@article{flood_performance_2013,
	title = {The performance of approximations of farm contiguity compared to contiguity defined using detailed geographical information in two sample areas in {Scotland}:  implications for foot-and-mouth disease modelling.},
	volume = {9},
	issn = {1746-6148 1746-6148},
	doi = {10.1186/1746-6148-9-198},
	abstract = {BACKGROUND: When modelling infectious diseases, accurately capturing the pattern  of dissemination through space is key to providing optimal recommendations for control. Mathematical models of disease spread in livestock, such as for foot-and-mouth disease (FMD), have done this by incorporating a transmission kernel which describes the decay in transmission rate with increasing Euclidean distance from an infected premises (IP). However, this assumes a homogenous landscape, and is based on the distance between point locations of farms. Indeed, underlying the spatial pattern of spread are the contact networks involved in transmission. Accordingly, area-weighted tessellation around farm point locations has been used to approximate field-contiguity and simulate the effect of contiguous premises (CP) culling for FMD. Here, geographic data were used to determine contiguity based on distance between premises' fields and presence of landscape features for two sample areas in Scotland. Sensitivity, positive predictive value, and the True Skill Statistic (TSS) were calculated to determine how point distance measures and area-weighted tessellation compared to the 'gold  standard' of the map-based measures in identifying CPs. In addition, the mean degree and density of the different contact networks were calculated. RESULTS: Utilising point distances {\textless}1 km and {\textless}5 km as a measure for contiguity resulted in poor discrimination between map-based CPs/non-CPs (TSS 0.279-0.344 and 0.385-0.400, respectively). Point distance {\textless}1 km missed a high proportion of map-based CPs; {\textless}5 km point distance picked up a high proportion of map-based non-CPs as CPs. Area-weighted tessellation performed best, with reasonable discrimination between map-based CPs/non-CPs (TSS 0.617-0.737) and comparable mean degree and density. Landscape features altered network properties considerably when taken into account. CONCLUSION: The farming landscape is not homogeneous. Basing contiguity on geographic locations of field boundaries and including landscape features known to affect transmission into FMD models are likely to improve individual farm-level accuracy of spatial predictions in the event of future outbreaks. If a substantial proportion of FMD transmission events are by contiguous spread, and CPs should be assigned an elevated relative transmission rate, the shape of the kernel could be significantly altered since ability to discriminate between map-based CPs and non-CPs is different over different Euclidean distances.},
	language = {eng},
	journal = {BMC veterinary research},
	author = {Flood, Jessica S. and Porphyre, Thibaud and Tildesley, Michael J. and Woolhouse, Mark E. J.},
	month = oct,
	year = {2013},
	pmid = {24099627},
	pmcid = {PMC4126065},
	keywords = {*Agriculture, *Models, Biological, Animals, Contact Tracing/methods/veterinary, Disease Outbreaks/veterinary, Foot-and-Mouth Disease/epidemiology/*transmission, Scotland/epidemiology},
	pages = {198}
}

{"_id":"yQW8dp6pSNodDre5X","bibbaseid":"flood-porphyre-tildesley-woolhouse-theperformanceofapproximationsoffarmcontiguitycomparedtocontiguitydefinedusingdetailedgeographicalinformationintwosampleareasinscotlandimplicationsforfootandmouthdiseasemodelling-2013","downloads":0,"creationDate":"2017-08-31T17:02:20.445Z","title":"The performance of approximations of farm contiguity compared to contiguity defined using detailed geographical information in two sample areas in Scotland: implications for foot-and-mouth disease modelling.","author_short":["Flood, J. S.","Porphyre, T.","Tildesley, M. J.","Woolhouse, M. E. J."],"year":2013,"bibtype":"article","biburl":"https://api.zotero.org/users/4242995/collections/79QXPRSR/items?key=zD4uWY4xk1YOLS3UQ7bLDMqH&format=bibtex&limit=100","bibdata":{"bibtype":"article","type":"article","title":"The performance of approximations of farm contiguity compared to contiguity defined using detailed geographical information in two sample areas in Scotland: implications for foot-and-mouth disease modelling.","volume":"9","issn":"1746-6148 1746-6148","doi":"10.1186/1746-6148-9-198","abstract":"BACKGROUND: When modelling infectious diseases, accurately capturing the pattern of dissemination through space is key to providing optimal recommendations for control. Mathematical models of disease spread in livestock, such as for foot-and-mouth disease (FMD), have done this by incorporating a transmission kernel which describes the decay in transmission rate with increasing Euclidean distance from an infected premises (IP). However, this assumes a homogenous landscape, and is based on the distance between point locations of farms. Indeed, underlying the spatial pattern of spread are the contact networks involved in transmission. Accordingly, area-weighted tessellation around farm point locations has been used to approximate field-contiguity and simulate the effect of contiguous premises (CP) culling for FMD. Here, geographic data were used to determine contiguity based on distance between premises' fields and presence of landscape features