Exploring variations and influencing factors of illegal adoption: A comparison between child trafficking and informal adoption.

BACKGROUND: Illegal adoption, which mainly includes child trafficking and informal adoption, has long been a prevalent social issue in China. However, the processes and patterns of illegal adoption are not well understood due to the scarcity of data. OBJECTIVE: The findings are expected to provide insightful clues for the government and the public to better understand the two categories of illegal adoption. PARTICIPANTS AND SETTING: This study included 4296 trafficking cases and 4499 informal adoption cases between 1949 and 2018. The data came from the 'Baby Coming Back Home' (https://www.baobeihuijia.com) website, which is the most comprehensive commonweal forum established by nongovernmental volunteers for finding missing persons in China. METHODS: Mathematical statistics and hot spot analysis were used to visualize the spatiotemporal pattern of illegal adoption. RESULTS: Child trafficking and informal adoption show opposite gender preferences and different age gradients. The numbers of both cases peaked in the early 1990s and then dropped. More than 50 % of all trafficked children were male, whereas approximately 83 % cases of informal adoption were female between 1980 and 2000. Hot spots of illegal adoption have shifted from the cities of the Huai River Basin to the southeastern coastal cities over time, 39.40 % of trafficking cases occurred in rural residential areas, and 52.45 % of informal adoption cases were observed in hospitals. CONCLUSIONS: Child trafficking and informal adoption are two different ways of adopting children in China. The combination of the one-child policy and the traditional culture of son preference shaped the different characteristics of the illegal adoption of children during a critical period.

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.

The spatial coupling effect between urban street network's centrality and collection & delivery points: A spatial design network analysis-based study.

The sustainable development of collection and delivery points and urban street network is an important consideration of logistic planners. Urban street networks have a significant impact on collection and delivery points' location, but the spatial relationship between the centrality of urban street network and collection and delivery points has not been studied using spatial design network analysis. In a multiple centrality assessment model, we used point of interest and street network data to evaluate the location of two types of collection and delivery points and the centrality of streets in Nanjing city, based on four indicators: closeness, betweenness, severance, and efficiency. Then, kernel density estimation and spatial autocorrelation are used to study spatial patterns of distribution and centrality coupling effects of urban street network and collection and delivery points. The results show that the centrality of Nanjing streets has a big influence on the location of the collection and delivery points, and the directions of different types of centrality also vary. The location of the Cainiao Stations are largely related to closeness, followed by betweenness, severance, and efficiency. China Post Stations and street centrality have a weak correlation between efficiency and severance, but no correlation between closeness and betweenness. Our results can help logistics enterprises and urban planners to develop collection and delivery points' network based on the urban street network.