scispace - formally typeset
Search or ask a question
Journal ArticleDOI

Preventable H5N1 avian influenza epidemics in the British poultry industry network exhibit characteristic scales.

06 Apr 2010-Journal of the Royal Society Interface (The Royal Society)-Vol. 7, Iss: 45, pp 695-701
TL;DR: H5N1 avian influenza transmission probabilities and containment strategies, here modelled on the British poultry industry network, show that infection dynamics can additionally express characteristic scales, and hotspots can make more effective inoculation targets.
Abstract: Epidemics are frequently simulated on redundantly wired contact networks, which have many more links between sites than are minimally required to connect all. Consequently, the modelled pathogen can travel numerous alternative routes, complicating effective containment strategies. These networks have moreover been found to exhibit ‘scale-free’ properties and percolation, suggesting resilience to damage. However, realistic H5N1 avian influenza transmission probabilities and containment strategies, here modelled on the British poultry industry network, show that infection dynamics can additionally express characteristic scales. These system-preferred scales constitute small areas within an observed power law distribution that exhibit a lesser slope than the power law itself, indicating a slightly increased relative likelihood. These characteristic scales are here produced by a network-pervading intranet of so-called hotspot sites that propagate large epidemics below the percolation threshold. This intranet is, however, extremely vulnerable; targeted inoculation of a mere 3–6% (depending on incorporated biosecurity measures) of the British poultry industry network prevents large and moderate H5N1 outbreaks completely, offering an order of magnitude improvement over previously advocated strategies affecting the most highly connected ‘hub’ sites. In other words, hotspots and hubs are separate functional entities that do not necessarily coincide, and hotspots can make more effective inoculation targets. Given the ubiquity and relevance of networks (epidemics, Internet, power grids, protein interaction), recognition of this spreading regime elsewhere would suggest a similar disproportionate sensitivity to such surgical interventions.

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI
TL;DR: A new approach to design effective targeted intervention strategies to mitigate and control the propagation of infections across heterogeneous contact networks is introduced, using a newly developed individual-level deterministic Susceptible-Infectious-Susceptible (SIS) epidemiological model.

24 citations

Journal ArticleDOI
31 Jan 2014-PLOS ONE
TL;DR: The hypothesis that increasing economic efficiency in the domestic ostrich industry in South Africa made the system more vulnerable to outbreak of Highly Pathogenic Avian Influenza (H5N2), and the results indicated that as time progressed, the network became increasingly vulnerable to pathogen outbreaks.
Abstract: Background: The focus of management in many complex systems is shifting towards facilitation, adaptation, building resilience, and reducing vulnerability. Resilience management requires the development and application of general heuristics and methods for tracking changes in both resilience and vulnerability. We explored the emergence of vulnerability in the South African domestic ostrich industry, an animal production system which typically involves 3-4 movements of each bird during its lifetime. This system has experienced several disease outbreaks, and the aim of this study was to investigate whether these movements have contributed to the vulnerability of this system to large disease outbreaks. Methodology/Principal Findings: The ostrich production system requires numerous movements of birds between different farm types associated with growth (i.e. Hatchery to juvenile rearing farm to adult rearing farm). We used 5 years of movement records between 2005 and 2011 prior to an outbreak of Highly Pathogenic Avian Influenza (H5N2). These data were analyzed using a network analysis in which the farms were represented as nodes and the movements of birds as links. We tested the hypothesis that increasing economic efficiency in the domestic ostrich industry in South Africa made the system more vulnerable to outbreak of Highly Pathogenic Avian Influenza (H5N2). Our results indicated that as time progressed, the network became increasingly vulnerable to pathogen outbreaks. The farms that became infected during the outbreak displayed network qualities, such as significantly higher connectivity and centrality, which predisposed them to be more vulnerable to disease outbreak. Conclusions/ Significance: Taken in the context of previous research, our results provide strong support for the application of network analysis to track vulnerability, while also providing useful practical implications for system monitoring and management.

22 citations


Cites background from "Preventable H5N1 avian influenza ep..."

  • ...Seasonal variation is not uncommon in domestic production systems, with comparable fluctuations observed in the British livestock [22,23] and poultry [25,26] industries....

    [...]

