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Simulation of the COVID-19 epidemic on the social network of Slovenia: estimating the intrinsic forecast uncertainty
ID
Zaplotnik, Žiga
(
Avtor
),
ID
Gavrić, Aleksandar
(
Avtor
),
ID
Medic, Luka
(
Avtor
)
PDF - Predstavitvena datoteka,
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(4,03 MB)
MD5: 5885BE0D4053ECC7CEA4C62419E4D3F3
URL - Izvorni URL, za dostop obiščite
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0238090
Galerija slik
Izvleček
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.
Jezik:
Angleški jezik
Ključne besede:
COVID-19
,
epidemiology
,
Slovenia
,
social networks
Tipologija:
1.01 - Izvirni znanstveni članek
Organizacija:
FMF - Fakulteta za matematiko in fiziko
Status publikacije:
Objavljeno
Različica publikacije:
Objavljena publikacija
Leto izida:
2020
Št. strani:
22 str.
Številčenje:
Vol. 15, art. e0238090
PID:
20.500.12556/RUL-124022
UDK:
616-036.22
ISSN pri članku:
1932-6203
DOI:
10.1371/journal.pone.0238090
COBISS.SI-ID:
26780419
Datum objave v RUL:
21.12.2020
Število ogledov:
1797
Število prenosov:
451
Metapodatki:
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Objavi na:
Gradivo je del revije
Naslov:
PloS one
Založnik:
Public Library of Science
ISSN:
1932-6203
COBISS.SI-ID:
2005896
Licence
Licenca:
CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:
http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:
To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:
21.12.2020
Sekundarni jezik
Jezik:
Slovenski jezik
Ključne besede:
koronavirus COVID-19
,
epidemije
,
socialne mreže
,
Slovenija
Projekti
Financer:
ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:
J1-9431
Naslov:
Prispevek Rossbyevih in inercijsko-težnostnih valov k vertikalni hitrosti in pretoku gibalne količine v ozračju
Financer:
ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:
P1-0188
Naslov:
Astrofizika in fizika atmosfere
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