Population-Based Serosurvey for Severe Acute Respiratory Syndrome Coronavirus 2 Transmission, Chennai, India

High SARS-CoV-2 Exposure in Rural Southern Mozambique After Four Waves of COVID-19: Community-Based Seroepidemiological Surveys

BACKGROUND

Mozambique was one of many African countries with limited testing capacity for SARS-CoV-2. Serosurveys, an alternative to estimate the real exposure to understand the epidemiology and transmission dynamics, have been scarce in Mozambique. Herein, we aimed to estimate the age-specific seroprevalence of SARS-CoV-2 in the general population of the Manhiça District, at four time points, for evaluating dynamics of exposure and the impact of vaccination.

METHODS

We conducted four community-based seroepidemiological surveys separated by 3 months between May 2021 and June 2022 to assess the prevalence of SARS-CoV-2 antibodies. An age-stratified (0-19, 20-39, 40-59, and ≥ 60 years) sample of 4810 individuals was randomly selected from demographic surveillance database, and their blood samples were analyzed using WANTAI SARS-CoV-2 IgG + IgM ELISA. Nasopharyngeal swabs from a subsample of 2209 participants were also assessed for active infection by RT-qPCR.

RESULTS

SARS-CoV-2 seroprevalence increased from 27.6% in the first survey (May 2021) to 63.6%, 91.2%, and 91.1% in the second (October 2021), third (January 2022), and fourth (May 2022) surveys, respectively. Seroprevalence in individuals < 18 years, who were not eligible for vaccination, increased from 23.1% in the first survey to 87.1% in the fourth. The prevalence of active infection was below 10.1% in all surveys.

CONCLUSIONS

A high seroprevalence to SARS-CoV-2 was observed in the study population, including individuals not eligible for vaccination at that time, particularly after circulation of the highly transmissible Delta variant. These data are important to inform decision making on the vaccination strategies in the context of pandemic slowdown in Mozambique.

Contribution of infection and vaccination to population-level seroprevalence through two COVID waves in Tamil Nadu, India

This study employs repeated, large panels of serological surveys to document rapid and substantial waning of SARS-CoV-2 antibodies at the population level and to calculate the extent to which infection and vaccination separately contribute to seroprevalence estimates. Four rounds of serological surveys were conducted, spanning two COVID waves (October 2020 and April-May 2021), in Tamil Nadu (population 72 million) state in India. Each round included representative populations in each district of the state, totaling ≥ 20,000 persons per round. State-level seroprevalence was 31.5% in round 1 (October-November 2020), after India's first COVID wave. Seroprevalence fell to 22.9% in round 2 (April 2021), a roughly one-third decline in 6 months, consistent with dramatic waning of SARS-Cov-2 antibodies from natural infection. Seroprevalence rose to 67.1% by round 3 (June-July 2021), with infections from the Delta-variant induced second COVID wave accounting for 74% of the increase. Seroprevalence rose to 93.1% by round 4 (December 2021-January 2022), with vaccinations accounting for 63% of the increase. Antibodies also appear to wane after vaccination. Seroprevalence in urban areas was higher than in rural areas, but the gap shrunk over time (35.7 v. 25.7% in round 1, 89.8% v. 91.4% in round 4) as the epidemic spread even in low-density rural areas.

