Abstract
In the article a virus transmission model is constructed on a simplified 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 semi-randomly 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.
Highlights
The ongoing COVID-19 epidemic has revealed a major gap in our ability to forecast the evolution of the epidemic
Simulation of the COVID-19 epidemic on the social network of Slovenia supported by ARRS Programme P1-0188. http://www.arrs.si/sl/ The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
Its relative uncertainty roughly reflects the uncertainty in the hospitalisation, intensive care unit (ICU) and Infection fatality ratio (IFR) ratios
Summary
The ongoing COVID-19 epidemic has revealed a major gap in our ability to forecast the evolution of the epidemic. For coronaviruses including SARS-CoV-2, there is evidence that some infectious cases, the so called superspreaders, spread virus more than others [5, 6] Their role is of the utmost importance when the population of infectious is small, i.e. in the initial uncontrolled phase of an epidemic and in its final controlled phase. Different nodes are infected at initial time, while each simulation uses different virus transmission parameters and disease progress parameters, which are perturbed according to their known distributions This approach allows to estimate the uncertainty of the epidemic forecasts in the case of controlled epidemic and uncontrolled epidemic. The probabilistic ensemble forecast of the COVID-19 epidemic for Slovenia and the contribution of different model components to the total forecast uncertainty are described in section Results, followed by the Discussion, conclusions and further outlook
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