Quarantine in a multi-species epidemic model with spatial dynamics

Arino, Julien; Jordan, Richard; Driessche, P. van den

doi:10.1016/j.mbs.2005.09.002

Cited by 126 publications

(99 citation statements)

References 36 publications

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“…11 Although this restriction may limit the realism of our model, it allows us to focus on the information effect for a mild infectious disease, e.g., flu. It is only under an extremely serious epidemic situation that the measures of strong quarantine or isolation would be implemented, 16 which will induce changes in the social network.…”

Section: Introductionmentioning

confidence: 99%

The impact of awareness on epidemic spreading in networks

Small

et al. 2012

Chaos: An Interdisciplinary Journal of Nonlinear Science

217

157

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We explore the impact of awareness on epidemic spreading through a population represented by a scale-free network. Using a network mean-field approach, a mathematical model for epidemic spreading with awareness reactions is proposed and analyzed. We focus on the role of three forms of awareness including local, global, and contact awareness. By theoretical analysis and simulation, we show that the global awareness cannot decrease the likelihood of an epidemic outbreak while both the local awareness and the contact awareness can. Also, the influence degree of the local awareness on disease dynamics is closely related with the contact awareness. The interplay between awareness and epidemic dynamics in networks has recently achieved much attention. The human responses to disease outbreaks can result in the reduction of susceptibility to infection, which in turn, can affect epidemic dynamics. So an epidemic model should include such factors. This issue has been studied from the perspective of awareness reactions. However, the impact of individual awareness is not entirely understood thus far because of its variety and complexity. In this work, we build a continuous mean-field (MF) model to study the impact of the three forms of awareness on the epidemic spreading in a finite scale-free (SF) network: contact awareness that increases with individual contact number; local awareness that increases with the fraction of infected contacts; and global awareness that increases with the overall disease prevalence. Theoretical analysis and simulation shows that the effect of these different types of awareness can be clearly classified. Both the contact awareness and the local awareness can raise the epidemic threshold, while the global awareness can only decrease the epidemic prevalence. These results also tell us that individual awareness contributes toward the inhibition of epidemic transmission.

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Section: Introductionmentioning

confidence: 99%

The impact of awareness on epidemic spreading in networks

Small

et al. 2012

Chaos: An Interdisciplinary Journal of Nonlinear Science

217

157

View full text Add to dashboard Cite

show abstract

“…The framework we outline here builds upon and extends existing work to model spatial spread of animal disease [14][15][16][17][18][19][20]. Our work highlights the important and interacting roles of geography, and the spatial aspects of host diversity, host distribution, long and short distance movement, human-livestock interactions, and possible interventions.…”

Section: Introductionmentioning

confidence: 98%

A Flexible Spatial Framework for Modeling Spread of Pathogens in Animals with Biosurveillance and Disease Control Applications

LaBute

McMahon

Brown

et al. 2014

IJGI

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Biosurveillance activities focus on acquiring and analyzing epidemiological and biological data to interpret unfolding events and predict outcomes in infectious disease outbreaks. We describe a mathematical modeling framework based on geographically aligned data sources and with appropriate flexibility that partitions the modeling of disease spread into two distinct but coupled levels. A top-level stochastic simulation is defined on a network with nodes representing user-configurable geospatial -patches‖. Intra-patch disease spread is treated with differential equations that assume uniform mixing within the patch. We use U.S. county-level aggregated data on animal populations and parameters from the literature to simulate epidemic spread of two strikingly different animal diseases agents: foot-and-mouth disease and highly pathogenic avian influenza. Results demonstrate the capability of this framework to leverage low-fidelity data while producing meaningful output to inform biosurveillance and disease control measures. For example, we show that the possible magnitude of an outbreak is sensitive to the starting location of the outbreak, OPEN ACCESS ISPRS Int. J. Geo-Inf. 2014, 3 639 highlighting the strong geographic dependence of livestock and poultry infectious disease epidemics and the usefulness of effective biosurveillance policy. The ability to compare different diseases and host populations across the geographic landscape is important for decision support applications and for assessing the impact of surveillance, detection, and mitigation protocols.

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“…While the qualitative properties of metapopulation (patchy) epidemic models have been widely studied in the literature, evaluating the intervention strategies in these models has received less attention (see, for instance, [2,3,6,11,14,18,19] and the references therein). It is particularly challenging to understand the dependence of movement between populations on the reproduction number [2,4,5]. Our procedure allows for the design of intervention strategies that target exclusively the movement of particular groups in the metapopulation SIRS model.…”

Section: Introductionmentioning

confidence: 99%

A new approach for designing disease intervention strategies in metapopulation models

Knipl

2015

Journal of Biological Dynamics

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We describe a new approach for investigating the control strategies of compartmental disease transmission models. The method rests on the construction of various alternative next-generation matrices, and makes use of the type reproduction number and the target reproduction number. A general metapopulation SIRS (susceptible-infected-recovered-susceptible) model is given to illustrate the application of the method. Such model is useful to study a wide variety of diseases where the population is distributed over geographically separated regions. Considering various control measures such as vaccination, social distancing, and travel restrictions, the procedure allows us to precisely describe in terms of the model parameters, how control methods should be implemented in the SIRS model to ensure disease elimination. In particular, we characterize cases where changing only the travel rates between the regions is sufficient to prevent an outbreak. ARTICLE HISTORY

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Quarantine in a multi-species epidemic model with spatial dynamics

Cited by 126 publications

References 36 publications

The impact of awareness on epidemic spreading in networks

The impact of awareness on epidemic spreading in networks

A Flexible Spatial Framework for Modeling Spread of Pathogens in Animals with Biosurveillance and Disease Control Applications

A new approach for designing disease intervention strategies in metapopulation models

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