SARS-CoV-2 Seroprevalence Following a Large-Scale Vaccination Campaign in Portugal: Results of the National Serological Survey, September - November 2021

Seroepidemiological assessment of SARS-CoV-2 vaccine responsiveness and associated factors in the vaccinated community of the Casablanca-Settat Region, Morocco

Assessing the prevalence of SARS-CoV-2 IgG positivity through population-based serological surveys is crucial for monitoring COVID-19 vaccination efforts. In this study, we evaluated SARS-CoV-2 IgG positivity within a provincial cohort to understand the magnitude of the humoral response against the SARS-CoV-2 vaccine and to inform evidence-based public health decisions. A community-based cross-sectional seroprevalence study was conducted, involving 10,669 participants who received various vaccines (two doses for BBIBP-CorV/Sinopharm, Covishield vaccine, and Pfizer/BioNTech, and one dose for Johnson & Johnson's Janssen COVID-19 vaccine). The study spanned 16 provinces in the Casablanca-Settat region from February to June 2022, during which comprehensive demographic and comorbidity data were collected. We screened samples for the presence of IgG antibodies using the SARS-CoV-2 IgG II Quant assay, which quantifies antibodies against the receptor-binding domain (RBD) of the spike (S) protein, measured on the Abbott Architect i2000SR. The overall crude seroprevalence was 96% (95% CI: 95.6-96.3%), and after adjustment for assay performance, it was estimated as 96.2% (95% CI: 95.7-96.6). The adjusted overall seroprevalences according to vaccine brands showed no significant difference (96% for BBIBP-CorV/Sinopharm, 97% for ChAdOx1 nCoV-19/Oxford/AstraZeneca, 98.5% for BNT162b2/Pfizer-BioNTech, and 98% for Janssen) (p = 0.099). Participants of older age, female sex, those with a history of previous COVID-19 infection, and those with certain chronic diseases were more likely to be seropositive among ChAdOx1 nCoV-19/Oxford/AstraZeneca and BBIBP-CorV/Sinopharm vaccinee groups. Median RBD antibody concentrations were 2355 AU/mL, 3714 AU/mL, 5838 AU/mL, and 2495 AU/mL, respectively, after two doses of BBIBP-CorV/Sinopharm, ChAdOx1 nCoV-19/Oxford/AstraZeneca, BNT162b2/Pfizer-BioNTech, and after one dose of Janssen (p < 0.0001). Furthermore, we observed that participants vaccinated with ChAdOx1 nCoV-19/Oxford/AstraZeneca and BBIBP-CorV/Sinopharm with comorbid chronic diseases exhibited a more pronounced response to vaccination compared to those without comorbidities. In contrast, no significant differences were observed among Pfizer-vaccinated participants (p > 0.05). In conclusion, our serosurvey findings indicate that all four investigated vaccines provide a robust humoral immune response in the majority of participants (more than 96% of participants had antibodies against SARS-CoV-2). The BNT162b2 vaccine was found to be effective in eliciting a strong humoral response compared to the other three vaccines. However, challenges still remain in examining the dynamics and durability of immunoprotection in the Moroccan context.

Understanding spatiotemporal patterns of COVID-19 incidence in Portugal: A functional data analysis from August 2020 to March 2022

During the SARS-CoV-2 pandemic, governments and public health authorities collected massive amounts of data on daily confirmed positive cases and incidence rates. These data sets provide relevant information to develop a scientific understanding of the pandemic's spatiotemporal dynamics. At the same time, there is a lack of comprehensive approaches to describe and classify patterns underlying the dynamics of COVID-19 incidence across regions over time. This seriously constrains the potential benefits for public health authorities to understand spatiotemporal patterns of disease incidence that would allow for better risk communication strategies and improved assessment of mitigation policies efficacy. Within this context, we propose an exploratory statistical tool that combines functional data analysis with unsupervised learning algorithms to extract meaningful information about the main spatiotemporal patterns underlying COVID-19 incidence on mainland Portugal. We focus on the timeframe spanning from August 2020 to March 2022, considering data at the municipality level. First, we describe the temporal evolution of confirmed daily COVID-19 cases by municipality as a function of time, and outline the main temporal patterns of variability using a functional principal component analysis. Then, municipalities are classified according to their spatiotemporal similarities through hierarchical clustering adapted to spatially correlated functional data. Our findings reveal disparities in disease dynamics between northern and coastal municipalities versus those in the southern and hinterland. We also distinguish effects occurring during the 2020-2021 period from those in the 2021-2022 autumn-winter seasons. The results provide proof-of-concept that the proposed approach can be used to detect the main spatiotemporal patterns of disease incidence. The novel approach expands and enhances existing exploratory tools for spatiotemporal analysis of public health data.

Seroprevalence of Specific SARS-CoV-2 Antibodies during Omicron BA.5 Wave, Portugal, April-June 2022

After the rapid spread of SARS-CoV-2 BA.5 Omicron lineage in Portugal, we developed a seroepidemiologic survey based on a sample of 3,825 residents. Results indicated that from April 27 through June 8, 2022, the estimated seroprevalence of SARS-CoV-2 nucleocapsid or spike IgG was 95.8%, which indicates a high level of protection.