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Predicting the Spatial Distribution of Hyalomma ssp., Vector Ticks of Crimean–Congo Haemorrhagic Fever in Iraq

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  • Nabaz R. Khwarahm

    (Department of Biology, College of Education, University of Sulaimani, Sulaimani 334, Kurdistan Region, Iraq)

Abstract

Crimean–Congo hemorrhagic fever (CCHF) typically spreads through ticks and is categorized as a viral hemorrhagic fever. CCHF is a fatal endemic disease in Iraq, and it has been reported sporadically since its first report in 1979. Recent outbreaks during 2021–2023 and their fatal consequences captured the interest of this study. CCHF is a tick-borne disease that represents a major challenge to the public health, social, and economic sectors. The geographical distribution of CCHF is closely linked with Hyalomma vector tick distribution. Therefore, predicting and mapping the spatial distribution of the disease vector in relation to relevant environmental factors provides invaluable information for establishing an early warning system based on which preventive measures can be taken to minimize the spread and, hence, the fatal consequences of CCHF. To achieve this, this study incorporates geospatial techniques and maximum entropy modeling (Maxent) to assess the habitat suitability of the Hyalomma vector and to identify the key environmental drivers contributing to its spatial distribution in Iraq. Utilizing the area under the ROC curve (AUC) as the performance metric, the model evaluation yielded successful results in predicting habitat suitability for Hyalomma vector ticks in Iraq. The AUC attained an average score of 0.885 with a regularization multiplier (β) set at 1. The Hyalomma ticks’ suitable habitat distribution within the study area covers a fraction of the total land, at approximately 51% (225,665 km 2 ) of the entire 441,724 km 2 region. Among these suitable areas, 41.57% (183,631 km 2 ) were classified as lowly suitable, 8.61% (38,039 km 2 ) as moderately suitable, and 0.9% (3994 km 2 ) as highly suitable. Several factors have significantly influenced Hyalomma vector tick distribution in Iraq. These include land cover (accounting for 50.8%), elevation (contributing 30.4%), NDVI (5.7%), temperature seasonality (4.7%), precipitation seasonality (3.3%), sheep density (2.3%), goat density (2.2%), and the mean diurnal range (0.5%). The findings of this study could have significant implications for establishing a strategic early warning system and taking preventive measures beforehand to minimize and control Crimean–Congo haemorrhagic fever in Iraq and similar ecoregions in the Middle East. As a primary precaution, this study recommends focusing on highly suitable areas (3994 km 2 ) in the southern part of Iraq for management and preventive actions.

Suggested Citation

  • Nabaz R. Khwarahm, 2023. "Predicting the Spatial Distribution of Hyalomma ssp., Vector Ticks of Crimean–Congo Haemorrhagic Fever in Iraq," Sustainability, MDPI, vol. 15(18), pages 1-13, September.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13669-:d:1238867
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    References listed on IDEAS

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    1. Kalthum O. Radha & Nabaz R. Khwarahm, 2022. "An Integrated Approach to Map the Impact of Climate Change on the Distributions of Crataegus azarolus and Crataegus monogyna in Kurdistan Region, Iraq," Sustainability, MDPI, vol. 14(21), pages 1-31, November.
    2. Barham A. HamadAmin & Nabaz R. Khwarahm, 2023. "Mapping Impacts of Climate Change on the Distributions of Two Endemic Tree Species under Socioeconomic Pathway Scenarios (SSP)," Sustainability, MDPI, vol. 15(6), pages 1-25, March.
    3. Carla Ippoliti & Luca Candeloro & Marius Gilbert & Maria Goffredo & Giuseppe Mancini & Gabriele Curci & Serena Falasca & Susanna Tora & Alessio Di Lorenzo & Michela Quaglia & Annamaria Conte, 2019. "Defining ecological regions in Italy based on a multivariate clustering approach: A first step towards a targeted vector borne disease surveillance," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-21, July.
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    1. Junwei Wang & Zhefei Zeng & Yonghao Chen & Qiong La, 2024. "Predicting the Potential Risk Area of the Invasive Plant Galinsoga parviflora in Tibet Using the MaxEnt Model," Sustainability, MDPI, vol. 16(11), pages 1-15, May.

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