ABSTRACT
A comprehensive SARS-CoV-2 genomic surveillance programme that integrates logistics, laboratory work, bioinformatics, analytics, and timely reporting was deployed through a public-private partnership in the city of Bengaluru, Karnataka in India. As a result, 12461 samples have been sequenced and reported to the Karnataka State public health officials as time-sensitive, decision support during the last one year and uploaded in global public databases in a timely manner. This programme has developed an analytics platform for studying SARS-CoV-2 sequences and their epidemiological context. Continuous sequencing effort enabled timely detection of emergence of Omicron variant in India and the subsequent spread of the same and its sub-lineages with more logistic growth (BA.10, BA.12 and BA.5) in Bengaluru. Our data also helped to provide timely information on variants to determine which of the Variants of Concern tracked globally, were observed in Bengaluru, ensuring targeted efforts and reducing unwarranted fear. This effort highlights the importance of, and the urgent need to, increase genomic surveillance to support the states with limited sequencing and bioinformatics capacity. We describe the development and deployment of this end-to-end solution for genomic surveillance of SARS-CoV-2 in the city of Bengaluru.
ABSTRACT
BackgroundGlobally, the routinely used case-based reporting and IgG serosurveys underestimate the actual prevalence of COVID-19. Simultaneous estimation of IgG antibodies and active SARS-CoV-2 markers can provide a more accurate estimation. MethodsA cross-sectional survey of 16416 people covering all risk groups was done between 3-16 September 2020 using the state of Karnatakas infrastructure of 290 hospitals across all 30 districts. All participants were subjected to simultaneous detection of SARS-CoV-2 IgG using a commercial ELISA kit, SARS-CoV-2 antigen using a rapid antigen detection test (RAT), and reverse transcription-polymerase chain reaction (RT-PCR) for RNA detection. Maximum-likelihood estimation was used for joint estimation of the adjusted IgG, active, and total prevalence, while multinomial regression identified predictors. FindingsThe overall adjusted prevalence of COVID-19 in Karnataka was 27 {middle dot}3% (95% CI: 25 {middle dot}7-28 {middle dot}9), including IgG 16 {middle dot}4% (95% CI: 15 {middle dot}1 - 17 {middle dot}7) and active infection 12 {middle dot}7% (95% CI: 11 {middle dot}5-13 {middle dot}9). The case-to-infection ratio was 1:40, and the infection fatality rate was 0 {middle dot}05%. Influenza-like symptoms or contact with a COVID-19 positive patient are good predictors of active infection. The RAT kits had higher sensitivity (68%) in symptomatic participants compared to 47% in asymptomatic. InterpretationThis is the first comprehensive survey providing accurate estimates of the COVID-19 burden anywhere in the world. Further, our findings provide a reasonable approximation of population immunity threshold levels. Using the RAT kits and following the syndromic approach can be useful in screening and monitoring COVID-19. Leveraging existing surveillance platforms, coupled with appropriate methods and sampling framework, renders our model replicable in other settings.
