TY - JOUR
T1 - Camel tick species distribution in Saudi Arabia and United Arab Emirates using MaxEnt modelling
AU - Perveen, Nighat
AU - Muzaffar, Sabir B.
AU - Jaradat, Areej
AU - Sparagano, Olivier A.
AU - Willingham, Arve L.
N1 - Publisher Copyright:
Copyright © The Author(s), 2024. Published by Cambridge University Press.
PY - 2024/8/1
Y1 - 2024/8/1
N2 - 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.
AB - 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.
KW - Hyalomma dromedarii
KW - MaxEnt
KW - Saudi Arabia
KW - UAE
KW - camel tick
KW - modelling
KW - species distribution
UR - http://www.scopus.com/inward/record.url?scp=85210389536&partnerID=8YFLogxK
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U2 - 10.1017/S0031182024001161
DO - 10.1017/S0031182024001161
M3 - Article
C2 - 39696876
AN - SCOPUS:85210389536
SN - 0031-1820
VL - 151
SP - 1024
EP - 1034
JO - Parasitology
JF - Parasitology
IS - 9
ER -