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Active regional surveillance for early detection of exotic/emerging pathogens of swine: A comparison of statistical methods for farm selection.
- Source :
-
Preventive veterinary medicine [Prev Vet Med] 2021 Feb; Vol. 187, pp. 105233. Date of Electronic Publication: 2020 Dec 10. - Publication Year :
- 2021
-
Abstract
- In this study, five spatially balanced sampling methods, i.e., generalized random-tessellation stratified (GRTS), local pivotal method (LPM), spatially correlated Poisson sampling (SCPS), local cube method (LCUBE), and balanced acceptance sampling (BAS) were compared to simple random sampling (SRS) based on a livestock disease transmission model on a hypothetical region (195 km × 300 km) populated with 6000 farms in terms of the probability of detection by sample size. Given a fixed sample size, four of the five spatially balanced sampling methods provided better performance than SRS, i.e., higher probabilities of detecting at least one infected farms over a range of regional prevalence evaluated (1%-5%). That is, for any given probability of detection, spatially balanced methods required testing fewer farms than SRS. In an era of pandemics, active regional surveillance for early detection of emerging pathogens becomes urgent, yet shrinking budgets impose intractable constraints. The better performance and higher efficiency of spatially balanced sampling methods suggests a potential improvement in regional livestock disease surveillances and a partial solution to the challenge of affordable surveillance.<br /> (Copyright © 2020 Elsevier B.V. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1873-1716
- Volume :
- 187
- Database :
- MEDLINE
- Journal :
- Preventive veterinary medicine
- Publication Type :
- Academic Journal
- Accession number :
- 33373958
- Full Text :
- https://doi.org/10.1016/j.prevetmed.2020.105233