2025
BSTVC: Interpreting Spatiotemporal Heterogeneity, Identifying Key Drivers, and Making Dynamic Predictions
A unified Bayesian “full-map” framework for moving from where and when effects vary, to which factors matter most, and finally to what is likely to happen next.
May, 2025. Research Update: Chao Song ‘s research team published a new paper titled “Spatiotemporal disparities in maternal mortality and the role of multiscale administrative levels: a 20-year study across Chinese counties.” We discovered temporally varying but spatially stable inequity patterns in maternal deaths at the county level in China. The contribution from the administrative county-level was the highest (29.15%, 95% CIs: 19.69%−35.06%).
Reference: Liao, L., Yuan, F., He, Y., Shixi, X., Tang, X., Xie, M., … & Song, C. Spatiotemporal disparities in maternal mortality and the role of multiscale administrative levels: a 20-year study across Chinese counties. Frontiers in Public Health, 13*, 1572382.
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April, 2025. Research Update: Chao Song ‘s research team published a Chinese paper titled “Medical Resource Allocation Efficiency in Small Areas: A Spatial-Temporal Evaluation Based on Sichuan County Panel Data (医疗资源配置效率的小区域时空评价：基于四川省县域面板数据的实证研究)” in the journal China Health Service Management (中国卫生事业管理).
Jaunary, 2025. Research Update: Spatial Joint Hazard Assessment of Landslide Susceptibility and Intensity
Chao Song, as the corresponding author, led a collaborative team from Sichuan University’s HEOA-West China Health and Medical Geography Group, along with Southwest Petroleum University, Emory University, the Institute of Geography, Chinese Academy of Sciences, Northeast Normal University, Xi’an Jiaotong University, and the National Institute for Disaster Prevention under the Ministry of Emergency Management. Their groundbreaking study, titled “Spatial Joint Hazard Assessment of Landslide Susceptibility and Intensity within a Single Framework: Environmental Insights from the Wenchuan Earthquake,” was published in **Science of The Total Environment **(2025). https://doi.org/10.1016/j.scitotenv.2025.178545
This research introduces two advanced Bayesian spatial joint regression models—Spatial Shared Component Model (SSCM) and Spatial Shared Hyperparameter Model (SSHM)—to assess both landslide susceptibility and intensity within a unified framework. This innovative approach overcomes previous limitations of separately evaluating these two hazard scenarios, offering a novel geospatial paradigm for multi-objective risk assessment in global environmental disaster management.
Jaunary, 2025. New R pacakage BSTVC (Bayesian Spatiotemporally Varying Coefficients modeling): Spatiotemporal heterogeneous perspective for analyzing influencing factors, identifying key drivers, and making dynamic predictions, all within a unified ‘full-map’ framework. https://github.com/songbi123/BSTVC
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