scholarly journals Targeted pandemic containment through identifying local contact network bottlenecks

2021 ◽  
Vol 17 (8) ◽  
pp. e1009351
Author(s):  
Shenghao Yang ◽  
Priyabrata Senapati ◽  
Di Wang ◽  
Chris T. Bauch ◽  
Kimon Fountoulakis
Keyword(s):  
Disease Transmission ◽  
Network Flow ◽  
State Of The Art ◽  
Simulation Models ◽  
Simulation Modelling ◽  
Structural Features ◽  
Contact Network ◽  
Contact Networks ◽  
Edge Betweenness ◽  
Models Of Disease

Decision-making about pandemic mitigation often relies upon simulation modelling. Models of disease transmission through networks of contacts–between individuals or between population centres–are increasingly used for these purposes. Real-world contact networks are rich in structural features that influence infection transmission, such as tightly-knit local communities that are weakly connected to one another. In this paper, we propose a new flow-based edge-betweenness centrality method for detecting bottleneck edges that connect nodes in contact networks. In particular, we utilize convex optimization formulations based on the idea of diffusion with p-norm network flow. Using simulation models of COVID-19 transmission through real network data at both individual and county levels, we demonstrate that targeting bottleneck edges identified by the proposed method reduces the number of infected cases by up to 10% more than state-of-the-art edge-betweenness methods. Furthermore, the proposed method is orders of magnitude faster than existing methods.

Advances from the nexus of animal behaviour and pathogen transmission: new directions and opportunities using contact networks

Behaviour ◽  
2018 ◽  
Vol 155 (7-9) ◽  
pp. 567-583 ◽  
Author(s):  
Stephan T. Leu ◽  
Stephanie S. Godfrey
Keyword(s):  
High Resolution ◽  
Disease Transmission ◽  
Network Models ◽  
Population Level ◽  
Pathogen Transmission ◽  
Molecular Techniques ◽  
Gps Tracking ◽  
Contact Network ◽  
Computational Techniques ◽  
Contact Networks

Abstract Contact network models have enabled significant advances in understanding the influence of behaviour on parasite and pathogen transmission. They are an important tool that links variation in individual behaviour, to epidemiological consequences at the population level. Here, in our introduction to this special issue, we highlight the importance of applying network approaches to disease ecological and epidemiological questions, and how this has provided a much deeper understanding of these research areas. Recent advances in tracking host behaviour (bio-logging: e.g., GPS tracking, barcoding) and tracking pathogens (high-resolution sequencing), as well as methodological advances (multi-layer networks, computational techniques) started producing exciting new insights into disease transmission through contact networks. We discuss some of the exciting directions that the field is taking, some of the challenges, and importantly the opportunities that lie ahead. For instance, we suggest to integrate multiple transmission pathways, multiple pathogens, and in some systems, multiple host species, into the next generation of network models. Corresponding opportunities exist in utilising molecular techniques, such as high-resolution sequencing, to establish causality in network connectivity and disease outcomes. Such novel developments and the continued integration of network tools offers a more complete understanding of pathogen transmission processes, their underlying mechanisms and their evolutionary consequences.

scholarly journals Indirect interactions influence contact network structure and diffusion dynamics

2019 ◽  
Vol 6 (8) ◽  
pp. 190845 ◽  
Author(s):  
Md Shahzamal ◽  
Raja Jurdak ◽  
Bernard Mans ◽  
Frank de Hoog
Keyword(s):  
Disease Transmission ◽  
Infected Individual ◽  
Indirect Interactions ◽  
Decay Rates ◽  
High Rate ◽  
Contact Network ◽  
Interaction Patterns ◽  
Contact Networks ◽  
Diffusion Dynamics ◽  
Airborne Disease

Interaction patterns at the individual level influence the behaviour of diffusion over contact networks. Most of the current diffusion models only consider direct interactions, capable of transferring infectious items among individuals, to build transmission networks of diffusion. However, delayed indirect interactions, where a susceptible individual interacts with infectious items after the infected individual has left the interaction space, can also cause transmission events. We define a diffusion model called the same place different time transmission (SPDT)-based diffusion that considers transmission links for these indirect interactions. Our SPDT model changes the network dynamics where the connectivity among individuals varies with the decay rates of link infectivity. We investigate SPDT diffusion behaviours by simulating airborne disease spreading on data-driven contact networks. The SPDT model significantly increases diffusion dynamics with a high rate of disease transmission. By making the underlying connectivity denser and stronger due to the inclusion of indirect transmissions, SPDT models are more realistic than same place same time transmission (SPST)-based models for the study of various airborne disease outbreaks. Importantly, we also find that the diffusion dynamics including indirect links are not reproducible by the current SPST models based on direct links, even if both SPDT and SPST networks assume the same underlying connectivity. This is because the transmission dynamics of indirect links are different from those of direct links. These outcomes highlight the importance of the indirect links for predicting outbreaks of airborne diseases.

scholarly journals Modeling workplace contact networks: The effects of organizational structure, architecture, and reporting errors on epidemic predictions

