key: cord-0921613-nlz71mlf authors: Laxmaiah, Avula; Rao, Nalam Madhusudhan; Arlappa, N.; Babu, Jagjeevan; Uday Kumar, P.; Singh, Priya; Sharma, Deepak; Mahesh, Anumalla V.; Santhosh Kumar, T.; Sabarinathan, R.; Santhos, Kumar M.; Ananthan, R.; Anwar, Basha D; Blessy, P.P.S.; Chandra, Kumar D.; Devaraj, P.; Devendra, S.; Mahesh, Kumar M.; Meshram, Indrapal I.; Naveen Kumar, B; Sharma, Paras; Raghavendra, P; Raghu, P.; Rajender, Rao K.; Ravindranadh, P.; Santosh, Kumar B; Sarika, G.; Srinivasa, Rao J; Surekha, M. V.; Sylvia, F.; Kumar, Deepak; Subba, Rao G.; Tallapaka, Karthik Bharadwaj; Sowpati, Divya Tej; Srivastava, Surabhi; Manoj, Murekhar V.; Hemalatha, Rajkumar; Mishra, Rakesh K title: SARS-CoV-2 seroprevalence in the city of Hyderabad, India in early 2021 date: 2021-11-19 journal: IJID Regions DOI: 10.1016/j.ijregi.2021.10.009 sha: 733d6038ece0af9c10050a47d2a2e1f2b6001f12 doc_id: 921613 cord_uid: nlz71mlf Background COVID-19 emerged as a global pandemic in 2020, rapidly spreading to most parts of the world. The proportion of infected individuals in a population can be reliably estimated via sero-surveillance, making it a valuable tool for planning control measures. We conducted a serosurvey study to investigate SARS-CoV-2 seroprevalence in the urban population of Hyderabad at the end of the first wave of infections. Methods The cross-sectional survey conducted in January 2021 included males and females aged 10 years and above, selected by multi-stage random sampling. 9363 samples were collected from 30 wards distributed over 6 zones of Hyderabad and tested for antibodies against SARS-CoV-2 nucleocapsid antigen. Results Overall seropositivity was 54.2%, ranging from 50-60% in most wards. Highest exposure appeared to be among 30-39y and 50-59y olds, 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% people were still susceptible, contributing to subsequent waves of infection. Coronavirus disease was declared a pandemic over a year ago, when the infection due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had spread worldwide (WHO, 2020) . During the first year of the COVID-19 pandemic, nearly 90 million cases were reported globally, with ~2 million deaths (WHO, 2021) . Serological studies estimating SARS-CoV-2 exposure in human populations suggest that the true number of SARS-CoV-2 infections may be much higher than the officially reported cases (Chen et al., 2021) . This can be attributed to various factors, including the occurrence of asymptomatic infections, variable seeking of health care for clinically mild cases, varied testing strategies in different countries, false-negative virological tests, and incomplete case reporting. Case reporting depends on several factors, including testing capacity, type of tests used, testing strategies, and health-seeking behaviour of the population. Many SARS-CoV-2 infections are mild or asymptomatic in nature and are less likely to be detected by the surveillance system. Therefore, population-based serosurveys are considered a valuable tool in estimating the proportion of the population infected with SARS-CoV-2. Another important use of serosurveys is to understand the demographic profiles of those at a higher risk of infection in different population groups. Large-scale population-based serosurveys are resource-intensive, and allocating scarce public health resources for this purpose could be challenging for many developing nations. Therefore, well designed population-based studies, with probability sampling and laboratory assays allowing high sensitivity and specificity followed by appropriate data analysis, play a crucial role in estimating the prevalence of the infected and susceptible populations (Murhekar et al., 2021a) . Serosurveys conducted in Mumbai (Malani et al., 2020) , Chennai (Selvaraju et al., 2021) and Karnataka have shown that in urban areas, the seroprevalence is much higher than that estimated at the national level. The Telangana media bulletin revealed that the positivity rate in Telangana was 6.2%, case fatality rate was 0.58% and recovery rate was 85.9% in October 2020. Almost one-third of the cases were from Greater Hyderabad Municipal Corporation (GHMC) areas. The recent ICMR national sero-surveillance study (December 2020) reported a prevalence of 21.5% as against 12.2% in August and 0.33% during May 2020 Murhekar et al., 2021b) . Though this survey included 3 districts of Telangana, the estimates are indicative of national level prevalence. At state level, the sample size was too small to be representative and no sample was drawn from the GHMC area, which has a population of 10.3 million, Hyderabad being the fourth most populous city in India. Considering the urgent need to estimate SARS-CoV-2 exposure in Hyderabad over the first year of the pandemic, we conducted a community-based seroprevalence study to assess the transmission of SARS-CoV-2 infection in the GHMC area. Our analysis estimates SARS-CoV-2 seroprevalence in the general population of Hyderabad, the socio-demographic risk factors for infection, and the trend of infectivity among various age groups, locations and