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- Bauer, Pavol, et al.
(författare)
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Fast event-based epidemiological simulations on national scales
- 2016
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Ingår i: The international journal of high performance computing applications. - : SAGE Publications. - 1094-3420 .- 1741-2846. ; 30, s. 438-453
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Tidskriftsartikel (refereegranskat)abstract
- We present a computational modeling framework for data-driven simulations and analysis of infectious disease spread in large populations. For the purpose of efficient simulations, we devise a parallel solution algorithm targeting multi-socket shared-memory architectures. The model integrates infectious dynamics as continuous-time Markov chains and available data such as animal movements or aging are incorporated as externally defined events. To bring out parallelism and accelerate the computations, we decompose the spatial domain and optimize cross-boundary communication using dependency-aware task scheduling. Using registered livestock data at a high spatiotemporal resolution, we demonstrate that our approach not only is resilient to varying model configurations but also scales on all physical cores at realistic workloads. Finally, we show that these very features enable the solution of inverse problems on national scales.
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| 2. |
- Engblom, Stefan, et al.
(författare)
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Bayesian epidemiological modeling over high-resolution network data
- 2020
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Ingår i: Epidemics. - : Elsevier BV. - 1755-4365 .- 1878-0067. ; 32
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Tidskriftsartikel (refereegranskat)abstract
- Mathematical epidemiological models have a broad use, including both qualitative and quantitative applications. With the increasing availability of data, large-scale quantitative disease spread models can nowadays be formulated. Such models have a great potential, e.g., in risk assessments in public health. Their main challenge is model parameterization given surveillance data, a problem which often limits their practical usage. We offer a solution to this problem by developing a Bayesian methodology suitable to epidemiological models driven by network data. The greatest difficulty in obtaining a concentrated parameter posterior is the quality of surveillance data; disease measurements are often scarce and carry little information about the parameters. The often overlooked problem of the model's identifiability therefore needs to be addressed, and we do so using a hierarchy of increasingly realistic known truth experiments. Our proposed Bayesian approach performs convincingly across all our synthetic tests. From pathogen measurements of shiga toxin-producing Escherichia coli O157 in Swedish cattle, we are able to produce an accurate statistical model of first-principles confronted with data. Within this model we explore the potential of a Bayesian public health framework by assessing the efficiency of disease detection and -intervention scenarios.
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| 8. |
- Widgren, Stefan, et al.
(författare)
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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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Ingår i: Veterinary Research. - : Springer Science and Business Media LLC. - 0928-4249 .- 1297-9716. ; 49
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Tidskriftsartikel (refereegranskat)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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| 9. |
- Andersson, Emma, et al.
(författare)
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Impact of first parity litter size on sow stayability and lifetime production
- 2015
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- To increase production level increase of number of piglets born per litter has been one of the main breeding goals during the last decades. The negative welfare consequences on piglets being born in a large litter are well known while the welfare impacts on sows that produce large litters are more uncertain. The aim of this study was to investigate the effect of first parity litter size on sow stayability and lifetime production. Sows having a small (<12 piglets total born; SL) or medium (12-14 piglets total born; ML) first parity litter size had significantly (p <0.001) more litters before end of production than sows having a large (>14 piglets total born; LL) first parity litter size. Sows with LL was significant (p<0.001) less likely to have a second litter than sows with SL and ML. Sows with SL and ML had the highest lifetime production of weaned piglets. The results of this study indicate that it is important take first parity litter size into account when assessing sow welfare and profitability in commercial piglet producing herds. Having a SL or ML was found to have a positive effect on sow stayability and lifetime production.
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