Indian Journal of Public Health

: 2021  |  Volume : 65  |  Issue : 3  |  Page : 256--260

Severe acute respiratory syndrome-coronavirus-2 seroprevalence study in Pimpri-Chinchwad, Maharashtra, India coinciding with falling trend – Do the results suggest imminent herd immunity?

Amitav Banerjee1, Bhargav Gaikwad2, Atul Desale2, Sudhir Laxman Jadhav3, Hetal Rathod3, Kajal Srivastava4,  
1 Professor and Head, Depatment of Community Medicine, Dr DY Patil Medical College, Hospital and Research Centre, Dr DY Patil Vidyapeeth, Pune, Maharashtra, India
2 Assistant Professor, Depatment of Community Medicine, Dr DY Patil Medical College, Hospital and Research Centre, Dr DY Patil Vidyapeeth, Pune, Maharashtra, India
3 Professor, Depatment of Community Medicine, Dr DY Patil Medical College, Hospital and Research Centre, Dr DY Patil Vidyapeeth, Pune, Maharashtra, India
4 Associate Professor, Depatment of Community Medicine, Dr DY Patil Medical College, Hospital and Research Centre, Dr DY Patil Vidyapeeth, Pune, Maharashtra, India

Correspondence Address:
Amitav Banerjee
Department of Community Medicine, Dr DY Patil Medical College, Hospital and Research Centre, Dr DY Patil Vidyapeeth, Pune, Maharashtra


Background: COVID-19 is a public health concern currently demanding continuous efforts to understand its epidemiology. Pimpri-Chinchwad township with a population of over 25 lakhs is located in Maharashtra, one of the worst affected states in India. After the incidence peaked in the township in mid-September 2020, cases started declining even as lockdown restrictions were eased. Objectives: A seroprevalence study was conducted to understand the transmission dynamics of the pandemic in this region. Methods: We carried out a population-based seroprevalence study for IgG antibodies for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) among 5000 residents 12 years and above selected by the cluster random sampling. We selected 50 clusters in slums, 80 clusters in tenements, and 70 clusters from housing societies. The field work for collection of samples was carried out from October 07 to October 17, 2020. We used kit from Abbott (SARS-CoV-2 IgG), which employs chemiluminescent microparticle immunoassay technology. The prevalence of IgG antibodies was expressed as point estimates with 95% confidence intervals (CIs). These were weighted for areas and cluster effect and further adjusted for test performance. Results: The overall seropositivity for IgG was 34.04% (95% CIl 31.3%–36.8%). Slum dwellers had 40.9% positivity rate (95% CI 37.0%–44.7%), those in tenements 41.2% (95% CI 37.7%–44.8%) and people living in housing societies had 29.8% positivity (95% CI 25.8%–33.8%). Conclusion: A considerable proportion of population had encountered the novel coronavirus approaching partial, if not complete, herd immunity, which may partly explain the declining trend in spite of easing of lockdown restrictions.

How to cite this article:
Banerjee A, Gaikwad B, Desale A, Jadhav SL, Rathod H, Srivastava K. Severe acute respiratory syndrome-coronavirus-2 seroprevalence study in Pimpri-Chinchwad, Maharashtra, India coinciding with falling trend – Do the results suggest imminent herd immunity?.Indian J Public Health 2021;65:256-260

How to cite this URL:
Banerjee A, Gaikwad B, Desale A, Jadhav SL, Rathod H, Srivastava K. Severe acute respiratory syndrome-coronavirus-2 seroprevalence study in Pimpri-Chinchwad, Maharashtra, India coinciding with falling trend – Do the results suggest imminent herd immunity?. Indian J Public Health [serial online] 2021 [cited 2022 Dec 3 ];65:256-260
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Full Text


COVID-19, a severe acute respiratory syndrome (SARS) caused by the novel coronavirus, is firmly established globally. Countries in the northern hemisphere are experiencing a resurgence of infections forcing reintroduction of restrictive measures while countries in the southern hemisphere are cautiously easing restrictions ever fearful of a “second wave.”[1] There is marked variation in mortality due to the novel coronavirus. Even early into the pandemic, it was noted that Western countries with their higher age and high prevalence of overweight were more affected as compared to Asian and African countries.[2] In spite of these differences, most mathematical models developed in the west were extrapolated to Asian and African countries with exponential projections of cases and deaths from COVID-19.[3] These models were subsequently off the mark even in the country of origin.[3] There is need for robust inputs from time to time for reliable mathematical models.

