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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

A schematic illustration of backward- and forward contact-tracing, and the network measures degree and contact chains. The encircled farm, P, represents the starting point for the contact tracing, in EpiContactTrace defined as the root. The arrows represent livestock movements, where t represents the point in time when the movement occurred. The left side shows ingoing contacts to P (backward tracing) and the right side outgoing contacts from P (forward tracing). The in-degree, i.e. direct ingoing contacts will be 3 (K, N and O) and correspondingly the out-degree will be 3 (Q, T and O). Since the same farm can be both among ingoing and outgoing contacts, this is exemplified with farm O. The measures ingoing and outgoing contact chain takes temporal aspect into account, i.e. the order in which the movements occurred. Given that t1 and t2 occurred before t3 and moreover that t4 occurred before t5 and that t5 occurred before t6 or t7, the ingoing contact chain will be 7. Given that ta occurred before tb and tc and moreover that td occurred before te or tf, and that te or tf occurred before tg, the outgoing contact chain will be 7. The movement arrow with time tx illustrates the case where the same farm is included in different parts of the chain creating a cross-contact. Although appearing in different parts of the chain, a farm will only be counted once when indicating the measure contact chain.
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Figure 2: A schematic illustration of backward- and forward contact-tracing, and the network measures degree and contact chains. The encircled farm, P, represents the starting point for the contact tracing, in EpiContactTrace defined as the root. The arrows represent livestock movements, where t represents the point in time when the movement occurred. The left side shows ingoing contacts to P (backward tracing) and the right side outgoing contacts from P (forward tracing). The in-degree, i.e. direct ingoing contacts will be 3 (K, N and O) and correspondingly the out-degree will be 3 (Q, T and O). Since the same farm can be both among ingoing and outgoing contacts, this is exemplified with farm O. The measures ingoing and outgoing contact chain takes temporal aspect into account, i.e. the order in which the movements occurred. Given that t1 and t2 occurred before t3 and moreover that t4 occurred before t5 and that t5 occurred before t6 or t7, the ingoing contact chain will be 7. Given that ta occurred before tb and tc and moreover that td occurred before te or tf, and that te or tf occurred before tg, the outgoing contact chain will be 7. The movement arrow with time tx illustrates the case where the same farm is included in different parts of the chain creating a cross-contact. Although appearing in different parts of the chain, a farm will only be counted once when indicating the measure contact chain.

Mentions: The sequential spread of diseases through live animal contacts has been described by Webb and Dubé and co-workers, through the network measure accessible world and infection chain[7,8]. Correspondingly, the possible source farms have been described using the ingoing infection chain[9]. In this article, we hereafter refer to these measures as outgoing contact chain and ingoing contact chain, since they measure contacts and not confirmed spread of infection. These two network measures take the temporal aspect of movements into account and in combination with detailed information on the specific contacts identified, they are ideal for both backward and forward tracing of contacts through live animal movements during an outbreak (Figure 2). Moreover, the measures can be used to identify farms with many ingoing contacts or outgoing contacts, i.e. at high risk of introduction of disease or for spreading disease. In other words, information that could be relevant for risk-based surveillance and targeted sampling, or for targeted interventions during an outbreak. The information could also be of interest whenever animal movements are investigated as a risk factor for diseases occurrence. So far, many network articles published have been related to understanding structure of movements, modelling disease outbreaks, or to analyse movements post outbreak [10,11]. Although the effects of contact tracing on disease spread within a network has been investigated [12], there are fewer publications related to work providing applications for use during an ongoing outbreak [13]. However, the use of network measures for risk-based surveillance has been suggested by several authors [9,11,14,15] and also tested [16,17].


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

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

A schematic illustration of backward- and forward contact-tracing, and the network measures degree and contact chains. The encircled farm, P, represents the starting point for the contact tracing, in EpiContactTrace defined as the root. The arrows represent livestock movements, where t represents the point in time when the movement occurred. The left side shows ingoing contacts to P (backward tracing) and the right side outgoing contacts from P (forward tracing). The in-degree, i.e. direct ingoing contacts will be 3 (K, N and O) and correspondingly the out-degree will be 3 (Q, T and O). Since the same farm can be both among ingoing and outgoing contacts, this is exemplified with farm O. The measures ingoing and outgoing contact chain takes temporal aspect into account, i.e. the order in which the movements occurred. Given that t1 and t2 occurred before t3 and moreover that t4 occurred before t5 and that t5 occurred before t6 or t7, the ingoing contact chain will be 7. Given that ta occurred before tb and tc and moreover that td occurred before te or tf, and that te or tf occurred before tg, the outgoing contact chain will be 7. The movement arrow with time tx illustrates the case where the same farm is included in different parts of the chain creating a cross-contact. Although appearing in different parts of the chain, a farm will only be counted once when indicating the measure contact chain.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 2: A schematic illustration of backward- and forward contact-tracing, and the network measures degree and contact chains. The encircled farm, P, represents the starting point for the contact tracing, in EpiContactTrace defined as the root. The arrows represent livestock movements, where t represents the point in time when the movement occurred. The left side shows ingoing contacts to P (backward tracing) and the right side outgoing contacts from P (forward tracing). The in-degree, i.e. direct ingoing contacts will be 3 (K, N and O) and correspondingly the out-degree will be 3 (Q, T and O). Since the same farm can be both among ingoing and outgoing contacts, this is exemplified with farm O. The measures ingoing and outgoing contact chain takes temporal aspect into account, i.e. the order in which the movements occurred. Given that t1 and t2 occurred before t3 and moreover that t4 occurred before t5 and that t5 occurred before t6 or t7, the ingoing contact chain will be 7. Given that ta occurred before tb and tc and moreover that td occurred before te or tf, and that te or tf occurred before tg, the outgoing contact chain will be 7. The movement arrow with time tx illustrates the case where the same farm is included in different parts of the chain creating a cross-contact. Although appearing in different parts of the chain, a farm will only be counted once when indicating the measure contact chain.
Mentions: The sequential spread of diseases through live animal contacts has been described by Webb and Dubé and co-workers, through the network measure accessible world and infection chain[7,8]. Correspondingly, the possible source farms have been described using the ingoing infection chain[9]. In this article, we hereafter refer to these measures as outgoing contact chain and ingoing contact chain, since they measure contacts and not confirmed spread of infection. These two network measures take the temporal aspect of movements into account and in combination with detailed information on the specific contacts identified, they are ideal for both backward and forward tracing of contacts through live animal movements during an outbreak (Figure 2). Moreover, the measures can be used to identify farms with many ingoing contacts or outgoing contacts, i.e. at high risk of introduction of disease or for spreading disease. In other words, information that could be relevant for risk-based surveillance and targeted sampling, or for targeted interventions during an outbreak. The information could also be of interest whenever animal movements are investigated as a risk factor for diseases occurrence. So far, many network articles published have been related to understanding structure of movements, modelling disease outbreaks, or to analyse movements post outbreak [10,11]. Although the effects of contact tracing on disease spread within a network has been investigated [12], there are fewer publications related to work providing applications for use during an ongoing outbreak [13]. However, the use of network measures for risk-based surveillance has been suggested by several authors [9,11,14,15] and also tested [16,17].

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