Establishment of hospital resilience framework in urban China: insight from Wuhan City.

Since the Corona Virus Disease 2019 (COVID-19) swept the world, many countries face a problem that is a shortage of medical resources. The role of emergency medical facilities in response to the epidemic is beginning to arouse public attention, and the construction of the urban resilient emergency response framework has become the critical way to resist the epidemic. Today, China has controlled the domestically transmitted COVID-19 cases through multiple emergency medical facilities and inclusive patient admission criteria. Most of the existing literature focuses on case studies or characterizations of individual facilities. This paper constructs an evaluation system to measure urban hospital resilience from the spatial perspective and deciphered the layout patterns and regularities of emergency medical facilities in Wuhan, the city most affected by the epidemic in China. Findings indicate that the pattern of one center and two circles are a more compelling layout structure for urban emergency medical facilities in terms of accessibility and service coverage for residents. Meanwhile, the Fangcang shelter hospital has an extraordinary performance in terms of emergency response time, and it is a sustainable facility utilization approach in the post-epidemic era. This study bolsters areas of the research on the urban resilient emergency response framework. Moreover, the paper summarizes new medical facilities' planning and location characteristics and hopes to provide policy-makers and urban planners with valuable empirical evidence.

Modeling of emergency support capacity and optimization of delivery service system for urban living materials under uncertain situations: a case study of Xi'an City during COVID-19 epidemic.

The severe acute respiratory syndrome coronavirus 2 (COVID-19) pandemic has brought a heavy burden and severe challenges to the global economy and society, forcing different countries and regions to take various preventive and control measures ranging from normal operations to partial or complete lockdowns. Taking Xi'an city as an example, based on multisource POI data for the government's vegetable storage delivery points, logistics terminal outlets, designated medical institutions, communities, etc., this paper uses the Gaussian two-step floating catchment area method (2SFCA) and other spatial analysis methods to analyze the spatial pattern of emergency support points (ESPs) and express logistics terminals in different situations. It then discusses construction and optimization strategies for urban emergency support and delivery service systems. The conclusions are as follows. (1) The ESPs are supported by large-scale chain supermarkets and fresh supermarkets, which are positively related to the population distribution.The spatial distribution of express logistics terminals is imbalanced, dense in the middle while sparse at the edges. 90% of express terminals are located within a 500 m distance of communities, however, some terminals are shared, which restrict their ability to provide emergency support to surrounding residents. (2) In general, accessibility increases as the number of ESPs increases; under normal traffic, as the distance threshold increases, the available ESPs increase but accessibility slightly decreases; with a traffic lockdown, the travel distance of residents is limited, and as ESPs increase, accessibility and the number of POIs covered significantly increase. (3) The spatial accessibility of the ESPs has a "dumbbell-shaped" distribution, with highest accessibility in the north and south, higher around the second ring road, slightly lower in the center, and lowest near the third ring road at east and west. (4) With the goal of "opening up the logistics artery and unblocking the distribution microcirculation", based on "ESPs + couriers + express logistics terminals + residents", this paper proposes to build and optimize the urban emergency support and delivery service system to improve the comprehensive ability of the city to cope with uncertain risks.

Establishment of hospital resilience framework in urban China: insight from Wuhan City

Since the Corona Virus Disease 2019 (COVID-19) swept the world, many countries face a problem that is a shortage of medical resources. The role of emergency medical facilities in response to the epidemic is beginning to arouse public attention, and the construction of the urban resilient emergency response framework has become the critical way to resist the epidemic. Today, China has controlled the domestically transmitted COVID-19 cases through multiple emergency medical facilities and inclusive patient admission criteria. Most of the existing literature focuses on case studies or characterizations of individual facilities. This paper constructs an evaluation system to measure urban hospital resilience from the spatial perspective and deciphered the layout patterns and regularities of emergency medical facilities in Wuhan, the city most affected by the epidemic in China. Findings indicate that the pattern of one center and two circles are a more compelling layout structure for urban emergency medical facilities in terms of accessibility and service coverage for residents. Meanwhile, the Fangcang shelter hospital has an extraordinary performance in terms of emergency response time, and it is a sustainable facility utilization approach in the post-epidemic era. This study bolsters areas of the research on the urban resilient emergency response framework. Moreover, the paper summarizes new medical facilities’ planning and location characteristics and hopes to provide policy-makers and urban planners with valuable empirical evidence.

