Tick-Borne Encephalitis Virus Seropositivity among Tick Infested Individuals in Serbia
Bibliographic record
Abstract
Tick-borne encephalitis (TBE), caused by the TBE virus (TBEV), is a life-threatening disease with clinical symptoms ranging from non-specific to severe inflammation of the central nervous system. Despite TBE is a notifiable disease in Serbia since 2004, there is no active TBE surveillance program for the serologic or molecular screening of TBEV infection in humans in the country. This prospective cohort study aimed to assess the TBEV exposure among tick-infested individuals in Serbia during the year 2020. A total of 113 individuals exposed to tick bites were recruited for the study and screened for anti-TBEV antibodies using a commercial indirect fluorescent antibody test (IFA) test. Blood samples from 50 healthy donors not exposed to tick bites were included as a control group. Most of the enrolled patients reported infestations with one tick, being I. ricinus the most frequent tick found in the participants. The TBEV seroprevalence was higher (13.27%, 15 total 113) in tick-infested individuals than in healthy donors (4%, 2 total 50), although the difference was not significant. Notably, male individuals exposed to tick bites showed five times higher relative risk (RR) of being TBEV-seropositive than healthy donors of the same gender (RR= 5.1, CI = 1.6–19; p = 0.007). None of the seropositive individuals developed clinical manifestations of TBE, but the first clinical-stage of Lyme borreliosis (i.e., erythema migrans) was detected in seven of them. Potential TBEV foci were identified in rural areas, mostly in proximity or within the Fruška Gora mountain. We conclude that the Serbian population is at high risk of TBEV exposure. Further epidemiological studies should focus on potential TBEV foci identified in this study. The implementation of active surveillance for TBEV might contribute to evaluating the potential negative impact of TBE in Serbia.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".