Spatial co-location patterns between early COVID-19 risk and urban facilities: a case study of Wuhan, China.

Introduction: COVID-19, being a new type of infectious disease, holds significant implications for scientific prevention and control to understand its spatiotemporal transmission process. This study examines the diverse spatial patterns of COVID-19 within Wuhan by analyzing early case data alongside urban infrastructure information. Methods: Through co-location analysis, we assess both local and global spatial risks linked to the epidemic. In addition, we use the Geodetector, identifying facilities displaying unique spatial risk characteristics, revealing factors contributing to heightened risk. Results: Our findings unveil a noticeable spatial distribution of COVID-19 in the city, notably influenced by road networks and functional zones. Higher risk levels are observed in the central city compared to its outskirts. Specific facilities such as parking, residence, ATM, bank, entertainment, and hospital consistently exhibit connections with COVID-19 case sites. Conversely, facilities like subway station, dessert restaurant, and movie theater display a stronger association with case sites as distance increases, hinting at their potential as outbreak focal points. Discussion: Despite our success in containing the recent COVID-19 outbreak, uncertainties persist regarding its origin and initial spread. Some experts caution that with increased human activity, similar outbreaks might become more frequent. This research provides a comprehensive analytical framework centered on urban facilities, contributing quantitatively to understanding their impact on the spatial risks linked with COVID-19 outbreaks. It enriches our understanding of the interconnectedness between urban facility distribution and transportation flow, affirming and refining the distance decay law governing infectious disease risks. Furthermore, the study offers practical guidance for post-epidemic urban planning, promoting the development of safer urban environments resilient to epidemics. It equips government bodies with a reliable quantitative analysis method for more accurately predicting and assessing infectious disease risks. In conclusion, this study furnishes both theoretical and empirical support for tailoring distinct strategies to prevent and control COVID-19 epidemics.

Research on Expansion Characteristics of Aquaculture Ponds and Variations in Ecosystem Service Value from the Perspective of Protecting Cultivated Lands: A Case Study of Liyang City, China.

In the context of global food insecurity, a large amount of cultivated land in China has been occupied by aquaculture ponds, leading to a series of variations in the ecological environment. The Chinese government pays close attention to the problem. In order to achieve sustainable development and ensure the safety of China's cultivated land, the paper uses Liyang City as an example to discuss the spatial characteristics of the expansion of aquaculture ponds through occupying cultivated lands and analyzes the variations in ecosystem service value and cultivated land function. The conclusions are as follows: (1) 2073.24 hectares of cultivated lands were occupied for expanding aquaculture ponds in Liyang from 2009 to 2019, and there was a small number of new aquaculture ponds in the ecological protection area, which shows that the aquaculture ponds in Liyang City are at the stage of disorderly expansion; (2) the total value of ecosystem services increased by 1.43%; supply and support services values decreased, but the increase in regulation and cultural services values was sufficient to more than compensate for the mentioned losses; and (3) the expansion of aquaculture ponds leads to a decrease in the carbon storage of cultivated land, which in turn has negative impacts such as an increase in atmospheric carbon concentration.

Research on adaption to air pollution in Chinese cities: Evidence from social media-based health sensing.

Air pollution seriously threats to human health. Understanding the health effects of air pollution is of great importance for developing countermeasures. However, little is known about the real-time impacts of air pollution on the human heath in a comprehensive way in developing nations, like China. To fill this research gap, the Chinese urbanites' health were sensed from more than 210.82 million Weibo (Chinese Twitter) data in 2017. The association between air pollution and the health sensing were quantified through generalized additive models, based on which the sensitivities and adaptions to air pollution in 70 China's cities were assessed. The results documented that the Weibo data can well sense urbanites' health in real time. With the different geographical characteristics and socio-economic conditions, the Chinese residents have adaption to air pollution, indicated by the spatial heterogeneity of the sensitivities to air pollution. Cities with good air quality in South China and East China were more sensitive to air pollution, while cities with worse air quality in Northwest China and North China were less sensitive. This research provides a new perspective and methodologies for health sensing and the health effect of air pollution.

Mapping the exposure and sensitivity to heat wave events in China's megacities.

The rising temperature makes the weather becoming more extreme. Understanding how extreme hot temperature-heat wave events (HWEs)-are likely to alter individual heat exposure and sensitivity is crucial for developing climate change mitigation and adaptation strategies. Despite the importance, little is known about the real-time impacts of HWEs on individual daily life in developing nations, like China. To fill this gap, we adopt over 1544 thousand Weibo (Chinese Twitter) social media data, coupled with meteorological conditions people face when posting, to assess the heat exposure and people's sensitivity to HWEs across 31 mega-cities in China. The results show the hotspot of Weibo heat is coincident with the extremely hot temperature, with a correlation of 0.7 (p < 0.05). The intensities, frequencies, and durations of HWEs in both geographical and social media space have high spatial heterogeneity. Its spatial variation can be explained by the type of climate zone and the unique geographical environment. The cities with extreme hot weather are more likely to adapt to the heatwave and less sensitivity to HWEs. The proposed framework, which integrates the real-time social media semantic analysis, statistical method, and spatial techniques, provides a new paradigm to assess the HWEs exposure and sensitivity analysis in China.