MétaCan
Menu
Back to cohort
Record W4385212919 · doi:10.1016/j.ttbdis.2023.102233

Changes in the geographic distribution of the blacklegged tick, Ixodes scapularis, in the United States

2023· review· en· W4385212919 on OpenAlexaboutno aff
Lars Eisen, Rebecca J. Eisen

Bibliographic record

VenueTicks and Tick-borne Diseases · 2023
Typereview
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsnot available
FundersAnimal and Plant Health Inspection ServiceNational Oceanic and Atmospheric AdministrationNational Institutes of HealthGeorgia Southern UniversityU.S. Department of Agriculture
KeywordsIxodes scapularisTickOdocoileusBiologyPopulationEcologyRange (aeronautics)GeographyIxodidaeDemography

Abstract

fetched live from OpenAlex

Ixodes scapularis (the blacklegged tick) was considered a species of no medical concern until the mid-1970s. By that time, the tick's geographic distribution was thought to be mainly in the southeastern United States (US), with additional localized populations along the Eastern Seaboard north to southern Massachusetts and in the Upper Midwest. Since 1975, I. scapularis has been implicated as a vector of seven human pathogens and is now widely distributed across the eastern US up to the border with Canada. Geographic expansion of tick-borne diseases associated with I. scapularis (e.g., Lyme disease, anaplasmosis, and babesiosis) is attributed to an expanding range of the tick. However, due to changes in tick surveillance efforts over time, it is difficult to differentiate between range expansion and increased recognition of already established tick populations. We provide a history of the documented occurrence of I. scapularis in the US from its description in 1821 to present, emphasizing studies that provide evidence of expansion of the geographic distribution of the tick. Deforestation and decimation of the white-tailed deer (Odocoileus virginianus), the primary reproductive host for I. scapularis adults, during the 1800s presumably led to the tick disappearing from large areas of the eastern US where it previously had been established. Subsequent reforestation and deer population recovery, together with recent climate warming, contributed to I. scapularis proliferating in and spreading from refugia where it had persisted into the early 1900s. From documented tick collection records, it appears I. scapularis was present in numerous locations in the southern part of the eastern US in the early 1900s, whereas in the north it likely was limited to a small number of refugia sites during that time period. There is clear evidence for established populations of I. scapularis in coastal New York and Massachusetts by 1950, and in northwestern Wisconsin by the late 1960s. While recognizing that surveillance for I. scapularis increased dramatically from the 1980s onward, we describe multiple instances of clearly documented expansion of the tick's geographic distribution in the Northeast, Upper Midwest, and Ohio Valley regions from the 1980s to present. Spread and local population increase of I. scapularis, together with documentation of Borrelia burgdorferi sensu stricto in host-seeking ticks, was universally followed by increases in Lyme disease cases in these areas. Southward expansion of northern populations of I. scapularis, for which the host questing behavior of the nymphal stage leads to substantially higher risk of human bites compared with southern populations, into Virginia and North Carolina also was followed by rising numbers of Lyme disease cases. Ongoing surveillance of ticks and tick-borne pathogens is essential to provide the data needed for studies that seek to evaluate the relative roles of land cover, tick hosts, and climate in explaining and predicting geographic expansion of ticks and tick-borne diseases.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.077
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.025
GPT teacher head0.285
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations102
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueTicks and Tick-borne DiseasesSame topicVector-borne infectious diseasesFrench-language works237,207