Results of Serosurveillance and Forecasting the Third Wave of COVID-19 in an Industrial District in India

Prevalence of immunoglobulin G (IgG) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in the industrial district of East Singhbhum (Jharkhand, India) from July, August, November, and December 2020 and January 2021 after the first wave and in July 2021 after the second wave of coronavirus disease 2021 (COVID-19) infections may be utilized to find the possibility of a third wave of COVID-19 infections. Based on the trend of the loss of protective IgG antibodies after the first wave and the seropositivity of 75% in the district in July 2021, simple forecasting and proportional estimates of the seropositivity in the next eight months and the estimated maximum number of the cases was done. We also considered the seropositivity without vaccination in July 2021 (63%). Additionally, the trend of the weekly RT-PCR and rapid antigen testing for SARS-CoV-2 may also preemptively predict an imminent wave. Based on the East Singhbhum population and the vaccination coverage with at least one dose till July 2021 (Covishield or Covaxin), it is estimated that a 4-5% monthly vaccination coverage rate of new individuals will not allow the seropositivity to fall below 50% and hold at bay a major wave. Vaccination coverage of 3% or less would allow a continuous drop in acquired immunity in the district and can potentially cause a rise in cases, making the community susceptible to a future surge of infections. A 3-5% vaccination rate of new individuals is unlikely to see a drop in the community seropositivity below 50% and the number of new cases of COVID-19 infections going above 478 to 712 per month at least till March 2022. The assumptions are based on presuming that there will be no new mutant of SARS-CoV-2 that escapes the immunity provided by previous infection or vaccination over the next eight months. However, currently, there is no evidence to speculate on any new variant of concern causing a major wave globally. The B.1.617.2 (delta) variant was first identified in October 2020 and there was a lag of six months to the second surge of COVID-19 infections in East Singhbhum, primarily caused by this variant. Additionally, 3% and above, with a rising weekly trend of reverse transcription-polymerase chain reaction (RT-PCR) positivity for SARS-CoV-2 can provide at least four to eight weeks advance warning before the peak of the wave if an imminent future wave is impending.


Introduction
Various models like the susceptible-infected-recovered (SIR) model [1], the susceptible-exposed-infectiousrecovered (SEIR) model [2], or the susceptible, undetected, tested (positive), and removed approach (SUTRA) model [3] are available in epidemiology to predict the outbreak of infectious diseases and have been used to estimate the future trend of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, due to the uncertainty of the disease spread, multiple unconsidered variables, including coronavirus disease (COVID)-appropriate behavior in the community and the evolving nature of the virus makes any long-term prediction difficult [1][2][3].
Before the availability of vaccines, the acquired immunity developed through clinical or subclinical infection with SARS-CoV-2 resulted in protective SARS-CoV-2 immunoglobulin G (IgG) antibodies. However, these antibodies decay over a period of weeks to months, again making the individual susceptible to infection [4]. It is speculated that when the IgG seropositivity falls below a certain threshold, the community is potentially again susceptible to another wave of the pandemic. Although SARS-CoV-2-specific IgG memory B cells and SARS-CoV-2-specific memory lymphocytes also provide antiviral immunity, their durability and effectiveness need further studies to assess their correlation to the protection [5]. Since the onset of SARS-CoV-2 vaccination, a longer-lasting acquired immunity is provided by all the above mechanisms. Currently, the susceptibility of a community to a surge of infection, thus overwhelming the healthcare infrastructure would depend on the acquired immunity developed either through previous infection or vaccination.
Based on the IgG seropositivity acquired through clinical or subclinical infection and its decline beyond two months, projections can be made about the next surge in COVID-19 infections in the community. However, if the vaccination coverage can be ramped up to neutralize the decrease in IgG seropositivity acquired through clinical or subclinical infection over a period to a cumulative acquired immunity above 70-75%, the community can prevent a large surge in infections.
This study presents the detailed findings of the prevalence of SARS-CoV-2 antibodies in July 2021 in an industrial district of East Singhbhum in the state of Jharkhand, India. We also correlate the findings of the previous prevalence of SARS-CoV-2 antibodies in the months of July, August, November, and December 2020 and January 2021 in the district along with the monthly incidence of new COVID-19 cases in the district to correlate with the vaccination coverage to suggest possible trajectories of COVID-19 infections in the future.

