Large-Scale Analysis of New Employee Network Dynamics

The COVID-19 pandemic has accelerated digital transformations across industries, but also introduced new challenges into workplaces, including the difficulties of effectively socializing with colleagues when working remotely. This challenge is exacerbated for new employees who need to develop workplace networks from the outset. In this paper, by analyzing a large-scale telemetry dataset of more than 10,000 Microsoft employees who joined the company in the first three months of 2022, we describe how new employees interact and telecommute with their colleagues during their "onboarding"period. Our results reveal that although new hires are gradually expanding networks over time, there still exists significant gaps between their network statistics and those of tenured employees even after the six-month onboarding phase. We also observe that heterogeneity exists among new employees in how their networks change over time, where employees whose job tasks do not necessarily require extensive and diverse connections could be at a disadvantaged position in this onboarding process. By investigating how web-based people recommendations in organizational knowledge base facilitate new employees naturally expand their networks, we also demonstrate the potential of web-based applications for addressing the aforementioned socialization challenges. Altogether, our findings provide insights on new employee network dynamics in remote and hybrid work environments, which may help guide organizational leaders and web application developers on quantifying and improving the socialization experiences of new employees in digital workplaces. © 2023 ACM.

Ensemble Deep Learning Framework for Situational Aspects-Based Annotation and Classification of International Student's Tweets during COVID-19

As the COVID-19 pandemic swept the globe, social media plat-forms became an essential source of information and communication for many. International students, particularly, turned to Twitter to express their struggles and hardships during this difficult time. To better understand the sentiments and experiences of these international students, we developed the Situational Aspect-Based Annotation and Classification (SABAC) text mining framework. This framework uses a three-layer approach, combining baseline Deep Learning (DL) models with Machine Learning (ML) models as meta-classifiers to accurately predict the sentiments and aspects expressed in tweets from our collected Student-COVID-19 dataset. Using the pro-posed aspect2class annotation algorithm, we labeled bulk unlabeled tweets according to their contained aspect terms. However, we also recognized the challenges of reducing data's high dimensionality and sparsity to improve performance and annotation on unlabeled datasets. To address this issue, we proposed the Volatile Stopwords Filtering (VSF) technique to reduce sparsity and enhance classifier performance. The resulting Student-COVID Twitter dataset achieved a sophisticated accuracy of 93.21% when using the random forest as a meta-classifier. Through testing on three benchmark datasets, we found that the SABAC ensemble framework performed exceptionally well. Our findings showed that international students during the pandemic faced various issues, including stress, uncertainty, health concerns, financial stress, and difficulties with online classes and returning to school. By analyzing and summarizing these annotated tweets, decision-makers can better understand and address the real-time problems international students face during the ongoing pandemic.

Stakeholder perspectives of adaptations of a burnout intervention for special education teachers

The high attrition and turnover rates of qualified special education teachers (SETs) is a significant concern exacerbated by COVID-19. Unfortunately, there are limited studies available on research-based interventions to decrease burnout. The purpose of this study was to describe our processes and results for adaptations and modifications of BREATHE, a burnout intervention originally developed for community mental health workers, into Burnout Reduction: Enhanced Awareness, Tools, Handouts, and Education: Evidence-based Activities for Stress for Educators (BREATHE-EASE) for special educators with guidance from the Framework for Reporting Adaptation and Modifications to Evidence-Based Interventions (FRAME). We applied the FRAME within a hybrid Type 1 trial for characterizing our approach. Four focus groups (N = 30;83% female) were conducted separately according to job title (SETs;school administrators), with semi-structured questions tailored to each group. Emergent thematic analysis was used to identify core themes related to adaptations, and results were presented to a subset of focus group members. Modifications involved content, context, and implementation changes for the adapted intervention, with most changes identified for content. FRAME was helpful for providing a systematic approach to integrate stakeholder-informed adaptations of a burnout intervention, addressing significant concerns of SET stress, burnout, and attrition.

Intergroup Contact, Traditional and Social Media Use, and Attitudes Toward Chinese People in COVID-19: US College Students' Perspective

Guided by cultivation theory and intergroup contact theory, we examined how U.S. college students' traditional media use and social media use for information about COVID-19, and direct contact with Chinese were associated with their behavioral attitudes toward Chinese people in this survey study. Findings indicated that contact quality was positively associated with attitudes toward Chinese people. Moderation analyses indicated that traditional media use negatively predicted behavioral attitudes toward Chinese people for those with no Chinese friends and was a nonsignificant predictor for those with one or more Chinese friends. Furthermore, results indicated that social media use was positively associated with attitudes toward Chinese people for those who had high contact quality with Chinese but was a nonsignificant predictor for those who had low contact quality. Overall findings ruminate the critical role of intergroup contact quality and friendship in reducing intergroup prejudice in COVID-19.

