Estimating various antibody classes against the SARSCoV-2 virus can reflect the true burden of disease in the population

Objectives: The objective of the study is to determine the significance of estimating total antibodies against Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) for determining the seroprevalence and to compare the seroprevalence calculated to that obtained by testing only immunoglobulin (Ig)G antibodies. Detection of total antibodies (IgA+IgM+IgG) could be an exact indicator in assessing immunological response against the COVID-19 infection and thereby the true burden of disease. Materials and Methods: This laboratory-based retrospective comparative study was conducted over 6 months. A total of 504 stored serum samples, tested for IgG antibodies using Chemiluminescent immunoassay (CLIA), were selected through convenience sampling. These samples were retested using the WANTAI SARS-CoV-2 Antibody Enzyme Linked Immunosorbent Assay (ELISA) to detect total antibodies (IgG+IgM+IgA) targeting the spike protein’s receptor-binding domain. Statistical analysis: The entire data is statistically analyzed using Statistical Package for Social Sciences (version 24.0, IBM Corporation, USA) for MS Windows. Being a non-comparative cross-sectional study, the statistical testing procedures were not required. Results: The seroprevalence calculated by estimating only IgG antibodies was 2.8% and that calculated by estimating total antibodies using the WANTAI assay was 20.6%. Hence, 17.8% of samples gave false-negative results when tested for IgG-only antibodies. Thus, the use of total antibodies in estimating seroprevalence will be more helpful than estimating only IgG antibodies, as total antibodies will give a real insight into true seroprevalence. Conclusions: Estimating total antibodies (IgA+IgM+IgG) is a valuable supplement to real-time polymerase chain reaction for detecting recent SARS-CoV-2 infection, especially in clinically suspected cases. It provides higher seroprevalence estimates than IgG alone, offering better insight into disease spread and immunity, and is essential for future epidemiological surveillance and outbreak preparedness.