Network structure-based interventions on spatial spread of epidemics in metapopulation networks

Wang, Bing; Gou, Min; Guo, Yike; Tanaka, Gouhei; Han, Yuexing

doi:10.1103/physreve.102.062306

Cited by 21 publications

(6 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To introduce the human heterogeneous contacts, the epidemics in networks model (or reaction-diffusion models on meta population networks) have played an essential role in journals with a physics focus [13,12,54,47]. Nevertheless, the model inference, fit or selection, uses highly computing-intensive numeric methods such as MCMC or particle filtering based on Monte Carlo simulations.…”

Section: Introductionmentioning

confidence: 99%

Use of mobile phone sensing data to estimate residence and mobility times in urban patches during the COVID-19 epidemic: The case of the 2020 outbreak in Hermosillo, Mexico

Ramírez-Ramírez

Montoya

Espinoza

et al. 2022

Preprint

View full text Add to dashboard Cite

It is often necessary to introduce the main characteristics of population mobility dynamics to model critical social phenomena such as the economy, violence, transmission of information, or infectious diseases. In this work, we focus on modeling and inferring urban population mobility using the geospatial data of its inhabitants. The objective is to estimate mobility and times inhabitants spend in the areas of interest, such as zip codes and census geographical areas. The proposed method uses the Brownian bridge model for animal movement in ecology. We illustrate its possible applications using mobile phone GPS data in 2020 from the city of Hermosillo, Sonora, in Mexico. We incorporate the estimated residence-mobility matrix into a multi-patch compartmental SEIR model to assess the effect of mobility changes due to governmental interventions.

show abstract

Section: Introductionmentioning

confidence: 99%

Use of mobile phone sensing data to estimate residence and mobility times in urban patches during the COVID-19 epidemic: The case of the 2020 outbreak in Hermosillo, Mexico

Ramírez-Ramírez

Montoya

Espinoza

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The infection occurs by the interaction of individuals within a subpopulation and the diffusion corresponds to their migration along the links between subpopulations, which is called reaction-diffusion (RD) process 31,34,35 . Some studies have explored the effects such as mobility rate and non-uniform intervention for suppressing epidemic [36][37][38] , whereas factors such as medical resources inevitably playing the uttermost role in suppressing epidemic have been ignored. As the outbreak of COVID-19 in Wuhan, China, the government promptly deployed medical resources from other cities to Wuhan, and consequently controlled the epidemic.…”

Section: Introductionmentioning

confidence: 99%

Intervention of resource allocation strategies on spatial spread of epidemic

Zhang

Han

Gou

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Medical resources are crucial in mitigating the epidemic, especially during pandemics such as the ongoing COVID-19. Thereby, reasonable resource deployment inevitably plays a significant role in suppressing the epidemic under limited resources. When an epidemic breaks out, people can produce resources for self-protection, or donate resources to help others. That is, the exchange of resources also affects the transmission between individuals, thus, altering the epidemic dynamics. To understand factors on resource deployment and the interplay between resource and transmission we construct a metapopulation network model with resource allocation. Our results indicate actively or promptly donating resources is not helpful to suppress the epidemic under both homogeneous population distribution (HOD) and heterogeneous population distribution (HED). Besides, strengthening the speed of resource production can significantly increase the recovery rate so that reduce the final outbreak size. These results may provide policy guidance towards epidemic containment.

show abstract

“…In real network systems (NS), processes that need to be stopped quickly are often unfolding: the spread of epidemics, forest fires, agricultural pests, computer viruses, invasion processes [1][2][3][4][5], etc. To prevent the spread of such phenomena by the system, the theory of complex networks usually uses methods of percolation theory [6], which consist in sequential removal of a certain part of network nodes and connections until the percolation cluster breaks up into unconnected components, one of which contains a threat.…”

Section: Introductionmentioning

confidence: 99%

Isolated Zones and Granulation of Complex Network Systems

Polishchuk

2021

2021 IEEE 12th International Conference on Electronics and Information Technologies (ELIT)

View full text Add to dashboard Cite

The problem of blocking certain areas of network systems and their boundary case, which is the granulation of network to a set of isolated zones, is investigated in the article. The losses that await the system due to blocking of its separate components are determined, and method for finding alternative ways of flow motion bypassing the isolated zone of network are proposed. The granulation process of the network system is reflected as a temporal network and the losses that await the system during the deployment of such processes are calculated.

show abstract

Network structure-based interventions on spatial spread of epidemics in metapopulation networks

Cited by 21 publications

References 32 publications

Use of mobile phone sensing data to estimate residence and mobility times in urban patches during the COVID-19 epidemic: The case of the 2020 outbreak in Hermosillo, Mexico

Use of mobile phone sensing data to estimate residence and mobility times in urban patches during the COVID-19 epidemic: The case of the 2020 outbreak in Hermosillo, Mexico

Intervention of resource allocation strategies on spatial spread of epidemic

Isolated Zones and Granulation of Complex Network Systems

Contact Info

Product

Resources

About