What Can We Learn from the Time Evolution of COVID‐19 Epidemic in Slovenia?. Issue 7 (4th June 2021)

• Record Type: Journal Article
• Authors: Bâldea, Ioan
• Is Part Of: Advanced theory and simulations. Volume 4:Issue 7(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-06-04
• Subjects: COVID‐19 -- epidemic propagation -- epidemiological curves -- linear fit model -- logistic model -- SARS‐CoV‐2 virus; Science -- Simulation methods -- Periodicals; Science -- Methodology -- Periodicals; Engineering -- Simulation methods -- Periodicals; Engineering -- Methodology -- Periodicals; 507.21
• DOI: 10.1002/adts.202000225
• Languages: English
• ISSNs: 2513-0390

Abstract

Abstract: A recent work indicates that temporarily splitting larger populations into smaller groups can efficiently mitigate the spread of SARS‐CoV‐2 virus. The fact that, soon afterward, 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. Motivated by this evolution, in this paper the time dynamics of coronavirus cases in Slovenia is investigated with emphasis on how efficient various containment measures act to diminish the number of COVID‐19 infections. Noteworthily, the present analysis does not rely on any speculative theoretical assumption; it is solely based on raw epidemiological data. 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 κ by a factor of four with respect to the unrestricted state, they only improve the κ‐value by ≈15% as compared to the much bearable state of social and economic life wherein wearing face masks and social distancing rules are enforced/followed. Significantly for behavioral and social science, our analysis may reveal an interesting self‐protection instinct of the population, which became manifest even before the official lockdown enforcement. Abstract : A novel method relying on raw epidemiologic data without speculative theoretical assumptions is proposed. Although based on the nonlinear logistic model, the analysis is amenable to linear regression. Applied to a specific case (Slovenia's COVID‐19 epidemic), this approach discourages too excessive curfews and travel restrictions, and unravels an interesting population's self‐protection instinct, which became manifest even before official lockdown enforcement.