Evidence map›Paper›PMID 40057413›Full record

ArticleTicks and tick-borne diseases2025

Estimating the density of questing Ixodes scapularis nymphs in the eastern United States using climate and land cover data.

Karen M Holcomb, Erik Foster, Rebecca J Eisen

Abstract read
In one paragraph

Article in Ticks and tick-borne diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. The niche ofOne health (Amsterdam, Netherlands) · 2026
    Article
  2. Why are the ticks winning, and what can we do about it?Ticks and tick-borne diseases · 2026
    Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Karen M HolcombDivision of Vector Borne Diseases, Centers for Disease Control and Prevention, 3156 Rampart Road, Fort Collins, CO 80521 USA. Electronic address: kholcomb@cdc.gov.
Erik FosterDivision of Vector Borne Diseases, Centers for Disease Control and Prevention, 3156 Rampart Road, Fort Collins, CO 80521 USA.
Rebecca J EisenDivision of Vector Borne Diseases, Centers for Disease Control and Prevention, 3156 Rampart Road, Fort Collins, CO 80521 USA.

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

Tick-borne diseases pose a persistent and increasing threat to public health. In the United States, the majority of human infections are caused by pathogens spread by the blacklegged tick, Ixodes scapularis. Most infections are reported during the summer months, when nymphal ticks are active in states in the Northeast and Upper Midwest. The density of questing I. scapularis nymphs (DON) provides an estimate for the risk of human encounters with nymphs, but it is a resource intensive metric to obtain from field sampling. Thus, DON estimates are limited in the US national tick surveillance database, the ArboNET Tick Module. We estimated DON across all counties in the eastern US using a zero-inflated negative binomial model utilizing tick surveillance data reported to ArboNET (2004-2023) as well as climate and land cover data. The model estimated generally low DON across the southeastern US and Great Plains states with higher estimates in the Upper Midwest and Northeast regions. We assigned counties to relative acarological encounter risk categories based on estimated DON: zero or lower quartile DON estimates were scored as low risk, whereas inter- and upper-quartile DON estimates were scored as moderate-high risk. Counties with moderate-high DON reported from field sampling were accurately categorized by the model as moderate-high encounter risk (99 % sensitivity). However, 80 % of sampled counties reporting low DON were classified as moderate-high risk (20 % specificity). These misclassified counties were typically situated in recently colonized areas in the Northeast and Upper Midwest and likely indicated areas potentially suitable for tick population expansion. Our model yielded a very high negative predictive value (96 %) indicating the model did very well estimating low relative encounter risk in counties where no or few nymphs were collected, and a fair positive predictive value (60 %) indicated that densities may not have reached an expected peak in some locations, particularly in the Northeast, Upper Midwest, and northern states in the Southeast. Further tick surveillance is needed to evaluate and to refine these predictions. The resulting maps are useful for estimating relative risk of nymphal encounters across the eastern US where field data are sparse and may aid in efforts aimed at promoting the use of personal protective measures in communities that are at risk for nymphal tick encounters.

Indexed as

Animal DistributionClimateIxodesAnimalsHumansNymphPopulation DensityUnited StatesBlacklegged tickDeer tickEncounter riskHost-seekingSurveillanceZero-inflated negative binomial model

Identifiers

PMID40057413
PMCPMC11925651

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.