Parameterization of the duration of infection stages of serotype O foot-and-mouth disease virus: an analytical review and meta-analysis with application to simulation models
Bibliographic record
Abstract
Foot-and-mouth disease (FMD) is considered one of the most important infectious diseases of livestock because of the devastating economic consequences that it inflicts in affected regions. The value of critical parameters, such as the duration of the latency or the duration of the infectious periods, which affect the transmission rate of the FMD virus (FMDV), are believed to be influenced by characteristics of the host and the virus. Disease control and surveillance strategies, as well as FMD simulation models, will benefit from improved parameter estimation. The objective of this study was to quantify the distributions of variables associated with the duration of the latency, subclinical, incubation, and infectiousness periods of FMDV transmission. A double independent, systematic review of 19 retrieved publications reporting results from experimental trials, using 295 animals in four reference laboratories, was performed to extract individual values related to FMDV transmission. Probability density functions were fitted to data and a set of regression models were used to identify factors associated with the assessed parameters. Latent, subclinical, incubation, and infectious periods ranged from 3.1 to 4.8, 2 to 2.3, 5.5 to 6.6, and 3.3 to 5.7 days, respectively. Durations were significantly (p < 0.05) associated independently with route of exposure, type of donor, animal species, strains, characteristics of sampling, and clinical signs. These results will contribute to the improvement of disease control and surveillance strategies and stochastic models used to simulate FMD spread and, ultimately, development of cost-effective plans to prevent and control the potential spread of the disease in FMD-free regions of the world.
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 | 0.027 | 0.064 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.039 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".