An Embedded Multiscale Modelling to Guide Control and Elimination of Paratuberculosis in Ruminants

In recent years, multiscale modelling approach has begun to receive an overwhelming appreciation as an appropriate technique to characterize the complexity of infectious disease systems. In this study, we develop an embedded multiscale model of paratuberculosis in ruminants at host level that integrates the within-host scale and the between-host. A key feature of embedded multiscale models developed at host level of organization of an infectious disease system is that the within-host scale and the between-host scale influence each other in a reciprocal (i.e., both) way through superinfection, that is, through repeated infection before the host recovers from the initial infectious episode. This key feature is demonstrated in this study through a multiscale model of paratuberculosis in ruminants. The results of this study, through numerical analysis of the multiscale model, show that superinfection influences the dynamics of paratuberculosis only at the start of the infection, while the MAP bacteria replication continuously influences paratuberculosis dynamics throughout the infection until the host recovers from the initial infectious episode. This is largely because the replication of MAP bacteria at the within-host scale sustains the dynamics of paratuberculosis at this scale domain. We further use the embedded multiscale model developed in this study to evaluate the comparative effectiveness of paratuberculosis health interventions that influence the disease dynamics at different scales from efficacy data.

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The Replication-Transmission Relativity Theory for Multiscale Modelling of Infectious Disease Systems

Scientific Reports ◽

10.1038/s41598-019-52820-3 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 2

Author(s):

Winston Garira

Keyword(s):

Infectious Disease ◽

Relativistic Theory ◽

Multiscale Model ◽

Scientific Basis ◽

Multiscale Modelling ◽

Relativity Theory ◽

Disease Dynamics ◽

Reciprocal Influence ◽

The Relationship ◽

Modelling Methods

Abstract It is our contention that for multiscale modelling of infectious disease systems to evolve and expand in scope, it needs to be founded on a theory. Such a theory would improve our ability to describe infectious disease systems in terms of their scales and levels of organization, and their inter-relationships. In this article we present a relativistic theory for multiscale modelling of infectious disease systems, that can be considered as an extension of the relativity principle in physics, called the replication-transmission relativity theory. This replication-transmission relativity theory states that at any level of organization of an infectious disease system there is no privileged/absolute scale which would determine, disease dynamics, only interactions between the microscale and macroscale. Such a relativistic theory provides a scientific basis for a systems level description of infectious disease systems using multiscale modelling methods. The central idea of this relativistic theory is that at every level of organization of an infectious disease system, the reciprocal influence between the microscale and the macroscale establishes a pathogen replication-transmission multiscale cycle. We distinguish two kinds of reciprocal influence between the microscale and the macroscale based on systematic differences in their conditions of relevancy. Evidence for the validity of the replication-transmission relativity theory is presented using a multiscale model of hookworm infection that is developed at host level when the relationship between the microscale and the macroscale is described by one of the forms of reciprocal influence.

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Towards the virtual artery: a multiscale model for vascular physiology at the physics–chemistry–biology interface

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2016.0146 ◽

2016 ◽

Vol 374 (2080) ◽

pp. 20160146 ◽

Cited By ~ 14

Author(s):

Alfons G. Hoekstra ◽

Saad Alowayyed ◽

Eric Lorenz ◽

Natalia Melnikova ◽

Lampros Mountrakis ◽

...

Keyword(s):

Multiscale Model ◽

Cellular Level ◽

Multiscale Modelling ◽

Multiscale Models ◽

Discussion Paper ◽

Vascular Physiology ◽

Health And Disease ◽

Mesoscopic Level ◽

Coupling Cell

This discussion paper introduces the concept of the Virtual Artery as a multiscale model for arterial physiology and pathologies at the physics–chemistry–biology (PCB) interface. The cellular level is identified as the mesoscopic level, and we argue that by coupling cell-based models with other relevant models on the macro- and microscale, a versatile model of arterial health and disease can be composed. We review the necessary ingredients, both models of arteries at many different scales, as well as generic methods to compose multiscale models. Next, we discuss how this can be combined into the virtual artery. Finally, we argue that the concept of models at the PCB interface could or perhaps should become a powerful paradigm, not only as in our case for studying physiology, but also for many other systems that have such PCB interfaces. This article is part of the themed issue ‘Multiscale modelling at the physics–chemistry–biology interface’.

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Real-time forecasting of infectious disease dynamics with a stochastic semi-mechanistic model

Epidemics ◽

10.1016/j.epidem.2016.11.003 ◽

2018 ◽

Vol 22 ◽

pp. 56-61 ◽

Cited By ~ 44

Author(s):

Sebastian Funk ◽

Anton Camacho ◽

Adam J. Kucharski ◽

Rosalind M. Eggo ◽

W. John Edmunds

Keyword(s):

Infectious Disease ◽

Real Time ◽

Mechanistic Model ◽

Disease Dynamics ◽

Infectious Disease Dynamics

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The Cavitational Potential of a Single-leaflet Virtual MHV: A Multi-Physics and Multiscale Modelling Approach

11th Mediterranean Conference on Medical and Biomedical Engineering and Computing 2007 - IFMBE Proceedings ◽

10.1007/978-3-540-73044-6_232 ◽

2007 ◽

pp. 895-898

Author(s):

Dan Rafiroiu ◽

V. Díaz-Zuccarini ◽

D.R. Hose ◽

P.V. Lawford ◽

A.J. Narracott ◽

...

Keyword(s):

Multiscale Modelling ◽

Modelling Approach

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Risk Causal Analysis of Traffic-Intensive Waters Based on Infectious Disease Dynamics

Journal of Marine Science and Engineering ◽

10.3390/jmse7080277 ◽

2019 ◽

Vol 7 (8) ◽

pp. 277

Author(s):

Yong-jun Chen ◽

Qing Liu ◽

Cheng-peng Wan

Keyword(s):

Infectious Disease ◽

Risk Factors ◽

Causal Model ◽

Cloud Model ◽

Rapid Development ◽

River Estuary ◽

Yangtze River Estuary ◽

Disease Dynamics ◽

Transmission Process ◽

Infectious Disease Dynamics

Accidents occur frequently in traffic-intensive waters, which restrict the safe and rapid development of the shipping industry. Due to the suddenness, randomness, and uncertainty of accidents in traffic-intensive waters, the probability of the risk factors causing traffic accidents is usually high. Thus, properly analyzing those key risk factors is of great significance to improve the safety of shipping. Based on the analysis of influencing factors of ship navigational risks in traffic-intensive waters, this paper proposes a cloud model to excavate the factors affecting navigational risk, which could accurately screen out the key risk factors. Furthermore, the risk causal model of ship navigation in traffic-intensive waters is constructed by using the infectious disease dynamics method in order to model the key risk causal transmission process. Moreover, an empirical study of the Yangtze River estuary is conducted to illustrate the feasibility of the proposed models. The research results show that the cloud model is useful in screening the key risk factors, and the constructed causal model of ship navigational risks in traffic-intensive waters is able to provide accurate analysis of the transmission process of key risk factors, which can be used to reduce the navigational risk of ships in traffic-intensive waters. This research provides both theoretical basis and practical reference for regulators in the risk management and control of ships in traffic-intensive waters.

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