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Influence of Host and Environmental Factors on the Distribution of the Japanese Encephalitis Vector Culex tritaeniorhynchus in China

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Listed:
  • Boyang Liu

    (Department of Veterinary Surgery, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China)

  • Xiang Gao

    (Department of Veterinary Surgery, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China)

  • Jun Ma

    (Department of Veterinary Surgery, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China)

  • Zhihui Jiao

    (Department of Veterinary Surgery, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China)

  • Jianhua Xiao

    (Department of Veterinary Surgery, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China)

  • Hongbin Wang

    (Department of Veterinary Surgery, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China)

Abstract

Culex tritaeniorhynchus is an important vector that transmits a variety of human and animal diseases. Japanese encephalitis (JE), an endemic disease in the Asia-Pacific region, is primarily transmitted by Cx. tritaeniorhynchus . Insufficient monitoring of vector mosquitoes has led to a poor understanding of the distribution of Cx. tritaeniorhynchus in China. To delineate the habitat of Cx. tritaeniorhynchus and any host and environmental factors that affect its distribution, we used a maximum entropy modeling method to predict its distribution in China. Our models provided high resolution predictions on the potential distribution of Cx. tritaeniorhynchus . The predicted suitable habitats of the JE vector were correlated with areas of high JE incidence in parts of China. Factors driving the distribution of Cx. tritaeniorhynchus in China were also revealed by our models. Furthermore, human population density and the maximum NDVI were the most important predictors in our models. Bioclimate factors and elevation also significantly impacted the distribution of Cx. tritaeniorhynchus . Our findings may serve as a reference for vector and disease control.

Suggested Citation

  • Boyang Liu & Xiang Gao & Jun Ma & Zhihui Jiao & Jianhua Xiao & Hongbin Wang, 2018. "Influence of Host and Environmental Factors on the Distribution of the Japanese Encephalitis Vector Culex tritaeniorhynchus in China," IJERPH, MDPI, vol. 15(9), pages 1-15, August.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:9:p:1848-:d:166048
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    References listed on IDEAS

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    1. Qiang Zhang & Jianfeng Li & Vijay Singh & Yungang Bai, 2012. "SPI-based evaluation of drought events in Xinjiang, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 64(1), pages 481-492, October.
    2. Bipin Kumar Acharya & Chunxiang Cao & Min Xu & Laxman Khanal & Shahid Naeem & Shreejana Pandit, 2018. "Present and Future of Dengue Fever in Nepal: Mapping Climatic Suitability by Ecological Niche Model," IJERPH, MDPI, vol. 15(2), pages 1-15, January.
    3. Shcheglovitova, Mariya & Anderson, Robert P., 2013. "Estimating optimal complexity for ecological niche models: A jackknife approach for species with small sample sizes," Ecological Modelling, Elsevier, vol. 269(C), pages 9-17.
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    Cited by:

    1. Yixin Tong & Honglin Jiang & Ning Xu & Zhengzhong Wang & Ying Xiong & Jiangfan Yin & Junhui Huang & Yue Chen & Qingwu Jiang & Yibiao Zhou, 2023. "Global Distribution of Culex tritaeniorhynchus and Impact Factors," IJERPH, MDPI, vol. 20(6), pages 1-15, March.

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