COVID-19 Serosurveillance May Facilitate Return-to-Work Decisions

Kršák, Martin; Johnson, Steven C.; Poeschla, Eric M.

doi:10.4269/ajtmh.20-0302

Cited by 16 publications

(12 citation statements)

References 13 publications

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“…Decisions like ‘back to the work’ and school require timely seroprevalence study. All these aspects necessitate highly sensitive and specific immunoassay [ 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

Development and performance evaluation of a rapid in-house ELISA for retrospective serosurveillance of SARS-CoV-2

Sil

Jahan²,

Haq³

et al. 2021

PLoS ONE

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Background In the ongoing pandemic situation of COVID-19, serological tests can complement the molecular diagnostic methods, and can be one of the important tools of sero-surveillance and vaccine evaluation. Aim To develop and evaluate a rapid SARS-CoV-2 specific ELISA for detection of anti-SARS-CoV2 IgG from patients’ biological samples. Methods In order to develop this ELISA, three panels of samples (n = 184) have been used: panel 1 (n = 19) and panel 2 (n = 60) were collected from RT-PCR positive patients within 14 and after 14 days of onset of clinical symptoms, respectively; whereas panel 3 consisted of negative samples (n = 105) collected either from healthy donors or pre-pandemic dengue patients. As a capturing agent full-length SARS-CoV2 specific recombinant nucleocapsid was immobilized. Commercial SARS-CoV2 IgG kit based on chemiluminescent assay was used for the selection of samples and optimization of the assay. The threshold cut-off point, inter-assay and intra-assay variations were determined. Results The incubation/reaction time was set at a total of 30 minutes with the sensitivity of 84% (95% confidence interval, CI, 60.4%, 96.6%) and 98% (95% CI, 91.1%, 100.0%), for panel 1 and 2, respectively; with overall 94.9% sensitivity (95% CI 87.5%, 98.6%). Moreover, the clinical specificity was 97.1% (95% CI, 91.9%, 99.4%) with no cross reaction with dengue samples. The overall positive and negative predictive values are 96.2% (95% CI 89.2%, 99.2%) and 96.2% (95% CI, 90.6% 99.0%), respectively. In-house ELISA demonstrated 100% positive and negative percent agreement with Elecsys Anti-SARS-CoV-2, with Cohen’s kappa value of 1.00 (very strong agreement), while comparing 13 positive and 17 negative confirmed cases. Conclusion The assay is rapid and can be applied as one of the early and retrospective sero-monitoring tools in all over the affected areas.

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“…Decisions like ‘back to the work’ and school require timely seroprevalence study. All these aspects necessitate highly sensitive and specific immunoassay [ 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

Development and performance evaluation of a rapid in-house ELISA for retrospective serosurveillance of SARS-CoV-2

Sil

Jahan²,

Haq³

et al. 2021

PLoS ONE

View full text Add to dashboard Cite

show abstract

“…At the level of populations, serologic data can provide insights into virus spread by enabling estimation of the overall attack rate, and seroprevalence estimates can elucidate the potential for herd immunity ( Stringhini et al, 2020 ; Bryant et al, 2020 ). In addition, these estimates are essential for developing accurate mathematical models of virus transmission dynamics, which provide the foundation for policies to reopen societies ( Krsak et al, 2020 ; Angulo et al, 2020 ; Kissler et al, 2020 ). At the level of individuals, the presence and concentration of antibodies against SARS-CoV-2 are indicators of past exposure, providing insights over a much wider temporal window than other metrics.…”

Section: Introductionmentioning

confidence: 99%

Quantifying antibody kinetics and RNA detection during early-phase SARS-CoV-2 infection by time since symptom onset

Borremans

Gamble

Prager

et al. 2020

eLife

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Understanding and mitigating SARS-CoV-2 transmission hinges on antibody and viral RNA data that inform exposure and shedding, but extensive variation in assays, study group demographics and laboratory protocols across published studies confounds inference of true biological patterns. Our meta-analysis leverages 3,214 datapoints from 516 individuals in 21 studies to reveal that seroconversion of both IgG and IgM occurs around 12 days post symptom onset (range 1-40), with extensive individual variation that is not significantly associated with disease severity. IgG and IgM detection probabilities increase from roughly 10% at symptom onset to 98-100% by day 22, after which IgM wanes while IgG remains reliably detectable. RNA detection probability decreases from roughly 90% to zero by day 30, and is highest in faeces and lower respiratory tract samples. Our findings provide a coherent evidence base for interpreting clinical diagnostics, and for the mathematical models and serological surveys that underpin public health policies.

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“…At the level of populations, serologic data can provide insights into the spread of the virus by enabling estimation of the overall attack rate, and seroprevalence estimates can elucidate the potential for herd immunity (Stringhini et al 2020). In addition, these estimates are essential for developing accurate mathematical models of virus transmission dynamics, which provide the foundation for policies to reopen societies (German et al 2020;Kissler et al 2020;Krsak et al 2020). At the level of individuals, the presence and concentration of antibodies against SARS-CoV-2 are indicators of past exposure, providing insights into incidence over a much wider temporal window than other metrics.…”

Section: Introductionmentioning

confidence: 99%

Quantifying antibody kinetics and RNA shedding during early-phase SARS-CoV-2 infection

Borremans

Gamble

Prager

et al. 2020

Preprint

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Our ability to understand and mitigate the spread of SARS-CoV-2 depends largely on antibody and viral RNA data that provide information about past exposure and shedding. Five months into the outbreak there is an impressive number of studies reporting antibody kinetics and RNA shedding dynamics, but extensive variation in detection assays, study group demographics, and laboratory protocols has presented a challenge for inferring the true biological patterns. Here, we combine existing data on SARS-CoV-2 IgG, IgM and RNA kinetics using a formal quantitative approach that enables integration of 3,214 data points from 516 individuals, published in 22 studies. This allows us to determine the mean values and distributions of IgG and IgM seroconversion times and titer kinetics, and to characterize how antibody and RNA detection probabilities change during the early phase of infection. We observe extensive variation in antibody response patterns and RNA detection patterns, explained by both individual heterogeneity and protocol differences such as targeted antigen and sample type. These results provide a robust reference for clinical management of individual patients, and a foundation for the mathematical models and serological surveys that underpin public health policies.

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COVID-19 Serosurveillance May Facilitate Return-to-Work Decisions

Cited by 16 publications

References 13 publications

Development and performance evaluation of a rapid in-house ELISA for retrospective serosurveillance of SARS-CoV-2

Development and performance evaluation of a rapid in-house ELISA for retrospective serosurveillance of SARS-CoV-2

Quantifying antibody kinetics and RNA detection during early-phase SARS-CoV-2 infection by time since symptom onset

Quantifying antibody kinetics and RNA shedding during early-phase SARS-CoV-2 infection

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