Seroprevalence studies suggest that the number of PCR-confirmed COVID-19 cases is significantly smaller than the true number of infections. I study logintidual seroprevalence data from 7 sites across the US, from early April 2020 to June 27. I show that not only COVID-19 seroprevalence does not seem to increase over time, there is no clear association between the number of cases reported during a period and the change in seroprevalence during the same time. I conclude that as they are, seroprevalence studies can only be used in the qualitative sense and distinguish between populations with no COVID-19 exposure, to those populations where the virus had already started spreading.

As the coronavirus disease 2019 (COVID-19), which is caused by the novel SARS-CoV-2, continues to spread rapidly around the world, there is a need for well validated serological assays that allow the detection of viral specific antibody responses in COVID-19 patients or recovered individuals. In this study, we established and used multiple indirect Enzyme Linked Immunosorbent Assay (ELISA)-based serological assays to study the antibody response in COVID-19 patients. In order to validate the assays we determined the cut off values, sensitivity and specificity of the assays using sera collected from pre-pandemic healthy controls, COVID-19 patients at different time points after disease-onset, and seropositive sera to other human coronaviruses. The developed SARS-CoV-2 S1 subunit of the spike glycoprotein and nucleocapsid (N)-based ELISAs not only showed high specificity and sensitivity but also did not show any cross-reactivity with other CoVs. We also show that all RT-PCR confirmed COVID-19 patients tested in our study developed both virus specific IgM and IgG antibodies as early as week one after disease onset. Our data also suggest that the inclusion of both S1 and N in serological testing would capture as many potential SARS-CoV-2 positive cases as possible than using any of them alone. This is specifically important for tracing contacts and cases and conducting large-scale epidemiological studies to understand the true extent of virus spread in populations.

This brief note aims to explain the scope in conducting large-scale serological surveys of SARS-CoV-2 to define the landscape of population immunity without overlooking the inherent uncertainty steaming from sampling design and diagnostic validity. The note completes with a succinct statistical appendix of simple methods for estimating prevalence from random population samples using imperfect diagnostic tests.