2015 ◽  
Vol 3 (3) ◽  
pp. 298-325 ◽  
Author(s):  
GAIL E. POTTER ◽  
TIMO SMIESZEK ◽  
KERSTIN SAILER
Keyword(s):  
Organizational Structure ◽  
Disease Transmission ◽  
Latent Variable ◽  
Respiratory Infections ◽  
Social Contact ◽  
Distance Measures ◽  
Contact Network ◽  
Variable Model ◽  
Contact Networks ◽  
Contact Patterns

AbstractFace-to-face social contacts are potentially important transmission routes for acute respiratory infections, and understanding the contact network can improve our ability to predict, contain, and control epidemics. Although workplaces are important settings for infectious disease transmission, few studies have collected workplace contact data and estimated workplace contact networks. We use contact diaries, architectural distance measures, and institutional structures to estimate social contact networks within a Swiss research institute. Some contact reports were inconsistent, indicating reporting errors. We adjust for this with a latent variable model, jointly estimating the true (unobserved) network of contacts and duration-specific reporting probabilities. We find that contact probability decreases with distance, and that research group membership, role, and shared projects are strongly predictive of contact patterns. Estimated reporting probabilities were low only for 0–5 min contacts. Adjusting for reporting error changed the estimate of the duration distribution, but did not change the estimates of covariate effects and had little effect on epidemic predictions. Our epidemic simulation study indicates that inclusion of network structure based on architectural and organizational structure data can improve the accuracy of epidemic forecasting models.

scholarly journals Predictors of free-roaming domestic dogs' contact network centrality and their relevance for rabies control

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Charlotte Warembourg ◽  
Guillaume Fournié ◽  
Mahamat Fayiz Abakar ◽  
Danilo Alvarez ◽  
Monica Berger-González ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Small World ◽  
Domestic Dogs ◽  
Contact Network ◽  
Potential Contribution ◽  
Dog Ownership ◽  
Contact Patterns ◽  
Rabies Control ◽  
The Social ◽  
Study Sites

AbstractFree roaming domestic dogs (FRDD) are the main vectors for rabies transmission to humans worldwide. To eradicate rabies from a dog population, current recommendations focus on random vaccination with at least 70% coverage. Studies suggest that targeting high-risk subpopulations could reduce the required vaccination coverage, and increase the likelihood of success of elimination campaigns. The centrality of a dog in a contact network can be used as a measure of its potential contribution to disease transmission. Our objectives were to investigate social networks of FRDD in eleven study sites in Chad, Guatemala, Indonesia and Uganda, and to identify characteristics of dogs, and their owners, associated with their centrality in the networks. In all study sites, networks had small-world properties and right-skewed degree distributions, suggesting that vaccinating highly connected dogs would be more effective than random vaccination. Dogs were more connected in rural than urban settings, and the likelihood of contacts was negatively correlated with the distance between dogs’ households. While heterogeneity in dog's connectedness was observed in all networks, factors predicting centrality and likelihood of contacts varied across networks and countries. We therefore hypothesize that the investigated dog and owner characteristics resulted in different contact patterns depending on the social, cultural and economic context. We suggest to invest into understanding of the sociocultural structures impacting dog ownership and thus driving dog ecology, a requirement to assess the potential of targeted vaccination in dog populations.

scholarly journals Identification of effective spreaders in contact networks using dynamical influence

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Ruaridh A. Clark ◽  
Malcolm Macdonald
Keyword(s):  
Disease Transmission ◽  
Average Rate ◽  
Laplacian Matrix ◽  
Disease Spread ◽  
Eigenvector Centrality ◽  
Contact Networks ◽  
Human Contact ◽  
Spread Dynamics ◽  
Definition Of ◽  
High Degree

AbstractContact networks provide insights on disease spread due to the duration of close proximity interactions. For systems governed by consensus dynamics, network structure is key to optimising the spread of information. For disease spread over contact networks, the structure would be expected to be similarly influential. However, metrics that are essentially agnostic to the network’s structure, such as weighted degree (strength) centrality and its variants, perform near-optimally in selecting effective spreaders. These degree-based metrics outperform eigenvector centrality, despite disease spread over a network being a random walk process. This paper improves eigenvector-based spreader selection by introducing the non-linear relationship between contact time and the probability of disease transmission into the assessment of network dynamics. This approximation of disease spread dynamics is achieved by altering the Laplacian matrix, which in turn highlights why nodes with a high degree are such influential disease spreaders. From this approach, a trichotomy emerges on the definition of an effective spreader where, for susceptible-infected simulations, eigenvector-based selections can either optimise the initial rate of infection, the average rate of infection, or produce the fastest time to full infection of the network. Simulated and real-world human contact networks are examined, with insights also drawn on the effective adaptation of ant colony contact networks to reduce pathogen spread and protect the queen ant.