A Mixture Model for Estimating SARS-CoV-2 Seroprevalence in Chennai, India

Serological assays used to estimate the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) often rely on manufacturers' cutoffs established on the basis of severe cases. We conducted a household-based serosurvey of 4,677 individuals in Chennai, India, from January to May 2021. Samples were tested for SARS-CoV-2 immunoglobulin G (IgG) antibodies to the spike (S) and nucleocapsid (N) proteins. We calculated seroprevalence, defining seropositivity using manufacturer cutoffs and using a mixture model based on measured IgG level. Using manufacturer cutoffs, there was a 5-fold difference in seroprevalence estimated by each assay. This difference was largely reconciled using the mixture model, with estimated anti-S and anti-N IgG seroprevalence of 64.9% (95% credible interval (CrI): 63.8, 66.0) and 51.5% (95% CrI: 50.2, 52.9), respectively. Age and socioeconomic factors showed inconsistent relationships with anti-S and anti-N IgG seropositivity using manufacturer cutoffs. In the mixture model, age was not associated with seropositivity, and improved household ventilation was associated with lower seropositivity odds. With global vaccine scale-up, the utility of the more stable anti-S IgG assay may be limited due to the inclusion of the S protein in several vaccines. Estimates of SARS-CoV-2 seroprevalence using alternative targets must consider heterogeneity in seroresponse to ensure that seroprevalence is not underestimated and correlates are not misinterpreted.

Seroprevalence of Anti-SARS-CoV-2 Antibodies in Chattogram Metropolitan Area, Bangladesh

Seroprevalence studies of COVID-19 are used to assess the degree of undetected transmission in the community and different groups such as health care workers (HCWs) are deemed vulnerable due to their workplace hazards. The present study estimated the seroprevalence and quantified the titer of anti-SARS-CoV-2 antibody (IgG) and its association with different factors. This cross-sectional study observed HCWs, in indoor and outdoor patients (non-COVID-19) and garment workers in the Chattogram metropolitan area (CMA, N = 748) from six hospitals and two garment factories. Qualitative and quantitative ELISA were used to identify and quantify antibodies (IgG) in the serum samples. Descriptive, univariable, and multivariable statistical analysis were performed. Overall seroprevalence and among HCWs, in indoor and outdoor patients, and garment workers were 66.99% (95% CI: 63.40-70.40%), 68.99% (95% CI: 63.8-73.7%), 81.37% (95% CI: 74.7-86.7%), and 50.56% (95% CI: 43.5-57.5%), respectively. Seroprevalence and mean titer was 44.47% (95% CI: 38.6-50.4%) and 53.71 DU/mL in the non-vaccinated population, respectively, while it was higher in the population who received a first dose (61.66%, 95% CI: 54.8-68.0%, 159.08 DU/mL) and both doses (100%, 95% CI: 98.4-100%, 255.46 DU/mL). This study emphasizes the role of vaccine in antibody production; the second dose of vaccine significantly increased the seroprevalence and titer and both were low in natural infection.

Assessing the burden of COVID-19 in developing countries: systematic review, meta-analysis and public policy implications

INTRODUCTION

The infection fatality rate (IFR) of COVID-19 has been carefully measured and analysed in high-income countries, whereas there has been no systematic analysis of age-specific seroprevalence or IFR for developing countries.

METHODS

We systematically reviewed the literature to identify all COVID-19 serology studies in developing countries that were conducted using representative samples collected by February 2021. For each of the antibody assays used in these serology studies, we identified data on assay characteristics, including the extent of seroreversion over time. We analysed the serology data using a Bayesian model that incorporates conventional sampling uncertainty as well as uncertainties about assay sensitivity and specificity. We then calculated IFRs using individual case reports or aggregated public health updates, including age-specific estimates whenever feasible.

RESULTS

In most locations in developing countries, seroprevalence among older adults was similar to that of younger age cohorts, underscoring the limited capacity that these nations have to protect older age groups.Age-specific IFRs were roughly 2 times higher than in high-income countries. The median value of the population IFR was about 0.5%, similar to that of high-income countries, because disparities in healthcare access were roughly offset by differences in population age structure.

CONCLUSION

The burden of COVID-19 is far higher in developing countries than in high-income countries, reflecting a combination of elevated transmission to middle-aged and older adults as well as limited access to adequate healthcare. These results underscore the critical need to ensure medical equity to populations in developing countries through provision of vaccine doses and effective medications.

SARS-CoV-2 seroprevalence in the city of Hyderabad, India in early 2021

Background

COVID-19 emerged as a global pandemic in 2020, spreading rapidly to most parts of the world. The proportion of infected individuals in a population can be reliably estimated via serosurveillance, making it a valuable tool for planning control measures. Our serosurvey study aimed to investigate SARS-CoV-2 seroprevalence in the urban population of Hyderabad at the end of the first wave of infections.

