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 Table of Contents  
ORIGINAL ARTICLE
Year : 2021  |  Volume : 7  |  Issue : 1  |  Page : 28-34

Study of seroconversion for severe acute respiratory syndrome: Coronavirus 2 IgG antibody in health-care workers in a non-COVID tertiary care hospital


Department of Biochemistry, IGIMS, Patna, Bihar, India

Date of Submission06-Jan-2021
Date of Decision17-Mar-2021
Date of Acceptance31-Mar-2021
Date of Web Publication28-Jun-2021

Correspondence Address:
Rekha Kumari
Department of Biochemistry, IGIMS, Patna, Bihar
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jigims.jigims_3_21

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  Abstract 


Background: SARS-CoV-2 possess higher risk of infection to Health Care Worker (HCW) from patients or other fellow HCW.
Aims and Objective: The aim of this study is to estimate the seroprevalence of SARS-CoV-2 Ig G antibody in a sample of HCW chosen randomly from a tertiary care hospital in Patna Bihar.
Results: Of the 169 participants screened from 8 July to 26 August 2020, 10.1%, (95% CI: 5.97-15.62) were seropositive for IgG antibody against SARS-CoV-2. The cumulative prevalence of SARS-CoV-2 infection (presence of antibodies or past or current positive rRT-PCR) was 10.7% ( 95% CI: 6.4–16.3). Among those with evidence of past or current infection, 5.6 % (1/18) had not been previously diagnosed with COVID-19.
Conclusion: We have observed a relatively low seroprevalence of antibodies among HCW at the peak of the COVID-19 epidemic in IGIMS Patna. Seroconversion occur with a mean of 14 days in HCW from the day of diagnosis with past or present infection of COVID-19.

Keywords: Seroconversion, seroprevalence, severe acute respiratory syndrome coronavirus 2


How to cite this article:
Kumari R, Kumari S, Kumar S, Bharti N. Study of seroconversion for severe acute respiratory syndrome: Coronavirus 2 IgG antibody in health-care workers in a non-COVID tertiary care hospital. J Indira Gandhi Inst Med Sci 2021;7:28-34

How to cite this URL:
Kumari R, Kumari S, Kumar S, Bharti N. Study of seroconversion for severe acute respiratory syndrome: Coronavirus 2 IgG antibody in health-care workers in a non-COVID tertiary care hospital. J Indira Gandhi Inst Med Sci [serial online] 2021 [cited 2021 Sep 25];7:28-34. Available from: http://www.jigims.co.in/text.asp?2021/7/1/28/318931




  Introduction Top


Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a new type of virus belonging to β-Coronavirus, first appeared in Wuhan, China, in December of 2019.[1] It was soon found that the virus was highly infectious and aggressive in spreading. Clinical symptoms of this new virus were different from SARS and so all the symptoms caused by it were grouped under the term COVID-19.[2],[3] As increasing the number of cases with high spreading rate and its severe nature were being reported in other countries, the World Health Organization declared COVID-19 as a pandemic on March 11, 2020.[4] The clinical presentation of SARS-CoV2 is very mild symptoms to severe pneumonia, acute respiratory distress syndrome often requiring ventilator support and death.[5] However, there are many evidences that indicate asymptomatic nature of the infection. Many individuals carry the virus without presenting any symptoms for several weeks.[6],[7],[8] Therefore, the exact number of individuals who are carrying this virus or have been previously infected by SARS-CoV-2 is largely unknown. For combating with such deadly virus, health-care workers (HCWs) are in the frontline. They have to provide clinical care to suspected and confirmed COVID-19 cases. Consequently, they are being exposed to a higher risk of acquiring the disease than the general population and if infected, pose a risk to vulnerable patients and fellow HCW.[9]