socio-economic backgrounds in the city of Hyderabad. The cross-sectional survey covered individuals aged 10 years and above. Assuming 10% seropositivity (Murhekar et al., 2021b) , a relative precision of 20%, confidence interval of 95%, design effect of 2.5, and non-response rate of 20%, we estimated a sample size of 2593 (rounded to 3,000) individuals in each age category to be effective. To carry out segregated analysis across age groups (≥10 years to 18 years, 18 years to 60 years and above 60 years), the survey was planned for a sample size of at least 9000 individuals from different locations (wards) in the city. The wards covered 6 different zones of Hyderabad, with the zones subdivided further into 19 circles (covering 30 Wards). About 30 wards were selected using a simple random sampling technique from the list of 150 wards in the GHMC area. Each selected ward was tentatively divided into 4 segments and from each segment nearly 25 households were covered by selecting the first household randomly and covering the next 24 households contiguously. Thus, a total of around 100 households were sampled from every ward, including all consenting and available males and females aged ≥10 years from each household. Subjects were included in the survey irrespective of their current COVID status. Non-consenting subjects, debilitated, bed-ridden or severely sick subjects were excluded from the study. A total of 5140 households (HHs) were contacted, of which 108 families (2.1%) were unreachable or had their door locked and a further 576 families were rejected. From a final tally of 4456 HHs (9785 participants), 268 individuals were excluded (2.8%) -the rejected population was random, and no particular gender or age group bias was observed. 9517 blood samples were collected along with the metadata as described in the next section. 154 samples were later rejected after antibody assays or had incomplete metadata, and final seroprevalence was assessed from the remaining 9363 samples. Ethical approval was taken from the Institutional Ethical Committee. Data were collected by 15 field teams and 3 lab teams. Each field team consisted of a medical officer/scientist, a technician and a phlebotomist. Each lab team consisted of a scientist (microbiologist) and 3 lab technicians. For supervision and monitoring, there were 3 survey coordinators, one lab coordinator and one overall study coordinator. The data collection was completed in the month of January in two phases, i) 1 st phase: 8 th -12 th January 2021 and ii) 2 nd Phase: 21-24 th January 2021. Data were collected through ODK based Computer Assisted Personal Interview with a structured questionnaire (Supplementary material 1) which had mostly closed ended questions, utilized in the previous 3 rounds of national sero-surveys, including in the districts and cities of Telangana. The study team visited the randomly selected households and briefed them about the survey objectives and the process involved. The state health department and other authorities actively participated to cooperate with the survey teams. Written informed individual consent was taken from all participants. Subjects 10-18 years of age were asked for consent which was counter signed by parents/legal guardians. A participant information sheet (PIS, Supplementary material 2) was also provided to each participant elucidating the study details. Interviews were conducted at the households as per the convenience of the participants in order to ensure privacy. No gift or monetary benefits were given to participants to participate in the survey. However, the antibody test result was shared with each individual confidentially. After obtaining written individual informed consent, information on socio-economic and demographic details (including name, age, gender, community, religion, educational status, occupation, family size and number of rooms), exposure history to COVID-19, symptoms suggestive of COVID-19 since the beginning of the pandemic, and clinical history of comorbidities was recorded. When there was unavailability of eligible individuals in a household, the data collection team moved onto the next household for enrolling the required number of subjects. Trained phlebotomists in each of the 15 survey teams collected 3-4 ml of venous blood from each participant. Serum was separated after centrifugation at ICMR-NIN. Estimation of SARS-CoV-2 specific antibodies was performed at the CSIR-CCMB, Hyderabad. Data were stored securely under the principal investigator's responsibility, with a focus on ensuring the participant's confidentiality. Samples were anonymized and except the principal investigator, the identifying details were not shared with anyone. However, the IgG antibody test results were shared with each individual for their information. Final reports and aggregated data were prepared without any identifying information. The samples were tested for total SARS-CoV-2 antibodies via electrochemiluminescence immunoassay using Elecsys Anti-SARS-Cov2 kit (Roche Cobas E411) based on a recombinant protein representing the nucleocapsid (N) antigen for antibody