|Year : 2021 | Volume
| Issue : 2 | Page : 171-177
Seroprevalence of SARS-COV2 antibodies among the serving personnel of south western command: A multi-centric study
Vikram Singh Grewal1, Kuntal Bandyopadhyay2, Ashish Jain3, Rakhi Dhawan4, Arunjeet Singh5, Kedar Jayant Raikar6, Navdeep Dahiya7, Chetan Kharche8, Sanjeev Satish Srivastava9, Manohar Dutt10, Atul Kotwal11
1 Col Health, HQ SWC (Med),48 Field Health Organization, Bathinda, India
2 OC, 48 Field Health Organization, Bathinda, India
3 CPO, HQ SWC (Med), MH, Jaipur, Rajasthan, India
4 Sr Registrar, MH, Jaipur, Rajasthan, India
5 HQ 1 Corps (Med), MH, Hisar, Haryana, India
6 DADH, 42 Arty Div (Med), MH, Hisar, Haryana, India
7 CO, MH, Hisar, Haryana, India
8 DADH, 24 Inf Div (Med), MH, Kota, Rajasthan, India
9 CO, 184 MH, MH, Kota, Rajasthan, India
10 CO, MH, Kota, Rajasthan, India
11 Executive Director, National Health System Resource centre (NHSRC), New Delhi, India
|Date of Submission||11-May-2021|
|Date of Decision||16-Jul-2021|
|Date of Acceptance||03-Aug-2021|
|Date of Web Publication||30-Sep-2021|
Lt Col (Dr) Kuntal Bandyopadhyay
48 Field Health Organization, Bathinda - 151 004, Punjab
Source of Support: None, Conflict of Interest: None
Background: Serological diagnosis has become an important tool to understand the extent of COVID-19 in the community. Thus, this study was conducted to estimate the prevalence of SARS-CoV-2 antibodies and to analyze various characteristics (risk factors) associated with SARS-CoV-2 infection among serving personnel in a large geographical area straddling four North Indian states. Materials and Methods: This multicentric, cross-sectional analytical study was conducted among serving personnel in eight stations spread over Punjab, UP, Haryana, and Rajasthan in October-November 2020. A total of 3680 (410 × 8 = 3280 general participants and 50 × 8 = 400 purposive samples) individuals were enrolled and tested using IgG ELISA kit (in four stations) and RAPID CARD-based tests (in the rest four stations). Results: While the overall seroprevalence was found to be 16.57% (610/3680 participants being positive), the seropositivity was found to be 12.01% (10.92%–13.70%) and 54% (52.35%–56.45%) among the study participant's and purposive sampling groups, respectively. While statistically significant association was found between seronegativity and attending any lecture on COVID-19 before the survey (P < 0.001) or following recommended protocols for the prevention of COVID-19 (P < 0.001), a similar association was found between seropositivity and occupation with high exposure to serving personnel or civilians (P < 0.001), having close contact (less than one meter) with COVID-19 confirmed cases in the past (P < 0.001) and being tested positive for COVID-19 in the past (P < 0.05). Conclusion: Our study found a moderate overall seroprevalence with low seroprevalence in few stations and high in the rest.