SARS-CoV-2 infection is confirmed by the real-time reverse-transcriptase polymerase chain reaction (rRT-PCR).[10] However, after recovery from this infection, RT-PCR is unable to present a clear account of the viral load status. IgG antibody is slow to develop but is more indicative of a previous infection whether symptomatic or asymptomatic.[11] Seroprevalence studies can provide relevant information on the proportion of people who have experienced a recent or past infection. Such studies when conducted in the community provide a better estimate of spread of infection, previous focal points of the disease, susceptibility and course of spread, thus helpful in policy-making to combat the dreadful disease. Although by scale the population of tertiary care hospital is very small, it is an active point of interaction with the SARS-CoV-2 virus. The increasing number of infection among HCW is well reported. The prevalence of SARS-CoV-2 antibodies among HCW is useful in identifying high-risk departments and adopting preventive safety measures to minimize the risk of infection. The time to seroconversion and the antibody levels elicited are not well characterized yet. There is still not well documentation about the association of seropositivity or antibody levels and protection against reinfection, as well as the duration of protective immunity.[12]

Due to ease in lockdown measure and mass migration of migrant laborers across the country, this dire situation had become very challenging to manage. In the month of June 2020, a huge mass of migrant laborers return to the state of Bihar leading to increase in cases in Bihar. Therefore, it was imperative to conduct a seroprevalence study to assess the burden of the disease. Although it cannot give a full view of the pandemic, it can help in understanding the nature of spread of the virus in a community.

Aims and objective

The aim of the study was to estimate the seroprevalence of IgG antibodies against SARS-CoV-2 and seroconversion duration of cases in a sample of HCW from IGIMS, Hospital Patna.


  Materials and Methods Top


Study design, population and setting.

It is a cross-sectional study conducted from July 8, to August 26, 2020. The study population included clinician, nursing staffs, routine laboratory worker, blood sample collectors, COVID-19 RT PCR testing technician, nasopharyngeal swab samplers (for SARS CoV 2 sampling), administrative staff (clerk, peon, guards, and officer), sanitation workers, and others.

Inclusion criteria

  1. Employees of IGIMS
  2. All age group
  3. Willing to participate in the study.


Exclusion criteria

  1. Absenteeism from the workplace in the last 30 days (i.e., on vacation, sick leave, and sabbatical)
  2. Working exclusively outside the hospital
  3. Retirement or end-of-contract planned within 2 months after the recruitment date
  4. Participating in COVID-19 clinical trials for preventive or treatment therapies.


Procedures

A random sample of 500 HCW was selected from the employees' database of the hospital. Selected individuals were approached telephonically following the order of the random list. Some individuals were excluded upon review of inclusion and exclusion criteria. After obtaining informed consent, we handed over a questionnaire to each participant, with the following information: Demographics (age, sex, household size, etc.), professional information (occupation and hospital department), clinical history such as history of COVID-19-compatible symptoms (cough and cold, body ache, headache, weakness, shortness of breath, fever, gastrointestinal (GI) upset, diarrhea, chest pain, anosmia, ageusia, decrease in blood, or platelet count) date of onset and resolution of symptoms, history of RT-PCR testing, comorbidities, history of bacille Calmette-Guérin (BCG) vaccination, and history of close contact with COVID-19 cases. We collected 5 ml venous blood draw in ethylenediaminetetraacetic acid vial for immunological assessments performed by trained nurses using appropriate personal protective equipment (PPE). The samples were transported to the laboratory within 3 h of sample collection.

Laboratory procedures

Quantification of antibodies to SARS-CoV-2 by Chemiluminescent Microparticle assay on Abbott Architect i2000 SR.

A two-step immunoassay for the detection of IgG antibodies to SARS-CoV-2 in human serum and plasma using the chemiluminescent microparticle immunoassay was done. The antigen used in the assay is SARS-CoV-2 nucleocapsid. The patient sample, SARS-CoV-2 antigen-coated paramagnetic microparticles and assay diluent are combined and incubated. IgG antibodies present in the patient sample bind to the antigen-coated microparticles. The mixture was washed. Anti-human IgG acridinium-labelled conjugate was added to create a reaction mixture and incubated. Following a wash cycle, Pre-Trigger and Trigger Solutions were added. The resulting chemiluminescent reaction was measured as a relative light unit (RLU). There was a direct relationship between the amount of IgG antibodies to SARS-CoV-2 in the sample and the RLU detected by the system optics. This relationship was reflected in the calculated index (S/C). The presence or absence of IgG antibodies to SARS-CoV-2 in the sample was determined by comparing the chemiluminescent RLU in the reaction to the calibrator RLU.

