scholarly journals Generative models of network dynamics provide insight into the effects of trade on endemic livestock disease

2021 ◽  
Vol 8 (3) ◽  
pp. 201715
Author(s):  
Martin A. Knight ◽  
Piran C. L. White ◽  
Michael R. Hutchings ◽  
Ross S. Davidson ◽  
Glenn Marion
Keyword(s):  
Disease Transmission ◽  
Network Dynamics ◽  
Generative Models ◽  
National Scale ◽  
Trade Networks ◽  
Scale Free ◽  
Livestock Disease ◽  
Endemic Diseases ◽  
Partnership Network ◽  
Individual Farm

We develop and apply analytically tractable generative models of livestock movements at national scale. These go beyond current models through mechanistic modelling of heterogeneous trade partnership network dynamics and the trade events that occur on them. Linking resulting animal movements to disease transmission between farms yields analytical expressions for the basic reproduction number R 0 . We show how these novel modelling tools enable systems approaches to disease control, using R 0 to explore impacts of changes in trading practices on between-farm prevalence levels. Using the Scottish cattle trade network as a case study, we show our approach captures critical complexities of real-world trade networks at the national scale for a broad range of endemic diseases. Changes in trading patterns that minimize disruption to business by maintaining in-flow of animals for each individual farm reduce R 0 , with the largest reductions for diseases that are most challenging to eradicate. Incentivizing high-risk farms to adopt such changes exploits ‘scale-free’ properties of the system and is likely to be particularly effective in reducing national livestock disease burden and incursion risk. Encouragingly, gains made by such targeted modification of trade practices scale much more favourably than comparably targeted improvements to more commonly adopted farm-level biosecurity.

scholarly journals Scale free is not rare in international trade networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Linqing Liu ◽  
Mengyun Shen ◽  
Chang Tan
Keyword(s):  
International Trade ◽  
Preferential Attachment ◽  
Developed Countries ◽  
Total Trade ◽  
Trade Networks ◽  
Scale Free ◽  
Weighted Networks ◽  
Free Exploration ◽  
Technology Products ◽  
Attachment Mechanism

AbstractFailing to consider the strong correlations between weights and topological properties in capacity-weighted networks renders test results on the scale-free property unreliable. According to the preferential attachment mechanism, existing high-degree nodes normally attract new nodes. However, in capacity-weighted networks, the weights of existing edges increase as the network grows. We propose an optimized simplification method and apply it to international trade networks. Our study covers more than 1200 product categories annually from 1995 to 2018. We find that, on average, 38%, 38% and 69% of product networks in export, import and total trade are scale-free. Furthermore, the scale-free characteristics differ depending on the technology. Counter to expectations, the exports of high-technology products are distributed worldwide rather than concentrated in a few developed countries. Our research extends the scale-free exploration of capacity-weighted networks and demonstrates that choosing appropriate filtering methods can clarify the properties of complex networks.

scholarly journals Disease transmission by cannibalism: rare event or common occurrence?

2007 ◽  
Vol 274 (1614) ◽  
pp. 1205-1210 ◽  
Author(s):  
Volker H.W Rudolf ◽  
Janis Antonovics
Keyword(s):  
Disease Transmission ◽  
Rare Event ◽  
Disease Spread ◽  
Necessary Condition ◽  
Transmission Route ◽  
Review Of The Literature ◽  
Common Occurrence ◽  
Endemic Diseases ◽  
Pathogen Dynamics ◽  
Transmission Modes

Cannibalism has been documented as a possible disease transmission route in several species, including humans. However, the dynamics resulting from this type of disease transmission are not well understood. Using a theoretical model, we explore how cannibalism (i.e. killing and consumption of dead conspecifics) and intraspecific necrophagy (i.e. consumption of dead conspecifics) affect host–pathogen dynamics. We show that group cannibalism, i.e. shared consumption of victims, is a necessary condition for disease spread by cannibalism in the absence of alternative transmission modes. Thus, endemic diseases transmitted predominantly by cannibalism are likely to be rare, except in social organisms that share conspecific prey. These results are consistent with a review of the literature showing that diseases transmitted by cannibalism are infrequent in animals, even though both cannibalism and trophic transmission are very common.