Keywords: Armed forces personnel, COVID-19, seroprevalence
|How to cite this article:|
Grewal VS, Bandyopadhyay K, Jain A, Dhawan R, Singh A, Raikar KJ, Dahiya N, Kharche C, Srivastava SS, Dutt M, Kotwal A. Seroprevalence of SARS-COV2 antibodies among the serving personnel of south western command: A multi-centric study. J Mar Med Soc 2021;23:171-7
|How to cite this URL:|
Grewal VS, Bandyopadhyay K, Jain A, Dhawan R, Singh A, Raikar KJ, Dahiya N, Kharche C, Srivastava SS, Dutt M, Kotwal A. Seroprevalence of SARS-COV2 antibodies among the serving personnel of south western command: A multi-centric study. J Mar Med Soc [serial online] 2021 [cited 2021 Nov 28];23:171-7. Available from: https://www.marinemedicalsociety.in/text.asp?2021/23/2/171/327204
| Introduction|| |
From its origin in Wuhan city, Hubei province of China in December 2019 to being declared a pandemic by the World Health Organization (WHO) on March 11, 2020, and thereafter, the various stages of lockdown and unlock, the disease has evolved a long way and has engulfed the entire globe as of today. Most of the cases of COVID-19 are either mild or asymptomatic. As per the WHO-China Joint Monitoring Mission Report and an analysis of 21 published reports, 5%–80% of SARS-CoV-2-infected patients have been noted to be asymptomatic. Thus, it is difficult to estimate the prevalence and geographical spread of the disease. Moreover, these asymptomatic and presymptomatic individuals can be a source of infection in the community.,,
Thus far, the most commonly used test with high validity and reliability for diagnosis of COVID-19 has been the reverse transcription-polymerase chain reaction (RT-PCR), performed using nasopharyngeal swabs or other upper respiratory tract specimens, including throat swab or, more recently, saliva. The COVID-19 infection can also be detected indirectly by measuring the host immune response to SARS-CoV-2 infection. Serological diagnosis is especially important for patients with mild-to-moderate illness who may present late, beyond the first 2 weeks of illness onset. Serological diagnosis also is becoming an important tool to understand the extent of COVID-19 in the community and to identify individuals who are immune and potentially “protected” from becoming infected.,
The asymptomatic individuals usually remain undiagnosed and undetected as facility-based passive surveillance efforts are likely to miss mild and asymptomatic cases. Through household-targeted, antibody-based active surveillance using serologic testing, we can minimize the biases of referral and selective testing affecting laboratory-based surveillance, generate evidence on the role of asymptomatic infection in driving transmission and estimate the extent of infection in a given population.
Based on the above, the Indian Council of Medical Research (ICMR) conducted two population-based cross-sectional serosurveys, in sixty districts across the country to estimate and monitor the trend of infection in the adult general population, determine the socio-demographic risk factors and delineate the geographical spread of the infection., The first round was conducted in May-June 2020 and second in August-September 2020 and the overall seroprevalence among the adult population was 0.73% and 7.1%, respectively. Subsequently, repeated serosurveys have been conducted by various states in the country and also by the ICMR. The Delhi sero-surveys showed a prevalence of 29.1% in July-August 2020 and 56% in Jan 2021., Tamil Nadu showed a prevalence of 31.6% in October-November 2020, Mumbai reported a 16.1% seroprevalence in nonslum areas and 54.1% in slum areas in June-July 2020, and Gujarat reported 17.6% seroprevalence in June-July 2020.
The armed forces population is a very special subset of the general population, with unique and independent primary, secondary and tertiary health care mechanisms to combat disease in place. This also holds good for COVID-19 where aggressive modalities have been put in by the AFMS - Armed Forces Medical Services. Owing to the professional requirement of traveling across the country on duty and regular interaction with the civil population during as well as postlockdown phase, estimation of the seropositivity among serving soldiers is important to understand the risks and manage the prevention and control activities efficiently. Thus, this study was conducted to estimate the prevalence of SARS-CoV-2 antibodies and to analyze various characteristics (risk factors) associated with SARS-CoV-2 infection among serving personnel in a large geographical area straddling four North Indian states.
| Materials and Methods|| |
This multicentric, cross-sectional analytical study was conducted among serving personnel in eight stations spread over Punjab, UP, Haryana, and Rajasthan in October and November 2020. The sample size was calculated with the desired level of confidence at 95%, the margin of error at 5% and 410 participants per station had 80% power to estimate the expected prevalence range from 4% to 40%. The inclusion criteria were all available serving personnel more than 18 years of age in the designated eight stations and the exclusion criteria were individuals on leave during the study period or individuals with any contraindication to phlebotomy.