Interpretation of the result

The ARCHITECT I 2000 System calculated the calibrator mean chemiluminescent signal from three calibrator replicates and stored the result. The results were reported by dividing the sample result by the stored calibrator result. The default result unit for the SARS-CoV-2 IgG assay was Index (S/C). The cutoff was 1.4 Index (S/C). The index value equal to or >1.4 was considered positive and the value <1.4 was taken as negative test result.

Sample size and statistical analysis

The sample size was calculated using the online sample size calculator.[13] For 50% prevalence at the time of beginning of the study[14] with a precision of 5% and a 95% CI and hospital population size of 2000, the sample size turn out to be 323, but we were able to collect data of only 169 participants. We tested the association between the variables with the Chi-square or Fisher's exact test (for categorical variables) and t Student's test (for continuous quantitative variables). Logistic regression model was run to evaluate the factors associated with seroprevalence of antibodies against SARS-CoV-2. For the variables to be included in the logistic regression model, we used a stepwise selection, starting with the full model, and using a P = 0.10 for the removal and 0.05 for the addition of variables. Spearman correlations were performed to assess the association of antibody index value with age. Mann–Whitney U test was used to compare the antibody index value between different groups. The analysis was carried out using the statistical software IBM SPSS Statistics Version 16.0 (IBM Co., Armonk, NY, USA).

Ethical consideration

The study was conducted after getting permission from Institutional Ethics Committee IGIMS, Patna through Letter No 1739/IEC/IGIMS/2020. Proper informed consent was taken from participant and purpose of the study was explained to all.

[TAG:2]Results [/TAG:2]

Baseline characteristics

From a total number of 200 HCW registered at IGIMS, Hospital, Patna. As of August 26, 2020, we approached all department and randomly selected individuals belonging to group of clinician, nursing staffs, routine laboratory worker, blood sample collectors, COVID-19 RT PCR testing technician and nasopharyngeal swab samplers, administrative staff and sanitation workers. A total of 169 participants were screened, out of which 122 (72.2%) were male and 47 (27.8%) were female. The mean age of the participants was 38.5 years (standard deviation: 11.6). 63 (37.3%) were clinicians, 3 (1.8%) were nurses, 25 (14.8%) were blood sample collector, 32 (18.9% were COVID-19 RT PCR testing technician, 21 (12.4%) were Administrative staff, 10 (5.9%) were routine laboratory worker, 4 (2.4%) were sanitation workers, and 11 (6.5%) belonged to others group.

Thirty-four percent of participants were in daily contact with patients. 4.7% of the participants reported having comorbidities and 5.9% reported having had COVID-19-compatible symptoms. 14.2% of participants had a history of BCG vaccination at time of birth. Eighteen participants were diagnosed with COVID-19 confirmed by rRT-PCR, of which only three had required hospital admission [Table 1] and [Table 2].
Table 1: Baseline characteristics of the study participants

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Table 2: Overall cumulative prevalence of infection (past/current real-time reverse-transcriptase polymerase chain reaction and/or antibodies)

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Seroprevalence of antibodies against severe acute respiratory syndrome coronavirus 2

Seventeen participants (10.1%) were seropositive for IgG against SARS-CoV-2. 5.6% (1/18) of HCW who had been previously diagnosed with COVID-19 by rRT-PCR did not show a detectable response of the antibody [Table 2]. The individual symptoms more strongly associated with seropositivity were (in order): Anosmia (odds ratio [OR]: 137.5, 95% confidence interval [CI]: 27.8–762.8), cough (OR: 134.2, 95% CI: 15.1–1193.2), ageusia (OR: 107.1, 95% CI: 19.6–584.6), weakness (OR: 107.1, 95% CI: 19.6–584.6) fever (OR: 105.7, 95% CI: 11.8–945.2), body ache (OR: 84.4, 95% CI: 15.6–456.9), GI upset (OR: 20.1, 95% CI: 1.73–235.3), all of them with a P < 0.0001 (Chi-square test). There was no reported case of pneumonia among the participants and only one had fall in platelet count.