RANDOM WALKS IN HETEROGENEOUS WEIGHTED PSEUDO-FRACTAL WEBS WITH THE SAME WEIGHT SEQUENCE

Fractals ◽  
2019 ◽  
Vol 27 (06) ◽  
pp. 1950089
Author(s):  
CHANGMING XING ◽  
LIN YANG
Keyword(s):  
Random Walks ◽  
Network Dynamics ◽  
Theoretical Research ◽  
Graph Models ◽  
Scale Free ◽  
Weight Sequence ◽  
Link Weight ◽  
Size Number ◽  
Graph Size ◽  
The Impact

Intuitively, link weight could affect the dynamics of the network. However, the theoretical research on the effects of link weight on network dynamics is still rare. In this paper, we present two heterogeneous weighted pseudo-fractal webs controlled by two weight parameters [Formula: see text] and [Formula: see text] ([Formula: see text]). Both graph models are scale-free deterministic graphs, and they have the same weight sequence when [Formula: see text] and [Formula: see text] are fixed. Based on their self-similar graph structure, we study the effect of heterogeneous weight on the random walks in graph with scale-free characteristics. We obtain analytically the average trapping time (ATT) for biased random walks in graphs with a trap located at a fixed node. Analyzing and comparing the obtained solutions, we find that in the large graph limit, the ATT for both graph models all grow as a power function of the graph size (number of nodes) with the exponent [Formula: see text] dependents on the ratio of parameters [Formula: see text] and [Formula: see text], but their exponents [Formula: see text] are not the same, one gets the minimum when [Formula: see text], while the other gets the maximum. Furthermore, the average weighted shortest path length (AWSPL) to the trap is calculated for both graph models, respectively. We show that when the graph size tends to infinity, their AWSPL grows unbounded with the graph size for most parameters. We hope that these results could help people understand the impact of heterogeneous weight on network dynamics.

scholarly journals Growing scale-free simplices

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Kiriil Kovalenko ◽  
Irene Sendiña-Nadal ◽  
Nagi Khalil ◽  
Alex Dainiak ◽  
Daniil Musatov ◽  
...  
Keyword(s):  
Degree Distribution ◽  
General Scheme ◽  
Simplicial Complexes ◽  
Generative Models ◽  
Analytical Control ◽  
Scaling Exponents ◽  
Scale Free ◽  
Pairwise Interactions ◽  
Order Structures ◽  
Insight Into

AbstractThe past two decades have seen significant successes in our understanding of networked systems, from the mapping of real-world networks to the establishment of generative models recovering their observed macroscopic patterns. These advances, however, are restricted to pairwise interactions and provide limited insight into higher-order structures. Such multi-component interactions can only be grasped through simplicial complexes, which have recently found applications in social, technological, and biological contexts. Here we introduce a model to grow simplicial complexes of order two, i.e., nodes, links, and triangles, that can be straightforwardly extended to structures containing hyperedges of larger order. Specifically, through a combination of preferential and/or nonpreferential attachment mechanisms, the model constructs networks with a scale-free degree distribution and an either bounded or scale-free generalized degree distribution. We arrive at a highly general scheme with analytical control of the scaling exponents to construct ensembles of synthetic complexes displaying desired statistical properties.

scholarly journals Growing Scale-Free Simplices

2020 ◽  
Author(s):  
Kiriil Kovalenko ◽  
Irene Sendina-Nadal ◽  
Nagi Khalil ◽  
Alex Dainak ◽  
Daniil Musatov ◽  
...  
Keyword(s):  
Degree Distribution ◽  
Preferential Attachment ◽  
General Scheme ◽  
Simplicial Complexes ◽  
Generative Models ◽  
Scaling Exponents ◽  
Scale Free ◽  
Pairwise Interactions ◽  
Order Structures ◽  
Insight Into

