Evidence map›Paper›PMID 33639938›Full record

ArticleBMC veterinary research2021

Spatial clustering of fourteen tick species across districts of Zimbabwe.

Munyaradzi Davis Shekede, Silvester Maravanyika Chikerema, Moregood Spargo, Isaiah Gwitira, Samuel Kusangaya, Aldridge Nyasha Mazhindu, Daud Nyosi Ndhlovu

Open access · goldAbstract read
In one paragraph

Article in BMC veterinary research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.1field-weighted citation impact, top 15% of its field
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

11 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
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  5. Observational
  6. The veterinary quarterly · 2024
    Article
  7. Article
  8. Parasitology · 2024
    Article
  9. Article
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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

7 authors at 1 institution in 1 country.

Munyaradzi Davis ShekedeDepartment of Geography Geospatial Sciences and Earth Observation, Faculty of Science, University of Zimbabwe, MP167 Mount Pleasant, Harare, Zimbabwe. shekede@gmail.com.ORCID http://orcid.org/0000-0002-6540-3316
Silvester Maravanyika ChikeremaDepartment of Clinical Veterinary Studies, Faculty of Veterinary Science, University of Zimbabwe, MP167 Mount Pleasant, Harare, Zimbabwe.
Moregood SpargoDepartment of Livestock and Veterinary Services, 18 Borrowdale Rd, Harare, Zimbabwe.
Isaiah GwitiraDepartment of Geography Geospatial Sciences and Earth Observation, Faculty of Science, University of Zimbabwe, MP167 Mount Pleasant, Harare, Zimbabwe.
Samuel KusangayaDepartment of Geography Geospatial Sciences and Earth Observation, Faculty of Science, University of Zimbabwe, MP167 Mount Pleasant, Harare, Zimbabwe.
Aldridge Nyasha MazhinduDepartment of Geography Geospatial Sciences and Earth Observation, Faculty of Science, University of Zimbabwe, MP167 Mount Pleasant, Harare, Zimbabwe.
Daud Nyosi NdhlovuDepartment of Clinical Veterinary Studies, Faculty of Veterinary Science, University of Zimbabwe, MP167 Mount Pleasant, Harare, Zimbabwe.
University of Zimbabwe · ZW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTicks transmit several diseases that result in high morbidity and mortality in livestock. Tick-borne diseases are an economic burden that negatively affect livestock production, cost countries billions of dollars through vaccine procurement and other disease management efforts. Thus, understanding the spatial distribution of tick hotspots is critical for identifying potential areas of high tick-borne disease transmission and setting up priority areas for targeted tick disease management. In this study, optimised hotspot analysis was applied to detect hotspots and coldspots of 14 common tick species in Zimbabwe. Data on the spatial distribution of tick species were obtained from the Epidemiology Unit of the Division of Veterinary Field Services of Zimbabwe.

resultsA total of 55,133 ticks were collected with Rhipicephalus decoloratus being the most common species (28.7%), followed by Amblyomma hebraeum (20.6%), and Rhipicephalus sanguineus sensu lato (0.06%) being the least common species. Results also showed that tick hotspots are species-specific with particular tick species occupying defined localities in the country. For instance, Amblyomma variegatum, Rhipicephalus appendiculatus, Rhipicephalus decoloratus, Rhipicephalus compostus, Rhipicephalus microplus, Rhipicephalus pravus, and Rhipicephalus simus were concentrated in the north and north eastern districts of the country. In contrast, Amblyomma hebraeum, Hyalomma rufipes, Hyalomma trancatum and Rhipicephalus evertsi evertsi were prevalent in the southern districts of Zimbabwe.

conclusionThe occurrence of broadly similar hotspots of several tick species in different districts suggests presence of spatial overlaps in the niche of the tick species. As ticks are vectors of several tick-borne diseases, there is high likelihood of multiple disease transmission in the same geographic region. This study is the first in Zimbabwe to demonstrate unique spatial patterns in the distribution of several tick species across the country. The results of this study provide an important opportunity for the development of spatially-targeted tick-borne disease management strategies.

Indexed as

Spatial AnalysisAnimal DistributionAnimalsArachnid VectorsIxodidaeZimbabweDisease managementGetis-Ord Gi* statisticHotspotsLivestock disease transmissionTick species

Identifiers

PMID33639938
PMCPMC7913385
OpenAlexW3133557000

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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.