Towards a constructed order of co-governance: Understanding the state-society dynamics of neighbourhood collaborative responses to COVID-19 in urban China.

The state-society relationship in neighbourhood governance has been a focal topic in the urban governance literature, though the existing scholarship was primarily drawn from non-crisis situations. Adopting a mixed-methods approach, this study investigates the intricate state-society dynamics manifested at the neighbourhood scale as state and societal actors collaborated during China's COVID-19 responses. Our study reveals a pattern of collaborative rather than confrontational dynamics between resident committees and other stakeholders during pandemic responses, which reflects the emergence of a constructed order of neighbourhood co-governance in urban China. Previous community-building reforms consolidated the political legitimacy, power and capacity of resident committees, which were empowered to play a critical coordinating role in bridging hierarchical state mobilisation and horizontal stakeholders in the collaborative pandemic responses. These findings contribute to a more nuanced understanding of neighbourhood co-governance in the international literature and provide lessons for resilience governance from a comparative lens.

Structural Comparison and Drug Screening of Spike Proteins of Ten SARS-CoV-2 Variants.

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has evolved many variants with stronger infectivity and immune evasion than the original strain, including Alpha, Beta, Gamma, Delta, Epsilon, Kappa, Iota, Lambda, and 21H strains. Amino acid mutations are enriched in the spike protein of SARS-CoV-2, which plays a crucial role in cell infection. However, the impact of these mutations on protein structure and function is unclear. Understanding the pathophysiology and pandemic features of these SARS-CoV-2 variants requires knowledge of the spike protein structures. Here, we obtained the spike protein structures of 10 main globally endemic SARS-CoV-2 strains using AlphaFold2. The clustering analysis based on structural similarity revealed the unique features of the mainly pandemic SARS-CoV-2 Delta variants, indicating that structural clusters can reflect the current characteristics of the epidemic more accurately than those based on the protein sequence. The analysis of the binding affinities of ACE2-RBD, antibody-NTD, and antibody-RBD complexes in the different variants revealed that the recognition of antibodies against S1 NTD and RBD was decreased in the variants, especially the Delta variant compared with the original strain, which may induce the immune evasion of SARS-CoV-2 variants. Furthermore, by virtual screening the ZINC database against a high-accuracy predicted structure of Delta spike protein and experimental validation, we identified multiple compounds that target S1 NTD and RBD, which might contribute towards the development of clinical anti-SARS-CoV-2 medicines. Our findings provided a basic foundation for future in vitro and in vivo investigations that might speed up the development of potential therapies for the SARS-CoV-2 variants.

Collaborative neighborhood governance and its effectiveness in community mitigation to COVID-19 pandemic: From the perspective of community workers in six Chinese cities.

The COVID-19 pandemic is a governance challenge for nations and cities across the world. While early observations have primarily focused on government actions, neighborhoods are at the frontline for coordinating grassroots level joint actions to fight against the pandemic. We draw from the collaborative governance theory and develop a theoretical framework for understanding the horizontal and hierarchical dynamics of collaborative neighborhood governance during crisis responses in urban China. Using a large-scale questionnaire survey of frontline community workers operated in six Chinese cities in February 2020, we conduct statistical analyses and find that the effectiveness of neighborhood collaboration in the pandemic control is predicted by both neighborhood social capital (i.e. civic engagement and citizen participation) and hierarchical steering by the government through setting policy priorities and providing support. Our research contributes to the international literature on neighborhood governance dynamics and provides policy lessons for improving neighborhood governance capacity in crisis response situations.

Coronavirus disease (COVID 2019): protocol for a living overview of systematic reviews.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic continues to grow worldwide, and systematic reviews (SRs)/meta-analyses (MAs) on COVID-19 can efficiently guide evidence-based clinical practice. However, SRs/MAs with weaknesses can mislead clinical practice and pose harm to patients, and too many useless SRs/MAs could pose confusion and waste sources. A "living" overview of SRs/MAs aims to provide an open, accessible and frequently updated resource summarizing the highest-level evidence of COVID-19, that can help evidence-users to quickly identify trusted evidence to guide the practice. This study aims to systematically give an overview SRs/MAs of COVID-19, assess their quality, and identify the best synthesis of evidence. METHODS: Databases including Medline, EMBASE, Web of Science, China National Knowledge Infrastructure (CNKI), China Biology Medicine (CBM) and WanFang were systematically searched on May 1, 2020 using relevant terms for identify SRs/MAs related to COVID-19. The study selection, data extraction and quality assessment will be performed by independent reviewers, and results will be crosschecked. The authoritative tools (AMSTAR-2, PRISMA and its extensions) will be used to assess the methodological quality and reporting quality of included SRs/MAs, and potential influence factors will be explored. The consistency of conclusions will be compared among reviews and the best evidence will be summarized. In addition, we will conduct exploratory meta-analyses (MAs) of individual studies when applicable. Data will be reported as number with (or) percentage, risk ratio (RR) or odds ratio (OR), mean difference (MD) or standardized mean difference (SMD) with 95% confidence interval (CI) according to the specific results. R3.6.1 and Microsoft Excel 2016 will be used to analyze and manage data. RESULTS: The results of this overview will be submitted to a peer-reviewed journal for publication. DISCUSSION: In this study, we will present for the first time, an overview of SRs/MAs, which provides a comprehensive, dynamic evidence landscape on prevalence, prevention, diagnosis, treatment, and prognosis of COVID-19.