Assessment of entomological risk for Lyme borreliosis along a north-to-south gradient from southern Virginia into North Carolina
Bibliographic record
Abstract
Lyme disease (LD) has become the most prevalent vector-borne disease in the United States and the sixth Nationally Notifiable disease. Surveillance of Lyme disease from the 1992-2016 has shown a sustained documented expansion of LD moving south into the border of Virginia and North Carolina, west into West Virginia, Tennessee, northwest into North Dakota, and North into Canada. This expansion of LD seems to be associated with expansion of the disease vector Ixodes scapularis, with newly established populations in the southwestern Appalachian and Piedmont regions of Virginia. The goal of the study was to characterize the entomological risk of the spread of LD from VA into NC. To determine the distribution and infection prevalence of I. scapularis along a northeastern-to-southwestern gradient from VA to NC, tick-flagging and hunter-harvested deer tick collecting approaches were used with samples tested by the CDC for infection. Flagging was comprised of periodic sampling sessions from October 2015 to July 2017, conducted at Fairy Stone, Mayo River, Hanging Rock, Pilot Mountain, Yadkin Island Park, and Lake Norman State Parks. Hunted deer processing stations Hilltop Farms (Walnut Cove, NC) and Game Butchers (Troutman, NC), were used for collecting ticks from hunter-harvested deer covering counties for the northern, central and southern North Carolina Piedmont regions. Ticks collected by flagging were suggestive of a north-to-south trend with no significant difference among the northernmost State Parks and a significant difference in abundance between the northern and southernmost State Parks. The highest number of I. scapularis ticks (0.7 per 100m) was collected from the north-most Virginia’s Fairy Stone and Hanging Rock State Parks, but no I. scapularis were collected from the southernmost Lake Norman location. Infection prevalence of ticks collected by flagging exhibited a general north-to-south declining trend. Though not statistically significant with highest infection rate approximately 25% at the north-most Fairy Stone State Park. For deer collected ticks, there was a significant north-to-south decrease in tick burden per deer, with the northern region located on the VA-NC border having the highest number of I. scapularis (6.0 per deer), followed by the central and the southern regions of NC. Infection prevalence of sampled ticks from deer are suggestive of a declining trend although not significant, with the northern region having the highest (17%), followed by the central region (11%), and no infection present in the southern region. Ixodes scapularis results collected from flagging, and hunter-harvested deer are highly suggestive of a north-to-south gradient in I. scapularis densities with Alexander and Iredell being the south-most I. scapularis positive counties. Borrelia burgdorferi infection results also suggest a north-to-south distribution, with B. burgdorferi appearing to have only made it as far south as the central counties of Yadkin and Forsyth. Entomological risk estimates for density of infected nymphs (DIN) and adults (DIA) of flagging and hunted deer also showed a north-to-south trend with Fairy Stone State Park having the highest (0.033) DIN and northern NC region having the highest (0.808) DIA. The results are consistent with first the spread of the vector followed by the pathogen.
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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 | 0.000 |
| 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 | 0.001 |
| 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".