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.

scholarly journals Using network properties to predict disease dynamics on human contact networks

2011 ◽  
Vol 278 (1724) ◽  
pp. 3544-3550 ◽  
Author(s):  
Gregory M. Ames ◽  
Dylan B. George ◽  
Christian P. Hampson ◽  
Andrew R. Kanarek ◽  
Cayla D. McBee ◽  
...  
Keyword(s):  
Degree Distribution ◽  
Stochastic Simulations ◽  
Disease Spread ◽  
Contact Structures ◽  
Contact Network ◽  
Contact Networks ◽  
Human Contact ◽  
Differential Equation Models ◽  
Network Properties ◽  
Intermediate Density

Recent studies have increasingly turned to graph theory to model more realistic contact structures that characterize disease spread. Because of the computational demands of these methods, many researchers have sought to use measures of network structure to modify analytically tractable differential equation models. Several of these studies have focused on the degree distribution of the contact network as the basis for their modifications. We show that although degree distribution is sufficient to predict disease behaviour on very sparse or very dense human contact networks, for intermediate density networks we must include information on clustering and path length to accurately predict disease behaviour. Using these three metrics, we were able to explain more than 98 per cent of the variation in endemic disease levels in our stochastic simulations.

scholarly journals Infectious disease transmission and contact networks in wildlife and livestock

2015 ◽  
Vol 370 (1669) ◽  
pp. 20140107 ◽  
Author(s):  
Meggan E. Craft
Keyword(s):  
Infectious Disease ◽  
Disease Transmission ◽  
Wild Animal ◽  
Disease Spread ◽  
Farmed Fish ◽  
Infectious Disease Transmission ◽  
Network Modelling ◽  
Flexible Tool ◽  
Contact Networks ◽  
Contact Data

The use of social and contact networks to answer basic and applied questions about infectious disease transmission in wildlife and livestock is receiving increased attention. Through social network analysis, we understand that wild animal and livestock populations, including farmed fish and poultry, often have a heterogeneous contact structure owing to social structure or trade networks. Network modelling is a flexible tool used to capture the heterogeneous contacts of a population in order to test hypotheses about the mechanisms of disease transmission, simulate and predict disease spread, and test disease control strategies. This review highlights how to use animal contact data, including social networks, for network modelling, and emphasizes that researchers should have a pathogen of interest in mind before collecting or using contact data. This paper describes the rising popularity of network approaches for understanding transmission dynamics in wild animal and livestock populations; discusses the common mismatch between contact networks as measured in animal behaviour and relevant parasites to match those networks; and highlights knowledge gaps in how to collect and analyse contact data. Opportunities for the future include increased attention to experiments, pathogen genetic markers and novel computational tools.

scholarly journals Cleanliness in context: reconciling hygiene with a modern microbial perspective

2016 ◽  
Author(s):  
Roo Vandegrift ◽  
Ashley C. Bateman ◽  
Kyla N. Siemens ◽  
May Nguyen ◽  
Jessica L. Green ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Community Context ◽  
Microbial Load ◽  
Disease Spread ◽  
Practice Research ◽  
Future Research ◽  
Skin Microbiota ◽  
Residual Moisture ◽  
Definition Of ◽  
Hand Drying

