Animal Plague Risk Zones in Qinghai Province, China Predicted via MaxEnt Model

A spatial prediction model for animal plague risk zones in Qinghai Province, China, developed using maximum entropy (MaxEnt) modeling. The model was trained on animal plague occurrence data from 1956 to 2022 and environmental variables, achieving an average AUC of 0.827. The research was authored by Yongshun Wang and shared under a CC-BY-4.0 license in April 2026.

Use Cases

• Mapping high-risk zones for plague surveillance based on predicted spatial distribution.
• Estimating human population exposure to plague risk based on the calculated population within predicted zones.
• Analyzing the influence of environmental factors like terrain and land use on plague distribution based on the model variables.
• Supporting targeted intervention strategies for plague prevention and control based on the model's spatial predictions.

Strengths

• Model performance is quantitatively reported with an average AUC of 0.827 and TSS of 0.5 on testing datasets.
• Provides concrete spatial outputs, predicting risk zones covering 234,000 km² and affecting an estimated 3.902 million people.
• Uses a long-term temporal range for occurrence data, spanning from 1956 to 2022.

Limitations

• The dataset is a 22.3 KB DOCX file, which suggests the primary data may be embedded in a document format rather than a structured data file.
• Column-level documentation is absent; field semantics and raw model inputs must be inferred after download.
• The description focuses on model results; the availability of the underlying occurrence and environmental data for reuse is unclear.

Provenance

Source

figshare, author Yongshun Wang.

Collection Method

Data on animal plague occurrence sites were collected and combined with terrain, bioclimatic, land use, and human disturbance variables for MaxEnt modeling.

Time Range

1956 to 2022

Freshness

Last updated 2026-04-28 04:29:05; freshness should be verified.

Geography

Qinghai Province, China