• Corpus ID: 214743438

Propagation and mitigation of epidemics in a scale-free network

  title={Propagation and mitigation of epidemics in a scale-free network},
  author={Gyula M. Szab'o},
  journal={arXiv: Populations and Evolution},
  • G. Szab'o
  • Published 31 March 2020
  • Mathematics
  • arXiv: Populations and Evolution
The epidemic curve and the final extent of the COVID-19 pandemic are usually predicted from the rate of early exponential raising using the SIR model. These predictions implicitly assume a full social mixing, which is not plausible generally. Here I am showing a counterexample to the these predictions, based on random propagation of an epidemic in Barabasi--Albert scale-free network models. The start of the epidemic suggests $R_0=2.6$, but unlike $\Omega\approx 70\%{}$ predicted by the SIR… 

Figures from this paper

Emerging Polynomial Growth Trends in COVID-19 Pandemic Data and Their Reconciliation with Compartment Based Models

The reported data from the COVID-19 pandemic outbreak in January - May 2020 are studied and the model shows a good agreement with the reported data and can be applied to improve predictions of the reported pandemic data and estimate some epidemic parameters.

Emerging algebraic growth trends in SARS-CoV-2 pandemic data

The results are formulated in terms of compartment type mathematical models of epidemics and it is shown how the findings can be applied to improve predictions of the reported pandemic data and estimate some epidemic parameters.

Exo-SIR: an epidemiological model to analyze the impact of exogenous spread of infection

Epidemics like Covid-19 and Ebola have impacted people’s lives significantly. The impact of mobility of people across the countries or states in the spread of epidemics has been significant. The

Power Laws in Superspreading Events: Evidence from Coronavirus Outbreaks and Implications for SIR Models

Evidence is documents from recent coronavirus outbreaks that SSEs follow a power law distribution with fat tails, or infinite variance, and it is shown that idiosyncratic uncertainties in S SEs will lead to large aggregate uncertainties in infection dynamics, even with large populations.

Time-adjusted Analysis Shows Weak Associations Between BCG Vaccination Policy and COVID-19 Disease Progression

In this study, we ascertain the associations between BCG vaccination policies and progression of COVID-19 through analysis of various time-adjusted indicators either directly extracted from the

Exo-SIR: An Epidemiological Model to Analyze the Impact of Exogenous Infection of COVID-19 in India

The Exo-SIR model is introduced - a novel model that captures both the exogenous and endogenous spread of the virus and is found that in the presence of exogenous infection, the endogenous infection peak becomes higher, and the peak occurs earlier.



A contribution to the mathematical theory of epidemics

The present communication discussion will be limited to the case in which all members of the community are initially equally susceptible to the disease, and it will be further assumed that complete immunity is conferred by a single infection.

Imperial College COVID-19 Response Team

  • 2020