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.

Epidemiology of hospital-based COVID- 19 cluster in a tertiary care cancer hospital, Chennai, India 2020.

OBJECTIVES: To identify risk factors associated with Coronavirus disease 2019 (COVID-19) in a Tertiary care cancer hospital-based cluster and recommend control measures. METHODS: We conducted tracing and confirmation among hospital and community contacts. We telephonically interviewed and abstracted information from hospital records and registers. We described the cluster by time, place and person. We conducted unmatched case-control study to compare risk factors and computed Odds Ratio (OR) and 95% confidence interval. RESULTS: We confirmed COVID-19 in 21 of 1478 tested (1.4%). Secondary attack (%) of COVID-19 among 824 contacts was higher among in-patients of block A (18), household contacts (3.4), housekeeping staff (3.3) and nurses (1.7). The cluster started on April 22 with two successive peaks five days apart and lasted until May 8. Being male, patients aged >33 years [OR = 30·7; 95% CI = 3·6 to 264], having hypertension [OR = 4·3; 95% CI = 1·1 to 16·7] or diabetes [OR = 3·8; 95% CI = 1·0 to 14·1] were associated with COVID-19. Mask compliance was poor (20%) among hospital workers. DISCUSSION: We recommended screening of all patients for diabetes and hypertension and isolation/testing of anyone with influenza-like illness for preventing COVID-19 clusters in hospital settings.

Entry and initial spread of COVID-19 in India: Epidemiological analysis of media surveillance data, India, 2020.

BACKGROUND: India reported first laboratory-confirmed case of coronavirus disease 2019 (COVID-19) on 30 January from Kerala. Media surveillance is useful to capture unstructured information about outbreaks. We established media surveillance and described the characteristics of the COVID-19 cases, clusters, deaths by time, place, and person during January-March 2020 in India. METHODS: The media surveillance team of ICMR-National Institute of Epidemiology abstracted data from public domains of India's Central and State health ministries, online news and social media platforms for the period of January 31 to March 26, 2020. We collected data on person (socio-demographics, circumstances of travel/contact, clinical and laboratory), time (date/period of reported exposures; laboratory confirmation and death) and place (location). We drew epidemic curve, described frequencies of cases by age and gender. We described available details for identified clusters. RESULTS: As of March 26, 2020, India reported 694 (Foreigners = 45, 6%) confirmed COVID-19 cases (Attack rate = 0.5 per million population) and 17 deaths (Fatality = 2.5%) from 21 States and 6 Union Territories. The cases were higher among 20-59 years of age (60 of 85) and male gender (65 of 107). Median age at death was 68 years (Range: 38-85 years). We identified 13 clusters with a total of 63 cases and four deaths among the first 200 cases. CONCLUSION: Surveillance of media sources was useful in characterizing the epidemic in the early phase. Hence, media surveillance should be integrated in the routine surveillance systems to map the events specially in context of new disease outbreaks.