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EpiContactTrace: an R-package for contact tracing during livestock disease outbreaks and for risk-based surveillance.

Nöremark M, Widgren S - BMC Vet. Res. (2014)

Bottom Line: In this study, an open source tool was developed to structure livestock movement data to facilitate contact-tracing in real time during disease outbreaks and for input in risk-based surveillance and sampling.The time-frames for backward and forward tracing can be specified independently and search can be done on one farm at a time or for all farms within the dataset.The open source makes it accessible and easily adaptable for different needs.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Disease Control and Epidemiology, SVA, National Veterinary Institute, 751 89 Uppsala, Sweden. maria.noremark@sva.se.

ABSTRACT

Background: During outbreak of livestock diseases, contact tracing can be an important part of disease control. Animal movements can also be of relevance for risk-based surveillance and sampling, i.e. both when assessing consequences of introduction or likelihood of introduction. In many countries, animal movement data are collected with one of the major objectives to enable contact tracing. However, often an analytical step is needed to retrieve appropriate information for contact tracing or surveillance.

Results: In this study, an open source tool was developed to structure livestock movement data to facilitate contact-tracing in real time during disease outbreaks and for input in risk-based surveillance and sampling. The tool, EpiContactTrace, was written in the R-language and uses the network parameters in-degree, out-degree, ingoing contact chain and outgoing contact chain (also called infection chain), which are relevant for forward and backward tracing respectively. The time-frames for backward and forward tracing can be specified independently and search can be done on one farm at a time or for all farms within the dataset. Different outputs are available; datasets with network measures, contacts visualised in a map and automatically generated reports for each farm either in HTML or PDF-format intended for the end-users, i.e. the veterinary authorities, regional disease control officers and field-veterinarians. EpiContactTrace is available as an R-package at the R-project website (http://cran.r-project.org/web/packages/EpiContactTrace/).

Conclusions: We believe this tool can help in disease control since it rapidly can structure essential contact information from large datasets. The reproducible reports make this tool robust and independent of manual compilation of data. The open source makes it accessible and easily adaptable for different needs.

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Related in: MedlinePlus

Example plots of a simple (a) and a more complex (b) contact structure between farms. The root is black, ingoing contact-farms are white, and farms reached through outgoing contacts are grey. Plots are generated using the EpiContactTrace example dataset Transfers with root 2838 and 2645.
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Figure 3: Example plots of a simple (a) and a more complex (b) contact structure between farms. The root is black, ingoing contact-farms are white, and farms reached through outgoing contacts are grey. Plots are generated using the EpiContactTrace example dataset Transfers with root 2838 and 2645.

Mentions: Furthermore, a plot to visualize the contact structure can be created. A farm existing both as ingoing and outgoing contact will in the plot be represented both in the ingoing and the outgoing part of the plot. The primary purpose of this plot is to give an immediate visual impression of the size of the network, in other words, the purpose is not to identify individual nodes (Figure 3a and b). The root is black, nodes included in ingoing contacts are white and nodes included in outgoing contacts are grey. In the plot the contacts are structured at different levels, i.e. all nodes with direct contact are shown at the same horizontal level closes to the root; the ones with indirect contact one step away are shown on the next level and so on.


EpiContactTrace: an R-package for contact tracing during livestock disease outbreaks and for risk-based surveillance.

Nöremark M, Widgren S - BMC Vet. Res. (2014)

Example plots of a simple (a) and a more complex (b) contact structure between farms. The root is black, ingoing contact-farms are white, and farms reached through outgoing contacts are grey. Plots are generated using the EpiContactTrace example dataset Transfers with root 2838 and 2645.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3974595&req=5

Figure 3: Example plots of a simple (a) and a more complex (b) contact structure between farms. The root is black, ingoing contact-farms are white, and farms reached through outgoing contacts are grey. Plots are generated using the EpiContactTrace example dataset Transfers with root 2838 and 2645.
Mentions: Furthermore, a plot to visualize the contact structure can be created. A farm existing both as ingoing and outgoing contact will in the plot be represented both in the ingoing and the outgoing part of the plot. The primary purpose of this plot is to give an immediate visual impression of the size of the network, in other words, the purpose is not to identify individual nodes (Figure 3a and b). The root is black, nodes included in ingoing contacts are white and nodes included in outgoing contacts are grey. In the plot the contacts are structured at different levels, i.e. all nodes with direct contact are shown at the same horizontal level closes to the root; the ones with indirect contact one step away are shown on the next level and so on.

Bottom Line: In this study, an open source tool was developed to structure livestock movement data to facilitate contact-tracing in real time during disease outbreaks and for input in risk-based surveillance and sampling.The time-frames for backward and forward tracing can be specified independently and search can be done on one farm at a time or for all farms within the dataset.The open source makes it accessible and easily adaptable for different needs.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Disease Control and Epidemiology, SVA, National Veterinary Institute, 751 89 Uppsala, Sweden. maria.noremark@sva.se.

ABSTRACT

Background: During outbreak of livestock diseases, contact tracing can be an important part of disease control. Animal movements can also be of relevance for risk-based surveillance and sampling, i.e. both when assessing consequences of introduction or likelihood of introduction. In many countries, animal movement data are collected with one of the major objectives to enable contact tracing. However, often an analytical step is needed to retrieve appropriate information for contact tracing or surveillance.

Results: In this study, an open source tool was developed to structure livestock movement data to facilitate contact-tracing in real time during disease outbreaks and for input in risk-based surveillance and sampling. The tool, EpiContactTrace, was written in the R-language and uses the network parameters in-degree, out-degree, ingoing contact chain and outgoing contact chain (also called infection chain), which are relevant for forward and backward tracing respectively. The time-frames for backward and forward tracing can be specified independently and search can be done on one farm at a time or for all farms within the dataset. Different outputs are available; datasets with network measures, contacts visualised in a map and automatically generated reports for each farm either in HTML or PDF-format intended for the end-users, i.e. the veterinary authorities, regional disease control officers and field-veterinarians. EpiContactTrace is available as an R-package at the R-project website (http://cran.r-project.org/web/packages/EpiContactTrace/).

Conclusions: We believe this tool can help in disease control since it rapidly can structure essential contact information from large datasets. The reproducible reports make this tool robust and independent of manual compilation of data. The open source makes it accessible and easily adaptable for different needs.

Show MeSH
Related in: MedlinePlus