Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Understanding the challenges and uncertainties of seroprevalence studies for SARS-CoV-2 |
| Συγγραφείς: |
David McConnell, Conor Hickey, NORMA BARGARY, Lea Trela-Larsen, Cathal Dominic Walsh, Michael Barry, Roisin Adams |
| Έτος έκδοσης: |
2021 |
| Θεματικοί όροι: |
COVID-19, SARS-CoV-2, coronavirus |
| Περιγραφή: |
SARS-CoV-2 continues to widely circulate in populations globally. Under detection is acknowledged and is problematic when attempting to capture the true prevalence. Seroprevalence studies, where blood samples from a population sample are tested for SARS-CoV-2 antibodies that react to the SARS-CoV-2 virus, are a common method for estimating the proportion of people previously infected with the virus in a given population. However, obtaining reliable estimates from seroprevalence studies is challenging for a number of reasons, and the uncertainty in the results is often overlooked by scientists, policy makers, and the media. This paper reviews the methodological issues that arise in designing these studies, and the main sources of uncertainty that affect the results. We discuss the choice of study population, recruitment of subjects, uncertainty surrounding the accuracy of antibody tests, and the relationship between antibodies and infection over time. Understanding these issues can help the reader to interpret and critically evaluate the results of seroprevalence studies. |
| Τύπος εγγράφου: |
article in journal/newspaper |
| Γλώσσα: |
unknown |
| Relation: |
10344/10115 |
| Διαθεσιμότητα: |
https://figshare.com/articles/journal_contribution/Understanding_the_challenges_and_uncertainties_of_seroprevalence_studies_for_SARS-CoV-2/19840207 |
| Rights: |
CC BY-NC-SA 1.0 |
| Αριθμός Καταχώρησης: |
edsbas.B4956770 |
| Βάση Δεδομένων: |
BASE |