Evolution and analysis of urban resilience and its influencing factors: a case study of Jiangsu Province, China.

This research uses panel data of cities in Jiangsu from 2009 to 2018 to construct a resilience framework that measures the level of urban resilience. A combination of the entropy method, Theil index, Moran ' sI , and the Spatial Durbin Model (SDM) is used to explore regional resilience development differences, the spatial correlation characteristics of urban resilience, and its influencing factors. The study finds that: (1) The spatial heterogeneity of regional resilience development is significant, as the overall level of resilience presents a spatial distribution pattern of descending from southern Jiangsu to central Jiangsu and to northern Jiangsu. (2) The total Theil index shows a wave-like downward trend during the study period. The differences between southern Jiangsu, central Jiangsu, and northern Jiangsu make up the main reason for the overall difference of urban resilience in Jiangsu Province. Among the three regions, the gap in resilience development level within southern Jiangsu is the largest. (3) There is a clear positive spatial correlation between urban resilience in the province and an obvious agglomeration trend of urban resilience levels. Among all subsystems, urban ecological resilience is the weakest and needs to be further improved. (4) Lastly, among the five factors affecting urban resilience, general public fiscal expenditure/GDP, which characterizes government factors, has the largest positive impact on urban resilience, while foreign trade has a negative impact. In the following studies, the theme of urban resilience should be constantly deepened, and more extensive data monitoring should be carried out for the urban system to improve the diversity of data sources, so as to assess urban resilience more accurately. Supplementary Information: The online version contains supplementary material available at 10.1007/s11069-022-05368-x.

Analysis for the spread of COVID-19 in China based on the impulsive partial differential equation with diffusion

At the beginning of 2020, COVID-19 broke out in Wuhan and quickly swept the world. At present, the global epidemic prevention and control is still facing severe challenges. Scientific and effective measures of the epidemic is crucial to epidemic prevention and control. In this paper, a COVID-19 diffusion prediction model is established based on the impulsive partial differential equation and traditional infectious disease model, which can describe the spatial diffusion of viruses. This is also a lack of other models. The model divides the total population into seven groups: susceptible, quarantine, exposed, asymptomatic, infected, diagnosed and recovered, while considering the influence of time and space on the spread of the virus. In order to test the model, we take Jiangsu Province in China as an example, compare the calculated results with the actual data, and verify the effectiveness of the model through numerical calculation. © COPYRIGHT SPIE.

[Time to initial diagnosis of imported malaria and its influencing factors in Jiangsu Province].

OBJECTIVE: To investigate the health-seeking behaviors of imported malaria cases after returning to China, and to investigate the factors affecting the time to initial diagnosis, so as to provide the scientific evidence for early identification of imported malaria cases and prevention of severe cases development and secondary transmission. METHODS: The individual demographic features, and the disease onset and the time to initial diagnosis of imported malaria cases in Jiangsu Province in 2019 were captured from the National Notifiable Disease Report System and the Information Management System for Parasitic Disease Control in China. The characteristics of health-seeking behaviors and epidemiological features of imported malaria cases were descriptively analyzed, and the factors affecting the time to initial diagnosis of imported malaria cases after returning to China were identified using multivariate logistic regression analysis. RESULTS: A total of 244 imported malaria cases were reported in Jiangsu Province in 2019, and the time to initial diagnosis of the cases were 1-12 days, with mean time of (1.53 ± 1.65) days, with median time of one day. The highest number of malaria cases seeking healthcare services were found on the day of developing primary symptoms (76 cases, 31.1%), followed by on the second day (68 cases, 27.9%), on the third day (46 cases, 18.9%), and 54 cases (22.1%) received initial diagnosis 3 days following presence of primary symptoms, including 3 cases with initial diagnosis at more than one week. High proportions of imported malaria cases with a delay in the time to initial diagnosis were seen in migrant workers who returned to China in January (14 cases, 5.7%) and December (13 cases, 5.3%) and those aged between 41 and 50 years (32 cases, 13.1%). Multivariate logistic regression analysis showed relative short time to initial diagnosis among imported malaria cases returning to China on March [odds ratio (OR) = 0.16, P = 0.03, 95% confidence interval (CI): (0.03, 0.85)] and those with a history of overseas malaria parasite infections [OR = 0.36, P = 0.001, 95% CI: (0.19, 0.67)]. CONCLUSIONS: Timely health-seeking behaviors should be improved among imported malaria cases in Jiangsu Province, patients with a history of overseas malaria infections require faster health-seeking activities.

Assessing urban resilience to public health disaster using the rough analytic hierarchy process method: A regional study in China

In the context of frequent occurrences of disasters worldwide, disaster-coping capability is imperative for risk reduction and contemporary emergency management. The global COVID-19 pandemic since 2020 has further highlighted the significance of resilience construction at different geographical scales. Overall, the conceptual cognition of resilience in disaster management covers multiple elements and has diverse yielding on regional assessment. This study assesses the local resilience to the public health disaster at the prefecture-level cities, focusing on two dimensions consisting of vulnerability and capability in the targeted provincial region of Jiangsu in China. To this end, based on the vulnerability-capability framework, the Rough Analytic Hierarchy Process (RAHP) method was applied to the resilience assessment. Drawing upon the criteria derived from literature, the criteria weights were determined with the RAHP method and we assessed urban resilience with census data. In addition, the hierarchical factors contributing to urban resilience were determined using robustness analysis. This research provides constructive ideas for regional disaster reduction and contributes to the government's capability to improve urban resilience. © 2022

Coupling and Coordination between Tourism Talents and Tourism Economy based on an Empirical Analysis of Jiangsu Province

With the increasingly effective control of the COVID-19 epidemic, the huge implicit demand for explosive tourism consumption growth in China is showing an urgent demand for tourism talents. In this paper, based on the concept of sustainable development and digital economy, the tourism economy is completely explained, the evaluation indicator system of tourism talents and tourism economy and the evaluation model of coupling coordination degree are established, and the coupling coordination between them is studied based on the data of Jiangsu from 2014 to 2018. The results show that (1) The comprehensive development level evaluation index of tourism talents and tourism economy in Jiangsu shows an upward trend, and the development speed of tourism economy is faster than that of tourism talents;(2) At present, the coupling coordination degree of tourism talents and tourism economy in Jiangsu is only at the lowest value of good coordination about 0.5, which has not broken through the antagonistic state and still needs to be improved. (3) The coupling and coordination level of tourism talents and tourism economy in Jiangsu Province shows the gradual improvement of "low coordination-moderate coordination-good coordination", which changes from the former lagging type of low-level and medium-level coordination tourism economy to the lagging type of good-level coordination tourism talents at present with 2017 as the turning point. © 2021 Kriedt Enterprises Ltd. All right reserved.