scholarly journals Balancing capacity and epidemic spread in the global airline network

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Robert Harper ◽  
Philip Tee
Keyword(s):  
Complex Networks ◽  
Transportation Networks ◽  
Disease Spread ◽  
Epidemic Spread ◽  
Spread Rate ◽  
Transport Networks ◽  
Travel Restrictions ◽  
Airline Network ◽  
Control Disease ◽  
Optimum Balance

AbstractThe structure of complex networks has long been understood to play a role in transmission and spreading phenomena on a graph. Such networks form an important part of the structure of society, including transportation networks. As society fights to control the COVID-19 pandemic, an important question is how to choose the optimum balance between the full opening of transport networks and the control of epidemic spread. In this work we investigate the interplay between network dismantling and epidemic spread rate as a proxy for the imposition of travel restrictions to control disease spread. For network dismantling we focus on the weighted and unweighted forms of metrics that capture the topological and informational structure of the network. Our results indicate that there is benefit to a directed approach to imposing travel restrictions, but we identify that more detailed models of the transport network are necessary for definitive results.

scholarly journals Locating the Epidemic Source in Complex Networks with Sparse Observers

2019 ◽  
Vol 9 (18) ◽  
pp. 3644 ◽  
Author(s):  
Xiang Li ◽  
Xiaojie Wang ◽  
Chengli Zhao ◽  
Xue Zhang ◽  
Dongyun Yi
Keyword(s):  
Complex Networks ◽  
Source Localization ◽  
Disease Spread ◽  
Initial Time ◽  
Epidemic Spread ◽  
Localization Accuracy ◽  
General Network ◽  
Maximum Spanning Tree ◽  
Comparison Algorithms ◽  
Empirical Networks

Epidemic source localization is one of the most meaningful areas of research in complex networks, which helps solve the problem of infectious disease spread. Limited by incomplete information of nodes and inevitable randomness of the spread process, locating the epidemic source becomes a little difficult. In this paper, we propose an efficient algorithm via Bayesian Estimation to locate the epidemic source and find the initial time in complex networks with sparse observers. By modeling the infected time of observers, we put forward a valid epidemic source localization method for tree network and further extend it to the general network via maximum spanning tree. The numerical analyses in synthetic networks and empirical networks show that our algorithm has a higher source localization accuracy than other comparison algorithms. In particular, when the randomness of the spread path enhances, our algorithm has a better performance. We believe that our method can provide an effective reference for epidemic spread and source localization in complex networks.

scholarly journals Lockdowns result in changes in human mobility which may impact the epidemiologic dynamics of SARS-CoV-2

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nishant Kishore ◽  
Rebecca Kahn ◽  
Pamela P. Martinez ◽  
Pablo M. De Salazar ◽  
Ayesha S. Mahmud ◽  
...  
Keyword(s):  
Urban Areas ◽  
Human Mobility ◽  
Unintended Consequences ◽  
Disease Spread ◽  
Epidemic Spread ◽  
Long Distance ◽  
Mobility Data ◽  
The World ◽  
Travel Restrictions ◽  
Long Distance Movement

AbstractIn response to the SARS-CoV-2 pandemic, unprecedented travel restrictions and stay-at-home orders were enacted around the world. Ultimately, the public’s response to announcements of lockdowns—defined as restrictions on both local movement or long distance travel—will determine how effective these kinds of interventions are. Here, we evaluate the effects of lockdowns on human mobility and simulate how these changes may affect epidemic spread by analyzing aggregated mobility data from mobile phones. We show that in 2020 following lockdown announcements but prior to their implementation, both local and long distance movement increased in multiple locations, and urban-to-rural migration was observed around the world. To examine how these behavioral responses to lockdown policies may contribute to epidemic spread, we developed a simple agent-based spatial model. Our model shows that this increased movement has the potential to increase seeding of the epidemic in less urban areas, which could undermine the goal of the lockdown in preventing disease spread. Lockdowns play a key role in reducing contacts and controlling outbreaks, but appropriate messaging surrounding their announcement and careful evaluation of changes in mobility are needed to mitigate the possible unintended consequences.

scholarly journals Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Meng-Chun Chang ◽  
Rebecca Kahn ◽  
Yu-An Li ◽  
Cheng-Sheng Lee ◽  
Caroline O. Buckee ◽  
...  
Keyword(s):  
Disease Surveillance ◽  
Initial Conditions ◽  
Human Mobility ◽  
Human Movement ◽  
Disease Spread ◽  
Spatial Spread ◽  
Movement Data ◽  
Intercity Travel ◽  
Travel Restrictions ◽  
The Impact

Abstract Background As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or linked to imported cases. Methods In collaboration with Facebook Data for Good, we characterized changes in movement patterns in Taiwan since February 2020, and built metapopulation models that incorporate human movement data to identify the high risk areas of disease spread and assess the potential effects of local travel restrictions in Taiwan. Results We found that mobility changed with the number of local cases in Taiwan in the past few months. For each city, we identified the most highly connected areas that may serve as sources of importation during an outbreak. We showed that the risk of an outbreak in Taiwan is enhanced if initial infections occur around holidays. Intracity travel reductions have a higher impact on the risk of an outbreak than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact. Conclusions To prepare for the potential spread within Taiwan, we utilized Facebook’s aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. We developed an interactive application that allows users to vary inputs and assumptions and shows the spatial spread of the disease and the impact of intercity and intracity travel reduction under different initial conditions. Our results can be used readily if local transmission occurs in Taiwan after relaxation of border control, providing important insights into future disease surveillance and policies for travel restrictions.

