Long-Term Urban Epidemic and Disaster Resilience: The Planning and Assessment of a Comprehensive Underground Resilience Core

This study utilizes the enclosed and stable environment of underground space for long-term sustainable planning for urban epidemics and disasters. Owing to the COVID-19 epidemic, cities require long-term epidemic-disaster management. Therefore, this study proposed a strategy for integrating multiple functions to plan a comprehensive Underground Resilience Core (URC). A planning and assessment methods of URC were proposed. With this methodology, epidemic- and disaster- URCs were integrated to construct a comprehensive-URC in underground spaces. The results show: (1) Epidemic-resilient URCs adopting a joint progressive approach with designated hospitals can rapidly suppress an epidemic outbreak. (2) The regularity of the morphology of underground spaces determines the area of the URC. Bar-shaped underground spaces have the potential for planning disaster-URCs. (3) The URC planning efficiency ranking is as follows: Bar shapes lead overall, T shapes are second under seismic resilience, and Cross shapes are second under epidemic resilience. (4) The potential analysis of planning a comprehensive-URC in the underground parking in Chinese cities showed that the recovery time can be advanced from 29% to 39% and the comprehensive resilience can be improved by 37.63%. The results of this study can serve as sustainable urban planning strategies and assessment tools for long-term epidemic-disaster management.

Blockchain-based Health Data Sharing for Continuous Disease Surveillance in Smart Environments

The Covid-19 pandemic ushered in multiple paradigms of personal health data sharing with particular emphasis on Person-to-Institution sharing and Institution-to-Institution sharing. While the data aggregated by technology companies and health authorities was instrumental in the development of vaccines and ultimately flattening the curve of infection rates, egregious abuses of privacy occurred. In many instances acceptable guarantees of appropriate utility for the data were not made available. Personal health data sharing for the containment of infections with privacy limitations present a classic case of collaboration among mutually distrustful entities. In this regard the blockchain network and attendant protocols for data integrity, transaction transmission and provenance can prove useful. Thus, in this paper we present a blockchain-based method for disease surveillance in a smart environment where smart contracts are deployed to monitor public locations instead of individuals. The data aggregated is analysed and tagged with a lifetime commensurate with the time for infection. Once the data utility period has elapsed the monitored data are removed from the active surveillance pool and the entities involved can be notified. Such a method of continual surveillance protects privacy by shifting the emphasis from individuals to locations. Experimental data suggests this method is efficient and can be implemented on top of existing disease surveillance strategies for later pandemics.

Face Mask Classification based on Transfer Learning and MobileNet V2

Face mask image recognition can detect and monitor whether people wear the mask. Currently, the mask recognition model research mainly focuses on different mask detection systems. However, these methods have limited working datasets, do not give safety alerts, and do not work appropriately on masks. This paper aims to use the face mask recognition detection model in public places to monitor the people who do not wear the mask or the wrong mask to reduce the spread of Covid-19. The mask detection model supports transfer learning and image classification. Specifically, the collected data are first collected and then divided into two parts: with_mask and without_mask. Then authors build, implement the model, and obtain accurate mask recognition models. This paper uses and size of images datasets tested respectively. The experimental results show that the effect of the image size of was relatively better, and the training accuracy of different MobileNetV2 models is about 95%. Our analysis demonstrates that MobileNetV2 can correctly classify Covid-19. © 2022 ACM.

A Guide to Mental Health in Family Under the COVID-19 Epidemic

This book tells us from a professional perspective how to deal with stress response in the family, effectively address family problems in the epidemic, and handle the infectious emotions. This book is a profound explanation of the new stress, conflicts, and problems arising at home amid the epidemic. It provides people with a psychological self-help scale to effectively distinguish the normal and abnormal states of psychological response. Besides, it also provides professional psychological assistance and suggestions for special groups, including children, the elderly, the quarantined, and the bereaved, in order to help all families actively respond to the epidemic with the power of psychology. © Beijing Normal University Press 2022.

