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- Widgren, Stefan, et al.
(author)
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Spatio-temporal modelling of verotoxigenic Escherichia coli O157 in cattle in Sweden: exploring options for control
- 2018
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In: Veterinary Research. - : Springer Science and Business Media LLC. - 0928-4249 .- 1297-9716. ; 49
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Journal article (peer-reviewed)abstract
- A spatial data-driven stochastic model was developed to explore the spread of verotoxigenic Escherichia coli O157 (VTEC O157) by livestock movements and local transmission among neighbouring holdings in the complete Swedish cattle population. Livestock data were incorporated to model the time-varying contact network between holdings and population demographics. Furthermore, meteorological data with the average temperature at the geographical location of each holding was used to incorporate season. The model was fitted against observed data and extensive numerical experiments were conducted to investigate the model's response to control strategies aimed at reducing shedding and susceptibility, as well as interventions informed by network measures. The results showed that including local spread and season improved agreement with prevalence studies. Also, control strategies aimed at reducing the average shedding rate were more efficient in reducing the VTEC O157 prevalence than strategies based on network measures. The methodology presented in this study could provide a basis for developing disease surveillance on regional and national scales, where observed data are combined with readily available high-resolution data in simulations to get an overview of potential disease spread in unobserved regions.
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| 6. |
- Engblom, Stefan, et al.
(author)
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Scalable population-level modelling of biological cells incorporating mechanics and kinetics in continuous time
- 2018
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In: Royal Society Open Science. - : The Royal Society. - 2054-5703. ; 5, s. 180379:1-17
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Journal article (peer-reviewed)abstract
- The processes taking place inside the living cell are now understood to the point where predictive computational models can be used to gain detailed understanding of important biological phenomena. A key challenge is to extrapolate this detailed knowledge of the individual cell to be able to explain at the population level how cells interact and respond with each other and their environment. In particular, the goal is to understand how organisms develop, maintain and repair functional tissues and organs. In this paper, we propose a novel computational framework for modelling populations of interacting cells. Our framework incorporates mechanistic, constitutive descriptions of biomechanical properties of the cell population, and uses a coarse-graining approach to derive individual rate laws that enable propagation of the population through time. Thanks to its multiscale nature, the resulting simulation algorithm is extremely scalable and highly efficient. As highlighted in our computational examples, the framework is also very flexible and may straightforwardly be coupled with continuous-time descriptions of biochemical signalling within, and between, individual cells.
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| 8. |
- Lindén, Jonatan, et al.
(author)
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Fine-grained local dynamic load balancing in PDES
- 2018
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In: Proc. 6th ACM SIGSIM Conference on Principles of Advanced Discrete Simulation. - New York : ACM Press. - 9781450350921 ; , s. 201-212
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Conference paper (peer-reviewed)
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