Book ChapterDOI
TL;DR: In this chapter, some concepts in disease modelling will be introduced, the relevance of selected network phenomena discussed, and results from real data and their relationship to network analyses summarised are summarised.
Abstract: Heterogeneous population structure can have a profound effect on infectious disease dynamics, and is particularly important when investigating “tactical” disease control questions. At times, the nature of the network involved in the transmission of the pathogen (bacteria, virus, macro-parasite, etc.) appears to be clear; however, the nature of the network involved is dependent on the scale (e.g. within-host, between-host, or between-population), the nature of the contact, which ranges from the highly specific (e.g. sexual acts or needle sharing at the person-to-person level) to almost completely non-specific (e.g. aerosol transmission, often over long distances as can occur with the highly infectious livestock pathogen foot-and-mouth disease virus—FMDv—at the farm-to-farm level, e.g. Schley et al. in J. R. Soc. Interface 6:455–462, 2008), and the timescale of interest (e.g. at the scale of the individual, the typical infectious period of the host). Theoretical approaches to examining the implications of particular network structures on disease transmission have provided critical insight; however, a greater challenge is the integration of network approaches with data on real population structures. In this chapter, some concepts in disease modelling will be introduced, the relevance of selected network phenomena discussed, and then results from real data and their relationship to network analyses summarised. These include examinations of the patterns of air traffic and its relation to the spread of SARS in 2003 (Colizza et al. in BMC Med., 2007; Hufnagel et al. in Proc. Natl. Acad. Sci. USA 101:15124–15129, 2004), the use of the extensively documented Great Britain livestock movements network (Green et al. in J. Theor. Biol. 239:289–297, 2008; Robinson et al. in J. R. Soc. Interface 4:669–674, 2007; Vernon and Keeling in Proc. R. Soc. Lond. B, Biol. Sci. 276:469–476, 2009) and the growing interest in combining contact structure data with phylogenetics to identify real contact patterns as they directly relate to diseases of interest (Cottam et al. in PLoS Pathogens 4:1000050, 2007; Hughes et al. in PLoS Pathogens 5:1000590, 2009).

16 citations


Cites background from "Preventable H5N1 avian influenza ep..."

  • ...Multi-scale percolation as described here has also been analysed in several real networks [39, 41]....

    [...]

Journal ArticleDOI
TL;DR: The susceptibility of the English and Welsh fish farming and fisheries industry to emergent diseases is assessed using a stochastic simulation model that considers reactive, proactive, and hybrid methods of control which correspond to a mixture of policy and the ease of disease detection.

15 citations


Cites background from "Preventable H5N1 avian influenza ep..."

  • ...…and undirected links, the effects of long-range connections (e.g., small-world networks), and emergent properties due to clustering, community association, or fragmentation of network parts (Keeling, 1999; Sharkey et al., 2006; Green et al., 2009; Munro and Gregory, 2009; Jonkers et al., 2010)....

    [...]

  • ..., small-world networks), and emergent properties due to clustering, community association, or fragmentation of network parts (Keeling, 1999; Sharkey et al., 2006; Green et al., 2009; Munro and Gregory, 2009; Jonkers et al., 2010)....

    [...]

Journal ArticleDOI
30 Jul 2013-PLOS ONE
TL;DR: Markovian susceptible-infectious-susceptible (SIS) dynamics on finite strongly connected networks is considered, applicable to several sexually transmitted diseases and computer viruses, and it is shown that the probability of invasion from any given individual is equal to the (probabilistic) endemic prevalence, following successful invasion, at the individual.
Abstract: Understanding models which represent the invasion of network-based systems by infectious agents can give important insights into many real-world situations, including the prevention and control of infectious diseases and computer viruses. Here we consider Markovian susceptible-infectious-susceptible (SIS) dynamics on finite strongly connected networks, applicable to several sexually transmitted diseases and computer viruses. In this context, a theoretical definition of endemic prevalence is easily obtained via the quasi-stationary distribution (QSD). By representing the model as a percolation process and utilising the property of duality, we also provide a theoretical definition of invasion probability. We then show that, for undirected networks, the probability of invasion from any given individual is equal to the (probabilistic) endemic prevalence, following successful invasion, at the individual (we also provide a relationship for the directed case). The total (fractional) endemic prevalence in the population is thus equal to the average invasion probability (across all individuals). Consequently, for such systems, the regions or individuals already supporting a high level of infection are likely to be the source of a successful invasion by another infectious agent. This could be used to inform targeted interventions when there is a threat from an emerging infectious disease.

15 citations

References
More filters
Journal ArticleDOI
TL;DR: The spatial dynamics of measles, for which detailed spatiotemporal data are available, may serve as a useful test of ideas applicable to other epidemiological and ecological systems with an important spatial component.
Abstract: This paper explores the relations between persistence and dynamics in measles epidemics. Most current models, including the stochastic seasonally forced and age-structured models examined here, fail to capture simultaneously the observed dynamics and persistence characteristics of epidemics in large urban populations before vaccination. Summary measures of persistence and trienniality allow us to compare epidemics in England, New York and Copenhagen with results of non-spatial and spatial stochastic models. Spatial (metapopulation) structure allow persistence and triennial dynamics to coexist i this class of models. The spatial dynamics of measles, for which detailed spatiotemporal data are available, may serve as a useful test of ideas applicable to other epidemiological and ecological systems with an important spatial component.

255 citations


"Preventable H5N1 avian influenza ep..." refers background in this paper

  • ...Others offer hope in identifying the most highly connected sites (hubs) as the most vulnerable part of such systems (Albert et al. 2000; Callaway et al. 2000; May & Lloyd 2001; Song et al. 2005; Jeger et al. 2007)....

    [...]

