Evidence map›Paper›PMID 38388882›Full record

ArticleExperimental & applied acarology2024

High-resolution prediction models for Rhipicephalus microplus and Amblyomma cajennense s.l. ticks affecting cattle and their spatial distribution in continental Ecuador using bioclimatic factors.

Ximena Pérez-Otáñez, Richar Rodríguez-Hidalgo, Sandra Enríquez, Maritza Celi-Erazo, Washington Benítez, Claude Saegerman, Franklin Vaca-Moyano, Lenin Ron-Garrido, Sophie O Vanwambeke

Abstract read
In one paragraph

Article in Experimental & applied acarology, 2024. 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.

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Acaricide resistance inFrontiers in veterinary science · 2026
    Article
  3. Article
  4. Review
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

9 authors.

Ximena Pérez-OtáñezInstituto de Investigación en Zoonosis-CIZ, Universidad Central del Ecuador, Quito, Ecuador. ximena.perezotanez@uclouvain.be.
Richar Rodríguez-HidalgoInstituto de Investigación en Zoonosis-CIZ, Universidad Central del Ecuador, Quito, Ecuador.
Sandra EnríquezInstituto de Investigación en Zoonosis-CIZ, Universidad Central del Ecuador, Quito, Ecuador.
Maritza Celi-ErazoInstituto de Investigación en Zoonosis-CIZ, Universidad Central del Ecuador, Quito, Ecuador.
Washington BenítezInstituto de Investigación en Zoonosis-CIZ, Universidad Central del Ecuador, Quito, Ecuador.
Claude SaegermanResearch Unit of Epidemiology and Risk Analysis Applied to Veterinary Science (UREAR-ULiège), Fundamental and Applied Research for Animals & Health (FARAH) Center, Faculty of Veterinary Medicine, University of Liege, Liège, Belgium.
Franklin Vaca-MoyanoInstituto de Investigación en Zoonosis-CIZ, Universidad Central del Ecuador, Quito, Ecuador.
Lenin Ron-GarridoInstituto de Investigación en Zoonosis-CIZ, Universidad Central del Ecuador, Quito, Ecuador.
Sophie O VanwambekeCenter for Earth and Climate Research, Earth & Life Institute, Université Catholique de Louvain-UCLouvain, Louvain-La-Neuve, Belgium.

Funding

Academy of Research and Higher Education (ARES) through the Research for Development Project (PRD) B1.31203.006-E6Belgian Development Cooperation (DGD), Ministry of Agriculture and Livestock of Ecuador (MAG), and Universidad Central del Ecuador (UCE). SENPLADES-SGPBV-2012-0237- OF-Programa Nacional de Cárnicos
6 · The paper itself

Abstract

In Ecuador, the main tick species affecting cattle are Rhipicephalus microplus and Amblyomma cajennense sensu lato. Understanding their spatial distribution is crucial. To assess their distribution, data from 2895 farms visited between 2012 and 2017 were utilized. Ticks were collected during animal inspections, with each farm's location georeferenced. Bioclimatic variables and vapor pressure deficit data were obtained from Climatologies at High resolution for the Earth´s Land Surface Areas (CHELSA) dataset. They were overlaid to develop predictive maps for each species using Random Forest (RF) models. The cross-validation results for RF prediction models showed high accuracy for both R. microplus and A. cajennense s.l. presence with values of accuracy = 0.97 and 0.98, sensitivity = 0.96 and 0.99, and specificity = 0.96 and 0.93, respectively. A carefully selected subset of bioclimatic variables was used to describe the presence of each tick species. Higher levels of precipitation had positive effect on the presence of R. microplus but a negative effect on A. cajennense s.l. In contrast, isothermality (BIO3) was more important for the presence of A. cajennense s.l. compared to R. microplus. As a result, R. microplus had a broader distribution across the country, while A. cajennense s.l. was mainly found in coastal areas with evident seasonality. The coexistence of both species in some regions could be attributed to transitional zones, whereas high altitudes limited tick presence. This information can aid in developing appropriate tick management plans, particularly considering A. cajennense s.l.'s broad host range species and R. microplus's specificity for cattle. Moreover, the predictive models can identify areas at risk of associated challenging hemoparasite, requiring special attention and mitigation measures.

Indexed as

AmblyommaAnimal DistributionCattle DiseasesClimateRhipicephalusTick InfestationsAnimalsCattleEcuadorAmblyomma cajennense s.l.BioclimaticCattle ticksDistribution modelEcuadorRhipicephalus microplusSuitability

Identifiers

PMID38388882
PMCPMC11035444

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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.