scholarly journals Epidemic Spreading and Equilibrium Social Distancing in Heterogeneous Networks

2022 ◽  
Author(s):  
Hamed Amini ◽  
Andreea Minca
Keyword(s):  
Heterogeneous Networks ◽  
Epidemic Spreading ◽  
Social Distancing

Modeling the dynamics of epidemic spreading on homogenous and heterogeneous networks

2014 ◽  
Vol 94 (11) ◽  
pp. 2308-2330 ◽  
Author(s):  
Yao Hu ◽  
Lequan Min ◽  
Yang Kuang
Keyword(s):  
Heterogeneous Networks ◽  
Epidemic Spreading

scholarly journals Modeling the Spatiotemporal Epidemic Spreading of COVID-19 and the Impact of Mobility and Social Distancing Interventions

2020 ◽  
Vol 10 (4) ◽  
Author(s):  
Alex Arenas ◽  
Wesley Cota ◽  
Jesús Gómez-Gardeñes ◽  
Sergio Gómez ◽  
Clara Granell ◽  
...  
Keyword(s):  
Epidemic Spreading ◽  
Social Distancing ◽  
The Impact

scholarly journals SOCIAL DISTANCING STRATEGIES AGAINST DISEASE SPREADING

Fractals ◽  
2013 ◽  
Vol 21 (03n04) ◽  
pp. 1350019 ◽  
Author(s):  
L. D. VALDEZ ◽  
C. BUONO ◽  
P. A. MACRI ◽  
L. A. BRAUNSTEIN
Keyword(s):  
Infectious Diseases ◽  
Healthy Individual ◽  
Percolation Theory ◽  
Quenched Disorder ◽  
Epidemic Spreading ◽  
Heterogeneous Distribution ◽  
Percolation Process ◽  
Social Distancing ◽  
Disease Spreading

The recurrent infectious diseases and their increasing impact on the society has promoted the study of strategies to slow down the epidemic spreading. In this review we outline the applications of percolation theory to describe strategies against epidemic spreading on complex networks. We give a general outlook of the relation between link percolation and the susceptible-infected-recovered model, and introduce the node void percolation process to describe the dilution of the network composed by healthy individual, i.e., the network that sustain the functionality of a society. Then, we survey two strategies: the quenched disorder strategy where an heterogeneous distribution of contact intensities is induced in society, and the intermittent social distancing strategy where health individuals are persuaded to avoid contact with their neighbors for intermittent periods of time. Using percolation tools, we show that both strategies may halt the epidemic spreading. Finally, we discuss the role of the transmissibility, i.e., the effective probability to transmit a disease, on the performance of the strategies to slow down the epidemic spreading.

Anomalous epidemic spreading in heterogeneous networks

2020 ◽  
Vol 102 (1) ◽  
Author(s):  
H. Zhang ◽  
G. H. Li
Keyword(s):  
Heterogeneous Networks ◽  
Epidemic Spreading

scholarly journals Effects of social distancing and isolation on epidemic spreading modeled via dynamical density functional theory

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Michael te Vrugt ◽  
Jens Bickmann ◽  
Raphael Wittkowski
Keyword(s):  
Density Functional Theory ◽  
Density Functional ◽  
Reaction Diffusion ◽  
Reaction Diffusion Equations ◽  
Disease Spread ◽  
Extended Model ◽  
Transient Phase ◽  
Epidemic Spreading ◽  
Functional Theory ◽  
Social Distancing

Abstract For preventing the spread of epidemics such as the coronavirus disease COVID-19, social distancing and the isolation of infected persons are crucial. However, existing reaction-diffusion equations for epidemic spreading are incapable of describing these effects. In this work, we present an extended model for disease spread based on combining a susceptible-infected-recovered model with a dynamical density functional theory where social distancing and isolation of infected persons are explicitly taken into account. We show that the model exhibits interesting transient phase separation associated with a reduction of the number of infections, and allows for new insights into the control of pandemics.

scholarly journals Epidemic spreading on heterogeneous networks with identical infectivity

2007 ◽  
Vol 364 (3-4) ◽  
pp. 189-193 ◽  
Author(s):  
Rui Yang ◽  
Bing-Hong Wang ◽  
Jie Ren ◽  
Wen-Jie Bai ◽  
Zhi-Wen Shi ◽  
...  
Keyword(s):  
Heterogeneous Networks ◽  
Epidemic Spreading

Analysis of epidemic spreading of an SIRS model in complex heterogeneous networks

2014 ◽  
Vol 19 (4) ◽  
pp. 1042-1054 ◽  
Author(s):  
Chun-Hsien Li ◽  
Chiung-Chiou Tsai ◽  
Suh-Yuh Yang
Keyword(s):  
Heterogeneous Networks ◽  
Epidemic Spreading ◽  
Sirs Model

Optimal Control of Fractional Order COVID-19 Epidemic Spreading in Japan and India 2020

2020 ◽  
Vol 15 (04) ◽  
pp. 207-236 ◽  
Author(s):  
Meghadri Das ◽  
G. P. Samanta
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Incomplete Information ◽  
Fractional Order ◽  
Compartmental Model ◽  
Transmission Dynamics ◽  
Epidemic Spreading ◽  
Social Distancing ◽  
First Case

In Japan, the first case of Coronavirus disease 2019 (COVID-19) was reported on 15th January 2020. In India, on 30th January 2020, the first case of COVID-19 in India was reported in Kerala and the number of reported cases has increased rapidly. The main purpose of this work is to study numerically the epidemic peak for COVID-19 disease along with transmission dynamics of COVID-19 in Japan and India 2020. Taking into account the uncertainty due to the incomplete information about the coronavirus (COVID-19), we have taken the Susceptible-Asymptomatic-Infectious-Recovered (SAIR) compartmental model under fractional order framework for our study. We have also studied the effects of fractional order along with other parameters in transfer dynamics and epidemic peak control for both the countries. An optimal control problem has been studied by controlling social distancing parameter.

scholarly journals Modeling the Consequences of Social Distancing Over Epidemics Spreading in Complex Social Networks: From Link Removal Analysis to SARS-CoV-2 Prevention

2021 ◽  
Vol 9 ◽  
Author(s):  
M. Bellingeri ◽  
M. Turchetto ◽  
D. Bevacqua ◽  
F. Scotognella ◽  
R. Alfieri ◽  
...  
Keyword(s):  
Social Networks ◽  
Temporal Dynamics ◽  
Epidemiological Models ◽  
Connected Component ◽  
Epidemic Spreading ◽  
Social Distancing ◽  
Promising Tool ◽  
The Social ◽  
Network Topologies ◽  
Pharmaceutical Interventions

In this perspective, we describe how the link removal (LR) analysis in social complex networks may be a promising tool to model non-pharmaceutical interventions (NPIs) and social distancing to prevent epidemics spreading. First, we show how the extent of the epidemic spreading and NPIs effectiveness over complex social networks may be evaluated with a static indicator, that is, the classic largest connected component (LCC). Then we explain how coupling the LR analysis and type SIR epidemiological models (EM) provide further information by including the temporal dynamics of the epidemic spreading. This is a promising approach to investigate important aspects of the recent NPIs applied by government to contain SARS-CoV-2, such as modeling the effect of the social distancing severity and timing over different network topologies. Further, implementing different link removal strategies to halt epidemics spreading provides information to individuate more effective NPIs, representing an important tool to offer a rationale sustaining policies to prevent SARS-CoV-2 and similar epidemics.

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