Spatio-temporal evolution and influencing factors of COVID-19 epidemic in Zhejiang Province

The global outbreak of novel Coronavirus Disease (COVID-19) epidemic has seriously endangered people's health and hindered rapid economic development. Geographic analysis of spatial and temporal transmission patterns in key regions can help prevent and control the epidemic. This paper takes Zhejiang province as the research area. With the help of POI data, the methods such as textual analysis, mathematical statistics, and spatial regression analysis are used to analyze the socio-demographic characteristics of confirmed cases and the spatio-temporal evolution of the epidemic, and then analyze its influencing factors. The results show that: (1) The age distribution of confirmed cases spanned a wide range, showing normal distribution of "large in the middle and small at both ends." (2) The epidemic period is divided into five stages: the initial period, the outbreak period, the steady decline period, the internal stable period, and the oversea input period. The interval between the onset time and announcing a confirmed case was mostly 0-6 d, and the time interval of non-local cases is longer than that of local cases, and the onset of most of the non-local cases occur on the day the patients leave their original place. There was no significant gender difference in the proportion of daily incidence, and the proportion of age had stage features. (3) The spatial distribution aligned in the direction of "Southeast-Northwest", the evolution trend developed from "single place distribution" to "multi-area cluster cases" and then to "key input" evolution, with "high-high" "high-low" clustering characteristics;The migration path of confirmed cases presented an obvious core-edge structure, and the first significant flow was from the center of Wuhan. (4) By analyzing the factors affecting the distribution of the epidemic,it is found that the ratio of the elderly population, per capita GDP, the proportion of the tertiary industry, the number of industries above the scale, and the distance from Wuhan were the dominant factors. Finally, several suggestions on targeted prevention and control measures are made, and the weaknesses of the study and future directions of efforts are pointed out.

Spatiotemporal evolution, pattern of diffusion, and influencing factors of the COVID-19 epidemic in Hainan Province, China.

Within 1 month after the first case occurred in Hainan Province, China, the number of confirmed cases rose to 168, and there was no increase in almost 3 months. As the southernmost province and a famous tourist destination in China, its regular economic exchanges and high-intensity population movements may affect the spread of the epidemic. It is of great theoretical and practical significance to investigate the spatiotemporal evolution, the pattern of diffusion, and factors influencing the coronavirus disease 2019 (COVID-19) epidemic in Hainan Province. Basic and geographic information of confirmed COVID-19 cases was obtained from government websites and other official media. We examined the groups of infection and calculated the diffusion ratio to demonstrate the trend of the epidemic. Map drawing, spatial analysis, and partial least squares regression were used to express the spatiotemporal evolution, the pattern of diffusion, and factors affecting the epidemic. Furthermore, we have made recommendations on the formulation and adaptation of possible future preventive steps. Results show that the COVID-19 epidemic in Hainan Province has substantial spatial heterogeneity but minimal distribution. The tourist city and central city have formed a dual-core pattern for the spread of the epidemic, which could extend to other similar regions. Population density, mobility, and level of urban development have been the major factors of epidemic distribution in the study area.

Spatio-temporal evolution and influencing mechanism of the COVID-19 epidemic in Shandong province, China.

The novel coronavirus pneumonia (COVID-19) outbreak that emerged in late 2019 has posed a severe threat to human health and social and economic development, and thus has become a major public health crisis affecting the world. The spread of COVID-19 in population and regions is a typical geographical process, which is worth discussing from the geographical perspective. This paper focuses on Shandong province, which has a high incidence, though the first Chinese confirmed case was reported from Hubei province. Based on the data of reported confirmed cases and the detailed information of cases collected manually, we used text analysis, mathematical statistics and spatial analysis to reveal the demographic characteristics of confirmed cases and the spatio-temporal evolution process of the epidemic, and to explore the comprehensive mechanism of epidemic evolution and prevention and control. The results show that: (1) the incidence rate of COVID-19 in Shandong is 0.76/100,000. The majority of confirmed cases are old and middle-aged people who are infected by the intra-province diffusion, followed by young and middle-aged people who are infected outside the province. (2) Up to February 5, the number of daily confirmed cases shows a trend of "rapid increase before slowing down", among which, the changes of age and gender are closely related to population migration, epidemic characteristics and intervention measures. (3) Affected by the regional economy and population, the spatial distribution of the confirmed cases is obviously unbalanced, with the cluster pattern of "high-low" and "low-high". (4) The evolution of the migration pattern, affected by the geographical location of Wuhan and Chinese traditional culture, is dominated by "cross-provincial" and "intra-provincial" direct flow, and generally shows the trend of "southwest → northeast". Finally, combined with the targeted countermeasures of "source-flow-sink", the comprehensive mechanism of COVID-19 epidemic evolution and prevention and control in Shandong is revealed. External and internal prevention and control measures are also figured out.