Extended compartmental model for modeling COVID‑19 epidemic in Slovenia

Fošnarič, Miha (author), Kamenšek, Tina (author), Žganec Gros, Jerneja (author), Žibert, Janez (author)

In the absence of a systematic approach to epidemiological modeling in Slovenia, various isolated mathematical epidemiological models emerged shortly after the outbreak of the COVID-19 epidemic. We present an epidemiological model adapted to the COVID-19 situation in Slovenia. The standard SEIR model was extended to distinguish between age groups, symptomatic or asymptomatic disease progression, and vaccinated or unvaccinated populations. Evaluation of the model forecasts for 2021 showed the expected behavior of epidemiological modeling: our model adequately predicts the situation up to 4 weeks in advance; the changes in epidemiologic dynamics due to the emergence of a new viral variant in the population or the introduction of new interventions cannot be predicted by the model, but when the new situation is incorporated into the model, the forecasts are again reliable. Comparison with ensemble forecasts for 2022 within the European Covid-19 Forecast Hub showed better performance of our model, which can be explained by a model architecture better adapted to the situation in Slovenia, in particular a refined structure for vaccination, and better parameter tuning enabled by the more comprehensive data for Slovenia. Our model proved to be flexible, agile, and, despite the limitations of its compartmental structure, heterogeneous enough to provide reasonable and prompt short-term forecasts and possible scenarios for various public health strategies. The model has been fully operational on a daily basis since April 2020, served as one of the models for decision making during the COVID-19 epidemic in Slovenia, and is part of the European Covid-19 Forecast Hub.

• Language: English
• Keywords: epidemiological modeling, mathematical epidemiological models, COVID-19, SEIR model, Slovenia
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: ZF - Faculty of Health Sciences
• Publication status: Published
• Publication version: Version of Record
• Publication date: 08.10.2022
• Year: 2022
• Number of pages: 12 str.
• Numbering: Vol. 12, art. 16916
• PID: 20.500.12556/RUL-141913
• UDC: 614:[519.2:616-036.22]
• ISSN on article: 2045-2322
• DOI: 10.1038/s41598-022-21612-7
• COBISS.SI-ID: 125101315
• Publication date in RUL: 11.10.2022

Record is a part of a journal

• Title: Scientific reports
• Shortened title: Sci. rep.
• Publisher: Nature Publishing Group
• ISSN: 2045-2322
• COBISS.SI-ID: 18727432

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Undetermined
• Keywords: epidemiološko modeliranje, matematični epidemiološki modeli, COVID-19, model SEIR, Slovenija

Projects

• Funder: ARRS - Slovenian Research Agency
• Project number: P2-0250-2018
• Name: Metrologija in biometrični sistemi