Promoting College Student's Systems Thinking

This study examined how college students in a medical school in China engaged in learning in asynchronous online learning environments during the COVID-19 health crisis. A quasi-experimental design approach was employed to compare if a class of students had better learning outcomes and developed systems thinking when asynchronous discussion forums incorporated an inquiry-based pedagogical approach in one unit, whereas the other unit followed a traditional instructor-led approach. In sum, 25 junior students participated in this study. Quantitative results show that the students had statistically significant higher assessment scores and improved systems thinking when the unit incorporated the inquiry-based pedagogical approach. Qualitative findings also demonstrated how students engaged in learning and how the instructor scaffolded students' inquiries and learning. Practical implications for instructors' teaching online courses are also discussed. © The author(s) 2023.

Potential Mechanism of Colchicine against COVID-19 and Non-Small Cell Lung Cancer based on Network Pharmacology and Bioinformatics Analysis

Colchicine is an alkaloid with antitumor effect isolated from Colchicum autumnale plants, it has been reported in multiple studies as a potential treatment for coronavirus disease-19 and this study applied network pharmacology and bioinformatics analysis to explore the potential mechanism of colchicine against non-small cell lung cancer and coronavirus disease-19. The R software was used to determine the differentially expressed genes of non-small cell lung cancer/coronavirus disease-19, and carry out prognostic analysis and clinical analysis of the differentially expressed genes, the targets of colchicine were obtained from various databases, the protein-protein interaction network of intersection targets of colchicine and non-small cell lung cancer/coronavirus disease-19 was constructed, enrichment analysis of gene ontology and kyoto encyclopedia of genes and genomes pathways was performed by Metascape database and the molecular docking and molecular dynamics simulation were completed. We obtained a total of 716 differentially expressed genes and identified 13 potential prognostic genes associated with the clinical characterization of non-small cell lung cancer/coronavirus disease-19 patients. C-C motif chemokine ligand 2, toll like receptor 4, intercellular adhesion molecule 1, peroxisome proliferator activated receptor gamma, interleukin 17A, interferon gamma, angiotensin I converting enzyme, fos proto-oncogene, nuclear factor kappa B inhibitor alpha, TIMP metallopeptidase inhibitor 1 and secreted phosphoprotein 1 were core targets. The intersection targets of colchicine and non-small cell lung cancer/coronavirus disease-19 were mainly enriched in biological processes such as inflammatory response, response to cytokine and response to lipopolysaccharide, as well as signal pathways such as interleukin 17 signaling pathway, hypoxia inducible factor 1 signaling pathway and nucleotide binding oligomerization domain-like receptor signaling pathway. The results of molecular docking showed that the colchicine is better combined with the core targets. Analysis of molecular dynamics simulation showed that the protein and ligand form a stabilizing effect. Based on bioinformatics analysis and network pharmacology, we obtained biomarkers that may be used for the prognosis of non-small cell lung cancer/coronavirus disease-19 patients and revealed that colchicine may play a potential role in the treatment of non-small cell lung cancer/coronavirus disease-19 by regulating multiple targets and multiple signaling pathways and participating in multiple biological processes.

A scoping review of tools to assess digital literacy among middle-aged and older adults for application to the practice of medical nutrition therapy

