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Camel tick species distribution in Saudi Arabia and United Arab Emirates using MaxEnt modelling

Nighat Perveen, Sabir B. Muzaffar, Areej Jaradat, Olivier A. Sparagano, Arve L. Willingham*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

19 Downloads (CityUHK Scholars)

Abstract

Ticks are important vectors and reservoirs of pathogens causing zoonotic diseases in camels and other livestock, rodents and other small mammals, birds and humans. Hyalomma dromedarii is the most abundant tick species in Saudi Arabia and United Arab Emirates (UAE) affecting primarily camels, and to a lesser extent, other livestock. Species presence data, land use/landcover, elevation, slope and 19 bioclimatic variables were used to model current and future distribution of H. dromedarii ticks using maximum entropy species distribution modelling (MaxEnt.). The model highlighted areas in the northern, eastern and southwestern parts of the study area as highly suitable for ticks. Several variables including land use/land cover (LULC) (53.1%), precipitation of coldest quarter (Bio19) (21.8%), elevation (20.6%), isothermality (Bio3) (1.9%), mean diurnal range [mean of monthly (max temp – min temp)] (Bio2) (1.8%), slope (0.5%), precipitation, seasonality (Bio15) (0.2%) influenced habitat suitability of ticks, predicting high tick density or abundance. Middle of the road scenario (ssp2-4.5) where CO2 levels remain similar to current levels, did not indicate a major change in the tick distributions. This tick distribution model could be used for targeting surveillance efforts and increasing the efficiency and accuracy of public health investigations and vector control strategies. © The Author(s), 2024. Published by Cambridge University Press
Original languageEnglish
Pages (from-to)1024-1034
JournalParasitology
Volume151
Issue number9
Online published19 Dec 2024
DOIs
Publication statusPublished - 2024

Research Keywords

  • camel tick
  • Hyalomma dromedarii
  • MaxEnt
  • modelling
  • Saudi Arabia
  • species distribution
  • UAE

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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