Impact of Two Different Recruitment Procedures (Random vs. Volunteer Selection) on the Results of Seroepidemiological Study (SARS-CoV-2)

Abstract

The proper recruitment of subjects for population-based epidemiological studies is critical to the external validity of the studies and, above all, to the sound and correct interpretation of the findings. Since 2020, the novel coronavirus SARS-CoV-2 pandemic has been a new factor that has been, additionally, hindering studies. Therefore, the aim of our study is to compare demographic, socio-economic, health-related characteristics and the frequency of SARS-CoV-2 infection occurrence among the randomly selected group and the group composed of volunteers. We compare two groups of participants from the cross-sectional study assessing the seroprevalence of SARS-CoV-2 coronavirus, which was conducted in autumn 2020, in three cities of the Silesian Voivodeship in Poland. The first group consisted of a randomly selected, nationally representative, age-stratified sample of subjects (1167 participants, “RG” group) and was recruited using personal invitation letters and postal addresses obtained from a national registry. The second group (4321 volunteers, “VG” group) included those who expressed their willingness to participate in response to an advertisement published in the media. Compared with RG subjects, volunteers were more often females, younger and professionally active, more often had a history of contact with a COVID-19 patient, post-contact nasopharyngeal swab, fewer comorbidities, as well as declared the occurrence of symptoms that might suggest infection with SARS-CoV-2. Additionally, in the VG group the percentage of positive IgG results and tuberculosis vaccination were higher. The findings of the study confirm that surveys limited to volunteers are biased. The presence of the bias may seriously affect and distort inference and make the generalizability of the results more than questionable. Although effective control over selection bias in surveys, including volunteers, is virtually impossible, its impact on the survey results is impossible to predict. However, whenever possible, such surveys could include a small component of a random sample to assess the presence and potential effects of selection bias.

Assessing the burden of COVID-19 in developing countries: systematic review, meta-analysis and public policy implications

“…While our analysis excluded convenience samples and focused exclusively on representative samples of the population, we recognise that such studies may also be susceptible to selection bias. Research conducted at various stages of the pandemic has found that individual preferences for testing can be associated with substantial bias in estimates of seroprevalence, with corresponding implications for estimates of population IFR 20 59. Such uncertainty can be incorporated into statistical models of prevalence and IFR 60 61.…”

“…Such samples are subject to intrinsic selection biases that may vary across different settings and hence would detract from systematic analysis of the data. Indeed, there is abundant evidence from the pandemic that convenience samples provide inaccurate estimates of seroprevalence, with assessments indicating that they are likely to overestimate the true proportion infected 20 21…”

Assessing the Burden of COVID-19 in Developing Countries: Systematic Review, Meta-Analysis, and Public Policy Implications

“…Consequently, studies of convenience samples – such as blood donors or residual sera from commercial laboratories – were excluded. Such samples are subject to intrinsic selection biases that may vary across different settings and hence would detract from systematic analysis of the data Indeed, there is abundant evidence from the pandemic that convenience samples provide inaccurate estimates of seroprevalence, with assessments indicating that they are likely to overestimate the true proportion infected (22, 23).…”

Infection fatality rate (IFR) during the course of COVID-19 pandemic in Upper Silesia Metropolitan Area (Poland) in 2020

“…Informację tę można uzupełnić wynikiem szacowania IFR na podstawie przeprowadzonego przez autorów niniejszej pracy dużego badania 4315 mieszkańców Katowic, Gliwic i Sosnowca, rekrutowanych z wykorzystaniem spontanicznej zgłaszalności, przy zachowaniu kryterium płci i wieku. Uzyskana w tej grupie częstość zakażenia SARS-CoV-2 wynosiła 23,5% [14]. W tym przypadku wartość IFR byłaby dwukrotnie niższa niż pochodząca z analizy danych reprezentatywnych, ale przede wszystkim obarczona błędem przeszacowania.…”