Simulation of the COVID-19 epidemic on the social network of Slovenia: estimating the intrinsic forecast uncertainty

Zaplotnik, Žiga (author), Gavrić, Aleksandar (author), Medic, Luka (author)

In the article a virus transmission model is constructed on a implified social network. The social network consists of more than 2 million nodes, each representing an inhabitant of Slovenia. The nodes are organised and interconnected according to the real household and elderly-care center distribution, while their connections outside these clusters are semirandomly distributed and undirected. The virus spread model is coupled to the disease progression model. The ensemble approach with the perturbed transmission and disease parameters is used to quantify the ensemble spread, a proxy for the forecast uncertainty. The presented ongoing forecasts of COVID-19 epidemic in Slovenia are compared with the collected Slovenian data. Results show that at the end of the first epidemic wave, the infection was twice more likely to transmit within households/elderly care centers than outside them. We use an ensemble of simulations (N = 1000) and data assimilation approach to estimate the COVID-19 forecast uncertainty and to inversely obtain posterior distributions of model parameters. We found that in the uncontrolled epidemic, the intrinsic uncertainty mostly originates from the uncertainty of the virus biology, i.e. its reproduction number. In the controlled epidemic with low ratio of infected population, the randomness of the social network becomes the major source of forecast uncertainty, particularly for the short-range forecasts. Virus transmission models with accurate social network models are thus essential for improving epidemics forecasting.

• Language: English
• Keywords: COVID-19, epidemiology, Slovenia, social networks
• Typology: 1.01 - Original Scientific Article
• Organization: FMF - Faculty of Mathematics and Physics
• Publication status: Published
• Publication version: Version of Record
• Year: 2020
• Number of pages: 22 str.
• Numbering: Vol. 15, art. e0238090
• PID: 20.500.12556/RUL-124022
• UDC: 616-036.22
• ISSN on article: 1932-6203
• DOI: 10.1371/journal.pone.0238090
• COBISS.SI-ID: 26780419
• Publication date in RUL: 21.12.2020

Record is a part of a journal

• Title: PloS one
• Publisher: PLOS
• ISSN: 1932-6203
• COBISS.SI-ID: 2005896

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.
• Licensing start date: 21.12.2020

Secondary language

• Language: Slovenian
• Keywords: koronavirus COVID-19, epidemije, socialne mreže, Slovenija

Projects

• Funder: ARRS - Slovenian Research Agency
• Project number: J1-9431
• Name: Prispevek Rossbyevih in inercijsko-težnostnih valov k vertikalni hitrosti in pretoku gibalne količine v ozračju

• Funder: ARRS - Slovenian Research Agency
• Project number: P1-0188
• Name: Astrofizika in fizika atmosfere