Introduction
Serological tests are a powerful tool in the monitoring of infectious
diseases and the detection of host immunity. To help fight the recent
coronavirus disease-2019 (COVID-19) pandemic representing our time’s
sincerest health and socioeconomic crisis, various serological assays
have been brought to market in record time. [1-5]. Many of these
tests were developed with the ultimate goal to monitor the infection
burden within a community, assess vaccination responses, and determine
the likelihood of protection against re-infection [5, 6].Broad implementation of serological COVID-19 tests has also been
envisioned to assess the effectiveness of control strategies and
facilitate decision-making on the reopening of schools, cultural
facilities, and businesses [7-10]. Further, such tests might form a
basis for the issue of immunity passports, the authorization of
international traveling, and the return of employees to work [9,
11]. Numerous serological studies have recently been conducted
[12-15], and governments worldwide have ordered millions of
serological tests to identify individuals with antibodies against severe
acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [16] without
prior in-depth clinical validation of the assays.
To enable a meaningful application and interpretation of serological
test results, such assays must (a) accurately identify patients with
previous COVID-19 and (b) correctly predict protective immunity acquired
by previous infection or vaccination [4, 6, 10]. Tests with
inadequate performance characteristics will result in misinterpretation
of data and might lead to questionable or even counter-productive health
policy decision [5, 16]. Problematically, manufacturers of
serological assays often provide diagnostic accuracy data generated
through biased studies and claiming to have a sensitivity and
specificity close to 100% [2, 5, 12] [17] [2, 10, 13, 18,
19]. Thus, estimates of diagnostic accuracy are regarded as unreliable
[2, 10, 20]. Many organizations, including the WHO, now call for the
development of reliable antibody tests and evaluation in appropriate
diagnostic accuracy studies [5, 9].
Here, we conducted a prospective cross-sectional study in a real-life
clinical setting, stringently fulfilling the requirements of a
diagnostic accuracy study, including (1) an adequately powered
prospective design studying clearly defined clinical questions, (2)
selection of a representative study population, (3) head-to-head
comparison of all significant serological testing strategies, (4)
rigorous choice and determination of reference standard, and (e) optimal
flow and timing. Specifically, we assessed whether different serological
testing strategies may (a) accurately identify patients with previous
COVID-19 and (b) correctly predict neutralizing antibodies against
SARS-CoV-2.