|Year : 2021 | Volume
| Issue : 1 | Page : 76-80
COVID-19 immunoglobulin G antibodies in healthy blood donors paving way to herd immunity
Rateesh Sareen, GN Gupta, Pankaj Agarwal, Shyan Saini
Department of Pathology and Transfusion Medicine, Santokba Durlabhji Memorial Hospital and Research Centre, Jaipur, Rajasthan, India
|Date of Submission||02-Feb-2021|
|Date of Decision||14-Feb-2021|
|Date of Acceptance||19-Feb-2021|
|Date of Web Publication||29-May-2021|
Dr. Rateesh Sareen
Department of Pathology and Transfusion Medicine, Santokba Durlabhji Memorial Hospital and Research Centre, Jaipur, Rajasthan
Source of Support: None, Conflict of Interest: None
Background and Objectives: Herd immunity is the immunity or resistance to particular infection that occurs in group of people when a very high percentage of individuals have been vaccinated or previously exposed to infection. The goal of this study was to assess the development of herd immunity to COVID-19 in parts of Western India. Methods: The study was conducted at a tertiary care hospital in India on routine blood donors who were tested for SARS-CoV-2 immunoglobulin G (IgG) antibody. We systematically investigated 808 healthy donors at various points of time in the 3-month period starting from September 2020 to November 2020 for SARS-CoV-2 seroprevalence. Results: The results of November month show a sudden increase (51.96%) in the later half. The seroprevalence in healthy donors in other towns and cities shows an aggregate average of SARS-CoV-2 IgG antibody 13.59% (200/1472) as against Jaipur city with 36.12% (292/808). Deedwana has higher seropositivity in blood donors 31.5% (24/76) whereas Sujangarh and Jhunjhunu did not have any donors with seropositive status. Conclusion: Our findings could be the tip of iceberg of emerging herd immunity to SARS-CoV-2 infection in India. Future research will determine how long these antibodies will last. Will they be protective toward future COVID-19 infection?
Keywords: Blood donors, herd immunity, SARS-CoV-2 immunoglobulin G antibodies
|How to cite this article:|
Sareen R, Gupta G N, Agarwal P, Saini S. COVID-19 immunoglobulin G antibodies in healthy blood donors paving way to herd immunity. Glob J Transfus Med 2021;6:76-80
|How to cite this URL:|
Sareen R, Gupta G N, Agarwal P, Saini S. COVID-19 immunoglobulin G antibodies in healthy blood donors paving way to herd immunity. Glob J Transfus Med [serial online] 2021 [cited 2023 Jan 30];6:76-80. Available from: https://www.gjtmonline.com/text.asp?2021/6/1/76/317177
| Introduction|| |
Herd immunity is the immunity or resistance to particular infection that occurs in group of people when a very high percentage of individuals have been vaccinated or previously exposed to infection. In context to the current ongoing pandemic, it could be achieved by any of the three ways – cross-reactivity among the related infective agents, vaccination, and infection. Cross-reactivity is not a bulletproof jacket against infection as it does not reduce the transmission of infections from an infected person and therefore will not help in reducing the incidence of new infections., Vaccination against COVID-19 is not a straightforward tool either. With so many potential candidates in pipeline, the efficacy, safety, ease of administration as well as logistics of vaccines are important factors that need to pass the test of time.
| Objectives|| |
The idea to assess herd immunity for COVID-19 came at the backdrop of a press release on July 28, 2020, by NITI Aayog on SARS-CoV-2 seroprevalence in Mumbai based on a study conducted jointly by the Municipal Corporation of Greater Mumbai (MCGM) and Tata Institute of Fundamental Research (TIFR) in three localities in Mumbai, namely Matunga, Chembur, and Dahisar. Samples collected from general population found a seroprevalence of 57% and 16% in slum and nonslum areas, respectively. The current study was conducted on healthy blood donors in the state of Rajasthan over a period of 3 months starting from September 2020 by estimation of serum immunoglobulin G (IgG) antibody titers on collected blood units.
| Materials and Methods|| |
The study was conducted at tertiary care hospital blood banks in Western India on routine blood donors who were tested for SARS-CoV-2 IgG antibody on VITROS platform (VITROS Immunodiagnostic Products Anti-SARS-CoV-2 IgG Test, Ortho-Clinical Diagnostics, Inc., NY, USA).
The study was done after approval from the ethics committee of the hospital.
Selection of donors
The donors were randomly selected and were divided into two groups: from Jaipur city and from areas excluding Jaipur district from various parts of the state. The seroprevalence in other towns of the state was estimated by random selection as it was not possible to perform testing for all blood donors; these areas were separate from the main city Jaipur so that they were geographically from a different subset with no overlapping of donors unlike in Jaipur, a metropolitan city.