determination, as per manufacturer's protocol. Samples that had >1 COI (cutoff index; signal sample/cutoff) were considered positive for presence of antibodies. Data were analysed and visualised using SPSS v.22 and ggplot2. In-house scripts were used for filtering and categorization of data. Samples with unknown data fields were removed from analysis. Seroprevalence was calculated based on the number of samples with antibody titre >1 COI and analyzed according to the demographic measures surveyed. Sample characteristics and outcome variables (seroprevalence) were described according to age groups, gender, education status, occupation, family size and number of rooms in the household in percentages. Chi square test was used to test the significance of differences in seroprevalence among groups, with p < 0.05 considered as statistically significant. Multivariate analysis was carried out with seropositivity as the dependent variable and the variables such as age, gender, level of education, number of rooms, family size, hypertensive or diabetic status as independent. For analysis of family transmission, households with only one member or those with no seropositive members were excluded. A total of 9517 blood samples were collected from 4456 households, residing in 30 wards distributed over 6 zones across the city of Hyderabad, India (see Methods). 154 samples were rejected or had incomplete metadata and seroprevalence was assessed from the remaining 9363 samples. Of these, 5076 were positive for the SARS-CoV-2 antibodies thus giving an overall positivity of 54.2% (95% CI: 53.2-55.2). Most of the wards surveyed had a uniform distribution of seropositivity ranging from 50-60% ( Figure 1 ). However, a few wards showed evidence of higher exposure to the coronavirus (maximum ward seroprevalence of ~72%) while 8 wards had seroprevalence <50%, indicating a more susceptible population in these areas. Out of the 6 zones making up the city, Secunderabad had the highest seroprevalence of 61.6%, while L.B. Nagar showed the lowest seroprevalence of 43.3%. The socioeconomic status and demographics of the participants are summarised in Table 1 . The study participants were ≥10 years of age (mean age = 36.6 years, SD = 16.4) and were grouped into 7 age groups. The lowest seroprevalence was seen among people in the age group >70 years (47.6%, p <0.05, CI 95%), possibly reflecting a poorer geriatric immune response or lower mobility and/or a greater degree of precautions taken by older individuals during the pandemic. The highest exposure was in the age group of 30-39 and 50-59 year olds (56.7%). The number of individuals in their 20s and 30s sampled was the highest (43% of total respondents), while there was a lower representation of older individuals (349 samples, grouped together in the > 70 years age group). Approximately 55% of the samples were from females. Enrolled individuals consisted of 5143 females and 4209 males and the weighted seroprevalence was marginally higher in females (55.2%, 95% CI, 53.8-56.6%) compared to males (53.0%, 95% CI, 51.5-54.5%). This difference was statistically significant (p=0.036) and the same trend was seen across all the age groups, except in individuals between 10 to 29 years (Table 2) . Nearly 84% of the participants were literate with the most common level of education being secondary school (24.75%) or graduation and above (22.3%). SARS-CoV-2 exposure levels were similar across the various educational strata, ranging between 52.7% and 57.5%, but only among the graduates, it remained low at 49.2% (p<0.001). The exposure levels also showed an increasing trend with the family size, ranging from 53.1% when the family size was up to 4 people and 58.8% when it was 8 or more (p<0.05) ( Table 2 ). Multivariate analysis confirmed that older age groups had lesser odds of being seropositive, while lower education levels and bigger family size had a higher risk of seropositivity (Table 3) . A majority (71.4%) of the individuals reported no known contact with COVID positive persons, yet 52.6% of them were seropositive (with possibly unknown source of infection), similar to the overall population prevalence (Table 2) . 3.61% individuals reported contact with a known COVID positive person outside their own household, and of these 67.3% were found to be seropositive. Only 2.57% of the total participants reported contact within their household and the seropositivity was found to be the highest (78.4%) within this group, suggestive of effective family transmission. In order to estimate the degree of household transmission, we analyzed the family members across all the households surveyed. Families consisted of 1-9 members, living in single or multi-room homes ranging from 1 to >5 rooms per household. Majority of the households surveyed constituted small families with 4 or fewer members (65.1%). Nearly half of the surveyed households dwelt in houses with only 2 rooms (51.2%). 