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Rajagopal PM, Sil S, Dinesh P, Shiju S, Arunkumar DP, Ramaiah SS, Lalitha HR, Mamatha T, Kantinath PA, Pujari L, Pradeep BS, Shenoy AB, Desai A, Munivenkatappa A, Gudi CS, Babu GR, Sudarshan MK. Assessing the Burden of COVID-19 among Children Aged 6-14 Years in Karnataka, India: A Cross-sectional Survey. Indian J Community Med 2024; 49:110-114. [PMID: 38425984 PMCID: PMC10900468 DOI: 10.4103/ijcm.ijcm_60_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 11/06/2023] [Indexed: 03/02/2024] Open
Abstract
Background India experienced three coronavirus disease (COVID-19) waves, with the third attributed to the highly contagious Omicron variant. Before the national vaccination rollout for children above 6, understanding severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin G (IgG) positivity in the pediatric population was essential. This study aims to assess the burden of Covid-19 infection and to estimate the seroprevalence in children aged 6 to 14 years in the state of Karnataka. Material and Methods We surveyed 5,358 children aged 6-14 across Karnataka using 232 health facilities, from June 6 to 14, 2022. We determined the sample size using the PPS (Population Proportional to Size) technique and employed cluster sampling. We tested all participants for SARS-CoV-2 IgG with an enzyme-linked immunosorbent assay (ELISA) kit and SARS-CoV-2 RNA with reverse transcription-polymerase chain reaction (RT-PCR). We sequenced samples with a cycle threshold (CT) value below 25 using whole genomic sequencing (WGS). Result We found an adjusted seroprevalence of IgG at 75.38% statewide, and we found 0.04% of children RT-PCR positive for COVID-19. We determined a case-to-infection ratio of 1:37 and identified the SARS-CoV-2 strains as Omicron, BA.5, and BA.2.10. Conclusion The study showed a high seroprevalence of IgG among children with low active infection. Omicron, BA. 5, and BA. 2.10 variants were detected through WGS.
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Affiliation(s)
- Padma M Rajagopal
- Deputy Director, State Surveillance Unit DHFW Karnataka, Karnataka, India
| | - Satyam Sil
- State Epidemiologist, IDSP, NHM Karnataka, Karnataka, India
| | - Prameela Dinesh
- State Microbiologist State Surveillance Unit, DHFW Karnataka, Karnataka, India
| | - Shilpa Shiju
- State Microbiologist IDSP, DHFW Karnataka, Karnataka, India
| | - D P Arunkumar
- Deputy Director eHealth, DHFW Karnataka, Karnataka, India
| | - Srinivas S Ramaiah
- State Epidemiologist- State Surveillance Unit, DHFW Karnataka, Karnataka, India
| | | | - T Mamatha
- State Consultant Training/Technical, IDSP, NHM Karnataka, Karnataka, India
| | | | - Lokesh Pujari
- Linux System Administrator, eHealth, DHFW Karnataka, Karnataka, India
| | - BS Pradeep
- Department of Epidemiology Centre for Public Health, NIMHANS, Karnataka, India
| | - Anusha B Shenoy
- Life Skills Training and Counselling Services Programme, Department of Epidemiology, NIMHANS, Karnataka, India
| | - Anita Desai
- Department of Neurovirology, NIMHANS, Bengaluru, Karnataka, India
| | - Ashok Munivenkatappa
- ICMR-National Institute of Virology Bangalore Unit, RGICD Campus, Bengaluru, Karnataka, India
| | - Chetan S Gudi
- Head SPMU and IT Officer, Urban Mission, RD Commisionarate, Bengaluru, Karnataka, India
| | | | - M K Sudarshan
- Community Medicine, Kempegowda Institute of Medical Sciences, Bengaluru, Karnataka, India
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Owusu-Boaitey N, Russell TW, Meyerowitz-Katz G, Levin AT, Herrera-Esposito D. Dynamics of SARS-CoV-2 seroassay sensitivity: a systematic review and modelling study. Euro Surveill 2023; 28:2200809. [PMID: 37227301 PMCID: PMC10283460 DOI: 10.2807/1560-7917.es.2023.28.21.2200809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 03/10/2023] [Indexed: 05/26/2023] Open
Abstract