With the COVID-19 pandemic there was a swift and necessary adoption of telehealth for medical care, including medical nutrition therapy services. While the pandemic control measures have entered a new phase in Australia, the federal government has pledged to continue some Medical Nutrition Therapy (MNT) services as virtual consultations. It is important to ensure that service is equitable for all in the community and that the digital divide does not prevent access for disadvantaged groups. Older patients may be particularly at risk, and it is important to assess their ability to understand and accept virtual care. The aim of this scoping review was to identify available tools for assessing digital literacy in middle-aged and older adults and to determine their feasibility for patient use and their applicability to MNT services. The review followed the Joanna Briggs Institute guide for scoping reviews.(1) Five medical databases, reference lists of the identified studies and publications from main authors were searched to source peer-reviewed articles published in English from 2014 to February 2021. Studies for inclusion were those that used or tested a digital literacy tool in participants aged 45 years and above. Quantitative study designs conducted in clinical, community or population settings were considered Studies not meeting these criteria were deemed ineligible. The results were synthesised in tabular form and with a narrative review The generalisability of the included studies was assessed, and the applicability of the identified tools were evaluated using a four point-scale informed by the National Health Medical Research Council guide for developers of guidelines. Searches yielded 866 articles of which 30 studies (31 reports) inclusive of 11,620 participants, were used in the final analysis. Seven tools for assessment of digital literacy were identified, and the electronic health Literacy Scale (eHEALS) and modifications of this tool were most frequently used. Other tools included the Computer Proficiency Questionnaire and variations for mobile and wireless networks. Most studies found low digital health literacy among older adults. The eHEALS was found to be the most applicable for practitioners to use for assessing suitability of virtual care for their patients. This tool is inclusive of eight questions self-administered using a Likert scale (5-point) and covering the domains of traditional literacy, health and scientific literacy, information literacy as well as media and computer literacy. The findings highlight the importance of locating an appropriate digital literacy tool for older adults to better inform telehealth-delivered MNT practice. Future studies should explore effective interventions and educational programs for disadvantaged and under-served populations to help connect them with healthcare services online.

Analysis of the Spatial Distribution and Associated Factors of the Transmission Locations of COVID-19 in the First Four Waves in Hong Kong

Understanding the space–time pattern of the transmission locations of COVID-19, as well as the relationship between the pattern, socioeconomic status, and environmental factors, is important for pandemic prevention. Most existing research mainly analyzes the locations resided in or visited by COVID-19 cases, while few studies have been undertaken on the space–time pattern of the locations at which the transmissions took place and its associated influencing factors. To fill this gap, this study focuses on the space–time distribution patterns of COVID-19 transmission locations and the association between such patterns and urban factors. With Hong Kong as the study area, transmission chains of the four waves of COVID-19 outbreak in Hong Kong during the time period of January 2020 to June 2021 were reconstructed from the collected case information, and then the locations of COVID-19 transmission were inferred from the transmission chains. Statistically significant clusters of COVID-19 transmission locations at the level of tertiary planning units (TPUs) were detected and compared among different waves of COVID-19 outbreak. The high-risk areas and the associated influencing factors of different waves were also investigated. The results indicate that COVID-19 transmission began with the Hong Kong Island, further moved northward towards the New Territories, and finally shifted to the south Hong Kong Island, and the transmission population shows a difference between residential locations and non-residential locations. The research results can provide health authorities and policy-makers with useful information for pandemic prevention, as well as serve as a guide to the public in the avoidance of activities and places with a high risk of contagion. © 2023 by the authors.

Research progress in antiviral therapy for novel coronavirus pneumonia.

Since the outbreak of novel coronavirus pneumonia (COVID-19), a number of clinical studies have been carried out globally in order to explore efficacy and safety of drugs for novel coronavirus (2019-nCoV). These studies were mainly focused on drugs with anti-2019-nCoV activity tested in vitro and those previously used for the treatment of SARS and Middle East respiratory syndrome, including remdesivir, lopinavir/ritonavir, chloroquine, hydroxychloroquine, arbidol, interferon, ribavirin, and etc. The recent clinical studies on anti-2019-nCoV drugs are reviewed in this article, but the current research results are inconsistent, which are insufficient to constitute evidence for the efficacy and safety of these drugs in the treatment of COVID-19. In the absence of specific antiviral agents, remdesivir can be a treatment option for patients with critical illness or rapid progress. Some clinical studies are still in progress. We are looking forward to more large-scale and multicenter clinical trials to provide safe and effective evidence for antiviral treatment in the future.Copyright © 2020 by the Chinese Medical Association.

A class of anomalous diffusion epidemic models based on CTRW and distributed delay

In recent years, the epidemic model with anomalous diffusion has gained popularity in the literature. However, when introducing anomalous diffusion into epidemic models, they frequently lack physical explanation, in contrast to the traditional reaction-diffusion epidemic models. The point of this paper is to guarantee that anomalous diffusion systems on infectious disease spreading remain physically reasonable. Specifically, based on the continuous-time random walk (CTRW), starting from two stochastic processes of the waiting time and the step length, time-fractional space-fractional diffusion, time-fractional reaction-diffusion and fractional-order diffusion can all be naturally introduced into the SIR (S: susceptible, I: infectious and R: recovered) epidemic models, respectively. The three models mentioned above can also be applied to create SIR epidemic models with generalized distributed time delays. Distributed time delay systems can also be reduced to existing models, such as the standard SIR model, the fractional infectivity model and others, within the proper bounds. Meanwhile, as an application of the above stochastic modeling method, the physical meaning of anomalous diffusion is also considered by taking the SEIR (E: exposed) epidemic model as an example. Similar methods can be used to build other types of epidemic models, including SIVRS (V: vaccine), SIQRS (Q: quarantined) and others. Finally, this paper describes the transmission of infectious disease in space using the real data of COVID-19. © 2023 World Scientific Publishing Company.

