SummaryBackgroundThe progression and distribution of SARS-CoV-2 is unknown because typically only symptomatic individuals are diagnosed.AimWe evaluated the seroprevalence of anti-SARS-CoV-2 in blood donors in Nuevo Leon, Mexico as a strategy for asymptomatic case detection of COVID-19 and epidemic progression.Methods/MaterialsWe tested 1968 blood donors that attended two regional donation centers in Northeast Mexico from January 1st to August 30, 2020, to identify anti-SARS-CoV-2 IgG by chemiluminescent immunoassay. Additionally, routine tests for donors including Brucella, Chagas, HCV, VDRL, HIV-1, and HBsAg identification were performed.ResultsWe found 77 donors reactive for anti-SARS-CoV-2 IgG (seroprevalence 3.99%) and none of them had reported recent COVID-19 symptoms. Donors aged 18 to 49 years (89.5%) were more likely to be seropositive compared to those aged 50 years or older (10.5%) (P<0.001). Prevalence of antibodies increased each epidemiological (EPI) week, parallel to the report of confirmed cases by RT-PCR, identifying the highest prevalence between EPI week 33 and 35 (10.2% to 19%). The metropolitan area of Monterrey recorded the highest number of cases. Routine tests showed that the prevalence of anti-Brucella was 0.13%, anti-HCV 0.5%, anti-HIV-1-2 0.14%, HBsAg 0.16%, Chagas 0.48% and syphilis 1.06%.ConclusionsThere is a growing trend of seroprevalence over time, parallel to the constantly increasing epidemic curve in our region and it was higher under 49 years of age associated with asymptomatic infection in donors from the Nuevo Leon area. Detection of anti-SARS-CoV-2 in blood donors is a potential tool for tracking the progression and identifying population exposure during the SARS-CoV-2 outbreak.

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The progression and distribution of the SARS-CoV-2 pandemic are continuously changing over time and can be traced by blood donors’ serological survey. Here, we investigated the seroprevalence of anti-SARS-CoV-2 antibodies in blood donors in Nuevo Leon, Mexico during 2020 as a strategy for the rapid evaluation of the spread of SARS-CoV-2 and asymptomatic case detection. We collected residual plasma samples from blood donors who attended two regional donation centers from January to December of 2020 to identify changes in anti-SARS-CoV-2 IgG prevalence. Plasma samples were analyzed on the Abbott Architect instrument using the commercial Abbott SARS-CoV-2 IgG chemiluminescent assay. We found a total of 99 reactive samples from 2068 analyzed plasma samples, resulting in a raw prevalence of 4.87%. Donors aged 18–49 years were more likely to be seropositive compared to those aged >50 years (p < 0.001). Weekly seroprevalence increased from 1.8% during the early pandemic stage to 27.59% by the end of the year. Prevalence was 1.46-fold higher in females compared to males. Case geographical mapping showed that Monterrey city recorded the majority of SARS-CoV-2 cases. These results show that there is a growing trend of seroprevalence over time associated with asymptomatic infection that is unnoticed under the current epidemiological surveillance protocols.

Introduction: Algorithms have been developed to predict the platelet yield after apheresis from the donor's data, as well as the effect on the blood cell count, to extract an acceptable platelet number without affecting the donor. However, the evaluation of these algorithms has not been widely reported. This study aimed to assess the accuracy of the predictive algorithms of the Trima Accel v. 6 blood collection system. Methods: Platelet concentrates (PCs) obtained by apheresis were analyzed. Platelet count and hematocrit were compared pre-and post-apheresis. Calculated post-apheresis platelet count (CPAPC), hematocrit (CPAH), and platelet yield (CPY), and their actual values were correlated. The bias of the algorithms was assessed with Bland-Altman plots, and the prediction of the extraction of single or double platelet products was evaluated. Results: Two hundred and seventy-nine PCs were analyzed. Post-apheresis platelet count (PAPC) and hematocrit were decreased. A moderate correlation was observed between CPY and the actual yield, with a negative bias, and a trend to increase alongside the magnitude of the measurements. CPAPC and CPAH were strongly correlated with their actual values without bias. Prediction of single or double platelet product extraction showed a significant agreement with the actual outcomes. Conclusions: The predictive algorithm for the platelet yield showed bias, and a trend to underestimate the actual platelet yields when they are higher. The algorithms for the prediction of the PAPC and hematocrit did not show bias, proving their accuracy. Prediction of a single or double platelet product extraction has a strong agreement with the APY.