Journal ArticleDOI
TL;DR: In this paper, the authors used the TSIR model to predict the long-term dynamics of measles and the balance between noise and determinism, as a function of population size.
Abstract: Two key linked questions in population dynamics are the relative importance of noise vs. density-dependent nonlinearities and the limits on temporal predictability of population abundance. We propose that childhood microparasitic infections, notably mea- sles, provide an unusually suitable empirical and theoretical test bed for addressing these issues. We base our analysis on a new mechanistic time series model for measles, the TSIR model, which captures the mechanistic essence of epidemic dynamics. The model, and parameter estimates based on short-term fits to prevaccination measles time series for 60 towns and cities in England and Wales, is introduced in a companion paper. Here, we explore how well the model predicts the long-term dynamics of measles and the balance between noise and determinism, as a function of population size. The TSIR model captures the basic dynamical features of the long-term pattern of measles epidemics in large cities remarkably well (based on time and frequency domain analyses). In particular, the model illustrates the impact of secular increases in birth rates, which cause a transition from biennial to annual dynamics. The model also captures the observed increase in epidemic irregularity with decreasing population size and the onset of local extinction below a critical community size. Decreased host population size is shown to be associated with an increased impact of demographic stochasticity. The interaction between nonlinearity and noise is explored using local Lyapunov exponents (LLE). These testify to the high level of stability of the biennial attractor in large cities. Irregularities are due to the limit cycle evolving with changing human birth rates and not due to complex dynamics. The geometry of the dynamics (sign and magnitude of the LLEs across phase space) is similar in the cities and the smaller urban areas. The qualitative difference in dynamics between small and large host communities is that demographic and extinction-recolonization stochasticities are much more influential in the former. The regional dynamics can therefore only be understood in terms of a core-satellite metapopulation structure for this host-enemy system. We also make a preliminary exploration of the model's ability to predict the dynamic consequences of measles vaccination.

250 citations


"Preventable H5N1 avian influenza ep..." refers background in this paper

  • ...networks, and stressed the bimodal outbreak response that typifies percolation (ca 5% of susceptibles infected below the threshold, and a giant component of infected sites appearing above it, analogous to a spreading forest fire) (Rhodes & Anderson 1996; Grenfell et al. 2002)....

    [...]

  • ...…The Royal Society networks, and stressed the bimodal outbreak response that typifies percolation (ca 5% of susceptibles infected below the threshold, and a giant component of infected sites appearing above it, analogous to a spreading forest fire) (Rhodes & Anderson 1996; Grenfell et al. 2002)....

    [...]

Journal ArticleDOI
TL;DR: A percolation threshold is identified in the structure of the livestock network, indicating that, while there is little possibility of a national epidemic of FMD in winter when the catastrophic 2001 epidemic began, there remains a risk in late summer or early autumn.
Abstract: Using a novel interpretation of dynamic networks, we analyse the network of livestock movements in Great Britain in order to determine the risk of a large epidemic of foot-and-mouth disease (FMD). This network is exceptionally well characterized, as there are legal requirements that the date, source, destination and number of animals be recorded and held on central databases. We identify a percolation threshold in the structure of the livestock network, indicating that, while there is little possibility of a national epidemic of FMD in winter when the catastrophic 2001 epidemic began, there remains a risk in late summer or early autumn. These predictions are corroborated by a non-parametric simulation in which the movements of livestock in 2003 and 2004 are replayed as they occurred. Despite the risk, we show that the network displays small-world properties which can be exploited to target surveillance and control and drastically reduce this risk.

231 citations


"Preventable H5N1 avian influenza ep..." refers background in this paper

  • ...However, our current study of the dynamics predicated upon a highly realistic network reveals additional features that also merit attention (Kao et al. 2006)....

    [...]

Journal ArticleDOI
TL;DR: It is suggested that heterogeneity in the epidemic will affect the phylogenetic distance distribution of the disease-causing organisms and the small world lattices are investigated, and the effects are even stronger.
Abstract: We consider a spatial model related to bond percolation for the spread of a disease that includes variation in the susceptibility to infection. We work on a lattice with random bond strengths and show that with strong heterogeneity, i.e. a wide range of variation of susceptibility, patchiness in the spread of the epidemic is very likely, and the criterion for epidemic outbreak depends strongly on the heterogeneity. These results are qualitatively different from those of standard models in epidemiology, but correspond to real effects. We suggest that heterogeneity in the epidemic will affect the phylogenetic distance distribution of the disease-causing organisms. We also investigate small world lattices, and show that the effects mentioned above are even stronger.

214 citations

01 Jan 2007
TL;DR: In this article, the authors analyzed the network of livestock movements in Great Britain in order to determine the risk of a large epidemic of foot-and-mouth disease (FMD).
Abstract: Using a novel interpretation of dynamic networks, we analyse the network of livestock movements in Great Britain in order to determine the risk of a large epidemic of foot-and-mouth disease (FMD). This network is exceptionally well characterized, as there are legal requirements that the date, source, destination and number of animals be recorded and held on central databases. We identify a percolation threshold in the structure of the livestock network, indicating that, while there is little possibility of a national epidemic of FMD in winter when the catastrophic 2001 epidemic began, there remains a risk in late summer or early autumn. These predictions are corroborated by a non-parametric simulation in which the movements of livestock in 2003 and 2004 are replayed as they occurred. Despite the risk, we show that the network displays small-world properties which can be exploited to target surveillance and control and drastically reduce this risk.

198 citations

Related Papers (5)