AbstractThe concept of hygiene is rooted in the relationship between cleanliness and the maintenance of good health. Since the widespread acceptance of the germ theory of disease, hygiene has become increasingly conflated with that of sterilization. Recent research on microbial ecology is demonstrating that humans have intimate and evolutionarily significant relationships with a diverse assemblage of microorganisms (ourmicrobiota). Human skin is home to a diverse, skin habitat specific community of microorganisms; this includes members that exist across the ecological spectrum from pathogen through commensal to mutualist. Most evidence suggests that the skin microbiota is likely of direct benefit to the host, and only rarely exhibits pathogenicity. This complex ecological context suggests that the conception of hygiene as a unilateral reduction or removal of microbes has outlived its usefulness. As such, we suggest the explicit definition of hygiene as ‘those actions and practices that reduce the spread or transmission of pathogenic microorganisms, and thus reduce the incidence of disease’. To examine the implications of this definition, we review the literature related to hand drying as an aspect of hand hygienic practice. Research on hand drying generally focuses on ‘hygienic efficacy’, a concept not typically defined explicitly, but nearly always including alterations to bulk microbial load. The corresponding literature is differentiable into two divisions: research supporting the use of forced air dryers, which typically includes effectiveness of drying as an aspect of hygienic efficacy; and research supporting the use of paper towels, which typically includes risk of aerosolized spread of microbes from hands as an aspect of hygienic efficacy. Utilizing a definition of hygiene that explicitly relies onreduction in disease spreadrather than alterations to bulk microbial load would address concerns raised on both sides of the debate. Future research should take advantage of cultivation-independent techniques, working to bridge the gap between the two existing divisions of research by using health outcomes (such as the spread of disease) as dependent variables, taking into account the microbial community context of the skin microbiota, and focusing on understanding the relative contribution of bioaerosols and residual moisture to the risk of disease transmission.

scholarly journals Revealing mechanisms of infectious disease transmission through empirical contact networks

2017 ◽  
Author(s):  
Pratha Sah ◽  
Michael Otterstatter ◽  
Stephan T. Leu ◽  
Sivan Leviyang ◽  
Shweta Bansal
Keyword(s):  
Infectious Disease ◽  
Disease Transmission ◽  
Network Models ◽  
Pathogen Transmission ◽  
Disease Spread ◽  
Contact Networks ◽  
Transmission Mechanisms ◽  
Disease Information ◽  
Crithidia Bombi ◽  
Transmission Pathways

AbstractThe spread of pathogens fundamentally depends on the underlying contacts between individuals. Modeling infectious disease dynamics through contact networks is sometimes challenging, however, due to a limited understanding of pathogen transmission routes and infectivity. We developed a novel tool, INoDS (Identifying Network models of infectious Disease Spread) that estimates the predictive power of empirical contact networks to explain observed patterns of infectious disease spread. We show that our method is robust to partially sampled contact networks, incomplete disease information, and enables hypothesis testing on transmission mechanisms. We demonstrate the applicability of our method in two host-pathogen systems: Crithidia bombi in bumble bee colonies and Salmonella in wild Australian sleepy lizard populations. The performance of INoDS in synthetic and complex empirical systems highlights its role in identifying transmission pathways of novel or neglected pathogens, as an alternative approach to laboratory transmission experiments, and overcoming common data-collection constraints.

scholarly journals The network of sheep movements within Great Britain: network properties and their implications for infectious disease spread

2006 ◽  
Vol 3 (10) ◽  
pp. 669-677 ◽  
Author(s):  
Istvan Z Kiss ◽  
Darren M Green ◽  
Rowland R Kao
Keyword(s):  
Great Britain ◽  
Disease Transmission ◽  
Foot And Mouth Disease ◽  
Small World ◽  
Disease Spread ◽  
Contact Networks ◽  
Geographical Regions ◽  
Network Properties ◽  
Path Lengths ◽  
Intense Activity

During the 2001 foot and mouth disease epidemic in the UK, initial dissemination of the disease to widespread geographical regions was attributed to livestock movement, especially of sheep. In response, recording schemes to provide accurate data describing the movement of large livestock in Great Britain (GB) were introduced. Using these data, we reconstruct directed contact networks within the sheep industry and identify key epidemiological properties of these networks. There is clear seasonality in sheep movements, with a peak of intense activity in August and September and an associated high risk of a large epidemic. The high correlation between the in and out degree of nodes favours disease transmission. However, the contact networks were largely dissasortative: highly connected nodes mostly connect to nodes with few contacts, effectively slowing the spread of disease. This is a result of bipartite-like network properties, with most links occurring between highly active markets and less active farms. When comparing sheep movement networks (SMNs) to randomly generated networks with the same number of nodes and node degrees, despite structural differences (such as disassortativity and higher frequency of even path lengths in the SMNs), the characteristic path lengths within the SMNs are close to values computed from the corresponding random networks, showing that SMNs have ‘small-world’-like properties. Using the network properties, we show that targeted biosecurity or surveillance at highly connected nodes would be highly effective in preventing a large and widespread epidemic.