Blockchain-based Health Data Sharing for Continuous Disease Surveillance in Smart Environments

The Covid-19 pandemic ushered in multiple paradigms of personal health data sharing with particular emphasis on Person-to-Institution sharing and Institution-toInstitution sharing. While the data aggregated by technology companies and health authorities was instrumental in the development of vaccines and ultimately flattening the curve of infection rates, egregious abuses of privacy occurred. In many instances acceptable guarantees of appropriate utility for the data were not made available. Personal health data sharing for the containment of infections with privacy limitations present a classic case of collaboration among mutually distrustful entities. In this regard the blockchain network and attendant protocols for data integrity, transaction transmission and provenance can prove useful. Thus, in this paper we present a blockchain-based method for disease surveillance in a smart environment where smart contracts are deployed to monitor public locations instead of individuals. The data aggregated is analysed and tagged with a lifetime commensurate with the time for infection. Once the data utility period has elapsed the monitored data are removed from the active surveillance pool and the entities involved can be notified. Such a method of continual surveillance protects privacy by shifting the emphasis from individuals to locations. Experimental data suggests this method is efficient and can be implemented on top of existing disease surveillance strategies for later pandemics. © 2023 IEEE.

Comparative study on epidemiological characteristics and public health interventions of COVID-19 among China, South Korea, the United States and France based on the poisson regression model

Objective To analyze the trend of COVID-19 epidemic and to comparatively evaluate effects of economic policies, containment and closure policies and health system policies in China , South Korea, the United States (US) and France. Methods Daily confirmed COVID-19 cases and daily comprehensive policy index, specific indicators in mainland China, South Korea, US and France were collected. Considering the lag effect of policy effects, poisson regression model was established to estimate the daily real-time regeneration (Rt) , and the log-log model with variable coefficient was used to compare the prevention and control effects of policies and measures in different countries. Results Containment and closure policies and health system policies were negatively correlated with Rt, and the cumulative lag effect weakens with the increase of lag time. Economic policies were negatively correlated with Rt only in US and France. The effect of American and French policies on Rt was weaker than that of China and South Korea. Conclusion Containment and closure policies and health system policies have a great effect on reducing Rt and controlling the epidemic, the timely and powerful comprehensive blockade measures at the early stage of the epidemic have better effects than mitigation measures. © 2023, Publication Centre of Anhui Medical University. All rights reserved.

COVID-19, the Belt and Road Initiative, Tianxia/The Chinese Universe, and Universal Human Rights

This chapter discusses how the Belt and Road Initiative (BRI) developed from an internally driven geopolitical undertaking to tackle the bottleneck in China's domestic economic development and regional security into a more ideological and global phenomenon. During the 2018 trade war with the United States, the Chinese started to redefine democracy, human rights, and a global political system with terms such as Tianxia/All-Under-Heaven and a Community with a Shared Future for Humankind. The chapter focuses on the impact that COVID-19 has had on the BRI and how the latter has adjusted to the pandemic since early 2020. The BRI, so one suggestion is, should be viewed as a dynamically emerging series of projects that can be shaped and directed to outcomes that benefit global security and prosperity. © Oxford University Press 2022.

USE OF ANGIOTENSIN-CONVERTING ENZYME INHIBITORS (ACEIs) AND ANGIOTENSIN-RECEPTOR BLOCKERS (ARBs) AND INCIDENCE OF PNEUMONIA OR INFLUENZA OR COVID-19: A SYSTEMATIC REVIEW AND META-ANALYSIS