The process of participants enrolment is depicted in [Figure 1]. A sampling frame was made in each station with all individuals fitting into the inclusion criteria and the method of sampling was stratified sampling method for each station followed by systematic random sampling in each stratum within the station. The strata of each station were the existing sectors earmarked in the station and used for Anti-Dengue Task Force activities. All sectors were equally covered and thus, the study had representative population from all sectors of a particular station. The number of persons sampled per sector was 82 (410/5) and were included in the study.
In addition, a purposive sample of those exposed to a large number of persons or civilians (owing to their job profile like persons in key/central appointments, salespersons in shopping areas, drivers, guards, sentries, etc.,) were added to the calculated sample size and analyzed separately. A sampling frame of all such individuals were made and a total of 50 such samples were selected and tested using simple random sampling method in each station.
A data collection team (comprising a team leader, a trained phlebotomist and two supporting members) was constituted at each station and all universal precautions for COVID-19 prevention were observed during all activities. After initial briefing about the study and obtaining written informed consent from the study participants, a questionnaire was given (Separate ID and form for each subject) and thereafter 3–5 ml of venous blood was collected and labeled (same ID as on form). The venous samples were centrifuged at the designated health-care facility and thereafter serum was obtained and stored. For the four stations with an ELISA reader installed, the sero-survey was conducted using an IgG ELISA kit (Covid Kavach Elisa/ERBA ELISA) and for the rest four stations, RAPID CARD-based antibody test kits (M/s S. D. Biosensor, Standard Q Covid-19 IgM/IgG Duo test) were used to conduct the sero-survey. Validation of Rapid kits with ELISA kits was done by cross-testing with ELISA test samples at the centers with ELISA kits for sero-survey.
The data were compiled, collated, and analyzed using software IBM SPSS version 20 and Epi info 7 by Centres for Disease Control and Prevention, Atlanta. The results were tabulated and appropriate statistics were used. The Institutional Ethical Committee of each station and also of the principal investigator's institution processed the protocol and provided the clearance.
| Results|| |
A total of 3680 participants (410 + 50 = 460 per station) aged more than 18 years were studied and were found to have a mean age of 36.3 ± 1.8 years with 407 (11.1%) being more than or equal to 50 years of age. The study included 3567 (96.9%) male and 113 (3.1%) female participants. Majority of the participants 2203 (59.9%) lived in unit accommodation while 1477 (40.1%) lived in married accommodation. A total of 2999 (81.5%) had education up to std XII, while 547 (14.9%) had completed graduation and 134 (3.6%) had a postgraduate or higher qualification. The station-wise details are depicted in [Table 1].
|Table 1: Demographic characteristics amongst study participants and station wise comparison|
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Among the 3680 (460 × 8) participants, 610 tested positive for the presence of IgG antibodies against SARS-CoV-2, resulting in a seroprevalence of 16.57% among the overall study population. Among the 3280 (410 × 8) sampled participant's group, 394 tested positive with a seroprevalence of 12.01% (10.92%–13.70%), while the seropositivity was found to be 54% (52.35%–56.45%) in the purposive sampling group with a total of 216 being found positive out of 400 (50 × 8) participants in that group. The station-wise details are shown in [Table 2].
|Table 2: Prevalence of seropositivity amongst the study participants and station wise comparison|
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[Table 3] shows the association of various parameters like the presence of co-morbidities, smoking, gender, and age with seropositivity among the participants. A statistically significant association was found between nonsmokers and seronegativity (P < 0.001) for two stations (Bikaner and Alwar). Statistically significant association was also found between attending any lecture on COVID-19 before the survey and seronegativity (P < 0.001), following recommended protocols for prevention of COVID-19 and seronegativity (P < 0.001), occupation with high exposure to serving personnel or civilians and seropositivity (P < 0.001), having close contact (<1 m) with COVID-19 confirmed cases in the past and seropositivity (P < 0.001) and being tested positive for COVID-19 in the past with seropositivity (P < 0.05) as depicted in [Table 4]. Multiple logistic regression by including the variables showing statistically significant association with seropositivity (P < 0.05) showed that those who attended any lecture on COVID-19 before the survey had 5.32 times higher odds of having seronegativity and those who followed recommended protocols for prevention of COVID-19 had 18.62 times higher odds of having seronegativity as compared to those who did not. Similarly, those who were not detailed for duties outside the station in the last 1 month before the survey had 18.54 times higher odds for being seronegative as compared to those who were detailed, while, those who did not have any close contact with confirmed COVID-19 patients (within 1 m) in the past or had not been tested positive with RT-PCR for SARS CoV-2 in the past had 7.56 and 15.05 times higher odds, respectively, for being seronegative as compared to those who did [Table 4].
