[Prediction of potential geographic distribution of <i>Oncomelania hupensis</i> in Yunnan Province using random forest and maximum entropy models].
Both RF and MaxEnt models are effective to predict the potential distribution of <i>O. hupensis</i> snails in Yunnan Province, which facilitates targeted <i>O. hupensis</i> snail control.
Authors
- Zhibing Zhang (ORCID: https://orcid.org/0000-0003-2797-9098)
- Xue Jing (ORCID: https://orcid.org/0000-0001-6957-1811)
- Miaogen Shen (ORCID: https://orcid.org/0000-0001-5742-8807)
- Jinxi Song (ORCID: https://orcid.org/0000-0001-9838-8063)
- L Wang
- Jinxin Zhou (ORCID: https://orcid.org/0000-0002-1806-944X)
- Xiao Feng (ORCID: https://orcid.org/0000-0003-4638-3927)
- Shumin Li (ORCID: https://orcid.org/0000-0001-8083-1071)
- Chen Chen (ORCID: https://orcid.org/0000-0003-3957-7061)
- Ye Zhang (ORCID: https://orcid.org/0009-0000-4883-8097)
- Hao Wang (ORCID: https://orcid.org/0000-0002-1708-8075)
- Yi Dong (ORCID: https://orcid.org/0000-0003-3047-7777)
- Hongtao Jiang (ORCID: https://orcid.org/0000-0002-5416-548X)
- Cong Du (ORCID: https://orcid.org/0000-0003-4179-2836)
- Jun Yan (ORCID: https://orcid.org/0000-0002-9948-242X)
- Jun Sun (ORCID: https://orcid.org/0000-0001-7369-7871)
- Peijun Qian
- Xilin Wang (ORCID: https://orcid.org/0000-0002-5285-365X)
Institutions
- Yunnan Institute of Endemic Diseases Control and Prevention (CN)
Publication Details
- Journal
- PubMed
- Published
- 2024-12-12
- DOI
- https://doi.org/10.16250/j.32.1915.2024136
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article