Data-driven network modelling of disease transmission using complete population movement data: spread of VTEC O157 in Swedish cattle. (December 2016)
- Record Type:
- Journal Article
- Title:
- Data-driven network modelling of disease transmission using complete population movement data: spread of VTEC O157 in Swedish cattle. (December 2016)
- Main Title:
- Data-driven network modelling of disease transmission using complete population movement data: spread of VTEC O157 in Swedish cattle
- Authors:
- Widgren, Stefan
Engblom, Stefan
Bauer, Pavol
Frössling, Jenny
Emanuelson, Ulf
Lindberg, Ann - Abstract:
- Abstract European Union legislation requires member states to keep national databases of all bovine animals. This allows for disease spread models that includes the time-varying contact network and population demographic. However, performing data-driven simulations with a high degree of detail are computationally challenging. We have developed an efficient and flexible discrete-event simulatorSimInf for stochastic disease spread modelling that divides work among multiple processors to accelerate the computations. The model integrates disease dynamics as continuous-time Markov chains and livestock data as events. In this study, all Swedish livestock data (births, movements and slaughter) from July 1st 2005 to December 31st 2013 were included in the simulations. VerotoxigenicEscherichia coli O157:H7 (VTEC O157) are capable of causing serious illness in humans. Cattle are considered to be the main reservoir of the bacteria. A better understanding of the epidemiology in the cattle population is necessary to be able to design and deploy targeted measures to reduce the VTEC O157 prevalence and, subsequently, human exposure. To explore the spread of VTEC O157 in the entire Swedish cattle population during the period under study, a within- and between-herd disease spread model was used. Real livestock data was incorporated to model demographics of the population. Cattle were moved between herds according to real movement data. The results showed that the spatial pattern inAbstract European Union legislation requires member states to keep national databases of all bovine animals. This allows for disease spread models that includes the time-varying contact network and population demographic. However, performing data-driven simulations with a high degree of detail are computationally challenging. We have developed an efficient and flexible discrete-event simulatorSimInf for stochastic disease spread modelling that divides work among multiple processors to accelerate the computations. The model integrates disease dynamics as continuous-time Markov chains and livestock data as events. In this study, all Swedish livestock data (births, movements and slaughter) from July 1st 2005 to December 31st 2013 were included in the simulations. VerotoxigenicEscherichia coli O157:H7 (VTEC O157) are capable of causing serious illness in humans. Cattle are considered to be the main reservoir of the bacteria. A better understanding of the epidemiology in the cattle population is necessary to be able to design and deploy targeted measures to reduce the VTEC O157 prevalence and, subsequently, human exposure. To explore the spread of VTEC O157 in the entire Swedish cattle population during the period under study, a within- and between-herd disease spread model was used. Real livestock data was incorporated to model demographics of the population. Cattle were moved between herds according to real movement data. The results showed that the spatial pattern in prevalence may be due to regional differences in livestock movements. However, the movements, births and slaughter of cattle could not explain the temporal pattern of VTEC O157 prevalence in cattle, despite their inherently distinct seasonality. … (more)
- Is Part Of:
- Veterinary research. Volume 47:Number 1(2016)
- Journal:
- Veterinary research
- Issue:
- Volume 47:Number 1(2016)
- Issue Display:
- Volume 47, Issue 1 (2016)
- Year:
- 2016
- Volume:
- 47
- Issue:
- 1
- Issue Sort Value:
- 2016-0047-0001-0000
- Page Start:
- 1
- Page End:
- 17
- Publication Date:
- 2016-12
- Subjects:
- Veterinary medicine -- Periodicals
Veterinary medicine -- France -- Periodicals
636.089 - Journal URLs:
- http://www.edpsciences.org/journal/index.cfm?edpsname=vetres ↗
http://www.veterinaryresearch.org/ ↗
http://www.vetres.org/ ↗
http://link.springer.com/ ↗
http://www.elsevier.com/homepage/elecserv.htt ↗ - DOI:
- 10.1186/s13567-016-0366-5 ↗
- Languages:
- English
- ISSNs:
- 0928-4249
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
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