Evidence map›Paper›PMID 39466807›Full record

ArticlePloS one2024

Modeling spatiotemporal dynamics of Amblyomma americanum questing activity in the central Great Plains.

Marlon E Cobos, Taylor Winters, Ismari Martinez, Yuan Yao, Xiangming Xiao, Anuradha Ghosh, Kellee Sundstrom, Kathryn Duncan, Robert E Brennan, Susan E Little and 1 more

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

11 authors.

Marlon E CobosDepartment of Ecology and Evolutionary Biology & Biodiversity Institute, University of Kansas, Lawrence, KS, United States of America.ORCID 0000-0002-2611-1767
Taylor WintersBiodiversity Institute, University of Kansas, Lawrence, KS, United States of America.
Ismari MartinezBiodiversity Institute, University of Kansas, Lawrence, KS, United States of America.
Yuan YaoSchool of Biological Sciences, Center for Earth Observation and Modeling, University of Oklahoma, Norman, OK, United States of America.
Xiangming XiaoSchool of Biological Sciences, Center for Earth Observation and Modeling, University of Oklahoma, Norman, OK, United States of America.
Anuradha GhoshDepartment of Biology, Pittsburg State University, Pittsburg, KS, United States of America.
Kellee SundstromCollege of Veterinary Medicine, Oklahoma State University, Stillwater, OK, United States of America.
Kathryn DuncanCollege of Veterinary Medicine, Oklahoma State University, Stillwater, OK, United States of America.
Robert E BrennanDepartment of Biology, Center for Interdisciplinary Biomedical Education and Research, University of Central Oklahoma, Edmond, OK, United States of America.ORCID 0000-0002-1287-4069
Susan E LittleCollege of Veterinary Medicine, Oklahoma State University, Stillwater, OK, United States of America.
A Townsend PetersonDepartment of Ecology and Evolutionary Biology & Biodiversity Institute, University of Kansas, Lawrence, KS, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ticks represent important vectors of a number of bacterial and viral disease agents, owing to their hematophagous nature and their questing behavior (the process in which they seek new hosts). Questing activity is notably seasonal with spatiotemporal dynamics that needs to be understood in detail as part of mediating and mitigating tick-borne disease risk. Models of the geography of tick questing activity developed to date, however, have ignored the temporal dimensions of that behavior; more fundamentally, they have often not considered the sampling underlying available occurrence data. Here, we have addressed these shortfalls for Amblyomma americanum, the most commonly encountered tick in the central Great Plains, via (1) detailed, longitudinal sampling to characterize the spatiotemporal dimensions of tick questing activity; (2) randomization tests to establish in which environmental dimensions a species is manifesting selective use; and (3) modeling methods that include both presence data and absence data, taking fullest advantage of the information available in the data resource. The outcome was a detailed picture of geographic and temporal variation in suitability for the species through the two-year course of this study. Such models that take full advantage of available information will be crucial in understanding the risk of tick-borne disease into the future.

Indexed as

AmblyommaSpatio-Temporal AnalysisAnimalsModels, BiologicalSeasons

Identifiers

PMID39466807
PMCPMC11515986

What OpenQuestion holds

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Registered trials

None linked

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.