ABSTRACT
The recent fast global spread of COVID-19 caused by a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) questions why and how the disease managed to be so effective against existing health protection measures. These measures, developed by many countries over centuries and strengthened over the last decades, proved to be ineffective against COVID-19. The sharp increase in human longevity and current transport systems in economically developing countries with the background of persisting cultural frameworks and stable local pools of high bacterial and viral mutations generated the wide gap between the established health protection systems and the new emerging diseases. SARS-CoV-2 targets human populations over the world with long incubation periods, often without symptoms, and serious outcomes. Hence, novel strategies are necessary to meet the demands of developing economic and social environments. Moreover, the ongoing climate change adds extra challenges while altering the existing system of interactions in biological populations and in human society. Climate change may lead to new sources of viral and microbial mutations, new ways of zoonotic disease transmission and to huge social and economic transformations in many countries. The present short Opinion applies a system approach linking biomedical, climate change, social and economic aspects and, accordingly, discusses the measures and more efficient means to avoid future pandemics.
ABSTRACT
Properly conducted serological survey can help determine infection disease true spread. This study aims to estimate the seroprevalence of SARS-CoV-2 antibodies in Saint Petersburg, Russia accounting for non-response bias. A sample of adults was recruited with random digit dialling, interviewed and invited for anti-SARS-CoV-2 antibodies. The seroprevalence was corrected with the aid of the bivariate probit model that jointly estimated individual propensity to agree to participate in the survey and seropositivity. 66,250 individuals were contacted, 6,440 adults agreed to be interviewed and blood samples were obtained from 1,038 participants between May 27 and June 26, 2020. Naïve seroprevalence corrected for test characteristics was 9.0% (7.2-10.8) by CMIA and 10.5% (8.6-12.4) by ELISA. Correction for non-response decreased estimates to 7.4% (5.7-9.2) and 9.1% (7.2-10.9) for CMIA and ELISA, respectively. The most pronounced decrease in bias-corrected seroprevalence was attributed to the history of any illnesses in the past 3 months and COVID-19 testing. Seroconversion was negatively associated with smoking status, self-reported history of allergies and changes in hand-washing habits. These results suggest that even low estimates of seroprevalence can be an overestimation. Serosurvey design should attempt to identify characteristics that are associated both with participation and seropositivity.