Abstract The past two decades have seen significant successes in our understanding of networked systems, from the mapping of real-world networks to the establishment of generative models recovering their observed macroscopic patterns. These advances, however, are restricted to pairwise interactions and provide limited insight into higher-order structures. Such multi-component interactions can only be grasped through simplicial complexes, which have recently found applications in social, technological and biological contexts. Here we introduce, study, and characterize a model to grow simplicial complexes of order two, i.e. nodes, links and triangles. Specifically, through a combination of preferential and/or non preferential attachment mechanisms, the model constructs networks with a scale-free degree distribution and an either bounded or scale-free generalized degree distribution. Allowing to analytically control the scaling exponents we arrive at a highly general scheme by which one is able to construct ensembles of synthetic complexes displaying desired statistical properties.

scholarly journals Contatos intradomiciliares: aspectos epidemiológicos e sua importância para eliminação da hanseníase

2020 ◽  
Vol 10 (32) ◽  
pp. 11-23
Author(s):  
André Wilian Lozano ◽  
José Martins Pinto Neto ◽  
Luana Laís Femina ◽  
Rogério Rodrigo Ramos ◽  
Susilene Maria Tonelli Nardi ◽  
...  
Keyword(s):  
Public Health ◽  
Disease Transmission ◽  
Index Case ◽  
Public Health Problem ◽  
Household Contacts ◽  
Endemic Diseases ◽  
Care Processes ◽  
The World ◽  
Leprosy Patients ◽  
Epidemiological Profile

O domicílio é apontado como importante ambiente de transmissão da hanseníase. Identificar e descrever os fatores sociodemográficos e epidemiológicos dos contatos intradomiciliares de casos de hanseníase, numa cidade hiperendêmica. Pesquisa descritiva e transversal, com 146 contatos. A maioria (83,6%) residia de 10 ou mais anos no município; relatou que não fizeram exame neurodermatológico (69,1%). 124 (84,9%) contatos possuíam uma cicatriz da vacina BCG-id e desses, 65 (52,4%) não receberam nenhuma dose após a descoberta do caso. Foram 28 casos novos intradomiciliares que adoeceram após o diagnóstico do caso índice. Deve-se implementar ações de melhoria quanto a vigilância de contatos de hanseníase com monitoramento dos resultados dos processos assistenciais que incluam ações específicas de controle dos comunicantes intradomiciliares, o qual consideramos como um dos pilares estratégicos para a quebra da cadeia epidemiológica da doençaDescritores: Hanseníase, Epidemiologia, Transmissão de Doença Infecciosa, Habitação. Intradomiciliary contacts: epidemiological aspects and their importance for the elimination of leprosyAbstract: Leprosy is a public health problem in Brazil and is second on the list of endemic diseases in the world. The household has been identified as an important environment for the transmission of leprosy. To identify and describe the clinical and epidemiological profile of leprosy patients and the sociodemographic and epidemiological profile of their household contacts. Descriptive, transversal research with 146 households. The majority lived in the municipality for 10 years or more; reported that they had not taken the dermato-neurological examination. 124 (84.9%) contacts had a BCG-id vaccine scar and of these, 65 (52.4%) received no dose after the case was discovered. There were 28 new household cases that became ill after the diagnosis of the index case. Improvement actions regarding leprosy contacts should be implemented with monitoring of the results of care processes, including actions and specifications for document control with household documents, or which considerations are necessaryDescriptors: Leprosy, Epidemiology, Disease Transmission Infectious, Household. Contactos intradomiciliarios: aspectos epidemiológicos y su importancia para la eliminación de la lepraResumen: El hogar se considera un importante entorno de transmisión de lepra. identificar y describir los factores sociodemográficos y epidemiológicos de los contactos domésticos en casos de lepra en una ciudad hiper-endémica. Investigación descriptiva y transversal, con 146 contactos. La mayoría (83,6%) vivió durante 10 años o más en el municipio; informaron que no se sometieron a un examen neurodermatológico (69,1%). 124 (84,9%) contactos tenían una cicatriz de vacuna BCG-id y de estos, 65 (52,4%) no recibieron ninguna dosis después del descubrimiento del caso. Hubo 28 nuevos casos en el hogar que enfermaron después del diagnóstico del caso índice. Se deben implementar acciones de mejora en relación con la vigilancia de los contactos de lepra con el monitoreo de los resultados de los procesos de atención que incluyen acciones específicas para el control de los contactos domésticos, que consideramos como uno de los pilares estratégicos para romper la cadena epidemiológica de la enfermedad.Descriptores: Lepra, epidemiología, Transmisión de Enfermedad Infecciosa, Vivienda.