Introduction: The respiratory tract infections (RTIs), including pneumonia, influenza and Coronavirus Disease 2019 (COVID-19), are the leading cause of hospitalization and mortality worldwide, contributing to elevated healthcare and societal costs. There is conflicting evidences about the effects of angiotensin converting enzyme inhibitor (ACEIs) or angiotensin II receptor blockers (ARBs) on the susceptibility of RTIs. Method(s): Systematic review of interventional and observational studies that reported use of ACEI or/and ARB on incidence of pneumonia or influenza or COVID-19. Searching was conducted in the databases of PubMed, Excerpta Medica Database (Embase), Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL), including the Cochrane Library until April 2022, and references of retrieved relevant articles. We assessed the quality of included studies by using Cochrane Collaboration Risk of Bias tool for Randomized Controlled Trials and Newcastle-Ottawa Scale for observational studies. DerSimonian Laird random-effects meta-analysis was conducted to pool effects for the incidence of pneumonia, influenza and COVID-19. Subgroup analyses were carried according to baseline morbidities (hypertension or cardiovascular diseases, cerebrovascular diseases, chronic kidney disease (CKD) and other non-communicable diseases). Pooled estimates of odds ratios (OR) and corresponding 95% confidence intervals (95% CI) were computed, and heterogeneity among studies was assessed using Cochran's Q test and the I2 metrics, with two tailed P values. Result(s): 73 studies met the inclusion criteria, of which 38 studies assessed the odds of pneumonia, 32 studies assessed Covid-19 and 3 studies assessed influenza. The quality of included studies was moderate. Use of ACEIs was associated with a significantly reduced odds of pneumonia (23 studies: OR 0.74, 95% CI 0.64 to 0.85;I2=76.8%), of COVID-19 (24 studies: OR 0.87, 95% CI 0.82 to 0.92;I2=81.9%) and influenza (3 studies: OR 0.75, 95% CI 0.57 to 0.98, I2=97.7%), compared with control treatment. Use of ARBs was also associated with reduced odds of COVID-19 (25 studies: OR 0.90, 95% CI 0.83 to 0.97;I2=91.9%), but not with odds of pneumonia or influenza. These findings remain consistent in the community population, patients with history of cerebrovascular diseases or cardiovascular diseases, but not in those with CKD, diabetes and chronic obstructive pulmonary diseases. Conclusion(s): The current evidence favours a putative protective role of ACEIs, not ARB in odds of pneumonia, COVID-19 and influenza. Patient populations that may benefit most are those within the community, history of cerebrovascular diseases and cardiovascular diseases. No conflict of interestCopyright © 2023

Comparison of hospital admissions in people with bronchiectasis between the covid-19 pandemic (2020) and pre-pandemic period (2019)

Objective: To analyse whether the COVID-19 pandemic (2020) resulted in differences in the characteristics of hospital admissions for a respiratory infection in adults with bronchiectasis compared to the pre-COVID-19 period. Method(s): An observational, retrospective study enrolling all adults admitted to the hospital between Jan 2009 and Dec 2020 for a respiratory infection with a computed-tomography-confirmed bronchiectasis. Admissions for COVID19 were excluded. Sociodemographic data, clinical data and admission characteristics were compared between prepandemic (2019) and pandemic (2020) period. Result(s): In 2019, 35 patients were admitted with a mean age of 77y (11), classified the 60% of them as severe according to the Bronchiectasis Severity Index (BSI). Three of these patients had to be readmitted in the same year. During this period, the proportion of admissions tested for viral infection was 28% and for bacterial infection was 72% of hospitalizations. A total of 25 patients were admitted in 2020, with a mean age of 74y (12), being the 76% severe. Readmissions in the same period were observed in four of these patients. Of the admissions, 57% were tested for viral infection and 73% for bacterial infection. The only difference observed for admission characteristics between both periods was the number of test for virus detection (11 (28%) in 2019 vs. 19 (57%) in 2020;p=0.02) (table 1). Conclusion(s): The number of viral infection test seems to increase during the pandemic period in comparison with pre-pandemic period during admissions for an exacerbation in adult patients with bronchiectasis.

"Special Times Call for Special Measures”: China's Regulation of COVID-19 through Criminal Justice Innovation

This article reveals how COVID-19 has provoked the enactment of recent emergency regulations and the implications for criminal justice policy and practice in the People's Republic of China (PRC). In what the authors describe as a principle that "special times call for special measures”, China's legal approach to the challenges created by COVID-19 resembles the country's enduring crime control "strike hard” strategy. Under the banner of "dynamic zero-COVID”, this analysis also demonstrates the practice of cautious law enforcement as seen through the "strike hard” practices. This is encapsulated by the augmentation and specification of "risk-creation” offences as well as the emerging trend that favours charging risk perverse actions as more serious offences when assessing punishment. © China: An International Journal.

