question: Since COVID-19 is extremely menacing human’s health, it is a significant to expose on its fator’s impacts for curbing the virus spreading. To tackle the complexity of COVID-19 expansion in spatial-temporal scale, This research is approriatedly analyzed the spatial-temporal heterogeneity at county-level in Texas. First,factors impacts of COVID-19 are captured on social, economic, and environmental multiple-facets and the Communality is extracted through Principal Component Analysis (PCA). Second, this research is used COVID-19 CC as the dependent variable and the common factors as the independent variable. According to the virus prevailing hierarchy, spatial-temporal disparity is are categorized four quarters in the modeling GWR analysis according to the virus prevailing hierarchy. The findings are exibited that GWR models provided higher fitness, more geodata-oriented information than OLS models. In Texas El Paso, Odessa, Midland, Randall and Potter County areas, population, hospitalization, and age structure presented static, positive influences on COVID-19 cumulative casesm, indicating they should be adopt stringent stratgies in curbing COVID-19. Winter is the most sensitive season for the virus spreading, implying the last quarter should be pay more attention to prevent the virus and take pracutions. This research are expected to provide references for preventing and controlling COVID-19 and related infectious dieseaces, evidences for disease surveillance and response systems to facilitate the appropriate uptake and reuse of geographical data.