Quantifying the impacts of COVID-19 on Sustainable Development Goals using machine learning models

Assessing the spatial-temporal environmental efficiency of global construction sector

The extensive waste emissions and energy consumption in the construction industry has spurred calls for sustainable development reform. Identifying valuable development paradigms through evaluating the spatial-temporal environmental efficiency (EE) of the construction sector offers an effective avenue for practice guidance. However, a comprehensive and detailed global analysis of the construction sector's EE remains lacking. This study applies the super-slack-based measure (Super-SBM) model to assess EE of the construction sector across 112 countries from 2006 to 2016. The results reveal relatively low overall EE performance of global construction sector, with notable disparities among countries and improvements were observed in certain years. Singapore, Malta, and Paraguay emerge as top performers, while Moldova, Swaziland, and Iceland rank at the bottom. The findings highlight significantly better EE in European and coastal Asian countries compared to inland Asian and African nations. Using the Tobit model, we identify that industrial structure, trade dependency, international cooperation, energy intensity, and geographic factors significantly influence EE, with varying impacts across countries of different income levels. These findings provide a comprehensive overview of the global construction sector's environmental efficiency, emphasizing the urgent need for increased awareness and the adoption of sustainable practices. The study offers practical policy implications, advocating for targeted strategies to balance economic development with environmental protection.

Advances and future directions of environmental risk research: A bibliometric review

Environmental risk is one of the world's most significant threats, projected to be the leading risk over the next decade. It has garnered global attention due to increasingly severe environmental issues, such as climate change and ecosystem degradation. Research and technology on environmental risks are gradually developing, and the scope of environmental risk study is also expanding. Here, we developed a tailored bibliometric method, incorporating co-occurrence network analysis, cluster analysis, trend factor analysis, patent primary path analysis, and patent map methods, to explore the status, hotspots, and trends of environment risk research over the past three decades. According to the bibliometric results, the publications and patents related to environmental risk have reached explosive growth since 2018. The primary topics in environmental risk research mainly involve (a) ecotoxicology risk of emerging contaminants (ECs), (b) environmental risk induced by climate change, (c) air pollution and health risk assessment, (d) soil contamination and risk prevention, and (e) environmental risk of heavy metal. Recently, the hotspots of this field have shifted into artificial intelligence (AI) based techniques and environmental risk of climate change and ECs. More research is needed to assess ecological and health risk of ECs, to formulize mitigation and adaptation strategies for climate change risks, and to develop AI-based environmental risk assessment and control technology. This study provides the first comprehensive overview of recent advances in environmental risk research, suggesting future research directions based on current understanding and limitations.

Long COVID science, research and policy

Long COVID represents the constellation of post-acute and long-term health effects caused by SARS-CoV-2 infection; it is a complex, multisystem disorder that can affect nearly every organ system and can be severely disabling. The cumulative global incidence of long COVID is around 400 million individuals, which is estimated to have an annual economic impact of approximately $1 trillion-equivalent to about 1% of the global economy. Several mechanistic pathways are implicated in long COVID, including viral persistence, immune dysregulation, mitochondrial dysfunction, complement dysregulation, endothelial inflammation and microbiome dysbiosis. Long COVID can have devastating impacts on individual lives and, due to its complexity and prevalence, it also has major ramifications for health systems and economies, even threatening progress toward achieving the Sustainable Development Goals. Addressing the challenge of long COVID requires an ambitious and coordinated-but so far absent-global research and policy response strategy. In this interdisciplinary review, we provide a synthesis of the state of scientific evidence on long COVID, assess the impacts of long COVID on human health, health systems, the economy and global health metrics, and provide a forward-looking research and policy roadmap.