Comparative study on epidemiological characteristics and public health interventions of COVID-19 among China, South Korea, the United States and France based on the poisson regression model.

Objective To analyze the trend of COVID-19 epidemic and to comparatively evaluate effects of economic policies, containment and closure policies and health system policies in China , South Korea, the United States (US) and France. Methods Daily confirmed COVID-19 cases and daily comprehensive policy index, specific indicators in mainland China, South Korea, US and France were collected. Considering the lag effect of policy effects, poisson regression model was established to estimate the daily real-time regeneration (Rt) , and the log-log model with variable coefficient was used to compare the prevention and control effects of policies and measures in different countries. Results Containment and closure policies and health system policies were negatively correlated with Rt, and the cumulative lag effect weakens with the increase of lag time. Economic policies were negatively correlated with Rt only in US and France. The effect of American and French policies on Rt was weaker than that of China and South Korea. Conclusion Containment and closure policies and health system policies have a great effect on reducing Rt and controlling the epidemic, the timely and powerful comprehensive blockade measures at the early stage of the epidemic have better effects than mitigation measures.Copyright © 2023, Publication Centre of Anhui Medical University. All rights reserved.

A Review of Mathematical Models of COVID-19 Transmission

Corona Virus Disease 2019 (COVID-19) is a disease caused by the novel coronavirus, and due to its rapid spread, the World Health Organization has declared it a worldwide outbreak. Since the first case was detected in December 2019, the fight against this deadly disease has begun. Numerous studies have been done on the COVID-19 outbreak's model of dissemination and epidemic patterns. It mainly focuses on the selection of methods, the determination of parameters, and the evaluation of prevention and control measures. Taking the spread of the COVID-19 epidemic as the research object, combined with the current development of the COVID-19 epidemic, this paper sorts out the relevant mathematical models for the study of the spread of COVID-19, among which the models based on Susceptible-Infected-Recovered (SIR) model and Susceptible-Exposed-Infectious-Removed (SEIR) model and the mathematical models combined with these two models are mainly selected. Finally, the importance of reasonable and effective control of parameters and multi-model combined modeling is pointed out in the future. © 2023 Xiaolin Lin, et al.

Nanotechnology for ultrafast nucleic acid amplification

Nucleic acid detection has been one of the most valued tools in point-of-care diagnostics from life science, agriculture, food safety and environmental surveillance, because of its high sensitivity, great specificity and simple operation. Since polymerase chain reactions (PCR) were discovered, more and more researchers attach importance to exploring ultrafast nucleic acid amplification methods for further expediting the process of detection and curbing infectious diseases' high spread rate, especially after the coronavirus disease 2019 (COVID-19) worldwide pandemic event. Nowadays, nanotechnology as one of the most cut-ting-edge technologies has aroused growing attention. In this review, we describe new advances in na-notechnology research for ultrafast nucleic acid amplification. We have introduced commonly used nanotechnologies, namely nanofluidics, nanoporous materials, nanoparticles and so on. Recent advances in these nanotechnologies for ultrafast sample pretreatments, accelerated enzymatic amplification and rapid heating/cooling processes was summarized. Finally, challenges and perspectives for the future applications of ultrafast nucleic acid amplification are presented.(c) 2022 Elsevier Ltd. All rights reserved.

