Lyme Borreliosis and Tick Surveillance Epidemiology in the WHO Regions of the Americas, Eastern Mediterranean, Europe, South-East Asia, and Western Pacific: A Systematic Literature Review (2005–2022) Beyond North America (Canada, United States of America), European Union Countries, and China
Bibliographic record
Abstract
Background and Methods: This Lyme borreliosis (LB) and Borrelia burgdorferi sensu lato (Bbsl)-infected Ixodes ticks surveillance review—from the WHO regions of the Americas, Eastern Mediterranean, Europe, South-East Asia, and Western Pacific—is informed by LB cases or incidence, Bbsl antibody seroprevalence, and Ixodes ( I. ) tick surveillance results from publications (2005–2022) and recent government websites. Results: LB cases, by the WHO region—country, were documented in the following: the Americas—Brazil and México; Europe—Russian Federation and Türkiye; South-East Asia—India; and Western Pacific—Japan, Mongolia, and South Korea. Mean incidence, cases/100,000 population per year (country, period), was as follows: Europe, 4.8 (Russian Federation, 2009–2021); Western Pacific, 0.01 (Japan, 2005–2021) and 0.03 (South Korea, 2012–2021). Two-tier testing Bbsl antibody seroprevalence estimate ranges were as follows: the Americas, 1.0–6.2% (Brazil), 4.6% (Colombia), and 23.1% (México); Europe, 0–15.8% (Türkiye); South-East Asia, 0.4–3.0% (India); and Western Pacific, 0–14.0% (Mongolia). Ixodes tick surveillance was presented by species (nymph, adult, or not reported, NR, life stage and [Bbsl-infected proportion]): the Americas—México, I. scapularis (NR [34.2%]); Eastern Mediterranean—Iran, I. ricinus (adult [0.9% Borrelia ]); Europe—Russian Federation, I. ricinus (nymph [27.3%], nymph/adult [33.4%], adult/NR [9.8–80.4%]) and I. persulcatus (adult/NR [12.0–75.3%]) and Türkiye, I. ricinus (adult/NR [19.9%]); and Western Pacific—Japan, I. persulcatus (nymph [0–10.0%], nymph/adult [1.8–23.6%], adult/NR [detected–up to 25.5%]) and Mongolia, I. persulcatus (nymph [detected], nymph/adult [49.4%], adult [7.0–49.7%]). Conclusions: LB burden might be underrecognized in certain countries of the Americas, Eastern Mediterranean, and South-East Asia, whereas LB cases or incidence, Bbsl antibody seroprevalence, and Bbsl-infected tick presence is established in certain countries of WHO Europe (Russian Federation and Türkiye) and Western Pacific (Japan, Korea, and Mongolia), and LB could be present in neighboring countries within these WHO regions (PROSPERO: CRD42021236906).
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".