Materials And Methods
Institutional approval was taken to study the prevalence of IgG SARS-CoV-2 antibodies in the community in the industrial district of East Singhbhum in the state of Jharkhand, India, in July, August, November, and December 2020 and January 2021 for the first wave of COVID-19 infections and in July 2021 after the second wave of COVID-19 infections. Based on the trend of the available data, projections were made for the months whose data was not available based on the drop in IgG SARS-CoV-2 antibodies in the available data, its correlation with the incidence of infection in the district [6], and forecasting of the seroprevalence of IgG SARS-CoV-2 antibodies till March 2022. The data for the month-wise incidence of new cases [6] and immunization coverage [7] was utilized for making the projections. The seroprevalence of IgG SARS-CoV-2 antibodies in the unimmunized in July 2021 was utilized to understand the prevalence of IgG SARS-CoV-2 antibodies from clinical or sub-clinical acquired infection.
Three milliliters of a random venous sample were collected for SARS-CoV-2 IgG antibodies, maintaining the cold chain with a temperature of 15-20 degrees Celsius before being processed and tested. Samples were collected from the workplace, community, hospital, and clinics. The samples were allowed to clot and then centrifuged at 4500 rpm for five minutes to collect the serum separately. While the SARS-CoV-2 IgG assay with the Access SARS-CoV-2 IgG assay (Beckman Coulter, Brea, California) was done in July, August, November, and December 2020 and January 2021, it was done with the Access SARS-CoV-2 IgG II in July 2021. The Access SARS-CoV-2 IgG and Access SARS-CoV-2 IgG II assay (Beckman Coulter, Brea, California) detects antibodies to the receptor-binding domain (RBD) of the spike protein. Based on the manufacturer guidelines, automated chemiluminescent immunoassay (CLIA) with the Access SARS-CoV-2 IgG assays, the signal-to-cut-off (S/CO) ratio above 1.0 was considered positive, S/CO ratio between 0.8 and 1.0 was considered equivocal, and S/CO ratio below 0.8 was considered negative for SARS-CoV-2 IgG antibodies. The Access SARS-CoV-2 IgG assay is reported to have 100% sensitivity and 99.8% specificity [4]. Similarly, with the Access SARS-CoV-2 IgG II assay, measured light units are converted to arbitrary units using the calibration curve; ≥ 10 AU/mL was considered positive, and < 10 AU/mL was considered negative for SARS-CoV-2 IgG antibodies. Access SARS-CoV-2 IgG II assay is reported to have 100% sensitivity and specificity [8]. The protective effect of the COVID-19 vaccine in India is derived from the existing literature, which suggests that even one dose is protective up to 61% from developing an infection, 70% from hospitalization, 96% from the need for oxygen therapy, and 95% from the need for intensive care unit admission [9].
It was hypothesized based on available literature that the SARS-CoV-2 IgG antibodies acquired by clinical or sub-clinical infections disappear over a period of time, however, COVID-19 vaccination provides a longerlasting immunity [10]. If the community vaccination as able to ramp up and ensure coverage to cover the drop in SARS-CoV-2 IgG antibodies acquired by clinical or sub-clinical infection, the community immunity can be ramped up for coverage above a certain threshold to ensure no major wave or surge of COVID-19 unless there is a major mutation resulting in immune escape from immunity acquired by previous infection or vaccination. The positivity of the RT-PCR samples for SARS-CoV-2 amongst a mix of diseased and asymptomatic close contacts of COVID-19 positive and those with a travel history outside the district/state was monitored. Additionally, the positivity of rapid, point-of-care antigen-based tests (RAT) for diagnosis of SARS-CoV-2 infection amongst asymptomatics was also monitored for the trend. Both these trends allow us to estimate how early before the onset of a peak can the surge in cases be predicted.

