A SPATIALLY-EXPLICIT STOCHASTIC MODEL FOR THE GULF COAST TICK.

Azmy S Ackleh, Sankar Sikder, Ursula Trigos-Raczkowski, Amy Veprauskas

Abstract read

In one paragraph

Article in Ecological modelling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Azmy S AcklehDEPARTMENT OF MATHEMATICS, UNIVERSITY OF LOUISIANA AT LAFAYETTE, LAFAYETTE, LA 70504-1010, USA.

Sankar SikderDEPARTMENT OF MATHEMATICS, UNIVERSITY OF LOUISIANA AT LAFAYETTE, LAFAYETTE, LA 70504-1010, USA.

Ursula Trigos-RaczkowskiDEPARTMENT OF MATHEMATICS, UNIVERSITY OF LOUISIANA AT LAFAYETTE, LAFAYETTE, LA 70504-1010, USA.

Amy VeprauskasDEPARTMENT OF MATHEMATICS, UNIVERSITY OF LOUISIANA AT LAFAYETTE, LAFAYETTE, LA 70504-1010, USA.

Funding

Spatial eco-epidemiology of tick-borne rickettisal pathogens R01AI136035 · NIAID · OLD DOMINION UNIVERSITY · PI GAFF, HOLLY · 2017 to 2021

$2.4M

NIAID NIH HHS R01 AI136035

6 · The paper itself

Abstract

Tick ecology is complicated and has many potentially negative effects, including disease transmission, host population declines, altered dynamics, and cascading interactions that disrupt entire ecological systems. Such negative effects could be mitigated through a careful analysis and understanding of how ticks disperse over a landscape. In this paper we develop a stage-structured spatially-explicit stochastic model for the Gulf Coast Tick (GCT),

Indexed as

Amblyomma maculatumBird migrationDemographic stochasticityHard ticksRickettsia parkeri rickettsiosisTick control mechanismsTick dispersal

Identifiers

PMID40726950

DOI10.1016/j.ecolmodel.2025.111234

PMCPMC12291094

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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.