BackgroundSerological surveys have been the gold standard to estimate numbers of SARS-CoV-2 infections, the dynamics of the epidemic, and disease severity. Serological assays have decaying sensitivity with time that can bias their results, but there is a lack of guidelines to account for this phenomenon for SARS-CoV-2.AimOur goal was to assess the sensitivity decay of seroassays for detecting SARS-CoV-2 infections, the dependence of this decay on assay characteristics, and to provide a simple method to correct for this phenomenon.MethodsWe performed a systematic review and meta-analysis of SARS-CoV-2 serology studies. We included studies testing previously diagnosed, unvaccinated individuals, and excluded studies of cohorts highly unrepresentative of the general population (e.g. hospitalised patients).ResultsOf the 488 screened studies, 76 studies reporting on 50 different seroassays were included in the analysis. Sensitivity decay depended strongly on the antigen and the analytic technique used by the assay, with average sensitivities ranging between 26% and 98% at 6 months after infection, depending on assay characteristics. We found that a third of the included assays departed considerably from manufacturer specifications after 6 months.ConclusionsSeroassay sensitivity decay depends on assay characteristics, and for some types of assays, it can make manufacturer specifications highly unreliable. We provide a tool to correct for this phenomenon and to assess the risk of decay for a given assay. Our analysis can guide the design and interpretation of serosurveys for SARS-CoV-2 and other pathogens and quantify systematic biases in the existing serology literature.
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Affiliation(s)
- Nana Owusu-Boaitey
- Case Western Reserve University School of Medicine, Cleveland, United States
- These authors contributed equally to this work
| | - Timothy W Russell
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | | | - Andrew T Levin
- Dartmouth College, Hanover, United States
- National Bureau for Economic Research, Cambridge, United States
- Centre for Economic Policy Research, London, United Kingdom
| | - Daniel Herrera-Esposito
- These authors contributed equally to this work
- Department of Psychology, University of Pennsylvania, Philadelphia, United States
- Laboratorio de Neurociencias, Universidad de la República, Montevideo, Uruguay
- Centro Interdisciplinario en Ciencia de Datos y Aprendizaje Automático, Universidad de la República, Montevideo, Uruguay
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Munyeku-Bazitama Y, Folefack GT, Yambayamba MK, Tshiminyi PM, Kazenza BM, Otshudiema JO, Guinko NT, Umba MD, Mulumba A, Baketana LK, Mukadi PK, Smith C, Muyembe-Tamfum JJ, Ahuka-Mundeke S, Makiala-Mandanda S. High SARS-CoV-2 Seroprevalence after Second COVID-19 Wave (October 2020-April 2021), Democratic Republic of the Congo. Emerg Infect Dis 2023; 29:89-97. [PMID: 36573545 PMCID: PMC9796206 DOI: 10.3201/eid2901.221009] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Serologic surveys are important tools for estimating the true burden of COVID-19 in a given population. After the first wave of SARS-CoV-2 infections, a household-based survey conducted in Kinshasa, Democratic Republic of the Congo, estimated >292 infections going undiagnosed for every laboratory-confirmed case. To ascertain the cumulative population exposure in Kinshasa after the second wave of COVID-19, we conducted a prospective population-based cross-sectional study using a highly sensitive and specific ELISA kit. The survey included 2,560 consenting persons from 585 households; 55% were female and 45% male. The overall population-weighted, test kit-adjusted SARS-CoV-2 seroprevalence was 76.5% (95% CI 74.5%-78.5%). The seroprevalence was 4-fold higher than during the first wave, and positivity was associated with age, household average monthly income, and level of education. Evidence generated from this population-based survey can inform COVID-19 response, especially vaccination campaign strategies in the context of vaccine shortages and hesitancy.
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