Micromodel and Analysis of COVID-19 Based on Hypergraph

In view of the fact that the existing propagation models ignore the influence of different fields and different virus variants on individual infection, and the classical propagation models only describe the macroscopic situation of virus transmission, which cannot be specific to individual cases, this paper proposes 67ya microscopic virus propagation model based on hypergraph (HC-SIRS). Firstly, the concept of hypergraph is used to divide different fields of individuals into corresponding hyperedges. Based on different contact probabilities of each hyperedge, the contact probability matrix is formed to relate the contact between individuals. The individual infection probability of micro-virus propagation model based on hypergraph is deduced, and the corresponding differential equation is established. Secondly, the basic regeneration number and its characteristics of the model are derived. The upper bound of the basic regeneration number of the model is less than or equal to that of the classical SIRS model, indicating that the virus is more difficult to spread in this model. In fact, the different fields people live in and the different personal constitutions have a certain impact on the spread of the virus. The model is more comprehensive, so it is more suitable for simulating the spread of the virus in theory. Finally, the COVID-19 data of Diamond Princess and two cities in China are used for simulation experiments, and the mean absolute error(MAE) is used as the evaluation standard. The results showed that HC-SIRS could well simulate the spread of COVID-19. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Structural Changes in Human Mobility Under the Zero-COVID Strategy in China

Over the past two years, China has wrested domestic control of the COVID-19 pandemic through non-pharmaceutical interventions. However, the extent to which the pandemic has changed people's travel behavior in the new normal under the zero-COVID policy is not yet clear. This study investigates the profound effects of the zero-COVID strategy on human mobility in 365 Chinese cities over time. Our results suggest the following: (1) Even between city pairs with no local cases, intercity mobility decreased by an average of 16%, whereas intra-city mobility increased by 9% compared with the pre-pandemic baseline. Long-distance travel decreased substantially, while trips below 100 km increased slightly. These new trends indicate a localized pattern which is presumably caused by the wide adoption of teleworking and virtual classes, as well as concerns about the safety and availability of public transportation. (2) Containment measures caused a considerably acute decline in intercity short-distance trips but exerted a markedly lasting effect on long-distance trips. (3) Cities with lower levels of urbanization, smaller population sizes, less labor force, and lower GDP and GDP per capita experienced greater reductions in mobility, which may be due to their insufficient management capabilities. (4) The Chinese government has adopted adaptive measures to contain outbreaks. Stricter and more timely responses led to faster recoveries in the second half of 2021 compared with the first half. Inter- and intra-city mobility decreased by 41% and 26%, respectively, within the first 2 weeks of an outbreak, and it took 6-7 weeks to return to pre-outbreak levels. © The Author(s) 2023.

Research and application progress of COVID-19 vaccine.

The coronavirus disease 2019 (COVID-19) pandemic is a serious threat to human life, health and social development. In response to this public health event, various COVID-19 vaccines have been rapidly developed around the world. To date, 41 vaccines have been approved for emergency use, and the use of vaccines has significantly reduced the morbidity and mortality of COVID-19. However, with the continuous mutants, especially the emergence of the Omicron variant, challenges to vaccine-induced immune protection are appearing, there is still a long way to go for the continued development of COVID-19 vaccines. This article briefly reviews the research progress of COVID-19 vaccine and its effect on mutant virus strains.Copyright © 2022 Authors. All rights reserved.