for two sample areas in Scotland. Sensitivity, positive predictive value, and the True Skill Statistic (TSS) were calculated to determine how point distance measures and area-weighted tessellation compared to the 'gold standard' of the map-based measures in identifying CPs. In addition, the mean degree and density of the different contact networks were calculated. RESULTS: Utilising point distances \\textless1 km and \\textless5 km as a measure for contiguity resulted in poor discrimination between map-based CPs/non-CPs (TSS 0.279-0.344 and 0.385-0.400, respectively). Point distance \\textless1 km missed a high proportion of map-based CPs; \\textless5 km point distance picked up a high proportion of map-based non-CPs as CPs. Area-weighted tessellation performed best, with reasonable discrimination between map-based CPs/non-CPs (TSS 0.617-0.737) and comparable mean degree and density. Landscape features altered network properties considerably when taken into account. CONCLUSION: The farming landscape is not homogeneous. Basing contiguity on geographic locations of field boundaries and including landscape features known to affect transmission into FMD models are likely to improve individual farm-level accuracy of spatial predictions in the event of future outbreaks. If a substantial proportion of FMD transmission events are by contiguous spread, and CPs should be assigned an elevated relative transmission rate, the shape of the kernel could be significantly altered since ability to discriminate between map-based CPs and non-CPs is different over different Euclidean distances.","language":"eng","journal":"BMC veterinary research","author":[{"propositions":[],"lastnames":["Flood"],"firstnames":["Jessica","S."],"suffixes":[]},{"propositions":[],"lastnames":["Porphyre"],"firstnames":["Thibaud"],"suffixes":[]},{"propositions":[],"lastnames":["Tildesley"],"firstnames":["Michael","J."],"suffixes":[]},{"propositions":[],"lastnames":["Woolhouse"],"firstnames":["Mark","E.","J."],"suffixes":[]}],"month":"October","year":"2013","pmid":"24099627","pmcid":"PMC4126065","keywords":"*Agriculture, *Models, Biological, Animals, Contact Tracing/methods/veterinary, Disease Outbreaks/veterinary, Foot-and-Mouth Disease/epidemiology/*transmission, Scotland/epidemiology","pages":"198","bibtex":"@article{flood_performance_2013,\n\ttitle = {The performance of approximations of farm contiguity compared to contiguity defined using detailed geographical information in two sample areas in {Scotland}: implications for foot-and-mouth disease modelling.},\n\tvolume = {9},\n\tissn = {1746-6148 1746-6148},\n\tdoi = {10.1186/1746-6148-9-198},\n\tabstract = {BACKGROUND: When modelling infectious diseases, accurately capturing the pattern of dissemination through space is key to providing optimal recommendations for control. Mathematical models of disease spread in livestock, such as for foot-and-mouth disease (FMD), have done this by incorporating a transmission kernel which describes the decay in transmission rate with increasing Euclidean distance from an infected premises (IP). However, this assumes a homogenous landscape, and is based on the distance between point locations of farms. Indeed, underlying the spatial pattern of spread are the contact networks involved in transmission. Accordingly, area-weighted tessellation around farm point locations has been used to approximate field-contiguity and simulate the effect of contiguous premises (CP) culling for FMD. Here, geographic data were used to determine contiguity based on distance between premises' fields and presence of landscape features for two sample areas in Scotland. Sensitivity, positive predictive value, and the True Skill Statistic (TSS) were calculated to determine how point distance measures and area-weighted tessellation compared to the 'gold standard' of the map-based measures in identifying CPs. In addition, the mean degree and density of the different contact networks were calculated. RESULTS: Utilising point distances {\\textless}1 km and {\\textless}5 km as a measure for contiguity resulted in poor discrimination between map-based CPs/non-CPs (TSS 0.279-0.344 and 0.385-0.400, respectively). Point distance {\\textless}1 km missed a high proportion of map-based CPs; {\\textless}5 km point distance picked up a high proportion of map-based non-CPs as CPs. Area-weighted tessellation performed best, with reasonable discrimination between map-based CPs/non-CPs (TSS 0.617-0.737) and comparable mean degree and density. Landscape features altered network properties considerably when taken into account. CONCLUSION: The farming landscape is not homogeneous. Basing contiguity on geographic locations of field boundaries and including landscape features known to affect transmission into FMD models are likely to improve individual farm-level accuracy of spatial predictions in the event of future outbreaks. If a substantial proportion of FMD transmission events are by contiguous spread, and CPs should be assigned an elevated relative transmission rate, the shape of the kernel could be significantly altered since ability to discriminate between map-based CPs and non-CPs is different over different Euclidean distances.},\n\tlanguage = {eng},\n\tjournal = {BMC veterinary research},\n\tauthor = {Flood, Jessica S. and Porphyre, Thibaud and Tildesley, Michael J. and Woolhouse, Mark E. 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