Statistical analysis
Data were maintained in Microsoft Excel (Microsoft® Corp., Redmond, WA), analyzed through the forecasting tools available in it, and a proportional estimation was performed based on previous months' data. Table 1 shows the number of new COVID-19 cases detected in the district of East Singhbhum (Jharkhand, India) and the IgG SARS-CoV-2 seropositivity in the community (monthly random sample size 1000-4575 individuals). While seropositivity for July, August, November, and December 2020 and January 2021 for the first wave of COVID-19 infections and in July 2021 after the second wave of COVID-19 infections were based on actual serosurveillance data; the projections for the remaining months were derived based on proportionate decrease based on previous months and forecasting on Microsoft Excel. The district has an estimated population of 27,88,488 [11] and based on the data available through the CoWIN portal on July 31, 2021, cumulatively, 25% of the population had received at least one dose of the COVID-19 vaccine [7].    [6][7], the IgG SARS-CoV-2 antibody positivity was 75% in July 2021. While 24% of the surveyed population in July 2021 had a laboratory-proven COVID-19 history, 79% of the surveyed population had received at least one dose, and 41% of the surveyed population had received both doses of a COVID-19 vaccine. The IgG SARS-CoV-2 seropositivity was 6% higher in males as compared to females (78% vs 72%). The seropositivity amongst the non-vaccinated (n=968) was significantly lower (63%) as compared to those who have received at least one dose (n=3607) (78%). The findings are represented in Figure 1. The seropositivity amongst the unvaccinated represents the seroconversion due to clinical or sub-clinical infection. Similarly, a 14% laboratory-proven history of previous COVID-19 infections amongst the 1,136 IgG SARS-CoV-2 negative individuals represents a loss of protective antibodies as evidenced in previous studies.

FIGURE 1: Findings of IgG SARS-CoV-2 serosurveillance in East Singhbhum (Jharkhand, India)
The findings of the serosurveillance were compared to the 4th National Serosurveillance conducted by the Indian Council of Medical Research (ICMR) in June-July 2021, across India. The seroprevalence of the IgG SARS-CoV-2 seropositivity was found out to be higher in East Singhbhum (75%) as compared to the country (68%) [12]. The age comparisons of both surveys are shown in Figure 2.  Based on the hypothesis that the IgG SARS-CoV-2 positivity was acquired either through infection (shorter lasting) or through vaccination (longer lasting) [10], predictions were derived for future immunity based on dropping seropositivity acquired by infection and ramp-up of vaccination in the district. Estimates were taken for 3%, 4%, and 5% coverage of the district with at least one dose of the COVID-19 vaccine. Based on these assumptions, projections were derived for the possible number of COVID-19 cases in East Singhbhum till March 2022 as depicted in Table 2. The immunity in the community is defined by the formula: Percentage immunity in the district = Immunity developed through acquired infection among unimmunized plus Immunity developed through vaccination.

