ABSTRACT
BackgroundSARS-CoV-2 serologic surveys estimate the proportion of the population with antibodies against historical variants which nears 100% in many settings. New analytic approaches are required to exploit the full information in serosurvey data. MethodUsing a SARS-CoV-2 anti-Spike (S) protein chemiluminescent microparticle assay, we attained a semi-quantitative measurement of population IgG titres in serial cross-sectional monthly samples of routine blood donations across seven Brazilian state capitals (March 2021-November 2021). In an ecological analysis (unit of analysis: age-city-calendar month) we assessed the relative contributions of prior attack rate and vaccination to antibody titre in blood donors. We compared blood donor anti-S titre across the seven cities during the growth phase of the Delta variant of concern (VOC) and use this to predict the resulting age-standardized incidence of severe COVID-19 cases. ResultsOn average we tested 780 samples per month in each location. Seroprevalence rose to >95% across all seven capitals by November 2021. Driven proximally by vaccination, mean antibody titre increased 16-fold over the study. The extent of prior natural infection shaped this process, with the greatest increases in antibody titres occurring in cities with the highest prior attack rates. Mean anti-S IgG was a strong predictor (adjusted R2 =0.89) of the number of severe cases caused by the Delta VOC in the seven cities. ConclusionsSemi-quantitative anti-S antibody titres are informative about prior exposure and vaccination coverage and can inform on the potential impact of future SARS-CoV-2 variants. SummaryIn the face of near 100% SARS-CoV-2 seroprevalence, we show that average semi-quantitative anti-S titre predicted the extent of the Delta variants spread in Brazil. This is a valuable metric for future seroprevalence studies.
ABSTRACT
BackgroundLittle evidence exists on the differential health effects of COVID-19 on disadvantaged population groups. Here we characterise the differential risk of hospitalisation and death in Sao Paulo state, Brazil and show how vulnerability to COVID-19 is shaped by socioeconomic inequalities. MethodsWe conducted a cross-sectional study using hospitalised severe acute respiratory infections (SARI) notified from March to August 2020, in the Sistema de Monitoramento Inteligente de Sao Paulo (SIMI-SP) database. We examined the risk of hospitalisation and death by race and socioeconomic status using multiple datasets for individual-level and spatio-temporal analyses. We explained these inequalities according to differences in daily mobility from mobile phone data, teleworking behaviour, and comorbidities. FindingsThroughout the study period, patients living in the 40% poorest areas were more likely to die when compared to patients living in the 5% wealthiest areas (OR: 1{middle dot}60, 95% CI: 1{middle dot}48 - 1{middle dot}74) and were more likely to be hospitalised between April and July, 2020 (OR: 1{middle dot}08, 95% CI: 1{middle dot}04 - 1{middle dot}12). Black and Pardo individuals were more likely to be hospitalised when compared to White individuals (OR: 1{middle dot}37, 95% CI: 1{middle dot}32 - 1{middle dot}41; OR: 1{middle dot}23, 95% CI: 1{middle dot}21 - 1{middle dot}25, respectively), and were more likely to die (OR: 1{middle dot}14, 95% CI: 1{middle dot}07 - 1{middle dot}21; 1{middle dot}09, 95% CI: 1{middle dot}05 - 1{middle dot}13, respectively). InterpretationLow-income and Black and Pardo communities are more likely to die with COVID-19. This is associated with differential access to healthcare, adherence to social distancing, and the higher prevalence of comorbidities. FundingThis project was supported by a Medical Research Council-Sao Paulo Research Foundation (FAPESP) CADDE partnership award (MR/S0195/1 and FAPESP 18/14389-0) (http://caddecentre.org/). This work received funding from the U.K. Medical Research Council under a concordat with the U.K. Department for International Development.
ABSTRACT
BackgroundPassive antibody therapy with convalescent plasma (CP) represents a promising alternative for the treatment of SARS-CoV-2 infection. The efficacy of CP therapy has been associated with high titers of neutralizing antibodies (nAbs) in the plasma of recovered patients, but the assays for quantifying nAbs are not widely available. Our goal was to develop a strategy to predict high titers of nAbs based on the results of anti-SARS-CoV-2 immunoassays and the clinical characteristics of the CP potential donors. MethodsTwo hundred and fourteen CP donors were enrolled and tested for the presence of anti-SARS-CoV-2 antibodies using two commercial immunoassays (IA): Anti-SARS-CoV-2 ELISA IgG EUROIMMUN and Anti-SARS-CoV-2 Chemiluminescence IgG Abbott. In parallel, quantification of neutralizing antibodies (nAbs) was performed using the Cytopathic effect-based virus neutralization test (CPE-VNT). Three criteria for identifying donors with high titers of nAbs ([≥]1:160) were tested: - Criterion1: Curve ROC Method; - Criterion 2: Conditional decision tree considering only the results from the IA and -Criterion 3: Conditional decision tree including both the IA results and the clinical variables. ResultsThe performance of Abbott and EUROIMMUN immunoassays was similar referring to both S/CO and predictive value for identifying nAbs titers [≥] 1:160. Regarding the three studied criteria for identifying CP donors with high nAbs titers ([≥] 1:160): 1) Criterion 1 showed 76.1% accuracy when the S/CO cut-off of 4.65 was used, 2) Criterion 2 presented 76.1% accuracy if the S/CO [≥] 4.57 was applied and 3) Criterion 3 had 71.6% accuracy if either S/CO [≥] 4.57 or S/CO between 2.68 and 4.57 and the last COVID-19-related symptoms occurred less than 19 days from donor recruiting were used. ConclusionThe results of SARS-CoV-2 immunoassays (S/CO) can be used to predict high nAbs titers of potential CP donors. This study has proposed three different criteria for identifying donors with [≥] 1:160 nAbs titer based on either solely S/CO results or S/CO together with clinical variables, all with high efficacy and accuracy.