Further studies on epidemiological factors influencing control of banana bunchy top disease and evaluation of control measures by computer simulation

1987 ◽  
Vol 38 (2) ◽  
pp. 373
Author(s):  
RN Allen
Keyword(s):  
Disease Control ◽  
Control Measure ◽  
Significant Loss ◽  
Control Measures ◽  
Disease Spread ◽  
Disease Symptoms ◽  
Control Disease ◽  
Banana Leaves ◽  
Time Required ◽  
Apparently Healthy

The basic infection rate of bunchy top disease in established bananas averaged 0.0342 new infections per infectious plant per day, but varied seasonally with a maximum in summer. The mean distance of spread for the aphid vector was 15.2 m. The latent period was 59.8 days and correlated with the time required for the growth of 3.7 new banana leaves. A microcomputer program was written to simulate spread of banana bunchy top disease in space and time. In the absence of disease control, disease spread from an initial primary infection in July or January to 124 or 153 infected plants, respectively, in one year. When disease control was maintained by removing diseased plants whenever the number of infected plants exceeded a given threshold, the numbers of diseased plants detected each inspection were positively correlated with the infection threshold, but the numbers of inspections required to maintain control increased markedly as the infection threshold was decreased. A practice of removing apparently healthy plants within 5 m of plants detected with bunchy top disease symptoms in five or more leaves was found to locate about 30% of the remaining undetected infected plants when disease was first detected in a plantation. However, its use as a routine control measure was ineffective in reducing the number of inspections required to maintain control or in reducing the risk of disease spreading to adjoining plantations. Removal of apparently healthy plants within 5 m had some bearing on disease control when applied around plants with disease symptoms in two leaves or less, but also caused a significant loss of healthy plants.

scholarly journals Changing travel patterns in China during the early stages of the COVID-19 pandemic

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Hamish Gibbs ◽  
◽  
Yang Liu ◽  
Carl A. B. Pearson ◽  
Christopher I. Jarvis ◽  
...  
Keyword(s):  
Public Health ◽  
Human Mobility ◽  
Transportation Network ◽  
Mainland China ◽  
Disease Spread ◽  
Travel Patterns ◽  
Network Analyses ◽  
Early Stages ◽  
Travel Restrictions ◽  
Spatio Temporal

Abstract Understanding changes in human mobility in the early stages of the COVID-19 pandemic is crucial for assessing the impacts of travel restrictions designed to reduce disease spread. Here, relying on data from mainland China, we investigate the spatio-temporal characteristics of human mobility between 1st January and 1st March 2020, and discuss their public health implications. An outbound travel surge from Wuhan before travel restrictions were implemented was also observed across China due to the Lunar New Year, indicating that holiday travel may have played a larger role in mobility changes compared to impending travel restrictions. Holiday travel also shifted healthcare pressure related to COVID-19 towards locations with lower healthcare capacity. Network analyses showed no sign of major changes in the transportation network after Lunar New Year. Changes observed were temporary and did not lead to structural reorganisation of the transportation network during the study period.

scholarly journals Model for the growth of the world airline network

2016 ◽  
Vol 27 (12) ◽  
pp. 1650141 ◽  
Author(s):  
T. Verma ◽  
N. A. M. Araújo ◽  
J. Nagler ◽  
J. S. Andrade ◽  
H. J. Herrmann
Keyword(s):  
Correlation Function ◽  
Growth Model ◽  
Physical Distance ◽  
Transport Networks ◽  
Model Network ◽  
The World ◽  
Airline Networks ◽  
Airline Network ◽  
The Difference

We propose a probabilistic growth model for transport networks which employs a balance between popularity of nodes and the physical distance between nodes. By comparing the degree of each node in the model network and the World Airline Network (WAN), we observe that the difference between the two is minimized for [Formula: see text]. Interestingly, this is the value obtained for the node–node correlation function in the WAN. This suggests that our model explains quite well the growth of airline networks.

scholarly journals Modeling the Novel Coronavirus (SARS-CoV-2) Outbreak in Sicily, Italy