Discussion
There is substantial literature evidence of rapid loss of protective IgG antibodies, starting as early as two months after acute infection [13]. Naturally acquired antibodies decrease at different rates after infection with SARS-CoV-2 [4,[14][15]. Observing its trend with the corresponding surge in infections can predict the future course in the community. While various predictive models exist, most of the mathematical models are derived based on the susceptible community, rate of rise and fall in infections, as well as the presumed immunity in the community. This is the first model based on actual serology data in a district, its trends, and vaccination coverage ramp-up. There is evidence available to show that that the immunity provided by COVID-19 vaccination is better and longer-lasting than that acquired after infection with SARS-CoV-2 [10]. Earlier reported reviews had concluded that there is a need for more robust seroprevalence data of IgG antibodies to predict the possible development of herd immunity [16]. It was suggested that "evidence-based and targeted public health measures informed by accurate real-world data" [16] would help us proactively plan to mitigate the challenges posed by the COVID-19 pandemic. Our analysis shows that in a district with 75% seropositivity of IgG antibodies, based on the existing population, it is possible to predict the percentage of the population that needs to be covered every month to prevent a surge in infections. The analysis shows, that in the East Singhbhum district (Jharkhand, India), with a seroprevalence of 75% IgG positivity, at least 4-5% of the population needs to be covered with at least one dose of vaccination (and subsequently the second dose) to prevent the seropositivity from dropping below 50%.
The delta (B.1.617.2) variant has now emerged and outcompeted the earlier rapidly spreading variants of concern (VOC) across the globe and is responsible for most infections globally and in India [17]. With wholegenome sequencing (WGS) of SARS-CoV-2 establishing that 75-90% of the COVID-19 infections in East Singhbhum district during the second wave were due to the B.1.617.2 or delta variant, it establishes the fact that a large majority of the community now has protective antibodies against the current globally dominant variant. The variant is considered to be 50% more transmissible than the alpha (B.1.1.7) variant [18], a higher secondary attack rate of 3% [19], and a modest reduction in vaccine effectiveness [19]. Based on this, it can reasonably be concluded that unless there is an emergence of a new variant of concern that escapes the immunity provided by previous infection (predominantly with the B.1.617.2 variant) or vaccination, there is unlikely to be a major surge of infection within the next six months if 4-5% of the East Singhbhum district continues to be vaccinated every month. While the predicted maximum number of infections range between 217-712 until March 2022, the actual numbers would depend upon COVID-appropriate behavior, travel restrictions, and extent of lockdown.
While there are many models to predict a surge in infections, a simplistic plotting of the week-on-week RT-PCR positivity for SARS-CoV-2 is better than RAT positivity and can pre-emptively predict the peak at least four to eight weeks ahead. Data from Tata Main Hospital, Jamshedpur (India), the largest tertiary care hospital in the studied district (East Singhbhum), show that a 3% positivity and a rising trend, can predict the onset up to four to eight weeks in advance based on the virulence of the virus. To date, there is very little literature evidence correlating the capability of RAT and RT-PCR positivity for SARS-CoV-2 to suggest the onset of a surge in COVID-19 infections.
One of the limitations of this analysis is that although similar in sensitivity and specificity, variability in the test kits used in the SARS-CoV-2 IgG assay during the various phases of the serosurveillance study can give variable results. While there is adequate evidence that immune protection against other human coronaviruses (HCoV) is not long-lasting, contrary evidence is also available showing the presence of potent "neutralizing activity even in the absence of detectable serum immunoglobulin G (IgG)" [15]. Additionally, besides the SARS-CoV-2 IgG antibodies, B cells and T cells also contribute to the immunity against COVID-19 infections [20]. However, the prediction model looks at the worst-case scenario to enable the community to ensure healthcare preparedness and long-lasting immunity may provide an even higher level of protection. The actual number of cases and hospitalization can be even lower. Another limitation of this analysis and prediction model is the fact that it has been presumed that there will be no new mutant of SARS-CoV-2 that escapes the immunity provided by previous infection or vaccination. The projected maximum number of cases from August 2021 to March 2022 is based on the limited evidence of the study on protective immunity provided by a single dose of the COVID vaccines available in India [9]. However, with increasing coverage and availability of many types of vaccines, we will better understand the immunity provided by the various vaccines. Additionally, the ramp-up of the second dose of the COVID vaccination could potentially result in further avoidance of an imminent third wave.

Conclusions
Based on the trend of seropositivity of the IgG SARS-CoV-2 antibody in a defined population and the trend of vaccination coverage, it is possible to predict the future trend and possibility of a surge in COVID-19 infections. This will give the health authorities and community an understanding of the percentage of the community that needs to be covered by vaccination every month to prevent future waves, provided there is no other variant of concern that escapes the immunity provided by previous COVID-19 infection or vaccination. Whole-genome sequencing (WGS) of SARS-CoV-2 enables the health care providers within the community to understand the incidence of the predominant COVID-19 variant and understand the susceptibility of the community to the prevalent variants of concern in the future. A trend of RT-PCR positivity for SARS-CoV-2 can establish that if the positivity is 3% and rising, it can predict the peak of a future wave four to eight weeks in advance. However, based on the seropositivity due to previous infection and vaccination coverage, it is more likely that the COVID-19 pandemic has entered a phase of endemicity where a simmering low level of transmission would continue amongst the susceptible for the next few months and years. However, increasing vaccination coverage would ensure a reduced need for hospital beds and critical care facilities.

Additional Information Disclosures
Human subjects: All authors have confirmed that this study did not involve human participants or tissue. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue.

Conflicts of interest:
In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work.