scholarly journals Livestock movement informs the risk of disease spread in traditional production systems in East Africa

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Divine Ekwem ◽  
Thomas A. Morrison ◽  
Richard Reeve ◽  
Jessica Enright ◽  
Joram Buza ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Production Systems ◽  
Control Strategies ◽  
Herd Size ◽  
Transmission Risk ◽  
Disease Spread ◽  
Transmission Potential ◽  
Spatial And Temporal Scales ◽  
Transmission Distance ◽  
Risk Of Disease

AbstractIn Africa, livestock are important to local and national economies, but their productivity is constrained by infectious diseases. Comprehensive information on livestock movements and contacts is required to devise appropriate disease control strategies; yet, understanding contact risk in systems where herds mix extensively, and where different pathogens can be transmitted at different spatial and temporal scales, remains a major challenge. We deployed Global Positioning System collars on cattle in 52 herds in a traditional agropastoral system in western Serengeti, Tanzania, to understand fine-scale movements and between-herd contacts, and to identify locations of greatest interaction between herds. We examined contact across spatiotemporal scales relevant to different disease transmission scenarios. Daily cattle movements increased with herd size and rainfall. Generally, contact between herds was greatest away from households, during periods with low rainfall and in locations close to dipping points. We demonstrate how movements and contacts affect the risk of disease spread. For example, transmission risk is relatively sensitive to the survival time of different pathogens in the environment, and less sensitive to transmission distance, at least over the range of the spatiotemporal definitions of contacts that we explored. We identify times and locations of greatest disease transmission potential and that could be targeted through tailored control strategies.

scholarly journals Genomic Tackling of Human Satellite DNA: Breaking Barriers through Time

2021 ◽  
Vol 22 (9) ◽  
pp. 4707
Author(s):  
Mariana Lopes ◽  
Sandra Louzada ◽  
Margarida Gama-Carvalho ◽  
Raquel Chaves
Keyword(s):  
Human Genome ◽  
Satellite Dna ◽  
Repetitive Sequences ◽  
Nucleotide Composition ◽  
Genomic Component ◽  
Genomic Studies ◽  
Human Genomic ◽  
Definition Of ◽  
High Degree

(Peri)centromeric repetitive sequences and, more specifically, satellite DNA (satDNA) sequences, constitute a major human genomic component. SatDNA sequences can vary on a large number of features, including nucleotide composition, complexity, and abundance. Several satDNA families have been identified and characterized in the human genome through time, albeit at different speeds. Human satDNA families present a high degree of sub-variability, leading to the definition of various subfamilies with different organization and clustered localization. Evolution of satDNA analysis has enabled the progressive characterization of satDNA features. Despite recent advances in the sequencing of centromeric arrays, comprehensive genomic studies to assess their variability are still required to provide accurate and proportional representation of satDNA (peri)centromeric/acrocentric short arm sequences. Approaches combining multiple techniques have been successfully applied and seem to be the path to follow for generating integrated knowledge in the promising field of human satDNA biology.

Comparative efficacy of five different rep-PCR methods to discriminate Escherichia coli populations in aquatic environments

2008 ◽  
Vol 58 (3) ◽  
pp. 537-547 ◽  
Author(s):  
B. R. Mohapatra ◽  
A. Mazumder
Keyword(s):  
Cluster Analysis ◽  
Disease Transmission ◽  
Management Practices ◽  
Gastrointestinal Disease ◽  
Function Analysis ◽  
Average Rate ◽  
Aquatic Environments ◽  
Correct Classification ◽  
Comparative Efficacy ◽  
E Coli

