98%
921
2 minutes
20
The immune response and specific antibody production in COVID-19 are among the key factors that determine both prognostics for individual patients and the global perspective for controlling the pandemics. So called "dark figure", that is, a part of population that has been infected but not registered by the health care system, make it difficult to estimate herd immunity and to predict pandemic trajectories. Here we present a follow up study of population screening for hidden herd immunity to SARS-CoV-2 in individuals who had never been positively diagnosed against SARS-CoV-2; the first screening was in May 2021, and the follow up in December 2021. We found that specific antibodies targeting SARS-CoV-2 detected in May as the "dark figure" cannot be considered important 7 months later due to their significant drop. On the other hand, among participants who at the first screening were negative for anti-SARS-CoV-2 IgG, and who have never been diagnosed for SARS-CoV-2 infection nor vaccinated, 26% were found positive for anti-SARS-CoV-2 IgG. This can be attributed to of the "dark figure" of the recent, fourth wave of the pandemic that occurred in Poland shortly before the study in December. Participants who were vaccinated between May and December demonstrated however higher levels of antibodies, than those who undergone mild or asymptomatic (thus unregistered) infection. Only 7% of these vaccinated participants demonstrated antibodies that resulted from infection (anti-NCP). The highest levels of protection were observed in the group that had been infected with SARS-CoV-2 before May 2021 and also fully vaccinated between May and December. These observations demonstrate that the hidden fraction of herd immunity is considerable, however its potential to suppress the pandemics is limited, highlighting the key role of vaccinations.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9462561 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0274095 | PLOS |
Viruses
July 2025
Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107 Leipzig, Germany.
: Epidemiological modeling is a vital tool for managing pandemics, including SARS-CoV-2. Advances in the understanding of epidemiological dynamics and access to new data sources necessitate ongoing adjustments to modeling techniques. In this study, we present a significantly expanded and updated version of our previous SARS-CoV-2 model formulated as input-output non-linear dynamical systems (IO-NLDS).
View Article and Find Full Text PDFActa Obstet Gynecol Scand
September 2025
Open Patient Data Explorative Network, Odense University Hospital, Odense, Denmark.
Introduction: Denmark is one of the safest places for childbirth, yet some women report dissatisfaction with their maternity care. However, some negative birth experiences may remain unreported due to thresholds for complaining. The study aimed to identify patterns of unreported negative birth experiences and to quantify the extent of these dark figures.
View Article and Find Full Text PDFJ Prev (2022)
June 2025
Institute of Sexology and Sexual Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany.
König's (2025) critique of the German Prevention Project Dunkelfeld mis-applies standards developed for adjudicated ("Hellfeld") offenders to a voluntary, non-forensic prevention setting. We clarify why context-appropriate science is essential for evaluating interventions that reach individuals whose child sexual abuse (CSA) behaviour remains hidden from the justice system. First, the large gap between official recidivism and high self-reported offending is not methodological failure but strong evidence of the well-documented "dark figure" of undetected sexual crime.
View Article and Find Full Text PDFComput Biol Med
July 2025
Department of Systems Immunology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany; Lower Saxony Center for Artificial Intelligence and Causal Methods in Medicine (CAIMed), Hannover, Germany. Electronic address:
Agent-based models have proven to be useful tools in supporting decision-making processes in different application domains. The advent of modern computers and supercomputers has enabled these bottom-up approaches to realistically model human mobility and contact behavior. The COVID-19 pandemic showcased the urgent need for detailed and informative models that can answer research questions on transmission dynamics.
View Article and Find Full Text PDFJ Prev (2022)
August 2025
Applied Social Sciences, University of Applied Sciences and Arts Dortmund, Emil-Figge-Straße 44, 44227, Dortmund, Germany.