients were listed according to their lasting time of incubation period, from shorter to longer. The clinical severity of each patient was described beside the patient ID. The red and blue symbols, “☻”, indicate the day of illness onset and hospital discharge respectively. “0” represents for total antibody undetectable at the time, and “1” for total antibody detectable. The gray bar indicates the incubation period. The serological status of each patient was presented only during the period of sample collection, without backward or forward extension. The green and orange bars represent for the periods with undetectable antibody (antibody negative period) and detectable antibody (antibody positive period) respectively, while the yellow bar showed the seroconversion period, during the period the seroconversion occurred.

FIGURE 3

Cumulative seroconversion rates and the dynamics of antibody levels since the onset of illness in 45 patients with COVID-19. a) The curves of the cumulative seroconversion rates for total antibody, IgM and IgG detected by ELISAs were plotted according to Kaplan-Meier methods. The serological status of patients was assigned to be negative before the time that the first sample was collected. For patients with a positive result of the first collected sample, the sero-status before the time that the first sample was collected is unknown and assigned as negative. The number of these patients at indicated days after exposure is shown in the brackets. b) The antibody levels were surrogated expressed using the relative binding signals compared to the cutoff value of each assay (S/CO). Four parameter logistic fitting curves were used to mimic the trends of antibody levels.

TABLE 4

Comparison of patients with short or long incubation periods

	Short incubation period group (0–5 d)	Long incubation period group (6–23 d)	P value
Number of patients	25	20	-
Incubation period, median (IQR)	2 (0, 4)	13 (9, 17)	<0.001
Age	51 (36, 63)	54 (46,65)	0.784
Proportion of critical case (n, %)	7 (28.0)	8 (40.0)	0.396
Viral load in the early stage of illness, median (IQR)#	27.8 (22.6,34.9)	27.0 (24.1, 30.1)	0.599
Days post exposure when the antibody converted, median (IQR)	13 (9, 15)	21 (17, 25)	<0.001
Days post onset when the antibody converted, median (IQR)	10 (9, 12)	7 (6, 10)	0.013

#The viral load was measured using the CT value of real-time RT-PCR when detecting the first available sputum samples collected after onset.

Discussion

The present study showed that nearly all (98.8%, 79/80) patients with COVID-19 converted to be seropositive during the illness course. Seroconversion was first observed on 7 d.p.e. The first detectible antibody was total antibody, followed by IgM and IgG, with a median seroconversion time of 15 d.p.e (9 d.p.o), 18 d.p.e (10 d.p.o) and 20 d.p.e (12 d.p.o). It is very similar to that observed in SARS-CoV-1 infection [17, 18]. Interestingly, the increase in antibody levels was accompanied by a decline in viral load.

Currently, the quarantine period is set as 14 days since close contact with a confirmed SARS-CoV-2 infection case. The proportion of infection that could not be screened out through RNA testing during the quarantine period remains unknown. However, it has been documented that some close contactors present symptoms and cause transmission after de-isolation [19]. It is believed that the antibody test might improve the sensitivity to detect infections, but the evidence had not been shown before. Our data showed that the cumulative seroconversion rate was 45.5% on 14 d.p.e. This result indicated that approximately half of the carriers could be screened out if antibodies were tested before de-isolation. The cumulative seroconversion rate reached 75% on 20 d.p.e (11 d.p.o). Seven patients (15.6%) had not presented any symptoms before 14 d.p.e., among them, 4 patients remained seronegative on 22 d.p.e (1 patient) and 25 d.p.e (3 patients). Hence, follow-up antibody testing and monitoring of respiratory symptoms for 2 weeks after de-isolation would be helpful to further reduce the risk of spread.

The median incubation period was 5 days (IQR, 2 to 10), very similar to that previously reported [4, 20]. The time required for seroconverting since exposure is significantly longer for patients with a long incubation period than for patients with a short incubation period (21 d versus 13 d, p<0.001). In contrast, the antibody of patients with a longer incubation period appeared on the earlier days post onset (7 d.p.o versus 10 d.p.o, p<0.05). The difference seems to not be biased by the competence of host immunity because of the similar age distribution between groups. Hence, it is more likely due to the lower intake dose of virus or less efficiency of virus reproduction in the host. Nevertheless, the longer incubation period does not change the initial viral load when the symptom onset occurs or the risk of experiencing critical status. Therefore, in addition to the onset time, the interpretation of the negative findings of antibodies in suspected infections should consider the exposure time as well. The faster seroconversion post onset suggests a longer incubation period.