Development of efficient techniques to discriminate the sources of E. coli in aquatic environments is essential to improve the surveillance of fecal pollution indicators, to develop strategies to identify the sources of fecal contamination, and to implement appropriate management practices to minimize gastrointestinal disease transmission. In this study the robustness of five different rep-PCR methods, such as REP-PCR, ERIC-PCR, ERIC2-PCR, BOX-PCR and (GTG)5-PCR were evaluated to discriminate 271 E. coli strains isolated from two watersheds (Lakelse Lake and Okanagan Lake) located in British Columbia, Canada. Cluster analysis of (GTG)5-PCR, BOX-PCR, REP-PCR, ERIC-PCR and ERIC2-PCR profiles of 271 E. coli revealed 43 clusters, 35 clusters, 28 clusters, 23 clusters and 14 clusters, respectively. The discriminant analysis of rep-PCR genomic fingerprints of 271 E. coli isolates yielded an average rate of correct classification (watershed-specific) of 86.8%, 82.3%, 78.4%, 72.6% and 55.8% for (GTG)5-PCR, BOX-PCR, REP-PCR, ERIC-PCR and ERIC2-PCR, respectively. Based on the results of cluster analysis and discriminant function analysis, (GTG)5-PCR was found to be the most robust molecular tool for differentiation of E. coli populations in aquatic environments.

The Use of Photogrammetry in Piping Design

1983 ◽  
Vol 197 (2) ◽  
pp. 125-138 ◽  
Author(s):  
P A Bracewell ◽  
U R Klement
Keyword(s):  
Information Retrieval ◽  
Mathematical Formulation ◽  
Three Dimensional ◽  
Cost Effective ◽  
Process Industry ◽  
Process Plant ◽  
Definition Of ◽  
High Degree ◽  
Positional Data

Piping design for ‘revamp’ projects in the process industry requires the retrieval of large amounts of ‘as-built’ data from existing process plant installations. Positional data with a high degree of accuracy are required. Photogrammetry, the science of measurement from photographs, was identified in Imperial Chemical Industries plc (ICI) as a suitable tool for information retrieval. The mathematical formulation enabling the definition of three-dimensional positions from photographic information is described. The process of using ICI's photogrammetric system for the definition of complete objects such as structures and pipes is illustrated. The need for specialized photogrammetric software for design purposes is explained. A case study describing how the photogrammetric system has been applied is described and graphical outputs from this exercise are shown. It is concluded that this particular photogrammetric system has proved to be a cost effective and accurate tool for the retrieval of ‘as-built’ information.

scholarly journals Sheep scab spatial distribution: the roles of transmission pathways

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Emily Joanne Nixon ◽  
Ellen Brooks-Pollock ◽  
Richard Wall
Keyword(s):  
Disease Transmission ◽  
Movement Control ◽  
Cost Effective ◽  
Infected Sheep ◽  
Disease Spread ◽  
Psoroptes Ovis ◽  
Long Distance ◽  
Sheep Scab ◽  
The Uk ◽  
The Impact

Abstract Background Ovine psoroptic mange (sheep scab) is a highly pathogenic contagious infection caused by the mite Psoroptes ovis. Following 21 years in which scab was eradicated in the UK, it was inadvertently reintroduced in 1972 and, despite the implementation of a range of control methods, its prevalence increased steadily thereafter. Recent reports of resistance to macrocyclic lactone treatments may further exacerbate control problems. A better understanding of the factors that facilitate its transmission are required to allow improved management of this disease. Transmission of infection occurs within and between contiguous sheep farms via infected sheep-to-sheep or sheep–environment contact and through long-distance movements of infected sheep, such as through markets. Methods A stochastic metapopulation model was used to investigate the impact of different transmission routes on the spatial pattern of outbreaks. A range of model scenarios were considered following the initial infection of a cluster of highly connected contiguous farms. Results Scab spreads between clusters of neighbouring contiguous farms after introduction but when long-distance movements are excluded, infection then self-limits spatially at boundaries where farm connectivity is low. Inclusion of long-distance movements is required to generate the national patterns of disease spread observed. Conclusions Preventing the movement of scab infested sheep through sales and markets is essential for any national management programme. If effective movement control can be implemented, regional control in geographic areas where farm densities are high would allow more focussed cost-effective scab management. Graphical Abstract

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