|Table 3: Association of various parameters with seropositivity and station wise comparison|
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|Table 4: Association of various coronavirus disease 2019 related practices with seropositivity (n=3680 [460×8])|
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| Discussion|| |
As brought out earlier that COVID-19 disease has more asymptomatic individuals than symptomatic cases and armed forces population being a special subset with its unique and self-sufficient health care system in place, it was a felt need to study the seroprevalence in this population as well. Among the various national and regional level sero-surveys being undertaken at various time intervals across the country, this study was also undertaken concurrently for the people in uniform under the area of responsibility of South Western Command as the first population-based seroprevalence study for armed forces, according to ICMR protocol.
This multicentric sero-surveillance study, done in October-November 2020 indicated a seroprevalence of 12.01% (10.92%–13.70%) among the sampled population across the eight selected military stations, ranging from as low as 3.90% (2.25%–6.26%) in Suratgarh military station to as high as 38.78% (31.04%–43.68%) in Jaipur military station. The seroprevalence among the purposive sampling group ranged from 44% (38.78%–49.34%) in Suratgarh station to 64% (60.21%–68.42%) in Kota military station, with overall seropositivity of 54% (52.35%–56.45%) in that group. The stark difference in the range of seropositivity among the two subgroups suggests that despite a similar demographic profile (age, gender, occupation, and education) among the participants of both the subgroups, the risk of contracting the infection is much higher in the purposive sampling group, as they are regularly exposed to more people, due to their immediate job profile during COVID-19 scenario.
The findings of this study (overall seroprevalence of 16.57%) were higher as compared to the two rounds of national serosurvey by ICMR but were comparable to the various regional serosurveys conducted between June and October 2020 across various cities and states of India, which reported a varying seroprevalence rate. The first round of national serosurvey conducted by ICMR in May-June 2020 reported a seroprevalence of 0.73% ranging from 0.62% to 1.03% across the various districts. However, the second round of the national serosurvey conducted in August-September 2020 reported a 10 folds jump with a seroprevalence of 7.1% among the adult population. While the national serosurvey reported a seroprevalence of 5.6% for rural areas, 9.4% for urban nonslum areas and 17.2% for urban slum areas, another study reported a 16.1% seroprevalence in nonslum areas and 54.1% in slum areas of Mumbai. Various other regional serosurvey reported seroprevalence rates from 16.4% in Karnataka (September 2020), 20.8% in Odisha (August 2020), 29.1% in Delhi (July-August 2020), and 34% in Pimpri-Chinchwad, Maharashtra (October 2020).
When compared to the dashboard of data available from various seroepidemiological studies globally on similar study parameters, our results were similar to the results from national serosurvey studies in Iran (17.1%), Demographic Republic of Congo (19.7%) and Chicago (19.8%), while it was higher as compared to Karachi, Pakistan (12.8%) and England (12.1%) and low as compared to Colombia (55.3%) and Maranhao, Brazil (40.4%).