In our logistic regression models with factors, we included age, sex, daily contact with patient, occupation, comorbidity, history of BCG vaccination, household size, and COVID-like symptoms. We performed univariable analysis [Table 3] and multivariable analysis with the above factors. We found only age and COVID-like symptoms to be significant factor. Factors such as occupation and daily contact with patients bears no significance to the model. Other remaining factors were also not significant. We found that with every one unit increase in age odds of being positive of antibody decreased by 12% (OR: 0.88, 95% CI: 0.78–0.99, P value [Wald's test] = 0.036) and those who had COVID like symptoms have very high odds of being seropositive (OR 160.9: 1.3; 95% CI: 10.1–2561.8; P value [Wald test] = 0.000).
Table 3: Univariable analysis of factors associated with IgG antibodies against severe acute respiratory syndrome coronavirus 2

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Among seropositive HCW, there were no statistically significant associations of antibody index value with sex (P = 0.87) [Figure 1]a. IgG antibody index value was negatively correlated with age (rho = −0.187, P value [Spearman] = 0.015) [Figure 1]b. IgG levels were higher in participants reporting COVID-19 compatible symptoms than in those reporting being asymptomatic (P = 0.000) [Figure 1]c.
Figure 1: Severe acute respiratory syndrome coronavirus 2 antibody index value by demographic and clinical variables. Log of Index value of IgG, against Receptor Binding Domain of the severe acute respiratory syndrome coronavirus 2 Spike glycoprotein by sex (a), age (b) and symptoms (c). The center line of boxes depicts the median of log of Index value; the lower and upper hinges correspond to the first and third quartiles; the distance between the first and third quartiles corresponds to the interquartile range; whiskers extend from the hinge to the highest or lowest value within 1.5 × interquartile range of the respective hinge. Asterix mark is outliers. Mann–Whitney U test was used to assess statistically significant differences in the antibody levels between groups in (a and c). Spearman test was used to calculate the correlation coefficients (rho) and P values (p) in (b), where the straight line depicts the linear regression and the free hand curve represents nonlinear regression calculated using the locally estimated scatterplot smoothing method

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Overall cumulative prevalence of past or current infection

Eighteen HCW had either a positive rRT-PCR in the past, at survey recruitment, or were positive during the survey antibody response [Table 2]. Thus, the cumulative prevalence of SARS-CoV-2 infection was 10.7% (95% CI: 6.4–16.3) [Table 2]. Among them, 44.4% (8/18) did not report any COVID-19 compatible symptom. Almost no case with symptoms that had not been previously diagnosed with COVID-19 was observed.


  Discussion Top


Amid the pandemic, the state of Bihar had experience community transmission of SARS-CoV-2 virus in the month of June due to easing of lockdown measure and migration of workers from metro cities from all over India. With our limited resources, this study aims to report the findings of seroprevalence of IgG antibodies against SARS-CoV-2 among a representative sample of IGIMS Patna Bihar, in a COVID-19 high burden country.

We found that 10.1% (95% CI: 5.97–15.62) of HCW from a tertiary care hospital at Patna (recruited from July 8, 2020, to August 26, 2020) developed detectable IgG antibodies. Given that HCW is a high-risk population for SARS-CoV-2, it is likely that the community seroprevalence is lower than this figure, showing that we are still very far from reaching the 67% herd immunity level that is estimated to be needed to protect the susceptible population,[15] assuming that this immunity prevents from reinfection. A recent sero-surveillance study in Delhi conducted between June 27, 2020 and July 10, 2020, done by National Center for Diseases Control in collaboration with Government of National Capital Territory of Delhi, found 23.48% of the population of Delhi to be seropositive for SARS-CoV-2.

