Rodents as Sentinels for the Prevalence of Tick-Borne Encephalitis Virus
Bibliographic record
Abstract
INTRODUCTION: Tick-borne encephalitis virus (TBEV) causes one of the most important flavivirus infections of the central nervous system, affecting humans in Europe and Asia. It is mainly transmitted by the bite of an infected tick and circulates among them and their vertebrate hosts. Until now, TBE risk analysis in Germany has been based on the incidence of human cases. Because of an increasing vaccination rate, this approach might be misleading, especially in regions of low virus circulation. METHOD: To test the suitability of rodents as a surrogate marker for virus spread, laboratory-bred Microtus arvalis voles were experimentally infected with TBEV and analyzed over a period of 100 days by real-time (RT)-quantitative polymerase chain reaction. Further, the prevalence of TBEV in rodents trapped in Brandenburg, a rural federal state in northeastern Germany with autochthonous TBE cases, was determined and compared with that in rodents from German TBE risk areas as well as TBE nonrisk areas. RESULTS: In experimentally infected M. arvalis voles, TBEV was detectable in different organs for at least 3 months and in blood for 1 month. Ten percent of all rodents investigated were positive for TBEV. However, in TBE risk areas, the infection rate was higher compared with that of areas with only single human cases or of nonrisk areas. TBEV was detected in six rodent species: Apodemus agrarius, Apodemus flavicollis, Apodemus sylvaticus, Microtus agrestis, Microtus arvalis, and Myodes glareolus. M. glareolus showed a high infection rate in all areas investigated. DISCUSSION AND CONCLUSION: The infection experiments proved that TBEV can be reliably detected in infected M. arvalis voles. These voles developed a persistent TBE infection without clinical symptoms. Further, the study showed that rodents, especially M. glareolus, are promising sentinels particularly in areas of low TBEV circulation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".