Comparative seroepidemiological data available from various countries across varied timelines show a range of seroprevalence among the varied population. While one study shows seroprevalence ranging from 0.4% (Seattle, US) to 59.3% (Oise, France) done between December 2019 and May 2020 for the general population, another study showed the range to be between 0.5% (Southeast and East Asia) to 18.8% (South Asia) for the general population and 1.6% (Central Asia and Europe) to 39.4% (South Asia) for at-risk population, done between January 2020 and August 2020. Thus, it is evident that the seroprevalence is guided by a number of factors like the geographical location, the period under study (as antibody titers might decline over a period of time among cases or rise in case of fresh transmission of infections), the specificity and the sensitivity of the serological tests used, the characteristics of the population under study (general or at risk), the density of population in the area of study and the general practices followed by the study population (COVID-19 preventive protocols followed or not).
The findings of our study indicate that seroprevalence did not differ by gender, age group, lifestyle, and the presence or absence of comorbidities, which is similar to the findings of the national serosurvey by ICMR indicating similar vulnerability amongst these variables for infection to SARS-CoV-2. However, a study in Geneva, Switzerland reported a higher seroprevalence among male population. The findings of our study suggest that seropositivity was higher amongst those who did not attend prior lecture/demo on COVID-19 prevention or did not follow the preventive protocols. Furthermore, those who had tested positive earlier for COVID-19 or had close contacts with confirmed cases or had increased exposure due to their job profile had higher seropositivity which is similar to the other studies.,
Our study has few limitations. First, some asymptomatic individuals may not seroconvert and some individuals may have been tested before seroconversion, so the data in this study may underestimate the true number of SARS-CoV-2 infections. Second, the study group excluded the age group <18 years and other dependants and hence, the results cannot be extrapolated to the entire population residing in the respective military stations. Thus, despite sincere efforts made to generate estimates applicable to the general population, representativeness is difficult to ensure. Third, since the population was exclusively from the military background, a healthy volunteer bias might underestimate the actual seroprevalence. Fourthly, the seroprevalence depends upon a number of factors as brought out earlier. Thus, this study gives the seroprevalence estimates for a cross-section of time only (study period) and might vary if a follow-up sero-survey is conducted in the same population over a different period.
Although vaccine against the COVID-19 virus has been recently made available by the Government of India and the process of nationwide vaccination for health care workers is underway, there is still no definitive cure for the disease and the duration of protection against the disease due to vaccination is also uncertain as of now. Thus, this study provides the prevaccination prevalence of seropositivity among serving personnel of South Western Command, with the aim of providing evidence for planning and preventive purposes in armed forces and also a scope of comparison once the vaccination campaign is successfully completed.
| Conclusion|| |
To conclude, our study found a moderate overall seroprevalence with low seroprevalence in few stations and high in the rest. The findings of this study should not be used to stigmatize any population or underestimate the efforts and preventive practices in any military station. The study only aims to provide an assessment of seroprevalence of COVID-19 infection among the serving personnel of South Western Command from various stations and also helps in identifying various factors associated with a higher risk of COVID-19 infection among the serving persons, to initiate better preventive measures to reduce their risk as well as to break the chain of further transmission. This study provides the prevaccination seroprevalence estimates among the military population and further thrusts the need of follow-up studies to assess and analyze the postvaccination seroprevalence as well as the pattern and duration of seroprotection provided by the antibodies.
We sincerely thank Col Umesh Kapoor, Sr Adv (Path), MH Jaipur, Lt Col G. Lakshmi Nair, Cl Spl (Path), 174 MH, Lt Col Madhukar Kumar, Gd Spl (Path), MH Hisar, Lt Col Anshum Bhalla, Gd Spl (Path), MH Mathura, Lt Col Yogendra Dwivedi, Gd Spl (Med), MH Kota, Maj SS Rathore, Gd Spl (Path), MH Jaipur, Maj Shilpi Gupta, Gd Spl (Micro), MH Jaipur, Maj Deepon Mukhopadhyay, MO (Med), 187 MH, Maj Eshita Raju, Gd Spl (Med), 184 MH, Maj Dharmendra Kumar, Gd Spl (Med), MH Alwar for their efforts and support in conducting this study.
Financial support and sponsorship
Funding for ELISA Kits provided by the HQ South Western Command and Rapid Kits provided by the office of DGAFMS.
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4]