Methods

This cross-sectional survey, conducted in January 2021 and including males and females aged 10 years and above, used multi-stage random sampling. 9363 samples were collected from 30 wards distributed over six zones of Hyderabad, and tested for antibodies against SARS-CoV-2 nucleocapsid antigen.

Results

Overall seropositivity was 54.2%, ranging from 50% to 60% in most wards. Highest exposure appeared to be among those aged 30–39 and 50–59 years, with women showing greater seropositivity. Seropositivity increased with family size, with only marginal differences among people with varying levels of education. Seroprevalence was significantly lower among smokers. Only 11% of the survey subjects reported any COVID-19 symptoms, while 17% had appeared for COVID-19 testing.

Conclusion

Over half the city's population was infected within a year of onset of the pandemic. However, ∼ 46% of people remained susceptible, contributing to subsequent waves of infection.

Seroprevalence of IgG antibodies against SARS-CoV-2 in India, March 2020 to August 2021: a systematic review and meta-analysis

INTRODUCTION

India experienced 2 waves of COVID-19 pandemic caused by SARS-CoV-2 and reported the second highest caseload globally. Seroepidemiologic studies were done to track the course of the pandemic. We systematically reviewed and synthesized the seroprevalence of SARS-CoV-2 in the Indian population.

METHODS

We included studies reporting seroprevalence of IgG antibodies against SARS-CoV-2 from March 1, 2020 to August 11, 2021 and excluded studies done only among patients with COVID-19 and vaccinated individuals. We searched published databases, preprint servers, and government documents using a combination of keywords and medical subheading (MeSH) terms of "Seroprevalence AND SARS-CoV-2 AND India". We assessed risk of bias using the Newcastle-Ottawa scale, the appraisal tool for cross-sectional studies (AXIS), the Joanna Briggs Institute (JBI) critical appraisal tool, and WHO's statement on the Reporting of Seroepidemiological Studies for SARS-CoV-2 (ROSES-S). We calculated pooled seroprevalence along with 95% Confidence Intervals (CI) during the first (March 2020 to February 2021) and second wave (March to August 2021). We also estimated seroprevalence by selected demographic characteristics.

RESULTS

We identified 3821 studies and included 53 studies with 905379 participants after excluding duplicates, screening of titles and abstracts and full-text screening. Of the 53, 20 studies were of good quality. Some of the reviewed studies did not report adequate information on study methods (sampling = 24% (13/53); laboratory = 83% [44/53]). Studies of 'poor' quality had more than one of the following issues: unjustified sample size, nonrepresentative sample, nonclassification of nonrespondents, results unadjusted for demographics and methods insufficiently explained to enable replication. Overall pooled seroprevalence was 20.7% in the first (95% CI = 16.1 to 25.3) and 69.2% (95% CI = 64.5 to 73.8) in the second wave. Seroprevalence did not differ by age in first wave, whereas in the second, it increased with age. Seroprevalence was slightly higher among women in the second wave. In both the waves, the estimate was higher in urban than in rural areas.

CONCLUSION

Seroprevalence increased by 3-fold between the 2 waves of the pandemic in India. Our review highlights the need for designing and reporting studies using standard protocols.

A Comparative Analysis of COVID-19 IgG Antibody Level and Socio-Demographic Status in Symptomatic and Symptomatic Population of South Andaman, India

Introduction: The serosurveillance of COVID-19 antibody levels and their difference between symptomatic and asymptomatic groups can help in understanding the immune status of the community and the factors affecting it. Hence, the study was undertaken to find the differences between these two groups with respect to antibodies level and other socio-demographic variables in the South Andaman district.

Methods: A population-based serosurveillance study covering more than 4,000 samples was carried out in the South Andaman district. The participants were selected by multistage cluster sampling. The venous blood samples were tested for IgG COVID-19 antibodies by Erba Lisa Elisa kit.

