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Mendeley readers
| Title |
Using scenario tree modelling for targeted herd sampling to substantiate freedom from disease
|
|---|---|
| Published in |
BMC Veterinary Research, August 2011
|
| DOI | 10.1186/1746-6148-7-49 |
| Pubmed ID | |
| Authors |
Sarah Blickenstorfer, Heinzpeter Schwermer, Monika Engels, Martin Reist, Marcus G Doherr, Daniela C Hadorn |
| Abstract |
In order to optimise the cost-effectiveness of active surveillance to substantiate freedom from disease, a new approach using targeted sampling of farms was developed and applied on the example of infectious bovine rhinotracheitis (IBR) and enzootic bovine leucosis (EBL) in Switzerland. Relevant risk factors (RF) for the introduction of IBR and EBL into Swiss cattle farms were identified and their relative risks defined based on literature review and expert opinions. A quantitative model based on the scenario tree method was subsequently used to calculate the required sample size of a targeted sampling approach (TS) for a given sensitivity. We compared the sample size with that of a stratified random sample (sRS) with regard to efficiency. |
Mendeley readers
The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 4% |
| Switzerland | 3 | 4% |
| Brazil | 2 | 3% |
| Japan | 1 | 1% |
| Unknown | 61 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 23 | 33% |
| Student > Ph. D. Student | 13 | 19% |
| Other | 6 | 9% |
| Student > Master | 5 | 7% |
| Student > Doctoral Student | 4 | 6% |
| Other | 8 | 11% |
| Unknown | 11 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 25 | 36% |
| Veterinary Science and Veterinary Medicine | 14 | 20% |
| Medicine and Dentistry | 7 | 10% |
| Mathematics | 3 | 4% |
| Environmental Science | 2 | 3% |
| Other | 2 | 3% |
| Unknown | 17 | 24% |