DEMOGRAPHICS INDUCE EXTINCTION OF DISEASE IN AN SIS MODEL BASED ON CONDITIONAL MARKOV CHAIN

2017 ◽  
Vol 25 (01) ◽  
pp. 145-171 ◽  
Author(s):  
XIAOFENG LUO ◽  
LILI CHANG ◽  
ZHEN JIN
Keyword(s):  
Markov Chain ◽  
Disease Transmission ◽  
Numerical Solutions ◽  
Deterministic Model ◽  
Moment Generating Function ◽  
Network Evolution ◽  
Stochastic Simulations ◽  
Disease Spread ◽  
Sis Model ◽  
Scale Free

Demographics have significant effects on disease spread in populations and the topological evolution of the underlying networks that represent the populations. In the context of network-based epidemic modeling, Markov chain-based approach and pairwise approximation are two powerful tools — the former can capture stochastic effects of disease transmission dynamics and the latter can characterize the dynamical correlations in each pair of connected individuals. However, to our best knowledge, the study on epidemic spreading in networks relying on these two techniques is still lacking. To fill this gap, in this paper, a deterministic pairwise susceptible–infected–susceptible (SIS) epidemic model with demographics on complex networks with arbitrary degree distributions is studied based on a continuous time conditional Markov chain. This deterministic model is rigorously derived — using the moment generating function — from the Kolmogorov differential equations for the evolution of individuals and pairs. It is found that demographics will induce the extinction of the disease by reducing the basic reproduction number or lowering the epidemic prevalence after the disease prevails. Moreover, due to the demographical effects, the resulting network tends to a homogeneous network with a degree distribution similar to Poisson distribution, irrespective of the initial network structure. Additionally, we find excellent agreement between numerical solutions and individual-based stochastic simulations using both Erdös–Renyi (ER) random and Barabási–Albert (BA) scale-free initial networks. Our results may provide new insights on the understanding of the influence of demographics on epidemic dynamics and network evolution.

The Dynamics on Single Networks

2018 ◽  
Author(s):  
Ginestra Bianconi
Keyword(s):  
Complex Networks ◽  
Diffusion Processes ◽  
Network Dynamics ◽  
Dynamical Behaviour ◽  
Emergent Properties ◽  
Epidemic Spreading ◽  
Scale Free ◽  
Free Network ◽  
The Rich ◽  
And Function

This chapter provides the relevant background on the network dynamics of complex networks formed by just one layer (single networks). Emergent properties of network dynamics are characterized using the framework of phase transitions. The major results on robustness of complex networks, percolation theory and epidemic spreading are presented, revealing the rich interplay between network structure and function. In this context particular emphasis is given to the implications of the scale-free network topology on these dynamical processes. Diffusion processes and synchronization and controllability are characterized on networks, revealing the relevance of spectral properties and peripheral nodes for determining their dynamical behaviour.

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