An epidemiological comparison of the US and Canadian Plum pox virus eradication programs
Bibliographic record
Abstract
Plum pox virus (PPV) is one of the most damaging viral diseases of Prunus spp. worldwide. The virus was first detected in North America in Pennsylvania in 1999, and in Ontario, Canada in 2000. Following the detection of PPV in Pennsylvania and Ontario, both countries implemented PPV survey and eradication programs. The eradication program was successful in Pennsylvania, as PPV was officially declared eradicated in 2009. However, PPV remains present in Ontario. The US and Canadian eradication programs had differing effects on the epidemiology of PPV in their respective countries. The objectives of this research, therefore, were to: (i) quantify the temporal and spatial dynamics of PPV at different spatial scales, and (ii) assess the sampling and testing systems utilized by the two survey/eradication programs. Using Ripley's L function (a measure of spatial dependence), it was found that PPV-positive Prunus blocks in Pennsylvania in 2000 were spatially dependent (clustered) for distances of 0.7 to 4.3 km. In Ontario, spatial dependence (clustering) of PPV-positive blocks was detected for distances of 1 to 25 km. When applied to consecutive years of PPV-positive blocks in Ontario, PPV-positive Prunus blocks were found to be spatially dependent on the location of PPV-positive blocks that were PPV-positive the previous year. This indicates that PPV-positive Prunus blocks are having an impact on the health status of other Prunus blocks, even in subsequent years after PPV-positive trees/blocks have been removed. Distance to 50% (D50) of new PPV-positive blocks in Pennsylvania from the previous years' PPV-positive blocks increased in an exponential manner until 2006, when there was a sharp decrease. Distance to 95% (D95) of new PPV-positive blocks increased in 2001, but then decreased in 2002. From 2002 to 2006, the distance to 95% of new PPV-positive Prunus blocks (D95) was consistently between 10 and 20 km. This may suggest that when relatively few PPV-positive blocks are thought to exist, it is best to search for new PPV-positive blocks from distances of 10 to 20 km from PPV-positive Prunus blocks that were detected the previous year. In Ontario, D50 and D95 tended to increase over time. The distance to 95% of positive blocks was consistently between 0.5 and 1.0 km from the previous years' PPV-positive blocks, indicating that new PPV-positive blocks are very near one another. This may support the idea of Ontario implementing a PPV eradication protocol based upon distance, because a large percentage of newly detected PPV-positive blocks are so close in proximity to the previous years' PPV-positive blocks. The spatial pattern of PPV-positive trees within Prunus blocks was found to be random in nine of 12 blocks. In the remaining three Prunus blocks, PPV-positive trees were significantly clustered (P ≤ 0.05).\nA simulation model was developed to determine the relative ability of the US and Canadian sampling and testing systems to detect PPV-positive Prunus trees. It was found that the US system had a PPV detection efficiency of approximately 72%, whereas the Canadian system had a PPV detection efficiency of approximately 41%. This indicates that the US sampling and testing system detects approximately 30% more PPV-positive trees than does the Canadian system. The simulation model was also used to determine how the two sampling and testing protocols affected PPV detection efficiency. The ELISA test kit used in the US (Agdia) was found to have a consistently higher PPV detection efficiency compared to the ELISA test kit used in Canada (Durviz). Detection efficiency tended to increase with increasing sample size, however there were diminishing returns in detection efficiency as sample size increased. Detection efficiency did not appreciably differ using a stratified (by scaffold) random sampling design compared to using a simple random sampling design. Finally, as the number of PPV-positive leaves required for a bulked leaf sample to test positive increased, PPV detection efficiency decreased. From these simulations, it can be concluded that PPV detection efficiency can be optimized by utilizing a 10 to 12 leaf/tree sample size, that requires only one PPV-positive leaf for a bulk sample to test positive for PPV.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".