Epidemic spreading in heterogeneous networks with recurrent mobility patterns

2020 ◽  
Vol 102 (2) ◽  
Author(s):  
Liang Feng ◽  
Qianchuan Zhao ◽  
Cangqi Zhou
Keyword(s):  
Heterogeneous Networks ◽  
Mobility Patterns ◽  
Epidemic Spreading

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 Interplay between population density and mobility in determining the spread of epidemics in cities

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Surendra Hazarie ◽  
David Soriano-Paños ◽  
Alex Arenas ◽  
Jesús Gómez-Gardeñes ◽  
Gourab Ghoshal
Keyword(s):  
Population Density ◽  
Urban Areas ◽  
Human Mobility ◽  
The United States ◽  
Mitigation Strategies ◽  
Mobility Patterns ◽  
Epidemic Spreading ◽  
Optimal Control Strategy ◽  
Global Trend ◽  
Data Driven Approach

AbstractThe increasing agglomeration of people in dense urban areas coupled with the existence of efficient modes of transportation connecting such centers, make cities particularly vulnerable to the spread of epidemics. Here we develop a data-driven approach combines with a meta-population modeling to capture the interplay between population density, mobility and epidemic spreading. We study 163 cities, chosen from four different continents, and report a global trend where the epidemic risk induced by human mobility increases consistently in those cities where mobility flows are predominantly between high population density centers. We apply our framework to the spread of SARS-CoV-2 in the United States, providing a plausible explanation for the observed heterogeneity in the spreading process across cities. Based on this insight, we propose realistic mitigation strategies (less severe than lockdowns), based on modifying the mobility in cities. Our results suggest that an optimal control strategy involves an asymmetric policy that restricts flows entering the most vulnerable areas but allowing residents to continue their usual mobility patterns.

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

EPIDEMIC SPREADING AND GLOBAL STABILITY OF A NEW SIS MODEL WITH DELAY ON HETEROGENEOUS NETWORKS

2015 ◽  
Vol 23 (04) ◽  
pp. 1550029 ◽  
Author(s):  
HUIYAN KANG ◽  
YIJUN LOU ◽  
GUANRONG CHEN ◽  
SEN CHU ◽  
XINCHU FU
Keyword(s):  
Global Stability ◽  
Heterogeneous Networks ◽  
Lyapunov Functional ◽  
Functional Differential Equations ◽  
Epidemic Spreading ◽  
Epidemic Threshold ◽  
Sis Model ◽  
Vector Population ◽  
Functional Differential ◽  
Disease Free

In this paper, we study a susceptible-infected-susceptible (SIS) model with time delay on complex heterogeneous networks. Here, the delay describes the incubation period in the vector population. We calculate the epidemic threshold by using a Lyapunov functional and some analytical methods, and find that adding delay increases the epidemic threshold. Then, we prove the global stability of disease-free and endemic equilibria by using the theory of functional differential equations. Furthermore, we show numerically that the epidemic threshold of the new model may change along with other factors, such as the infectivity function, the heterogeneity of the network, and the degrees of nodes. Finally, we find numerically that the delay can affect the convergence speed at which the disease reaches equilibria.

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