2020 ◽  
Vol 17 (14) ◽  
pp. 4964 ◽  
Author(s):  
Andrea Maugeri ◽  
Martina Barchitta ◽  
Sebastiano Battiato ◽  
Antonella Agodi
Keyword(s):  
Transmission Rate ◽  
Control Measures ◽  
Transmission Dynamics ◽  
The Novel ◽  
Epidemic Spread ◽  
Transmission Rates ◽  
Contact Precautions ◽  
Travel Restrictions ◽  
Novel Coronavirus ◽  
Reported Data

Italy was the first country in Europe which imposed control measures of travel restrictions, quarantine and contact precautions to tackle the epidemic spread of the novel coronavirus (SARS-CoV-2) in all its regions. While such efforts are still ongoing, uncertainties regarding SARS-CoV-2 transmissibility and ascertainment of cases make it difficult to evaluate the effectiveness of restrictions. Here, we employed a Susceptible-Exposed-Infectious-Recovered-Dead (SEIRD) model to assess SARS-CoV-2 transmission dynamics, working on the number of reported patients in intensive care unit (ICU) and deaths in Sicily (Italy), from 24 February to 13 April. Overall, we obtained a good fit between estimated and reported data, with a fraction of unreported SARS-CoV-2 cases (18.4%; 95%CI = 0–34.0%) before 10 March lockdown. Interestingly, we estimated that transmission rate in the community was reduced by 32% (95%CI = 23–42%) after the first set of restrictions, and by 80% (95%CI = 70–89%) after those adopted on 23 March. Thus, our estimates delineated the characteristics of SARS-CoV2 epidemic before restrictions taking into account unreported data. Moreover, our findings suggested that transmission rates were reduced after the adoption of control measures. However, we cannot evaluate whether part of this reduction might be attributable to other unmeasured factors, and hence further research and more accurate data are needed to understand the extent to which restrictions contributed to the epidemic control.

scholarly journals Epigrass: a tool to study disease spread in complex networks.

2007 ◽  
Author(s):  
Flávio Codeço Coelho ◽  
Claudia Codeco ◽  
Oswaldo Cruz
Keyword(s):  
Complex Networks ◽  
Disease Spread

scholarly journals Static and dynamic properties of selected stochastic processes on complex networks

2020 ◽  
Author(s):  
Jeremi Ochab
Keyword(s):  
Random Walk ◽  
Complex Networks ◽  
Random Walks ◽  
Dynamic Properties ◽  
Finite Size ◽  
Disease Spread ◽  
Maximal Entropy ◽  
Centrality Measures ◽  
Topological Features ◽  
The Subject

This thesis is concerned with the properties of a number of selected processes taking place on complex networks and the way they are affected by structure and evolution of the networks. What is meant here by 'complex networks' is the graph-theoretical representations and models of various empirical networks (e.g., the Internet network) which contain both random and deterministic structures, and are characterised among others by the small-world phenomenon, power-law vertex degree distributions, or modular and hierarchical structure. The mathematical models of the processes taking place on these networks include percolation and random walks we utilise.The results presented in the thesis are based on five thematically coherent papers. The subject of the first paper is calculating thresholds for epidemic outbreaks on dynamic networks, where the disease spread is modelled by percolation. In the paper, known analytical solutions for the epidemic thresholds were extended to a class of dynamically evolving networks; additionally, the effects of finite size of the network on the magnitude of the epidemic were studied numerically. The subject of the second and third paper is the static and dynamic properties of two diametrically opposed random walks on model highly symmetric deterministic graphs. Specifically, we analytically and numerically find the stationary states and relaxation times of the ordinary, diffusive random walk and the maximal-entropy random walk. The results provide insight into localisation of random walks or their trapping in isolated regions of networks. Finally, in the fourth and fifth paper, we examine the utility of random walks in detecting topological features of complex networks. In particular, we study properties of the centrality measures (roughly speaking, the ranking of vertices) based on random walks, as well as we conduct a systematic comparative study of random-walk based methods of detecting modular structure of networks.These studies thus aimed at specific problems in modelling and analysis of complex networks, including theoretical examination of the ways the behaviour of random processes intertwines with the structure of complex networks.

scholarly journals Modelling and analysis of transportation networks using complex networks: Poland case study

2015 ◽  
Vol 36 (4) ◽  
pp. 55-65 ◽  
Author(s):  
Zbigniew Tarapata
Keyword(s):  
Complex Networks ◽  
Complex Network ◽  
Transportation Networks ◽  
Small World ◽  
Scale Free ◽  
Empirical Results

In the paper a theoretical bases and empirical results deal with analysis and modelling of transportation networks in Poland using complex networks have been presented. Properties of complex networks (Scale Free and Small World) and network's characteristic measures have been described. In this context, results of empirical researches connected with characteristics of passenger air links network, express railway links network (EuroCity and InterCity) and expressways/highways network in Poland have been given. For passenger air links network in Poland results are compared with the same networks in USA, China, India, Italy and Spain. In the conclusion some suggestions, observations and perspective dealing with complex network in transportation networks have been presented.

Sign in / Sign up

Export Citation Format

Share Document