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

Laxmaiah, Avula; Rao, Nalam Madhusudhana; Arlappa, Nimmathota; Babu, J. D. Monesh; Kumar, Praveen; Singh, Priya; Sharma, Deepak; Mahesh, Anumalla V.; Kumar, T. Santhosh; Sabarinathan, R.; Santhos, Kumar M.; Ananthan, R.; Anwar, Basha D; Blessy, P.P.S.; Chandra, Kumar D.; Devaraj, P.; Devendra, Senan; Mahesh, Kumar M.; Meshram, Indrapal I.; Kumar, B.V. Manoj; Sharma, Paras; Raghavendra, Parimala; Raghu, Padmanabhan; Rajender, Rao K.; Ravindranadh, P.; Santosh, Kumar; Sarika, G.; Srinivasa, Rao J; Mullapudi, Surekha Venkata; Sylvia, F.; Kumar, Deepak; Subba, Rao G.; Tallapaka, Karthik Bharadwaj; Sowpati, Divya Tej; Srivastava, Surabhi; Manoj, Murekhar V.; Hemalatha, R.; Mishra, Rakesh

doi:10.1016/j.ijregi.2021.10.009

Cited by 7 publications

(5 citation statements)

References 18 publications

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“…The population-weighted and test kit-adjusted seroprevalence of 76.5% was nearly 4 times higher than that reported after the first wave (16.6%), reflecting an extensive community transmission after the lightening of lockdown measures, including the travel ban implemented during the first wave (5). Lower seroprevalence estimates were reported in Bangladesh (63.1%), Mali (58.5%), India (54.2%), Zimbabwe (53.0%), Kenya (44.2%), and Sierra Leone (2.6%) during similar periods (16)(17)(18)(19)(20)(21)(22). The characteristics of the test kit used and the variability in exposure levels across countries might explain differences in seroprevalence estimates.…”

Section: Discussionmentioning

confidence: 80%

“…In our study and that of Bangladesh, an ELISA-based test detecting total antibodies against the RBD of the spike protein was used ( 10 , 16 ). Studies from Zimbabwe and India used serologic assays, targeting IgGs directed against the nucleocapsid protein, which are known to wane faster over time than those directed against the spike protein ( 18 , 19 , 23 ). Studies from Mali and Kenya used serologic tests that only targeted anti-spike IgG, thus missing newly infected persons who could bear anti-spike IgM rather than IgG ( 17 , 20 ).…”

Section: Discussionmentioning

confidence: 99%

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High SARS-CoV-2 Seroprevalence after Second COVID-19 Wave (October 2020–April 2021), Democratic Republic of the Congo

Bazitama¹,

Folefack²,

Yambayamba³

et al. 2023

Emerg. Infect. Dis.

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T wo years after the first detected case of in Kinshasa, Democratic Republic of the Congo (DRC), the country experienced 4 subsequent waves of the virus, with peaks in June 2020 and January, June, and December 2021 (1). As observed across countries in Africa, the second wave in DRC was severe compared with the first wave in terms of dis-ease incidence and associated deaths, partly because of lightening of stringent public health countermeasures implemented during the first wave, including international travel restrictions, and the spread of SARS-CoV-2 Beta variant (B.1.351) from southern Africa countries (2,3). By March 6, 2021, a total of 26,468 laboratory-confirmed cases were reported, including 712 virus-related deaths and 132,929 tests performed; Kinshasa accounted for nearly 75% of all reported cases (1).The true burden of COVID-19 in Kinshasa is likely underestimated because PCR testing is conducted mainly on symptomatic persons meeting the case definition, omitting a large portion of persons who become infected with SARS-CoV-2 but are either asymptomatic or paucisymptomatic. Limited testing facilities throughout Africa, combined with the population's underutilization of healthcare services, further widened the gap between the number of actual infections and detected cases (2,4). On the basis of data from a previously conducted household-based survey in Kinshasa after the first wave, we reported an infection-to-case ratio of 292:1 and a prevalence of 16.6% (5). The survey underscored the critical role of serologic surveys as complementary tools to routine testing results for guiding public health interventions.

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Section: Discussionmentioning

confidence: 80%

Section: Discussionmentioning

confidence: 99%

High SARS-CoV-2 Seroprevalence after Second COVID-19 Wave (October 2020–April 2021), Democratic Republic of the Congo

Bazitama¹,

Folefack²,

Yambayamba³

et al. 2023

Emerg. Infect. Dis.

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“…[ 12 ] In a study conducted in urban wards of Hyderabad in January 2021, the seropositivity among children in the age group of 10-19 was 54.6%. [ 13 ] A study conducted in the slums of Bangalore in April 2021 showed overall seropositivity of 20.3%. [ 14 ] Whereas a study conducted in the rural district of south India after the second wave showed high seroprevalence (45.8%) of COVID-19 infection among children below 18 years.…”

Section: Discussionmentioning

confidence: 99%

Assessing the Burden of COVID-19 among Children Aged 6-14 Years in Karnataka, India: A Cross-sectional Survey

Rajagopal,

Sil,

Dinesh

et al. 2024

Indian Journal of Community Medicine

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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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“…All these results were robust to fitting separately a model using only assay antigen (the detailed results of this model fit are provided in Supplementary Figure S3) and a model using only analytic technique (detailed results provided in Supplementary Figure S4), and Roche Elecsys S [14] Vitros Ortho CoV2T total [13,14] Wantai ELISA [14,[117][118][119][120] LumiraDx [22] Tosoh S sandwich [75] Tosoh N sandwich [75] SenASTrIS test [106,107] Abbot Quant II [44] COVIDAR [64][65][66] Luminex xMAP, RBD portion [101] Mount Sinai [103] Sinai Health ELISA, S [110] University of Rio de Janeiro [84,112] Roche Elecsys N [12][13][14][15]20,42,43,57,[67][68][69][70][71][72][73][74][75][76] GenScript cPass [14,44,56] THL Finland FMIA [94] Biozek…”

Section: Assay Characteristics Determine Seroreversionmentioning

confidence: 99%

Dynamics of SARS-CoV-2 seroassay sensitivity: a systematic review and modelling study

et al. 2023

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Background Serological 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. Aim Our 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. Methods We 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). Results Of 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. Conclusions Seroassay 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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SARS-CoV-2 seroprevalence in the city of Hyderabad, India in early 2021

Cited by 7 publications

References 18 publications

High SARS-CoV-2 Seroprevalence after Second COVID-19 Wave (October 2020–April 2021), Democratic Republic of the Congo

High SARS-CoV-2 Seroprevalence after Second COVID-19 Wave (October 2020–April 2021), Democratic Republic of the Congo

Assessing the Burden of COVID-19 among Children Aged 6-14 Years in Karnataka, India: A Cross-sectional Survey

Dynamics of SARS-CoV-2 seroassay sensitivity: a systematic review and modelling study

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