Population-based seroprevalence studies carried out during different stages of the pandemic at various regions can provide inputs for such models and predict how the pandemic will play out in a particular place. By unearthing mild and asymptomatic infections, they can refine the infection fatality rate (IFR), to enable models predict number of deaths more accurately. Moreover, they can enable policy planners to adapt their control strategies based on the transmission dynamics of a place. In addition such studies have other uses. They can provide evidence of the efficacy of restrictive measures like lockdowns in breaking the chain of transmission, and finally can gauge the level of herd or population immunity and its potential to act as speed breakers to transmission.

The findings of such surveys can also be useful to identify vulnerable regions and populations, i.e. those with low antibody levels. In subsequent waves, the pandemic can generate surge in such regions. Inputs from serosurveys can help in focused protection of such areas either by nonpharmacological interventions or vaccination on priority.

The Pimpri-Chinchwad township, with a population of about 25 lakhs, in Pune district, in the State of Maharashtra, India where the present serosurvey was done, had peak incidence in the middle of September 2020 which thereafter showed a steep fall. We carried out the present study to understand the dynamics of transmission of the novel coronavirus in this population.

 Materials and Methods

The study was approved by the Institutional Review Board of Dr DY Patil Vidyapeeth (Deemed University), Pune, Maharashtra. Written informed consent/assent as applicable was obtained from the participants, and the test results were communicated to them.

Study setting, study population, and sampling

Pimpri-Chinchwad, the twin township has undergone rapid industrialization in the past few decades. According to the latest information obtained from the Pimpri-Chinchiwad Municipal Corporation, the population of this twin township is 2,497,085 spread over an area of 181 km2. The type of settlements can be divided into slum, tenements, and housing societies with modern amenities. Total population of slum was 427,780 (17.13%); that of tenements was 511,696 (20.49%); and housing societies population was 1,557,609 (62.38%).

Sample size calculation

Assuming the seroprevalence rate of 5% with acceptable difference of 1% and design effect for cluster sampling of 2.5% with 95% confidence interval (CI), sample size was estimated to 4561 which was rounded off to 5000 participants.

Method of sampling

The target population was all inhabitants of this twin township 12 years and above. Population proportionate cluster sampling was done from the three types of settlements. From each cluster, five households were selected with the assumption that each household will have five members. If <5 members were in a household, or if in a particular household consent was not forthcoming from some member, then next 5th house was selected till the sample size for that cluster was completed. Each cluster had preidentified local landmarks (e.g., a temple, or a shop/store, etc.,) from which every 5th house was selected to get maximum spatial representation. From each cluster, 25 participants were selected. A total of 5000 blood samples were collected from 200 clusters representing the whole population of the twin township. Since the beginning of the pandemic, high transmission was noted in the population dwelling in slums and tenements. Higher representation based on population was given to slums (1.5 times) and tenements (2 times) for the selection and distribution of clusters [Table 1].{Table 1}

The slums and tenements constituted a smaller proportion of the overall population than housing societies. To get a better picture of the seroprevalence in these areas, oversampling was done. Oversampling is an accepted procedure to get a better representation of smaller groups.[4]

Records available with the health department of the Pimpri-Chinchwad Municipal Corporation (PCMC) were also closely monitored for trends and case fatality rates as ascertained from detected cases, to enable triangulation of the study results with these.

The collections of blood samples were done by house to houses visit by ten teams. Each team consisted of one Community Medicine resident, one trained phlebotomist, one medico-social worker, one auxillary nurse midwife, and one accredited social health activist, the latter two being familiar with the local community. Besides demographic data, symptoms of influenza such as illness and results of reverse transcription-polymerase chain reaction/rapid antigen tests, if any, in the past 3 months were also recorded.