IgG antibody by ELISA.[16] The second serological survey conducted between August 1 and August 7 found the figure increased to 28.3%. In some studies, the positive test rate was 54.1% (95% CI: 52.7–55.6) and 16.1% (95% CI: 14.9–17.4) in slums and nonslums, respectively, in Mumbai, India.[17] This also implies lower to moderate infection fatality rate.[17],[18] This study has a low seroprevalence of SARS CoV 2 antibodies. However, it is compatible with the overall 18.1% seroprevalence preliminary results finding in Bihar among cluster settlements across six districts as reported by the Ministry of Health in the month of August 2020. The likely higher availability of PPE compared with other hospitals, and the early implementation of rRT-PCR screening programs in HCW working in COVID-19 units, coupled with timely case identification and effective contact tracing and quarantines for those outside COVID-19 unit, could explain a relatively low number of infections in our study. Combining data from antibody detection and previous or current positive rRT-PCR, the cumulative prevalence of SARSCoV-2 infection rose to 10.7%. However, out of those positive for SARSCoV-2 infection, 44.4% were asymptomatic, indicating a large percentage of infections were undetected.[19] This calls for early detection/screening programs to be broadly and timely implemented in HCW to decrease in-hospital transmission as well as reinforce the critical role of PPE usage.[20] The likelihood of being seropositive was higher in participants who reported having any COVID-19 symptom (OR: 160.9) during the month of July and August 2020. Although most COVID-19 symptoms are common to many other upper respiratory viral infections, those more highly associated with seropositivity were anosmia (OR: 137.5, 95% CI: 27.8–762.8), cough (OR: 134.2, 95% CI: 15.1–1193.2), ageusia (OR: 107.1, 95% CI: 19.6–584.6), weakness (OR: 107.1, 95% CI: 19.6–584.6), and fever (OR: 105.7, 95% CI: 11.8–945.2), all of them with a P < 0.0001 (Chi-square test). Anosmia and ageusia (both OR >100) seem to be quite specific for COVID-19.[21],[22] As expected, having developed the disease was the most important factor associated with the development of antibodies (OR: 200.4). With every 1 year increase in age, odds of seropositivity decreased by 12% which can be explained by relatively high younger population in the hospital employees working group. None of the professional categories or being directly involved in clinical care were factors associated with higher odds of being seropositive, which might be explained by a higher perception of risk leading to a better protection with PPEs, more careful practices and thus, a lower risk of acquiring the infection.[23] Nonetheless, the relatively low number of seropositive HCW in our sample hinders any firm conclusion about the associations between professional categories, level of patient interaction, and risk of infection. Some of our subject recently contracted the disease during the study period and were screened after 2 weeks of the discharge from hospital or from the date of being RT PCR tested positive. This is in line with previous reports showing that seroconversion occurs between 2 and 3 weeks after the onset of symptoms.[12] Importantly, we detected no difference in IgG index value among both gender (Mann–Whitney U test P = 0.87) but highly significant difference in index value in those who had COVID-19 like symptoms to that who were asymptomatic [Figure 3]a and [Figure 3]c. In our study, the age of the participant was seen to bear a negative correlation with the IgG index value (Spearman rho = −0.187, P = 0.015) [Figure 1]b, which indicates that younger subjects have lower levels of antibody. Furthermore, there is higher proportion of asymptomatic cases among young seropositive participants. If it is confirmed that asymptomatic subjects have lower levels of antibodies,[24] this could have impact on the detection of seroconversion in this specific group. Given the current lack of evidence on the correlation of SARS-CoV-2 antibody levels and protection against reinfection, no recommendations should be derived for seropositive HCW at an individual level. This study also shows that around 44.4% of asymptomatic individual were seropositive that had easily left out and could had contribute as carrier of the virus. Thus, enforcement of rRT-PCR screening programs for all HCW, regardless of the presence of symptoms, is highly recommended in health-care settings to reduce the risk of hospital-acquired SARS-CoV-2 infections.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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