Impact of decreased aerosols during the COVID-19 pandemic on winter wheat gross primary productivity and water use efficiency

Rapid and comprehensive lockdowns to contain the coronavirus 2019 (COVID-19) pandemic reduced anthropogenic emissions and, thereby, decreased the aerosol optical depth (AOD) in Xiangyang, Hubei Province. However, their complicated interactions make quantifying the contribution of decreased aerosols to crop growth challenging. Here, we explored the indirect effects of decreased aerosol concentrations on the gross primary productivity (GPP) and water use efficiency (WUE) of winter wheat by quantifying the contributions of key environmental factors. Our results showed high temporal and spatial associations between aerosols (represented by AOD), GPP, and WUE before, during, and after the COVID-19 pandemic. AOD decreased by 23.8% +/- 10.1%, whereas GPP and WUE increased by 16.5% +/- 5.8% and 17.0% +/- 15.3%, respectively. The GeoDetector model revealed that photosynthetically active radiation (PAR) had a major impact on GPP and WUE, followed by precipitation, surface soil moisture, subsurface soil moisture, and surface temperature. Moreover, causality analysis showed a causal relationship between AOD and the dominant factors (PAR and precipitation) during the lockdown, thereby indicating a positive effect of decreased aerosols on GPP and WUE changes of winter wheat. Our findings assist in understanding the mechanisms causing GPP and WUE changes, given the environmental factors that changed significantly during the pandemic. (c) 2022 Society of Photo-Optical Instrumentation Engineers (SPIE)

Gaining resilience through transformative services in cause-related events: an interaction ritual chain perspective

PurposeThis study aims to unlock a ritual chain mechanism that promotes socio-mental (or socio-psychological) resilience. This study draws on interaction ritual chains theory and the concept of transformative service to answer the question of how people could be inspired toward an elevated level of group solidarity, emotional energy, morality and, thus, socio-mental resilience. Design/methodology/approachThis study took a qualitative approach resting upon online reviews and observations from an augmented food festival about hot pot delicacies dedicated to medical workers fighting hard amid the early coronavirus outbreak. FindingsThe results of this study point to four primary ritual outcomes (e.g. emotional energy, group solidarity, symbols of relationships and standards of morality) along with a two-tier micro-macro socio-mental resilience sustainability paradigm. Research limitations/implicationsEmpirical findings from this study could help operators to justify their transformative initiatives as means for customers to replenish their depleted physical and mental resources. Originality/valueThis inquiry presents new nuances to interaction ritual chains. This study also extends the transformative role of hospitality services to accentuate a linkage among individuals, communities and the society.

Computational tools for aptamer identification and optimization

Aptamers are single-stranded DNA or RNA oligonucleotides that can selectively bind to a specific target. They are generally obtained by SELEX, but the procedure is challenging and time-consuming. Moreover, the identified aptamers tend to be insufficient in stability, specificity, and affinity. Thus, only a handful of aptamers have entered the practical use stage. Recently, computational approaches have demonstrated a significant capacity to assist in the discovery of high-performance aptamers. This review discusses the advances achieved in several aspects of computational tools in this field, as well as the new progress in machine learning and deep learning, which are used in aptamer identification and optimization. To illustrate these computationally aided processes, aptamer selections against SARS-CoV-2 are discussed in detail as a case study. We hope that this review will aid and motivate researchers to develop and utilize more computational techniques to discover ideal aptamers effectively. Copyright © 2022 Elsevier B.V.

Hemophagocytosis in a Severe COVID-19 Patient

The novel coronavirus (SARS-CoV-2) infection has become a heavy burden on global health. Although the coronavirus disease 2019 (COVID-19) may adversely affect multiple organs and systems of infected patients, to the best of our knowledge, there is little investigation of the SARS-CoV-2's impact on bone marrow. Our clinical and cytological findings in this case of severe COVID-19 infection provide novel insights into the pathogenesis of SARS-CoV-2 infection in the hematopoietic system. We recommend that physicians consider SARS-CoV-2 infection's effect on bone marrow in patients who are slow to recover and suggest that a better understanding of the bone marrow morphology in COVID-19-infected patients is needed. © 2022 Journal of Bone and Joint Surgery Inc.. All rights reserved.