Quality control and supervision of field work

A customized program was developed which allowed the location of each households to be recorded on a cloud server and plotted on the map dynamically along with the necessary information which includes team number and date and time stamp. The field investigators were trained to send location after taking samples from each household. The sampling, progress, and performance of each team were monitored real-time at and feedback was sent which effectively acted as an internal quality control system. The distribution of households, clusters as well as the raw data can be accessed at

Timing and duration of the survey

The field work started on October 07, 2020. This coincided with the downward trend of cases in the administrative area of PCMC [Figure 1]. By October 17, 2020, 5000 samples were collected.{Figure 1}

Testing of samples for IgG antibodies

We resorted to automated two-step immunoassay for the qualitative detection of IgG antibodies to SARS-coronavirus-2 (SARS-CoV-2) in human serum using chemiluminescent microparticle immunoassay technology developed by Abbott, Chicago, IL, USA. The sensitivity for this kit has been reported to be 92.7% (95% CI 90.2–94.8), and the specificity 99.9% (95% CI 99.4%–100%).[5]

Statistical analysis

Epi Info 7a statistical and epidemiological software developed by Center for Disease Control Atlanta was used for data entry and analysis of the results. The seroprevalence rates in different types of strata (slum, tenement, and housing society), across age groups, and gender, weighted for area and further adjusted for cluster effect were expressed in percentages with 95% CI. These rates were further adjusted for test performance by the formula:


Where π represents the population prevalence of antibodies, q is the proportion positive for the test, s the specificity and r is the sensitivity of the test.[6] The Standard Error (SE) for this test adjusted rate was calculated by SE = √Elc − p) D/n where p is the test adjusted rate, D is the design effect and n is the number.[7] Ninety-five percent CI were then calculated by p ± 1.96 × SE.


The nonresponse rate was around 10% which was made up as explained under material and methods.

The overall positivity for IgG weighted for area and adjusted for cluster effect is shown in [Table 2]. Highest was among tenement dwellers followed by slum dwellers and lowest among people staying in better quality houses.{Table 2}

Age and gender wise distribution of seropositivity is shown in [Table 3]. Overall female had higher rates. Age wise elderly in the bracket of 51–65 years had the highest seroprevalence at 38.2%, closely followed by adolescents and teenagers in age group 12–17 years with positivity rate of 37.6%.{Table 3}

Previous symptoms

Those symptomatic in the past 3 months showed a seropositivity of 40.1% (95% CI 34.5–45.7). Even those who were asymptomatic showed a positivity of 29.7% (95% CI 26.9–32.5).

Previous reverse transcription polymerase chain reaction/rapid antigen tested

Among those previous positives, sero-prevalence was 86.8% (95% CI 81.8–90.8) and among those who were negative was 32.1% (95% CI 30.8–33.5).

The PCMC records revealed 1484 cumulative deaths around October 23 in the total population of 24,97,085. The total confirmed cases according to the PCMC records at this point of time were 86735.

Infection fatality rate

If we take 34% of the population who had encountered the novel coronavirus and extrapolate it to the total population of the twin township which is 24, 97, 085 we get an estimate of 849,009 number of people who have been infected with the virus (with the assumption of same rate among children below 12 years who were not surveyed). The PCMC records showed 1484 cumulative deaths around the time of the survey. Taking 1484 as numerator and 849,009 as the denominator the IFR works out to be 0.17%.


A systematic review and meta-analysis of 47 studies worldwide found seroprevalence of antibodies to COVID-19 varied from 0.37% to 22.1% with a pooled estimate of 3.38% (95% CI 3.05%–3.72%).[8] This review did not include any study from India.

Initial studies from India, the second largest and one of the densely populated countries in the world, with its varied geographical and cultural characteristics were informal without proper peer review or formal publication. These studies from the various parts of the country found the prevalence of IgG antibodies against the novel coronavirus ranging from 15% to 51%.[9],[10],[11],[12],[13]

The Indian Council of Medical Research (ICMR), conducted the first nationwide serosurvey for COVID-19 antibodies from May 11 to June 04, 2020, which revealed a low countrywide seropositivity of 0.73% (95 CI 0.34–1.13).[14]

On a repeat serosurvey by ICMR from August 17 to September 22, 2020, the countrywide seroprevalence rate was 6.6%.[15] The results of this second survey are yet to be peer reviewed and published.