Analysis of a Typical COVID-19 Outbreak Spread by Tourist Groups

Background: Novel coronavirus disease (SARS-COV-2 infection or COVID-19) is a respiratory tract infection that has been linked to severe acute respiratory syndrome transmitted particularly through touching and respiration. The purpose of this study is to understand the epidemiological characteristics of COVID-19 cases in a typical tourist-related outbreak and explore the possible route for its transmission. Method(s): All data and epidemiological survey reports of COVID-19 cases in the outbreak were reported by provincial and urban (county) Centers for Disease Control and Prevention and Health Commissions nationwide from October 16th to November 5th, 2021. The epidemiological survey reports included information on gender, age, source of infection (imported from other provinces or locally acquired), daily life track and itinerary, date of symptom onset, and date of diagnosis. The data were analyzed using descriptive statistical methods, one-way analysis of variance, independent t-test, and Chi-square tests. Histograms and percentage stacked area plots were used to describe the epidemiological characteristics of the outbreaks. Result(s): The COVID-19 outbreak associated with the tourist groups has involved 551 COVID-19 cases, with a median age of 44 years (interquartile range: 30-59 years), gradually spreading from the northwestern region to the national level across 15 provinces of China. One-fifth of the cases (16.0%) had traveled to Ejin Banner, resulting in 68 second-generation cases. We estimated an outbreak on 11 flights and 19 trains, accounting for a total of 27 confirmed cases. In addition, 42 clusters of outbreak cases were also reported to occur, 21 (50.0%) in households and 10 (23.81%) in restaurants. About 106 confirmed cases were related to the gatherings in restaurants. The median incubation period for this COVID-19 outbreak was 7 days (inter-quartile range: 5-10 days). Conclusion(s): The survey results indicated that this COVID-19 outbreak originated in Ejin Banner and was spread by tourist groups, which was a typical infection outbreak promoted by travel. Our results further confirmed that travel needs to be more strictly weighed in pandemics like COVID-19, and people need to pay more attention to the prevention against infectious diseases, particularly when traveling in a tourist group.Copyright © 2022 Zheng et al.

Media representations of China amid COVID-19: A corpus-assisted critical discourse analysis

Although there has been an increasing number of studies investigating media representations of the COVID-19 outbreak around the world, less international attention has been given to Chinese media outlets' coverage of the COVID-19 outbreak than that of their western counterparts. This study employs corpus-assisted critical discourse analysis to investigate how China is linguistically represented in a state-run English-language news media. The analysis reveals that China is respectively represented as a victim, a fighter, and a cooperative/supportive country with ideological implications for global solidarity and humanitarianism. This study sheds light on the effective use of discursive strategies in promoting international cooperation and building a national image amid a global health crisis. The value of using corpus-assisted critical discourse analysis to examine national image is also highlighted. © The Author(s) 2023.

Etiology, clinical features, infection control and therapy of SARS-CoV-2 Omicron variant.

The Omicron variant of SARS-CoV-2 is a new variant of concern after Alpha, Beta, Gamma and Delta variants. The amino acid mutations in the viral antigens, especially in the receptor binding region (RBD) of spike protein, were significantly more than those of other variants, which lead to the significant increase of infectivity, transmissibility and immune escape of Omicron variant. In addition, those spike mutations impaired the protective effect of vaccination. When compared to the infection of other variants, the latency of Omicron variant infection was significantly shortened, and the pathogenicity decreased markedly, which is in consistence with the fact that the vast majority of infected individuals showed no symptoms or only mild disease. Exacerbations in patients infected by Omicron variant were often associated with the progress of underlying disease. Early detection and medical isolation of infected persons, careful personal protection measures to cut off transmission routes, and active vaccination to protect susceptible people are key measures to prevent the spread of Omicron variant epidemic. A small number of patients infected with Omicron variant may develop so-called long COVID-19, post-COVID-19 syndrome, or post-COVID-19 condition, which means that long-term follow-up is needed in those patients. Effective anti-Omicron variant therapy can shorten the course of infection, promote the recovery from infection, and also contribute to the control of infection. Therefore, the development of antiviral drugs with ideal cost-benefit ratio and convenient administration is one of the research hotspot in the future.Copyright © 2022 Authors. All rights reserved.

Beyond Natural Language Processing: Building Knowledge Graphs to Assist Scientists Understand COVID-19 Concepts

To combat COVID-19, scientists must digest the vast amount of relevant biomedical knowledge in the literature to understand disease mechanisms and related biological functions. Nearly 3,000 scientific papers are published on PubMed every day. This knowledge bottleneck has resulted in severe delays in developing COVID-19 vaccines and drugs. Our research produces a hierarchy of knowledge concepts related to COVID-19, designed to assist scientists in answering questions and generating summaries. It aims to discover scientific and comprehensive knowledge to extract fine-grained multimedia elements (i.e., physical and visual structures, relational events and events, and chemical knowledge). Our project is toward one step in natural language understanding: detailed contextual sentences, subgraphs, and knowledge subgraphs are the first time to be automatically generated, and relations and coreferences of COVID-19 mentions will be sketched. Extensive results show that our method outperforms other state-of-the-art methods. In addition, we have published the generated knowledge graph on Google Drive1 and released the source in the Github2. © 2022 ACM.

