A recent work (DOI 10.1101/2020.3310) indicated that temporarily splitting larger populations into smaller groups can efficiently mitigate the spread of SARS-CoV-2 virus. Significantly for behavioral and social science, our analysis of the time dependence kappa = kappa(t) may reveal an interesting self-protection instinct of the population, which became manifest even before the official lockdown enforcement. Out of the results presented here, the most important one is perhaps the finding that, while imposing drastic curfews and travel restrictions reduce the infection rate kappa by a factor of four with respect to the unrestricted state, they only improve the kappa-value by ~15 % as compared to the much bearable state of social and economical life wherein (justifiable) wearing face masks and social distancing rules are enforced/followed. Noteworthily, the present analysis does not rely on any speculative theoretical assumption it is solely based on raw epidemiological data. Motivated by this evolution, in this paper we investigate the time dynamics of coronavirus cases in Slovenia with emphasis on how efficient various containment measures act to diminish the number of COVID-19 infections. The fact that, soon afterwards, on May 15, 2020, the two million people Slovenia was the first European country proclaiming the end of COVID-19 epidemic within national borders may be relevant from this perspective. ficiently mitigate the spread of SARS-CoV-2 virus. Properly designed and timely executed studies using probability-based samples combined with routine target-testing figures provide reliable data that can be used to make informed decisions on relaxing or strengthening disease mitigation strategies.Ī recent work (DOI 10.1101/2020.3310) indicated that temporarily splitting larger populations into smaller groups can ef. Conclusions The low prevalence of active COVID-19 infections found in this study accurately predicted the dynamics of the epidemic in Slovenia over the subsequent month. No newly diagnosed infections occurred in the cohort during the first 3-week follow-up round. Two of 1366 participants tested positive for SARS-CoV-2 RNA (prevalence 0.15% posterior mean 0.18%, 95% Bayesian confidence interval 0.03–0.47 95% highest density region (HDR) 0.01–0.41). Results A total of 1368 individuals (46%) consented to participate and completed the questionnaire. After 3 weeks, participants were interviewed for the presence of COVID-19–compatible clinical symptoms and signs, including in household members, and offered immediate testing for SARS-CoV-2 RNA if indicated. Each participant filled in a detailed baseline questionnaire with basic sociodemographic data and detailed medical history compatible with COVID-19. SARS-CoV-2 RNA was detected in nasopharyngeal samples using the cobas 6800 SARS-CoV-2 assay. Methods A probability-based sample of the Slovenian population comprising data from 2.1 million people was selected from the Central Population Register (n = 3000). Baseline SARS-CoV-2 RNA testing results and the first 3-week follow-up results are presented. We conducted the first nationwide population study using a probability-based sample to assess active severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, combined with a longitudinal follow-up of the entire cohort over the next 6 months. Abstract Objectives Accurate population-level assessment of the coronavirus disease 2019 (COVID-19) burden is fundamental for navigating the path forward during the ongoing pandemic, but current knowledge is scant.
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