1473 households had no seropositive family members and were not considered for the family transmission analysis. Among families where at least one member was seropositive, no specific trends could be observed with increasing room number or space for isolation in the context of avoiding infection spread. Though more than half the population was positive in the antibody assay, indicating a prior exposure to SARS-CoV-2, very few individuals appeared for COVID testing (17% of our study group) (Figure 2a) . Importantly, 87.2% of the COVID test positive individuals (either Rapid Antigen Test or RT-PCR test positives) still had detectable antibodies to the virus, suggesting retention of the antibody response at the time of this study (Figure 2b ), compared to only ~53% of those who were not tested, or 55% of those who were negative for the COVID test. However, since the precise dates of the COVID testing were not available, the period of the retention of antibody response cannot be estimated from this study. We also looked for their symptoms status, and found that only about 11% of the total individuals surveyed (1009 out of 9363) reported any of the symptoms known to be associated with COVID-19. These results suggest that most of the seropositive people were unaware of having contracted the infection and a majority of them remained asymptomatic. As expected, the seropositivity was higher in the symptomatic group (61.7%) compared to the asymptomatic group. Among the eight symptoms covered in our survey (Table 2) , cough and fever were reported by nearly 550 (5.87%) individuals while diarrhea, excessive tiredness, sore throat, and loss of smell and taste were reported by very few individuals (<340). Loss of smell and taste, however, showed the strongest association with seropositivity among the few individuals who reported these symptoms (>86%). Among those reporting the relatively more common symptoms of cough and fever, seroprevalence was also found to be higher than the population average (ranging from 61-72.5%). Most of the symptomatic individuals suffered from only one or two symptoms (487/1009, 48.3% and 328/1009, 32.5%, respectively) while a few reported a combination of 3 or more symptoms (194/1009, 19.2%). Very few participants reported being afflicted with comorbidities or other systemic diseases associated with increased severity of COVID-19; 78% of the subjects had none of the 8 comorbidities tested (Table 2) . Further, even among the individuals with more prevalent comorbidities such as diabetes and hypertension (1623 individuals), there was no change in seropositivity, which remained at 54.1%. We found lower seropositivity (40%) among selfdeclared smokers compared to the non-smokers. Although the number of participants who smoked was small (275), these results were significant (p<0.05, 95% CI) and suggest possible protection against COVID-19. It remains to be established if there are any behavioural links that reduced the chance of infection in this study group or whether they have poorer or shorter duration of antibody response. The Indian Council of Medical Research (ICMR) has been carrying out repeated crosssectional surveys in 70 districts from 21 states for national level estimation and 3 rounds of surveys have already been completed and reported. Since these surveys are not sufficient to draw inferences at a micro level, the present survey was designed to estimate seroprevalence levels at the end of the first year of the pandemic in the GHMC area (Hyderabad, India), between the first and the second waves of infections. Pan-India seroprevalence studies began in May 2020 in India (when the assumed prevalence was 1% or lower). A series of studies done in New Delhi in 2020 have shown that the adjusted seroprevalence declined from 28.4% in August to 24.1% in September and 24.7% in October. It was also reported that participants with lower per capita income, living in slums or overcrowded households and those with diabetes comorbidity had significantly higher statistical odds of having antibody positivity (Sharma et al) . The seroprevalence was, at its lowest, found to be 1% in the state of Kerala and at pan-India level in June , increasing to 19% in November (Kallathiyan et al., 2020) . We have documented much higher seroprevalence in Hyderabad (54.2%) than that seen in other states such as Tamil Nadu (31%) , Uttar Pradesh, Gujarat, West Bengal, Madhya Pradesh, Karnataka and Chhattisgarh (41%) (Singh et al., 2021) in the same time frame (November 2020 to January 2021). A few other studies have reported much lower seroprevalence of 17.6% in Ahmedabad and 3.1% in Srinagar (Khan et al., 2021) in November-December 2020. The findings of our study are similar to those from Mumbai (Malani et al., 2020) , Chennai (Selvaraju et al., 2021) and in Karnataka conducted during the months of July 2020, suggesting that urban populations have had much higher seroprevalence than the national average prevalent at that time. Indeed, globally also larger geographical regions may report lower seropositivity than when measured in urban and local pockets. A study conducted in September to December 2020 in southern Italy found only 5.8% seropositivity (Napolitano et al.) . Another study in France by Petit et al. conducted in June 2020 showed a seroprevalence of 