Powassan virus, a scoping review of the global evidence
Bibliographic record
Abstract
BACKGROUND: Powassan virus (POWV), a flavivirus discovered in 1958, causes sporadic but severe cases of encephalitis in humans. Since 2007, the number of human Powassan cases diagnosed each year in the USA has steadily increased. This is in agreement with predictions that Powassan cases may increase in North America as a result of increased exposure to infected ticks. However, the increase may also reflect improved diagnostics and reporting among other factors. METHODS: A scoping review was prioritized to identify and characterize the global literature on POWV. Following an a priori developed protocol, a comprehensive search strategy was implemented. Two reviewers screened titles and abstracts for relevant research and the identified full papers were used to characterize the POWV literature using a predetermined data characterization tool. RESULTS: One hundred and seventy-eight articles were included. The majority of the studies were conducted in North America (88.2%) between 1958 and 2017. Both genotypes of POWV (Powassan lineage 1 and Deer Tick virus) were isolated or studied in vitro, in vectors, nonhuman hosts and human populations. To date, POWV has been reported in 147 humans in North America. The virus has also been isolated from five tick species, and several animals have tested positive for exposure to the virus. The relevant articles identified in this review cover the following eight topics: epidemiology (123 studies), pathogenesis (66), surveillance (33), virus characterization (22), POWV transmission (8), diagnostic test accuracy (8), treatment (4) and mitigation strategies (3). CONCLUSION: The literature on POWV is relatively small compared with other vector-borne diseases, likely because POWV has not been prioritized due to the small number of severe sporadic human cases. With the projected impact of climate change on tick populations, increases in the number of human cases are expected. It is recommended that future research efforts focus on closing some of the important knowledge gaps identified in this scoping review.
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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 | 0.012 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.036 | 0.027 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".