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Post-acute sequelae of COVID-19 (PASC) are long-term consequences of SARS-CoV-2 infection that can substantially impair quality of life. Underlying mechanisms ranging from persistent virus to innate and adaptive immune dysregulation have been discussed. Here, we profiled plasma of 181 individuals from the cohort study for digital health research in Germany (DigiHero) including individuals after mild to moderate COVID-19 with or without PASC and uninfected controls. We focused on soluble factors related to monocyte/macrophage biology and on circulating SARS-CoV-2 spike (S1) protein as potential biomarker for persistent viral reservoirs. At a median time of eight months after infection, we found pronounced dysregulation in almost all tested soluble factors including both pro-inflammatory and pro-fibrotic cytokines. These perturbations were remarkably independent of ongoing symptoms, but further correlation and regression analyses suggested PASC specific patterns involving CCL2/MCP-1 and IL-8 as well as long-term persistence of high IL-5 and IL-17F levels. None of the analyzed factors correlated with the detectability or levels of circulating S1 indicating that this represents an independent subset of patients with PASC. This data confirms prior evidence of immune dysregulation and persistence of viral protein in PASC and illustrates its biological heterogeneity that still awaits correlation with clinically defined PASC subtypes.
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High antibody affinity against the ancestral SARS-CoV-2 strain seems to be necessary (but not always sufficient) for the control of emerging immune-escape variants. Therefore, aiming at strong B cell somatic hypermutation - not only at high antibody titers - is a priority when utilizing vaccines that are not targeted at individual variants. Here, we developed a next-generation sequencing based SARS-CoV-2 B cell tracking protocol to rapidly determine the level of immunoglobulin somatic hypermutation at distinct points during the immunization period. The percentage of somatically hypermutated B cells in the SARS-CoV-2 specific repertoire was low after the primary vaccination series, evolved further over months and increased steeply after boosting. The third vaccination mobilized not only naive, but also antigen-experienced B cell clones into further rapid somatic hypermutation trajectories indicating increased affinity. Together, the strongly mutated post-booster repertoires and antibodies deriving from this may explain why the booster, but not the primary vaccination series, offers some protection against immune-escape variants such as Omicron B.1.1.529. Brief summaryPriming SARS-CoV-2 vaccinations generate antibodies from low-level matured B cells while the third vaccination strongly boosts somatic hypermutation potentially explaining different protection from immune-escape variants.
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Post-acute sequelae of COVID-19 (PASC) emerge as a global problem with unknown molecular drivers. In a digital epidemiology approach, we rapidly recruited 8,077 individuals out of 129,733 households in Halle (Saale) to the cohort study for digital health research in Germany (DigiHero). These responded to a basic questionnaire followed by a PASC-focused survey and blood sampling in case of prior positive SARS-CoV-2 testing in their household. The presented analysis is based on the first 318 DigiHero participants, the majority thereof after mild infections. PASC were reported in 67.8% of cases, consisted predominantly in fatigue, dyspnea and concentration deficit, persisted in 60% over the follow-up period of on average eight months and their resolution was unaffected by post-infection vaccination. PASC was not associated with post-COVID-19 autoantibodies, but with elevated levels of IL-1{beta}, IL-6 and TNF-. Blood profiling and single-cell data from validation cohorts with early infection suggested the induction of these cytokines in COVID-19 lung pro-inflammatory macrophages creating a self-sustaining feedback loop. Our data indicate a long-lasting cytokine triad -potentially underlying PASC symptoms - to be driven by macrophage primed during infection. We demonstrate how the combination of digital epidemiology with selective biobanking can rapidly generate hints towards disease mechanisms.
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BackgroundThe effect of contact reduction measures on infectious disease transmission can only be assessed indirectly and with considerable delay. However, individual social contact data and population mobility data can offer near real-time proxy information. AimTo compare social contact data and population mobility data with respect to their ability to predict transmission dynamics during the first wave of the SARS-CoV-2 pandemic in Germany. MethodsWe quantified the change in social contact patterns derived from self-reported contact survey data collected by the German COVIMOD study from 04/2020-06/2020 (compared to the pre-pandemic period), and estimated the percentage mean reduction in the effective reproduction number R(t) over time. We compared these results to the ones based on R(t) estimates from open-source mobility data and to R(t) values provided by the German Public Health Institute. ResultsWe observed the largest reduction in social contacts (90%, compared to pre-pandemic data) in late April corresponding to the strictest contacts reduction measures. Thereafter, the reduction in contacts dropped continuously to a minimum of 73% in late June. R(t) estimates based on social contacts underestimated measured R(t) values slightly in the time of strictest contact reduction measures but predicted R(t) well thereafter. R(t) estimates based on mobility data overestimated R(t) considerably throughout the study. ConclusionsR(t) prediction accuracy based on contact survey data was superior to the one based on population mobility data, indicating that measuring changes in mobility alone is not sufficient for understanding changes in transmission dynamics triggered by public health measures.
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BackgroundA considerable proportion of SARS-CoV-2 transmission occurs from asymptomatic and pre-symptomatic cases. Therefore, different polymerase chain reaction (PCR)- or rapid antigen test (RAT)-based approaches are being discussed and applied to identify infectious cases that would have gone undetected (e.g., in nursing homes). In this article, we provide a framework to estimate the time-dependent risk of being infectious after a negative SARS-CoV-2 test and we simulate the number of expected cases over time in populations of individuals who initially tested negative. MethodsA Monte Carlo approach is used to simulate infections that occurred over a one-week period in populations with 1,000 individuals following a negative SARS-Cov-2 test. Parameters representing the application of PCR tests or RATs are utilized, and SARS-CoV-2 7-day incidences between 25 and 200 per 100,000 people are considered. Simulation results are compared to case numbers predicted via a mathematical equation. ResultsThe simulations showed a linear increase in cases over time in populations of individuals who initially tested SARS-CoV-2 negative. The different false negative rates of PCR tests and RATs have a strong impact on the number of simulated cases. The simulated and the mathematically predicted case numbers were comparable. However, Monte Carlo simulations highlight that, due to random effects, infectious cases can exceed predicted case numbers even shortly after a test was conducted. ConclusionsThe analysis demonstrates that the number of infectious cases in a population can be effectively reduced by the screening of asymptomatic individuals. However, the time since the negative test and the underlying SARS-CoV-2 incidence are critical parameters in determining the observed subsequent number of cases in tested populations.
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Nearly all mass gathering events (MGEs) worldwide have been banned since the outbreak of SARS-CoV-2 as they are supposed to pose a considerable risk for transmission of COVID-19. We investigated transmission risk of SARS-CoV-2 by droplets and aerosols during an experimental indoor MGE (using N95 masks and contact tracing devices) and conducted a simulation study to estimate the resulting burden of disease under conditions of controlled epidemics. The number of exposed contacts was <10 for scenarios with hygiene concept and good ventilation, but substantially higher otherwise. Of subsequent cases, 0%-23% were attributable to MGEs. Overall, the expected additional effect of indoor MGEs on burden of infections is low if hygiene concepts are applied and adequate ventilation exists. One Sentence SummarySeated indoor events, when conducted under hygiene precautions and with adequate ventilation, have small effects on the spread of COVID-19.