2.1%, while a similar population-based study estimated 9% seropositivity of the population of Saint Petersburg, Russia (Barchuk et al.) . An important caveat to note is that antibody testing kits used in seroprevalence surveys aren't very sensitive nor are they all uniform, and direct comparisons of results from different studies should be interpreted cautiously. We found gender-specific differences in seropositivity levels as also documented by some of the above-mentioned serosurveys in India. Females appear to generate better protective antibody responses than do males following vaccination against influenza, yellow fever, dengue, and several other viruses (Offord, 2021) . Differential exposure and susceptibility, and behavioural and immunological divergence between the genders have been cited to account for higher seroprevalence found in other surveys in the country. A recent review looking at global seroprevalence rates concluded that in most other countries, however, males had a slightly higher seropositivity than females, or there was no difference found between the genders (Lai et al., 2020) . Though we found no correlation with any known comorbidities some difference in seroprevalence was seen with smoking, which causes the upregulation of ACE-2 receptor (Leung et al., 2020) . Most of the survey subjects appeared to be asymptomatic for the known COVID-19 symptoms prevalent in the first wave of infections, and were likely unaware of their infected status. It is unclear whether genetic and/or environmental and behavioural differences contribute to any of the observed differences among individuals. Larger studies in these target groups are needed for direct comparison and further conclusions. The strength of this study lies in its robust sampling mechanism and the uniformly high coverage in terms of the geographical distribution of the study area. However self-reporting remains a caveat -the history of co-morbidities and demographic and socio-economic inputs were recorded based on the information provided by the participants. The time frame for history of COVID-19 infection and symptoms (a reference period covering upto 9 months at the time of survey) could also be a source of recall bias. About 11% of the families and about 13% of eligible subjects in all the age groups were not available in their houses and could not participate in the survey. Finally, considering that SARS-CoV-2 infection was still considered a stigmatising event at the time of the survey, some participants may not have disclosed accurate information. The same holds true for risk behaviours such as smoking and medical history and social desirability bias issues should be kept in mind while evaluating the data. A significant aspect of this study was the identification of pockets of low seroprevalence (as low as 31%) at the start of this year. These represent a reservoir of uninfected and susceptible individuals, that may have contributed to the large degree of cases seen in the second wave of infections across the country. With the ongoing vaccination drive expected to take many months to complete, and the emergence of novel variants of the virus that may have properties of immune escape or increased transmission, we cannot afford to let our guard down at this stage. Frequent serosurveys will be essential in monitoring the course of the pandemic in the months ahead. This study shows that the overall SARS-CoV-2 seropositivity was about 54% among the population of GHMC, Hyderabad, Telangana, not including children below 10 years of age. It is highly desirable that, irrespective of the seropositivity levels seen in the beginning of this year, most eligible individuals get vaccinated, taking advantage of the available vaccines that provide robust protection. A high number of SARS-CoV-2 infections, as seen in the preceding few months, provide the replicating virus with a chance to acquire mutations with consequences for current pandemic mitigation strategies. In the worst case scenario, the benefits gained by high seroprevalence or the ongoing vaccination drive may be undone by emerging immune escape variants. It is, therefore, highly advisable to promote the continued use of non-pharmacological measures like wearing masks, hand hygiene and physical distancing while avoiding indoor and large-scale gatherings. This work was supported by institutional funding of ICMR-NIN and CSIR-CCMB, with generous support from Bharath Biotech Pvt. Limited. Bharath Biotech Pvt. Limited was involved in procurement & supply of the test kits and had no role in design of the study, data handling, sample analysis or in the preparation of the manuscript. All authors had access to all the data in the study and had final responsibility for the decision to submit for publication. Ethical approvals were obtained from the Institutional Ethical Committee (NIN-ICMR). Written informed consent was obtained from all the survey participants. Samples were anonymized, and privacy of individual participants was maintained. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 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