Early decision indicators for foot-and-mouth disease outbreaks in non-endemic countries
Disease managers face many challenges when deciding on the most effective control strategy to manage an outbreak of foot and mouth disease (FMD). Decisions have to be made under conditions of uncertainty and where the situation is continually evolving. In addition, resources for control are often li...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2016-11-01
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| Series: | Frontiers in Veterinary Science |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fvets.2016.00109/full |
| _version_ | 1818858224343842816 |
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| author | Michael Graeme Garner Iain East Mark Stevenson Robert Sanson Thomas Rawdon Richard Bradhurst Sharon Roche Pham van Ha Pham van Ha Thomas Kompas |
| author_facet | Michael Graeme Garner Iain East Mark Stevenson Robert Sanson Thomas Rawdon Richard Bradhurst Sharon Roche Pham van Ha Pham van Ha Thomas Kompas |
| author_sort | Michael Graeme Garner |
| collection | DOAJ |
| description | Disease managers face many challenges when deciding on the most effective control strategy to manage an outbreak of foot and mouth disease (FMD). Decisions have to be made under conditions of uncertainty and where the situation is continually evolving. In addition, resources for control are often limited. A modelling study was carried out to identify characteristics measurable during the early phase of a FMD outbreak that might be useful as predictors of the total number of infected places, outbreak duration and the total area under control. The study involved two modelling platforms in two countries (Australia and New Zealand) and encompassed a large number of incursion scenarios. Linear regression, classification and regression tree and boosted regression tree analyses were used to quantify the predictive value of a set of parameters on three outcome variables of interest: the total number of infected places, outbreak duration and the total area under control. The number of infected premises, number of pending culls, area under control, estimated dissemination ratio, and cattle density around the index herd at days 7, 14 and 21 following first detection were associated with each of the outcome variables. Regression models for the size of the area under control had the highest predictive value (R2 = 0.51-0.9) followed by the number of infected premises (R2 = 0.3-0.75) and outbreak duration (R2 = 0.28-0.57). Predictability improved at later time points in the outbreak. Predictive regression models using various cut-points at day 14 to define small and large outbreaks had positive predictive values of 0.85‒0.98 and negative predictive values of 0.52‒0.91, with 79‒97% of outbreaks correctly classified. On the strict assumption that each of the simulation models used in this study provide a realistic indication of the spread of FMD in animal populations our conclusion is that relatively simple metrics available early in a control program can be used to indicate the likely magnitude of an FMD outbreak under Australian and New Zealand conditions. |
| first_indexed | 2024-12-19T08:52:53Z |
| format | Article |
| id | doaj.art-287e496f0d054b569d504f11969ff783 |
| institution | Directory Open Access Journal |
| issn | 2297-1769 |
| language | English |
| last_indexed | 2024-12-19T08:52:53Z |
| publishDate | 2016-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Veterinary Science |
| spelling | doaj.art-287e496f0d054b569d504f11969ff7832022-12-21T20:28:41ZengFrontiers Media S.A.Frontiers in Veterinary Science2297-17692016-11-01310.3389/fvets.2016.00109227206Early decision indicators for foot-and-mouth disease outbreaks in non-endemic countriesMichael Graeme Garner0Iain East1Mark Stevenson2Robert Sanson3Thomas Rawdon4Richard Bradhurst5Sharon Roche6Pham van Ha7Pham van Ha8Thomas Kompas9Department of Agriculture and Water ResourcesDepartment of Agriculture and Water ResourcesThe University of MelbourneAsureQuality LimitedMinistry for Primary IndustriesThe University of MelbourneDepartment of Agriculture and Water ResourcesAsureQuality LimitedAustralian National UniversityThe University of MelbourneDisease managers face many challenges when deciding on the most effective control strategy to manage an outbreak of foot and mouth disease (FMD). Decisions have to be made under conditions of uncertainty and where the situation is continually evolving. In addition, resources for control are often limited. A modelling study was carried out to identify characteristics measurable during the early phase of a FMD outbreak that might be useful as predictors of the total number of infected places, outbreak duration and the total area under control. The study involved two modelling platforms in two countries (Australia and New Zealand) and encompassed a large number of incursion scenarios. Linear regression, classification and regression tree and boosted regression tree analyses were used to quantify the predictive value of a set of parameters on three outcome variables of interest: the total number of infected places, outbreak duration and the total area under control. The number of infected premises, number of pending culls, area under control, estimated dissemination ratio, and cattle density around the index herd at days 7, 14 and 21 following first detection were associated with each of the outcome variables. Regression models for the size of the area under control had the highest predictive value (R2 = 0.51-0.9) followed by the number of infected premises (R2 = 0.3-0.75) and outbreak duration (R2 = 0.28-0.57). Predictability improved at later time points in the outbreak. Predictive regression models using various cut-points at day 14 to define small and large outbreaks had positive predictive values of 0.85‒0.98 and negative predictive values of 0.52‒0.91, with 79‒97% of outbreaks correctly classified. On the strict assumption that each of the simulation models used in this study provide a realistic indication of the spread of FMD in animal populations our conclusion is that relatively simple metrics available early in a control program can be used to indicate the likely magnitude of an FMD outbreak under Australian and New Zealand conditions.http://journal.frontiersin.org/Journal/10.3389/fvets.2016.00109/fullVaccinationsimulationregressionanalysisfmdDecision-support |
| spellingShingle | Michael Graeme Garner Iain East Mark Stevenson Robert Sanson Thomas Rawdon Richard Bradhurst Sharon Roche Pham van Ha Pham van Ha Thomas Kompas Early decision indicators for foot-and-mouth disease outbreaks in non-endemic countries Frontiers in Veterinary Science Vaccination simulation regression analysis fmd Decision-support |
| title | Early decision indicators for foot-and-mouth disease outbreaks in non-endemic countries |
| title_full | Early decision indicators for foot-and-mouth disease outbreaks in non-endemic countries |
| title_fullStr | Early decision indicators for foot-and-mouth disease outbreaks in non-endemic countries |
| title_full_unstemmed | Early decision indicators for foot-and-mouth disease outbreaks in non-endemic countries |
| title_short | Early decision indicators for foot-and-mouth disease outbreaks in non-endemic countries |
| title_sort | early decision indicators for foot and mouth disease outbreaks in non endemic countries |
| topic | Vaccination simulation regression analysis fmd Decision-support |
| url | http://journal.frontiersin.org/Journal/10.3389/fvets.2016.00109/full |
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