Results: 5.3% of total individuals (217) were symptomatic whereas 94.7% (3,872) were asymptomatic. The symptomatic individuals had lower antibodies (33.6%) as compared to asymptomatic individuals (40.1%) (p-value=0.059). In the age group of 31-45 years, antibody positivity in the asymptomatic group was significantly higher than in the symptomatic group (p-value 0.031). The antibody positivity was higher in moderate to severe cases who needed hospital admission. The antibody positivity was found similar in both the groups in front-line workers as well as in non-front-line workers (p-value=0.104, 0.274, respectively).

Conclusion: The antibody positivity was higher in asymptomatic individuals as compared to symptomatic individuals, particularly in the age group of 31-45 years. The higher level of antibody positivity in asymptomatic individuals reflected a stronger immune response which led to no clinical manifestations. The antibody positivity was also found higher in moderate to severe cases undergoing hospital admission whereas antibodies positivity was found similar in front-line and non-front-line workers.

Seroprevalence of SARS-CoV-2 antibodies in Bali Province: Indonesia shows underdetection of COVID-19 cases by routine surveillance

The international tourist destination of Bali reported its first case of Coronavirus Disease 2019 or COVID-19 in March 2020. To better understand the extent of exposure of Bali's 4.3 million inhabitants to the COVID-19 virus, we performed two repeated cross-sectional serosurveys stratified by urban and rural areas. We used a highly specific multiplex assay that detects antibodies to three different viral antigens. We also assessed demographic and social risk factors and history of symptoms. Our results show that the virus was widespread in Bali by late 2020, with 16.73% (95% CI 12.22-21.12) of the population having been infected by that time. We saw no differences in seroprevalence between urban and rural areas, possibly due to extensive population mixing, and similar levels of seroprevalence by gender and among age groups, except for lower seroprevalence in the very young. We observed no difference in seroprevalence between our two closely spaced surveys. Individuals reporting symptoms in the past six months were about twice as likely to be seropositive as those not reporting symptoms. Based upon official statistics for laboratory diagnosed cases for the six months prior to the survey, we estimate that for every reported case an additional 52 cases, at least, were undetected. Our results support the hypothesis that by late 2020 the virus was widespread in Bali, but largely undetected by surveillance.

A seroprevalence study of Covid 19 antibody after 1st wave of the pandemic in South Andaman district, India

Background

The seroepidemiological studies are essential to analyze spread of Covid 19 infection in the remote islands of Andaman and Nicobar. Hence, the present study was conducted to estimate the seroprevalence of Covid 19 antibodies in the South Andaman district.

Methods

A cross-sectional study was performed in South Andaman District after 1st wave of the Covid 19 pandemic in the island. The participants of age 18 years and above were selected by multistage cluster sampling. The blood samples were tested for IgG Covid antibodies by Erba Lisa Elisa kit. The data was analyzed by descriptive analysis and Chi Square/Fisher Exact test.

Result

The seroprevalence of Covid 19 in the S. Andaman district was found to be 39.3%. The COVID 19 antibody positivity was significantly higher in urban population (44.09%) as compared to rural population (34.27%) and in females of 41–60 years age group (45.5%) as compared to females of other age groups. The antibody positivity was similar among the population of containment and buffer zone (p-value 0.684).

Conclusion

The seropositivity in the South Andaman district was higher due to the influx of tourists on the island. The rural people in South Andaman remained less affected by the pandemic as the rural areas were far flung and thinly populated. The antibody positivity was similar in residents of containment and buffer zone because there were more social contacts and movement of the people on the island due to their extensive family linkage.

