Assessment of Seroprevalence to SARS-CoV-2 in Various Population Cohorts Using Logit Regression Models During Initial Period of Herd Immunity Formation

Abstract

The aim of the study was to assess the dynamics of seroprevalence to SARS-CoV-2 in various population groups during the initial period of herd immunity formation based on multivariate analysis using logit regression models.Materials and methods. The study involved 1561 individuals divided into three population cohorts: people living with HIV/AIDS (PLHA), healthy blood donors, medical workers. The presence of antibodies to SARS-CoV-2 was determined in blood serum through ELISA using commercial reagent kits. Multivariate analysis of the dynamics of seroprevalence to SARS-CoV-2 was carried out using logistic regression models.Results and discussion. It has been revealed that probability of detecting IgG antibodies to SARS-CoV-2 significantly increased among the donors and medical workers in the spring-autumn 2020 series (p=0.005 и p<0.001, respectively), which corresponds to seroprevalence shift in the general population. Groups of donors and medical workers can be considered as indicator groups that characterize the herd immunity in reference to SARS-CoV-2, as well as the intensity of COVID-19 epidemic process. Seroprevalence to SARS-CoV-2 in PLHA group was at a consistently high level throughout the observation period. The generated logistic regression models made it possible to determine the trends in the development of the epidemic situation based on multifactorial analysis of the dynamics of seroprevalence to SARS-CoV-2.

Keywords

• seroprevalence
• sars-cov-2
• new coronavirus infection
• enzyme-linked immunosorbent assay
• indicator groups