Estimation of the basic reproduction number of COVID-19 from the incubation period distribution

The estimates of the future course of spreading of the SARS-CoV-2 virus are frequently based on Markovian models in which the duration of residence in any compartment is exponentially distributed. Accordingly, the basic reproduction number $$R_0$$ is also determined from formulae where it is related to the parameters of such models. The observations show that the start of infectivity of an individual appears nearly at the same time as the onset of symptoms, while the distribution of the incubation period is not an exponential. Therefore, we propose a method for estimation of $$R_0$$ for COVID-19 based on the empirical incubation period distribution and assumed very short infectivity period that lasts only few days around the onset of symptoms. We illustrate this venerable approach to estimate $$R_0$$ for six major European countries in the first wave of the epidemic. The calculations show that even if the infectivity starts 2 days before the onset of symptoms and stops instantly when they appear (immediate isolation), the value of $$R_0$$ is larger than that from the classical, SIR model. For more realistic cases, when only individuals with mild symptoms spread the virus for few days after onset of symptoms, the respective values are even larger. This implies that calculations of $$R_0$$ and other characteristics of spreading of COVID-19 based on the classical, Markovian approaches should be taken very cautiously

Application of modal analysis in assessing attack vulnerability of complex networks

In this paper we propose an alternative way to study robustness and vulnerability of complex networks, applying a modal analysis. The modal weights of the network nodes are considered as a measure for their busyness, which is further used for preferential removal of nodes and attack simulation. Analyses of the attack vulnerability are carried out for several generic graphs, generated according to ER and BA algorithms, as well as for some examples of manmade networks. It was found that a modal weight based attack causes significant disintegration of manmade networks by removing a small fraction of the busiest nodes, comparable to the one based on the node degree and betweenness centrality.JRC.DG.G.5-European laboratory for structural assessmen

Application of modal analysis in assessing attack vulnerability of complex networks

In this paper we propose an alternative way to study robustness and vulnerability of complex networks, applying a modal analysis. The modal weights of the network nodes are considered as a measure for their busyness, which is further used for preferential removal of nodes and attack simulation. Analyses of the attack vulnerability are carried out for several generic graphs, generated according to ER and BA algorithms, as well as for some examples of manmade networks. It was found that a modal weight based attack causes signi¯cant disintegration of manmade networks by removing a small fraction of the busiest nodes, comparable to the one based on the node degree and betweenness centralityJRC.DG.G.5-European laboratory for structural assessmen