Lipid-Based Poly(I:C) Adjuvants Strongly Enhance the Immunogenicity of SARS-CoV-2 Receptor-Binding Domain Vaccine

Background The outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has greatly threatened public health. Recent studies have revealed that the spike receptor-binding domain (RBD) of SARS-CoV-2 is a potent target for vaccine development. However, adjuvants are usually required to strengthen the immunogenicity of recombinant antigens. Different types of adjuvants can elicit different immune responses. Methods We developed an RBD recombinant protein vaccine with a polyriboinosinic acid-polyribocytidylic acid [poly(I:C)] adjuvant to evoke a strong immune response. The delivery of poly(I:C) was optimized in two steps. First, poly(I:C) was complexed with a cationic polymer, poly-l-lysine (PLL), to form poly(I:C)-PLL, a polyplex core. Thereafter, it was loaded into five different lipid shells (group II, III-1,2-distearoyl-sn-glycero-3-phosphocholine [DSPC], III-1,2-dioleoyl-sn-glycero-3-phosphoethanolamine [DOPE], IV-DOPE, and IV-DSPC). We performed an enzyme-linked immunosorbent assay and enzyme-linked immunosorbent spot assay to compare the ability of the five lipopolyplex adjuvants to enhance the immunogenicity of the SARS-CoV-2 RBD protein, including humoral and cellular immune responses. Finally, the adjuvant with the highest immunogenicity was selected to verify the protective immunity of the vaccine through animal challenge experiments. Results Recombinant RBD protein has low immunogenicity. The different adjuvants we developed enhanced the immunogenicity of the RBD protein in different ways. Among the lipopolyplexes, those containing DOPE (III-DOPE and IV-DOPE) elicited RBD-specific immunoglobulin G antibody responses, and adjuvants with four components elicited better RBD-specific immunoglobulin G antibody responses than those containing three components (P < 0.05). The IC50 and IC90 titers indicated that the IV-DOPE lipopolyplex had the greatest neutralization ability, with IC50 titers of 1/117,490. Furthermore, in the challenge study, IV-DOPE lipopolyplex protected mice from SARS-CoV-2 infection. On the fourth day after infection, the average animal body weights were reduced by 18.56% (24.164 ± 0.665 g vs. 19.678 ± 0.455 g) and 0.06% (24.249 ± 0.683 g vs. 24.235 ± 0.681 g) in the MOCK and vaccine groups, respectively. In addition, the relative expression of viral RNA in the vaccinated group was significantly lower than that in the MOCK group (P < 0.05). Interstitial inflammatory cell infiltration was observed in the MOCK group, whereas no obvious damage was observed in the vaccinated group. Conclusions The IV-DOPE-adjuvanted SARS-CoV-2 recombinant RBD protein vaccine efficiently protected mice from SARS-CoV-2 in the animal challenge study. Therefore, IV-DOPE is considered an exceptional adjuvant for SARS-CoV-2 recombinant RBD protein-based vaccines and has the potential to be further developed into a SARS-CoV-2 recombinant RBD protein-based vaccine. © Wolters Kluwer Health, Inc. All rights reserved.

The Architectural Planning Strategies for Multifamily Housing in a Post-Pandemic World

The rapid spread of COVID-19 not only created a global public health crisis, but also affected almost every aspect of our lives. After investigating the fundamental impact of the COVID-19 outbreak on housing needs, this study envisions what multifamily housing will look like in a post-pandemic world. Through the lessons learned during the COVID-19 pandemic, the design of residential architecture should incorporate preventive and mitigating measures to cope with any future epidemics. After factoring this new reality, this study aims to develop architectural planning strategies for multifamily housing, particularly mid to high-rise apartment housing as a predominant housing typology in Korea. An in-depth multi-disciplinary literature review was carried out to examine previous outbreaks and their impacts, assess the transmission of viruses in built environments, and observe the emerging lifestyles that resulted in the new approach of living, working, and interacting. Comparative analyses of existing guidelines for multifamily housing in response to COVID-19 were also conducted to develop a conceptual framework of architectural planning more suitable for multifamily housing in Korea. As a result of this study, a set of architectural strategies that accommodated new lifestyles while promoting quality of life through an occupant's health and well-being were established. This strategy set is intended to provide a foundation for further research to generate more detailed design considerations for future residential developments. © 2022 Architectural Institute of Korea.