Additional donor selection criteria
In addition to the routine criteria for selection of blood donors, the following additional criteria were applied based on national guidelines:
- Donor should be free of any flu-like symptom for 28 days before blood donation
- The donor should not have a close contact with suspected or confirmed SARS-CoV-2 cases in the past 28 days before blood donation
- The donor should not have a history of travel to a containment zone – domestic or international in the past 28 days
- The donor should not have a history of SARS-CoV-2 infection.
The donor consent for testing for SARS-CoV-2 antibody was taken at the time of blood donation in writing. The sample used was serum, the same sample used for transfusion-transmitted infection testing.
The results were tabulated on Microsoft Excel sheet. Statistical analyses were performed using MedCalc for Windows, version 19.4 (MedCalc Software, Ostend, Belgium). The sample size was calculated using the following formulae:
Sample size is calculated using the formula: n = (Z2 × P × [1 − P])/e2
Z = Value from standard normal distribution corresponding to desired confidence level (Z = 1.96 for 95% confidence interval [CI])
P is expected true proportion
e is desired precision (half desired CI width).
Based on the estimated proportion of 0.3, desired precision of 0.05, and CI of 0.95 in a population of 3,500,000, the minimum sample size was calculated as 323 individuals.
| Results|| |
In the current study, we systematically investigated 808 healthy donors at various points of time starting from September 2020 to November 2020 for SARS-CoV-2 seroprevalence. During the initial month, i.e., in September, the samples tested were less than in the later month of November. [Figure 1] shows the trend of SARS-CoV-2 antibody in asymptomatic COVID-19 carriers over 3 months in Jaipur city. The results of November month show a sudden increase (51.96%) that coincides with COVID-19 symptomatic and polymerase chain reaction-confirmed cases by that time.
|Figure 1: The prevalence of COVID.19 immunoglobulin G antibody in blood donors in Jaipur city|
Click here to view
[Table 1] shows the seroprevalence in healthy donors in other towns and cities; their aggregate average was 13.59% (200/1472) as against Jaipur city with 36.12% (292/808). Deedwana has higher seropositivity in blood donors 31.5% (24/76) whereas Sujangarh and Jhunjhunu did not have any seropositive healthy blood donor.
|Table 1: Seroprevalence in blood donors in different areas in Rajasthan, India between September and November 2020|
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It is pertinent to note that the study population was healthy asymptomatic blood donors with no history of symptoms or SARS-CoV-2 infection, or close contact with SARS-CoV-2 individuals. The majority of blood donors were males.
| Discussion|| |
The presence of IgG in the donors suggested that they had past infection as none of them tested positive for IgM seropositivity. A similar study from China showed that the seroprevalence of COVID-19 IgG antibody was 2.29%, 0.029%, and 0.0074% in Wuhan, Shenzhen, and Shijiazhuang, respectively, from January 2020 to April 2020.
The trends of the present study show a rise in IgG seroprevalence in healthy blood donors over a 3-month period. In comparison with literature studies,,,,,, on seroprevalence in other cities of the world, our rate of IgG positivity is high [Table 2]. It is possible that as the other studies were done early in the pandemic between April and May 2020, the seropositivity was low.
Our study seems to highlight the development of immunity blood donors who represent the general population. A similar study by Younas et al. in July 2020 showed 21.4%–37.7% COVID seroprevalence in Pakistan. An Indian study by MCGM and TIFR in July 2020 in Mumbai estimated seroprevalence in general population as 57% and 16% in slum and nonslum areas.
Our study is unique as it is the first one in India to address the issue of emerging herd immunity by estimating IgG seropositivity in healthy blood donors spanning over a period of 3 months. Population-based serological surveillance is of vital importance to assess the prevalence of SARS-CoV-2 and to estimate the emerging herd immunity.
There have been several newspaper reports pertaining to the development of herd immunity to SARS-CoV-2. A group of scientists in early October released a document called the great Barrington declaration where they promulgated the theory of herd immunity that called for return to normal life for people at lower risk of severe COVID-19 infection and allowing SARS-CoV-2 to spread in sufficient level imparting herd immunity. This was met with criticism by another group of scientists in The Lancet who considered it as a dangerous approach.
Smith in 1970 and Dietz in 1975 devised a theorem for calculating herd immunity. Based on it, Based on the theorem, if immunity is achieved randomly such that an average individual contacted is R0, then for incidence of infection to decline, the proportion of immunity should exceed (R0 − R1)/R0 or simply 1 − 1/R0. This concept has been used for estimation of herd immunity levels that are required for vaccination. It is still unclear how we can rely upon this theory as the population is always heterogeneous and this simplified approach might not give real targets for vaccination. Calculation of herd immunity is not all that simple. For example, R0 will vary between populations from city to city and even within the same city depending on crowding/population density, migration, and government efforts at the local level. Similarly, it varies between slums and nonslums as social distancing, hygiene, use of common facilities, etc., are factors that affect the transmission chain. The initial cohort of 425 confirmed cases in Wuhan, China, estimated an R0 of 2.2, however, recent estimates place R0 at 5.7. If few assume R0 as 3 for SARS-COV-2, the herd immunity threshold comes to 67%, thereby implying that two-thirds of our population need to be infected or vaccinated to achieve herd immunity. In contrast if R0 is assumed 2, then 50% of population needs to be vaccinated for development of herd immunity to SARS COV-2 infection.