Recently, Guan et al. [4] reported that the median time from the onset of symptoms to needing mechanical ventilator support is 9.3 days. Therefore, timely diagnosis and admission to the hospital within 7 d.p.o might be crucial to lower the fatality of COVID-19 infection. Zhao et al. [21] reported that the overall RNA positive rate was lower than 70% in patients in the first week post symptom onset and fell to 50% in the next week. Several reports indicated that many patients were finally diagnosed by RNA testing through daily repeat sampling and testing, and many cases that were strongly epidemiologically linked to SARS-CoV-2 exposure and with typical lung radiological findings remained RNA negative [7]. In our study, the RNA positive rate was 100% when admitted to the hospital, but it cannot be excluded that some patients were not diagnosed due to their undetectable viral RNA. Another reason for the relatively high RNA positive rate in our study is that we used a deep sputum sample for RNA testing, in contrast to the more convenient and popular throat/nasal swabs in many other hospitals. This suggests that lower respiratory samples, such as deep sputum and bronchoalveolar lavage, might be more reliable for SARS-CoV-2 RNA detection.

Similar to the RNA test, the negative antibody finding in the early stage of illness could not exclude the possibility of infection. Our study showed that the seroconversion rate on 7 d.p.o reached 64.1% and then increased to over 90% in the next week. The relatively long window period of seroconversion indicates that, for searching previously exposed patients or subclinical carriers, the specific serology should not replace RNA detection but could be an important complement. Furthermore, the fact that nearly all patients will convert to antibody positive and that the titre increased rapidly underlines the usage of antibody tests in confirming or excluding the diagnosis of SARS-CoV-2 infection if the convalescent sample was tested.

The present data showed that the sensitivity of total antibody detection was higher than that of IgM and IgG (p<0.001), while the specificities were overall comparable when the same testing technique (ELISA, CLMA or LFIA) was used. The detection of total antibody is based on double-antigen sandwich methodology. It can detect any type of antibody, including IgM, IgG and IgA, in principle. In addition, the two Fab arms of the same antibody molecule need to bind to the coated antigen and the enzyme-conjugated antigen, which guarantees the specificity of the test and then allows a high concentration of antigens to be used for coating and second binding to increase the sensitivity of the assay. Therefore, it is not unexpected that the sensitivity of total antibody detection is superior to that of IgM and IgG detection in our study. Usually, IgM is considered a marker of current or recent infection, while IgG is considered a marker of post or recent infection. The implications of total antibodies are not so straight and are less commonly used in clinical practice. However, the total antibody test outweighs IgM and IgG if the sensitivity is the top priority and has been frequently used in blood transfusion product screening, such as human immunodeficiency virus and hepatitis C virus. For the current urgent need for a sensitive diagnosis for SARS-CoV-2 infection to contain the spread, the Ab test might be a better choice than IgM or IgG, particularly considering that the virus invaded human society less than 4 months ago and the prevalence of antibody induced post infection is nearly zero. Recently, similar findings were reported by Lassaunière et al. that the total antibody testing by the same Wantai SARS-CoV-2 Ab ELISA as the present study outperformed the assays detecting specific IgG or IgA only in sensitivity and specificity [22]. A Hong Kong group also reported that antibody seroconversion occurred around 10 days after onset, and the patients showed lower viral load in seroconverted stages than earlier [23]. Interestingly, in their study more patients had earlier seroconversion for IgG than IgM. We noted that the indirect ELISA methodology was applied for IgG and IgM antibody detection in their study, despite the μ-chain capture methodology is preferred for IgM testing. Thus it might be explained by the different analytical sensitivity between the assays for detection IgG and IgM.

In our study, antibody tests based on ELISA, CMIA and LFIA were validated and showed good performance overall. CMIA has the advantages of automatic operation and being rapid, high-throughput, objective and quantitative, but it requires a costly specific instrument. ELISA is low-cost, objective and high-throughput and is widely used in most medical laboratories worldwide. LFIA is a rapid point-of-care test that does not require special instrumentation is very convenient and is easy to operate, but the reading of the results is subjective. The establishment of different immunoassays provides flexible choices for users.

Up to date, several reports on antibody response to SARS-CoV-2 infection post illness onset had been published [21-25]. Although the profiles of antibody response presented in these reports are generally the same, the orders of IgM and IgG seroconversion reported are conflicting. This is possible because of differences in the sensitivity of the assays used in these studies.

The limitations of the study include the following: 1) only symptomatic infections were enrolled; therefore, whether the antibody response to asymptomatic infection follows similar features remains to be determined; 2) most blood samples were collected at 1 month post onset, so the duration of antibodies cannot be estimated; 3) the antibody levels were not exactly titrated, and different antigens were used in total antibody (RBD), IgM (RBD) and IgG (Nucleoprotein), hence the correlation of the degree of antibody response with clinical severity is not investigated; and 4) no blood sample was collected during the incubation period, and that the serological status before onset was artificially assigned to be negative might overestimate the needing time for seroconversion. Future studies are needed to better understand the antibody response profile of SARS-CoV-2 infection and to precisely interpret the clinical meaning of serology findings.

In conclusion, a typical acute antibody response is induced during SARS-CoV-2 infection. Serology testing provides an important complement to RNA testing for pathogenic specific diagnosis and helpful information to evaluate the adapted immunity status of patients. It should be strongly recommended that well-validated antibody tests be applied in clinical management and public health practice to improve the control of COVID-19 infection.