The latest nationwide serosurvey by ICMR indicates that restrictive measures to control the virus do not work as evidenced by widespread IgG positivity in the country. It also tentatively refines the IFR to 0.05% given 21% or 30 crores in India having encountered the virus with cumulative fatality of around 1.5 lakhs.[16]

The present systematically planned and executed study on a representative sample of inhabitants of the twin township from one of the heaviest affected states of India reiterates the findings from other parts of India carried out in recent months (albeit unpublished), indicating that the novel coronavirus has run through one third of the population particularly in busy townships and industrial hubs. The findings of the study may also explain the sharp decline in daily new cases in Pimpri-Chinchwad mid-September onward which continued to fall during the duration of the serosurvey.

The findings of the study also refine the IFR at 0.17%, much lower than IFR of 0.68% (95% CI 0.53%–0.82%), reported in a systematic review and meta-analysis, which did not include any study from Asian countries except for one study from China.[17] This suggests that the Indian population may be less susceptible to fatality due to lower age profile and body mass index as compared to the Western population.[2] Predictive models of fatality from COVID-19 should factor in such nuances and regional findings to ensure better accuracy. Accurate and regionally refined IFR is an important input for such mathematical models and also for framing appropriate public health policy.

The evidence of widespread transmission from the different parts of the country also questions the efficacy of lockdown, an issue of great relevance to all countries as many in the northern hemisphere are falling back on this strategy with the onset of the so called, “second wave.” India's lockdown was hailed as one of the best in the world by the WHO.[18] If there is no solid evidence for the efficacy of lockdown in preventing community transmission, then the “cure” is likely to be worse than the “malady” particularly in poor countries like India with its large burden of diseases of poverty such as child malnutrition, tuberculosis, and malaria. The serosurvey results indicate that about 8–9 lakhs of the population of the twin township have been infected as against the confirmed cumulative cases numbering 86,735 at the time of the survey, i.e., ten times more cases are likely to be in the community for every detected case.

Paradoxically, in spite of India having implemented one of the best and most rigid lockdown in the world, the recent seropositivity rates for IgG levels from different states in India are the highest for any country. A systematic review and meta-analysis of SARS-CoV-2 found seroprevalence ranging from the lowest of 0.37% to the highest of 22.1% with a pooled estimate of 3.38%.[4] Most of the studies in this meta-analysis were from the Northern hemisphere, stressing the need for local data for local policy making.


Just when it appeared that the worst is over for India, surges in COVID-19 cases started occurring in various parts of the country, particularly Maharashtra including the twin-township where this study was carried out. This raises many concerns. Are more people who were cloistered for the past year, particularly the young, are moving out and mixing leading to the “second wave?” Are the mutants of the novel coronavirus responsible for this phenomenon of steep rise? Will past infections or the vaccines protect from these mutants? When the dust settles, repeat serosurveys of the population can resolve some of these issues.


The authors would like to thank Dr. J S Bhawalkar, Dean, Dr. DY Patil Medical College, Hospital and Research Centre, Dr. DY Patil Vidyapeeth, Pune for administrative support. Dr. Chandrasekhar Raut, of Central Research Laboratory, Dr. DY Patil Medical College, Hospital and Research Centre, Pune for his supervision and quality control of testing of the samples. Dr. Pavan Salve and Dr. Varsha Dange from Medical Department PCMC for coordinating the field workers and administrative support. Last but not the least, our residents in Community Medicine namely, Dr. Shweta Gangurde, Dr. Biswajit Chaklader, Dr. Nirankush Borah, Dr. Gracia Marb Anderson Sohkhlet, Dr. Deepu Palal, Dr. Prerna Verma, Dr. Vallari Jadhav, Dr. Kavita Thakur, Dr. S Johnson and Dr. Sandeep Nallapu who actually undertook the field work.

Financial support and sponsorship

This study was financially supported by Pimpri-Chinchwad Municipal Corporation.

Conflicts of interest

There are no conflicts of interest.


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