BACKGROUND This study aimed to investigate trends in the epidemiology of the leading sexually transmitted diseases (STDs), acquired immune deficiency syndrome (AIDS), gonorrhea, and syphilis, in the 31 provinces of mainland China. MATERIAL AND METHODS This retrospective study analyzed the incidence data of STDs from official reports in China between 2004 and 2016. The grey model first order one variable, or GM (1,1), time series forecasting model for epidemiological studies predicted the incidence of STDs based on the annual incidence reports from 31 Chinese mainland provinces. Hierarchical cluster analysis was used to group the prevalence of STDs within each province. RESULTS The prediction accuracy of the GM (1,1) model was high, based on data during the 13 years between 2004 and 2016. The model predicted that the incidence rates of AIDS and syphilis would continue to increase over the next two years. Cluster analysis showed that 31 provinces could be classified into four clusters according to similarities in the incidence of STDs. Group A (Sinkiang Province) had the highest reported prevalence of syphilis. Group B included provinces with a higher incidence of gonorrhea, mainly in the southeast coast of China. Group C consisted of southwest provinces with a higher incidence of AIDS. CONCLUSIONS The GM (1,1) model was predictive for the incidence of STDs in 31 provinces in China. The predicted incidence rates of AIDS and syphilis showed an upward trend. Regional distribution of the major STDs highlights the need for targeted prevention and control programs.

Two large earthquakes, the Maduo M_S 7.4 earthquake and the Menyuan M_S 6.9 earthquake, have been successfully recorded on the Chinese mainland, since the data of the CSES satellite were put into service for earthquake prediction work on the Chinese mainland at the end of April 2020. Obvious variations in O⁺ density and electron density were found during our weekly data processing work during 5–11 May 2021 and 28 December 2021–2 January 2022, respectively. Two warnings of impending events around the anomalous areas within two weeks had been reported immediately after the anomaly appearance. The Maduo M_S 7.4 earthquake occurred on 22 May 2021 and the Menyuan M_S 6.9 earthquake on 8 January 2022, during these two warning periods. More details were revealed after these two large shocks occurred. Ionospheric enhancement took place on 8 May 2021, with a magnitude of 41.6% for O⁺ density and 22.2% for electron density, a distance of 680 km from the Maduo epicenter, 14 days prior to the event. Before the Menyuan earthquake, ionospheric enhancement took place on 28 December 2021, as well as during its revisiting orbit on 2 January 2022, with a magnitude of 47.3% for O⁺ density and 38.4% for electron density, an epicentral distance of 120 km, 11 and 6 days prior to this event. The Kp index was also examined to avoid the influence from solar activities. Despite this, accurate earthquake prediction is not possible due to much uncertainty, such as the correct location and magnitude of an impending event. Thus, long-term practice and comprehensive investigation of the seismo-ionospheric influence are necessary in the future.

Global climate change has intensified flood disasters at the local scale. In response, this study constructs a flood resilience indicator system at the urban scale based on the “pressure-state-response” (PSR) model. Indicator weights were determined using the analytic hierarchy process–entropy weight method (AHP-EWM), the flood resilience of 35 cities within the Yellow River Basin from 2010 to 2021, and their spatiotemporal evolution patterns, spatial correlations, and determinants were analyzed. The results indicate that flood resilience shows an upward trend over time, with stronger resilience observed in upstream and downstream cities and weaker resilience in midstream cities. The spatial correlation of flood resilience was significantly positive in 2010, 2015, and 2021, while it exhibited non-significant, fluctuating declines in other years. Most cities in Henan and Shandong provinces are characterized as high–high agglomeration type, whereas most cities in Shanxi and Shaanxi provinces are classified as low–low type. Drainage efficiency, municipal investment, resilient planning, and urbanization have significant positive impacts on flood resilience, while the urban registered unemployment rate shows a positive spatial spillover effect. This study analyzed the flood resilience of cities in the Yellow River Basin from a comprehensive and logically coherent perspective and concluded with targeted recommendations aimed at enhancing flood resilience in the region.