Our findings suggest that we are near approaching the threshold for herd immunity.
In June, Kwok et al., published in, the Journal of Infection the estimated threshold of herd immunity levels for SARS-CoV-2 infection that were required to afford protection to people, the herd immunity levels varied from country to country for instance it was 85% for Bahrain and 5.66% for Kuwait, as per their study involving thirty countires.,
Transient changes in population behavior like social distancing, stringent lock down, restricted movement of people decreases R0 and could change the calculated herd immunity threshold levels. The example of Brazilian city of Manaus gave jolt to herd immunity theory as high mortality rates in May were followed by slowdown of cases in August, but the cases increased again in November. The city situated in Amazon state in Brazil shows the impact on mortality rates of a largely unmitigated outbreak, where even with an estimated 76% of the population being infected, herd immunity was not achieved.
In the recent study, the fifth serosurvey for COVID-19 antibodies in country's capital, New Delhi, with a population of more than 2 crores showed that 50%–60% of the population have been found to have antibodies. Similarly, there are reports that mention the prevalence of COVID-19 antibodies in Pune city stood at 85% with a sample size 1659 of the study population. Kashmir during the second round of serosurvey in November 2020 showed that 38.8% of population had COVID-19 antibodies. The figures for Indore are 7%–8%, Puducherry – 22.7%, and Chennai – 32.3%. Some states despite being the epicenter of pandemic are yet to conduct serosurvey. A similar serosurvey from Lucknow city with a population of 50 lakhs showed an increase of COVID-19 antibodies from 22% in November 2020 to 50%–60% in February 2021.
The strategy of relying on herd immunity for any country will call for large number of sick people, especially those above 60 years of age with comorbidities resulting in increased death toll which will be uncomfortable for political and social setups. There is a lack of evidence in medical literature by which may confidently rely on antibody protection afforded to those recovered from COVID-19 infection. There are instances in history where smallpox and polio were eradicated by mass vaccination strategy without relying on spread of natural infection to afford herd immunity. We are in the 21st century, and we cannot afford to add on morbidity. In the absence of vaccine, there will be sufficient number of people in whom disease can start again and bring the dormant infections into a full-blown pandemic.
Nearly 0.98 million cases have recovered in India, and so far in Jaipur district, there were 56,982 cases, 53,812 recoveries, and 499 deaths as on December 29, 2020. The recovered cases would add to the already existing pool of healthy blood donors who are positive for anti-COVID IgG antibodies contributing to increased immunity on community level. The press briefing by World Health Organization Chief Scientist Sumya Swaminathan on January 11, 2021, suggested that higher levels of herd immunity as close as 90% may be required for attaining herd immunity in COVID-19 infection as against 60%–70% predicted earlier.
Where our study only focused on healthy asymptomatic donors, adding symptomatic recovered COVID cases will definitely yield higher levels of herd immunity.
Limitations of study and future directions
There were few limitations in our study including limited number of samples, lack of gender association due to scarcity of female donors, and selection of specified population, i.e., healthy donors having different demographic characteristics. It is a single-center study to highlight the seroprevalence among blood donors both in tier I city and peripheral towns.
The strength of the study is that it involves healthy blood donors with exclusion of patients with COVID-19 infection, symptoms, or proximity with a COVID-19-infected person, unlike other studies in literature.
Our study will be stimulus to others in the field of transfusion medicine for better understanding of COVID pandemic, antibody prevalence, and their role as protective antibodies.
| Conclusion|| |
If we extrapolate the findings of our study on general population which understandably is more heterogeneous, our findings could be the tip of iceberg of emerging herd immunity to SARS-CoV-2 in India. How long will these antibodies last? Will they be protective toward the future COVID-19 infection? Will they be effective against the emerging UK or South African strains? These are questions which are difficult to answer at this point of time. We need to regularly keep surveillance on the seroprevalence in coming months. We do not advocate the notion that herd immunity is achieved and other measures can be relaxed as natural infection seldom paved way for disease eradication in the past without vaccination. However, it calls for a more vigilant approach; follow up studies on SARS COV2 infected individuals and epidemiological studies on population. If re-infections occur, we will never be able to achieve herd immunity through natural transmission.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2]