2020
December 1, 2020. Academic post: Bayesian Spatiotemporally Varying Coefficients (STVC) model: Exploring spatiotemporal nonstationarity for health geography phenomena.
October 2020. Personnel change: Chao Song, as associate professor, joined the Department of Health Related Social and Behavioral Science, West China School of Public Health (West China Fourth Hospital), Sichuan University (SCU). His major task will revolve around research and teaching on Health GIScience, Medical Geography, and Spatiotemporal Statistics.
Meantime, Chao Song serves as a research fellow at the Institute for Healthy Cities under the guidance of PI Pan Jay.
September 2020. Chao Song (PI) was funded by the general project of the National Natural Science Foundation of China (NSFC) (2021-2024). This four-year general project will focus on further developing the cutting-edge Bayesian STVC modeling framework and employing the improved local spatiotemporal models to solve the frontier science problems of maternal health in China.
September 2020. Science blog (in Chinese) “Bayesian Spatiotemporally Varying Coefficients (STVC) model: Exploring spatiotemporal nonstationarity for health geography phenomena” invited by WeChat Official Account “GIS and Health” belonging to CPGIS (The international association of Chinese professionals in geographic information sciences).
August 13, 2020. Academic work from Chao Song’s team has been officially published in the journal Int. J. Environ. Res. Public Health (SSCI Q1, SCI, IF=2.849). In this study, we validated the hypothetical theories that both environmental and socioeconomic aspects had pivotal roles in affecting the small-area healthcare resource inequalities, and such covariate impacts varied locally (heterogeneity) along with both space and time scales, which had been supported by an advanced Bayesian STVC modeling of the county-level hospital beds data in southwest China. The article information is listed below.
Song, C.*1; Wang, Y.1; Yang, X.; Yang, Y.; Tang, Z.; Wang, X.; Pan, J*. Spatial and Temporal Impacts of Socioeconomic and Environmental Factors on Healthcare Resources: A County-Level Bayesian Local Spatiotemporal Regression Modeling Study of Hospital Beds in Southwest China. Int. J. Environ. Res. Public Health 2020, 17, 5890. DOI: https://doi.org/10.3390/ijerph17165890
Spatial and temporal autocorrelated nonstationarity in various healthcare-covariate relationships detected by the Bayesian STVC model. DOI: https://doi.org/10.3390/ijerph17165890
August 11, 2020. Chao Song started reviewing a revised research article for the journal IJGIS.
June 23, 2020. Chao Song reviewed a research article for the journal Scientific Reports.
June 2020. Academic article published: Chao Song’s first author article titled “Spatiotemporally Varying Coefficients (STVC) model: a Bayesian local regression to detect spatial and temporal nonstationarity in variables relationships ” was accepted in the journal Annals of GIS (ESCI). DOI:10.1080/19475683.2020.1782469.
In this article, we presented a literature review of the theoretical statistical basis of the newly proposed Bayesian Spatiotemporally Varying Coefficients (STVC) model, which is the first Bayesian-based local spatiotemporal regression method to detect spatial and temporal nonstationarity in heterogeneous relationships among variables. A general formula paradigm of Bayesian STVC modeling was introduced in detail for the first time, to provide a guideline for practitioners to develop custom-built STVC models to solve broader issues in the real world. We further applied the Bayesian STVC model to firstly explore the spatiotemporal heterogeneous relationships between the county-level healthcare resources and various socioeconomic conditions in northeast China for ten years, expanding the limited knowledge of the complex local-scale healthcare equalities.
May 2020. Chao Song reviewed a revised research article for the journal Environmental Science and Pollution Research.
April 2020. STVCapp (closed beta version 1.02), a web application to detect spatiotemporal nonstationarity in variables relationships supported by the Bayesian STVC model, was newly developed. Spatiotemporally Varying Coefficients (STVC) model is a Bayesian-based local spatiotemporal regression with the aim of simultaneously detecting spatial and temporal nonstationarity in response-covariates relations, through separately estimating posterior local-scale coefficients over different space areas and periods of time (Song, et al. 2019).
Mar. 2020. Chao Song (Principle Investigator, PI) was funded by two projects on spatiotemporal modeling of healthcare resources over China, namely, the Applied Basic Research Funded Project of Sichuan Science and Technology Department (No. 2020YJ0117), and the Humanities and Social Sciences Research Fund Project of Southwest Petroleum University (No. 2019RW021).
Mar. 2020, Chao Song started serving as a member of the Health-GIS Committee of CPGIS (The international association of Chinese professionals in geographic information sciences).
Mar. 2020, SWPU news: Two papers of Chao Song’s academic team were selected as ESI Highly cited papers.
Mar. 2020. Chao Song reviewed an original research article for the journal INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE (IJGIS).
Feb. 2020. Chao Song reviewed an original research article for the journal Environmental Science and Pollution Research.
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Chao Song's Research Chronicles: Exploring Health & Medical Geography 