Using Machine Learning to Predict Place-Based Risks for Staphylococcus aureus Infections in Children

Background: Community-onset Staphylococcus aureus (CO-S. aureus) pediatric infections, methicillin-resistant S. aureus (MRSA) and methicillin-susceptible S. aureus (MSSA) continue to contribute to the burden of infections seen in the ambulatory setting in the US. Individual risk factors have been identified, but place-based factors and specific geographic locality have not been well-studied. The purpose of this study is to predict place-based factors that contribute to the spread of CO-S. aureus in a major urban area using maximum entropy (MaxEnt), a machine learning technique. Methods: Electronic medical records from two pediatric hospitals (2002 to 2016) were retrospectively reviewed. Inclusion criteria: a confirmed S. aureus infection within 48 hours of hospital admission (CO-S. aureus), < 19 years old, and a geo-referenced address within Atlanta's metropolitan statistical area (MSA). Fourteen place-based factors, at the US Census block group level, were included in the MaxEnt models: < 18 years old, Caucasian, African American, ethnicity, poverty, education attainment, crowding, daycare, kindergarten enrollment, distance to K-12 school, distance to a children's hospital, distance to a daycare center, and population density. A total of four models (CO-MRSA early, CO-MSSA early, CO-MRSA later, and CO-MSSA later) were run using the MaxEnt software. For each model, 75% and 25% of data was randomly assigned to training and testing groups, respectively. Models were assessed by jack-knife tests. Results: 16,124 records met eligibility criteria for MaxEnt models. The training Area Under the Curve (AUC) ranged from 0.771 to 0.837 and the test AUC ranged from 0.769 to 0.804. Population density had the highest contribution in predicting CO-MRSA and CO-MSSA locations, which was confirmed by jack-knife tests. Conclusion: By applying MaxEnt to pediatric CO-S. aureus infections in the Atlanta MSA, it was found that higher risks of CO-S. aureus infections may exist in more densely populated areas. MaxEnt can be utilized to identify potential future areas of CO-MRSA and CO-MSSA infections based on estimated or predicted changes to the place-based factors used to build these models. Disclosures: Lilly Immergluck, MD, MS, GSK: Clinical Trial- PI;Merck: Vaccine Trial Site- serve as PI;Moderna: Board Member;Novavax: Part of CoVID-19 Phase 3 Trial through US Covid Prevention Network.

First-Time Chinese Online Students' Expectations of Their Instructors in Fully Online Learning Environments

The global COVID-19 lockdowns caused universities to shift from face-to-face instruction to online. Since online teaching was used as a supplement to the traditional in-person instruction before the pandemic in China, Chinese college students were forced to learn in fully online learning (FOL) environments with very little preparation. These first-time online students faced challenges that significantly impacted their confidence and ability to succeed as online learners. Fortunately, the instructor can play a crucial role in conducting early interventions to reduce students' online learning anxiety but understanding these students' expectations of their online instructor is necessary for using appropriate teaching strategies. As a result, this study investigates 439 first-time Chinese online students' expectations of their instructor in FOL environments during the emergent transition. Results indicate that several characteristics are highly expected by new online Chinese learners, such as being familiar with technology, being knowledgeable about the subject, and respecting other students. This study is expected to point Chinese universities and others toward best practices in preparing their faculty members for online course instruction, thus further enhancing first-time online students' learning experiences. © 2022, The Online Learning Consortium. All rights reserved.

Agenda-Setting of the Public Health Emergencies (COVID-19) Based on Audience's Perspective

The outbreak of sudden public health incidents notes the agenda setting of the media in the process of message diffusion, but the audience's expectation for the media framework is seldom paid attention to. Through an online questionnaire, the media usage, satisfaction, intuitive evaluation of different message framing and placement methods of the audience (N=401) are investigated. The results notes that: audiences attach the most importance to message placement and gain-framing, where the importance of message placement is basically the same as the agenda setting of official media;audiences are satisfied with media coverage overall and are most concerned about the speed of media response, while the ability to deal with false message needs to be improved;some audiences attach equal importance to additional message on sudden public events. This study proposes an audience-led agenda-setting in response to public health emergencies, providing a new perspective to understand the audience's message needs and agenda setting. © 2022 ACM.