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Identification of the high-risk area for schistosomiasis transmission in China based on information value and machine learning: a newly data-driven modeling attempt

Crossref DOI link: https://doi.org/10.1186/s40249-021-00874-9

Published Online: 2021-06-27

Published Print: 2021-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Gong, Yan-Feng

Zhu, Ling-Qian

Li, Yin-Long

Zhang, Li-Juan

Xue, Jing-Bo

Xia, Shang

Lv, Shan

Xu, Jing

Li, Shi-Zhu http://orcid.org/0000-0003-3172-5218
Funding

Funding for this research was provided by:

National Major Science and Technology Projects of China (2016ZX10004222-004)

the Fifth Round ofThree-Year Public Health Action Plan of Shanghai (GWV-10.1-XK13)
License Information

Text and Data Mining valid from 2021-06-27

Version of Record valid from 2021-06-27
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Article History

Received: 21 April 2021

Accepted: 15 June 2021

First Online: 27 June 2021

Declarations

:

: This paper was based on an analysis of routinely collected surveillance data from national institute of parasitic diseases, China CDC. No individual information was revealed.

: Not applicable.

: The authors declare that they have no competing interests.

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