Inferring the COVID-19 infection fatality rate in the community-dwelling population: a simple Bayesian evidence synthesis of seroprevalence study data and imprecise mortality data

Estimating the coronavirus disease-2019 (COVID-19) infection fatality rate (IFR) has proven to be particularly challenging –and rather controversial– due to the fact that both the data on deaths and the data on the number of individuals infected are subject to many different biases. We consider a Bayesian evidence synthesis approach which, while simple enough for researchers to understand and use, accounts for many important sources of uncertainty inherent in both the seroprevalence and mortality data. With the understanding that the results of one's evidence synthesis analysis may be largely driven by which studies are included and which are excluded, we conduct two separate parallel analyses based on two lists of eligible studies obtained from two different research teams. The results from both analyses are rather similar. With the first analysis, we estimate the COVID-19 IFR to be 0.31% [95% credible interval (CrI) of (0.16%, 0.53%)] for a typical community-dwelling population where 9% of the population is aged over 65 years and where the gross-domestic-product at purchasing-power-parity (GDP at PPP) per capita is $17.8k (the approximate worldwide average). With the second analysis, we obtain 0.32% [95% CrI of (0.19%, 0.47%)]. Our results suggest that, as one might expect, lower IFRs are associated with younger populations (and may also be associated with wealthier populations). For a typical community-dwelling population with the age and wealth of the United States we obtain IFR estimates of 0.43% and 0.41%; and with the age and wealth of the European Union, we obtain IFR estimates of 0.67% and 0.51%.

Seroprevalence of SARS-CoV-2 specific IgG antibodies among eye care workers in South India

PURPOSE

Health care workers are at higher risk of acquiring the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. This study aims to understand the seroprevalence of anti-SARS-CoV-2 IgG antibody among the eye care workers in South India.

METHODS

The participants included eye care workers from the nine eye care centres. All the participants were interviewed with a questionnaire to obtain essential information about socio-demographics, past contact with COVID-19 patients and additional information as recommended by Indian Council of Medical Research, India. Serum samples were tested for anti-SARS-CoV-2 IgG antibodies by ELISA.

RESULTS

A total of 1313 workers were included and 207 (15.8%) were positive for the SARS-CoV-2 IgG antibody. The seropositivity was higher in the moderate risk group (19.5%) followed by low (18.6%) and high risk (13.7%) groups. The seropositivity was significantly higher among i) day scholars compared to hostellers (OR - 2.22, 1.56 to 3.15, P ​< ​0.0001), ii) individuals with history of flu-like illness (4.57, 3.08-6.78, P ​< ​0.001) or who were symptomatic or in contact with COVID 19 positive cases (2.2, 1.02-4.75, P - 0.043) and iii) individuals with history of systemic illness (2.11, 1.39-3.21, P ​< ​0.001). Individuals (11.97%) who had no history of contact or any illness were also seropositive.

CONCLUSIONS

The effectiveness of the protective measures taken against COVID infection was evident from the lower percentage of seropositivity in the high risk group. The study highlighted the need to create awareness among individuals to follow strict safety measures even in non-work hours and also in social circles.

Age- & sex-specific infection fatality ratios for COVID-19 estimated from two serially conducted community-based serosurveys, Chennai, India, 2020

Background & objectives

Infection fatality ratio (IFR) is considered a more robust and reliable indicator than case fatality ratio for severity of SARS-CoV-2 infection. Age- and sex-stratified IFRs are crucial to guide public health response. Infections estimated through representative community-based serosurveys would gauge more accurate IFRs than through modelling studies. We describe age- and sex-stratified IFR for COVID-19 estimated through serosurveys conducted in Chennai, India.

Methods

Two community-based serosurveys were conducted among individuals aged ≥10 yr during July and October 2020 in 51 of the 200 wards spread across 15 zones of Chennai. Total number of SARS-CoV-2 infections were estimated by multiplying the total population of the city aged ≥10 yr with the weighted seroprevalence and IFR was calculated by dividing the number of deaths with the estimated number of infections.

Results

IFR was 17.3 [95% confidence interval (CI): 14.1-21.6] and 16.6 (95% CI: 13.8-20.2) deaths/10,000 infections during July and October 2020, respectively. Individuals aged 10-19 years had the lowest IFR [first serosurvey (R1): 0.2/10,000, 95% CI: 0.2-0.3 and second serosurvey (R2): 0.2/10,000, 95% CI: 0.1-0.2], and it increased with age and was highest among individuals aged above 60 yr (R1: 140.0/10,000, 95% CI: 107.0-183.8 and R2: 111.2/10,000, 95% CI: 89.2-142.0).

