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Mapping ticks and tick-borne pathogens in China.

Guo-Ping ZhaoYi-Xing WangZheng-Wei FanYang JiMing-Jin LiuWen-Hui ZhangXin-Lou LiShi-Xia ZhouHao LiSong LiangWei LiuYang YangLi-Qun Fang
Published in: Nature communications (2021)
Understanding ecological niches of major tick species and prevalent tick-borne pathogens is crucial for efficient surveillance and control of tick-borne diseases. Here we provide an up-to-date review on the spatial distributions of ticks and tick-borne pathogens in China. We map at the county level 124 tick species, 103 tick-borne agents, and human cases infected with 29 species (subspecies) of tick-borne pathogens that were reported in China during 1950-2018. Haemaphysalis longicornis is found to harbor the highest variety of tick-borne agents, followed by Ixodes persulcatus, Dermacentor nutalli and Rhipicephalus microplus. Using a machine learning algorithm, we assess ecoclimatic and socioenvironmental drivers for the distributions of 19 predominant vector ticks and two tick-borne pathogens associated with the highest disease burden. The model-predicted suitable habitats for the 19 tick species are 14‒476% larger in size than the geographic areas where these species were detected, indicating severe under-detection. Tick species harboring pathogens of imminent threats to public health should be prioritized for more active field surveillance.
Keyphrases
  • public health
  • gram negative
  • machine learning
  • antimicrobial resistance
  • genetic diversity
  • endothelial cells
  • multidrug resistant
  • deep learning
  • high resolution
  • risk assessment
  • climate change
  • infectious diseases