Developments in Rechargeable Mno2Electrodes for Lithium Batteries

1988 ◽  
Vol 135 ◽  
Author(s):  
Michael M Thackeray
Keyword(s):  
Lithium Batteries ◽  
Lithium Battery ◽  
Electrode Materials ◽  
State Of The Art ◽  
Structural Features ◽  
Rechargeable Batteries ◽  
Current State ◽  
Alternative Systems ◽  
Battery Technology ◽  
Made In

AbstractConsiderable efforts are in progress to develop rechargeable batteries as alternative systems to the nickel-cadmium battery. In this regard, several advances have been made in ambient-temperature lithium battery technology, and specifically in the engineering of rechargeable lithium/manganese dioxide cells. This paper reviews the current state of the art in rechargeable Li/MnO2battery technology; particular attention is paid to the structural features of various MnO2electrode materials which influence their electrochemical and cycling behaviour in lithium cells.

scholarly journals Using Semantic Technology To Model Persona For Adaptable Agents

2021 ◽  
Author(s):  
Johannes Nguyen ◽  
Thomas Farrenkopf ◽  
Michael Guckert ◽  
Simon T. Powers ◽  
Neil Urquhart
Keyword(s):  
Road Traffic ◽  
State Of The Art ◽  
Software Agents ◽  
Simulation Models ◽  
Agent Model ◽  
Semantic Technology ◽  
Art Research

In state of the art research a growing interest in the application of agent models for the simulation of road traffic can be observed. Software agents are particularly suitable for the representation of travellers and their goal-oriented behaviour. Although numerous applications based on these types of models are already available, the options for modelling and calibration of the agents as goal-oriented individuals are either simplified to aggregated parameters or associated with overly complex and opaque implementation details. This makes it difficult to reuse available simulation models. In this paper, we demonstrate how the combination of persona models together with semantic methods can be applied to achieve a well-structured agent model that allows for improved reusability.

scholarly journals Zoomqa: Residue-Level Single-Model QA Support Vector Machine Utilizing Sequential and 3D Structural Features

2021 ◽  
Author(s):  
Kyle Hippe ◽  
Cade Lilley ◽  
William Berkenpas ◽  
Kiyomi Kishaba ◽  
Renzhi Cao
Keyword(s):  
Protein Complex ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
State Of The Art ◽  
Chemical Properties ◽  
Structural Features ◽  
Residue Level ◽  
Support Vector ◽  
Single Model

ABSTRACTMotivationThe Estimation of Model Accuracy problem is a cornerstone problem in the field of Bioinformatics. When predictions are made for proteins of which we do not know the native structure, we run into an issue to tell how good a tertiary structure prediction is, especially the protein binding regions, which are useful for drug discovery. Currently, most methods only evaluate the overall quality of a protein decoy, and few can work on residue level and protein complex. Here we introduce ZoomQA, a novel, single-model method for assessing the accuracy of a tertiary protein structure / complex prediction at residue level. ZoomQA differs from others by considering the change in chemical and physical features of a fragment structure (a portion of a protein within a radius r of the target amino acid) as the radius of contact increases. Fourteen physical and chemical properties of amino acids are used to build a comprehensive representation of every residue within a protein and grades their placement within the protein as a whole. Moreover, ZoomQA can evaluate the quality of protein complex, which is unique.ResultsWe benchmark ZoomQA on CASP14, it outperforms other state of the art local QA methods and rivals state of the art QA methods in global prediction metrics. Our experiment shows the efficacy of these new features, and shows our method is able to match the performance of other state-of-the-art methods without the use of homology searching against database or PSSM matrix.Availabilityhttp://[email protected]

scholarly journals Retail store customer flow and COVID-19 transmission

2021 ◽  
Vol 118 (11) ◽  
pp. e2019225118
Author(s):  
Robert A. Shumsky ◽  
Laurens Debo ◽  
Rebecca M. Lebeaux ◽  
Quang P. Nguyen ◽  
Anne G. Hoen
Keyword(s):  
Disease Transmission ◽  
Dominant Mode ◽  
Direct Transmission ◽  
Throughput Rate ◽  
Full Compliance ◽  
Population Prevalence ◽  
Direct Exposure ◽  
Close Proximity ◽  
Mode Of Transmission ◽  
Models Of Disease

We examine how operational changes in customer flows in retail stores affect the rate of COVID-19 transmission. We combine a model of customer movement with two models of disease transmission: direct exposure when two customers are in close proximity and wake exposure when one customer is in the airflow behind another customer. We find that the effectiveness of some operational interventions is sensitive to the primary mode of transmission. Restricting customer flow to one-way movement is highly effective if direct exposure is the dominant mode of transmission. In particular, the rate of direct transmission under full compliance with one-way movement is less than one-third the rate under two-way movement. Directing customers to follow one-way flow, however, is not effective if wake exposure dominates. We find that two other interventions—reducing the speed variance of customers and throughput control—can be effective whether direct or wake transmission is dominant. We also examine the trade-off between customer throughput and the risk of infection to customers, and we show how the optimal throughput rate drops rapidly as the population prevalence rises.

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