Interpretation & conclusions

Our findings suggested that the IFR increased with age and was high among the elderly. Therefore, elderly population need to be prioritized for public health interventions including vaccination, frequent testing in long-term care facilities and old age homes, close clinical monitoring of the infected and promoting strict adherence to non-pharmaceutical interventions.

High prevalence of anti-SARS-CoV-2 antibodies after the first wave of COVID-19 in Kinshasa, Democratic Republic of the Congo: results of a cross-sectional household-based survey

Background

In October 2020, after the first wave of coronavirus disease 2019 (COVID-19), only 8290 confirmed cases were reported in Kinshasa, Democratic Republic of the Congo, but the real prevalence remains unknown. To guide public health policies, we aimed to describe the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin G (IgG) antibodies in the general population in Kinshasa.

Methods

We conducted a cross-sectional, household-based serosurvey between 22 October 2020 and 8 November 2020. Participants were interviewed at home and tested for antibodies against SARS-CoV-2 spike and nucleocapsid proteins in a Luminex-based assay. A positive serology was defined as a sample that reacted with both SARS-CoV-2 proteins (100% sensitivity, 99.7% specificity). The overall weighted, age-standardized prevalence was estimated and the infection-to-case ratio was calculated to determine the proportion of undiagnosed SARS-CoV-2 infections.

Results

A total of 1233 participants from 292 households were included (mean age, 32.4 years; 764 [61.2%] women). The overall weighted, age-standardized SARS-CoV-2 seroprevalence was 16.6% (95% CI: 14.0–19.5%). The estimated infection-to-case ratio was 292:1. Prevalence was higher among participants ≥40 years than among those <18 years (21.2% vs 14.9%, respectively; P < .05). It was also higher in participants who reported hospitalization than among those who did not (29.8% vs 16.0%, respectively; P < .05). However, differences were not significant in the multivariate model (P = .1).

Conclusions

The prevalence of SARS-CoV-2 is much higher than the number of COVID-19 cases reported. These results justify the organization of a sequential series of serosurveys by public health authorities to adapt response measures to the dynamics of the pandemic.

Incorporating false negative tests in epidemiological models for SARS-CoV-2 transmission and reconciling with seroprevalence estimates

Susceptible-Exposed-Infected-Removed (SEIR)-type epidemiologic models, modeling unascertained infections latently, can predict unreported cases and deaths assuming perfect testing. We apply a method we developed to account for the high false negative rates of diagnostic RT-PCR tests for detecting an active SARS-CoV-2 infection in a classic SEIR model. The number of unascertained cases and false negatives being unobservable in a real study, population-based serosurveys can help validate model projections. Applying our method to training data from Delhi, India, during March 15-June 30, 2020, we estimate the underreporting factor for cases at 34-53 (deaths: 8-13) on July 10, 2020, largely consistent with the findings of the first round of serosurveys for Delhi (done during June 27-July 10, 2020) with an estimated 22.86% IgG antibody prevalence, yielding estimated underreporting factors of 30-42 for cases. Together, these imply approximately 96-98% cases in Delhi remained unreported (July 10, 2020). Updated calculations using training data during March 15-December 31, 2020 yield estimated underreporting factor for cases at 13-22 (deaths: 3-7) on January 23, 2021, which are again consistent with the latest (fifth) round of serosurveys for Delhi (done during January 15-23, 2021) with an estimated 56.13% IgG antibody prevalence, yielding an estimated range for the underreporting factor for cases at 17-21. Together, these updated estimates imply approximately 92-96% cases in Delhi remained unreported (January 23, 2021). Such model-based estimates, updated with latest data, provide a viable alternative to repeated resource-intensive serosurveys for tracking unreported cases and deaths and gauging the true extent of the pandemic.