Geographic distribution of Tick-borne encephalitis virus complex
Bibliographic record
Abstract
A comprehensive understanding of the geographic distribution of the tick-borne encephalitis virus (TBEV) complex is necessary due to increasing transboundary movement and cross-reactivity of serological tests. This review was conducted to identify the geographic distribution of the TBEV complex, including TBE virus, Alkhurma haemorrhagic fever virus, Kyasanur forest disease virus, louping-ill virus, Omsk haemorrhagic fever virus, and Powassan virus. Published reports were identified using PubMed, EMBASE, and the Cochrane library. In addition to TBEV complex case-related studies, seroprevalence studies were also retrieved to assess the risk of TBEV complex infection. Among 1406 search results, 314 articles met the inclusion criteria. The following countries, which are known to TBEV epidemic region, had conducted national surveillance studies: Austria, China, Czech, Denmark, Estonia, Finland, Germany, Hungary, Italy, Latvia, Norway, Poland, Romania, Russia, Switzerland, Sweden, Slovenia, and Slovakia. There were also studies/reports on human TBEV infection from Belarus, Bulgaria, Croatia, France, Japan, Kyrgyzstan, Netherland, and Turkey. Seroprevalence studies were found in some areas far from the TBEV belt, specifically Malaysia, Comoros, Djibouti, and Kenya. Kyasanur forest disease virus was reported in southwestern India and Yunnan of China, the Powassan virus in the United States, Canada, and east Siberia, Alkhurma haemorrhagic fever virus in Saudi Arabia and east Egypt, and Louping-ill virus in the United Kingdom, Ireland, and east Siberia. In some areas, the distribution of the TBEV complex overlaps with that of other viruses, and caution is recommended during serologic diagnosis. The geographic distribution of the TBEV complex appears to be wide and overlap of the TBE virus complex with other viruses was observed in some areas. Knowledge of the geographical distribution of the TBEV complex could help avoid cross-reactivity during the serologic diagnosis of these viruses. Surveillance studies can implement effective control measures according to the distribution pattern of these viruses.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".