The efficacy of social distance and ventilation effectiveness in preventing COVID-19 transmission

Applying a Pedestrian Level of Service in the Context of Social Distancing: The Case of the City of Madrid

During the COVID-19 pandemic, there has been a lot of discussion about keeping interpersonal distance to prevent the virus from spreading. To keep this interpersonal distance, authorities at different levels have taken measures to reduce people's interactions, such as reducing capacities, curfews, pop-up cycle lanes, temporary pedestrianisation, and lockdowns. Many of these temporary measures have been perceived from a static view. Nevertheless, in a scenario of "new normality" or in the face of a possible new pandemic, the amount of data (big data) generated by different sources, such as sensors, in large cities has extraordinary potential to be used together with tactical urbanism for quick adaptation. The aim of this study was to gain insight into the aforementioned issues by analysing spatio-temporal patterns of pedestrian mobility and developing a variation of the pedestrian level of service measure; the pandemic pedestrian level of service (P-PLOS). This measure provides a dynamic view of pavement capacities according to the interpersonal distance recommendations during the pandemic. P-PLOS was tested in the city of Madrid based on the pedestrian counter data that was provided by the local government through its open data website. We found that the application of P-PLOS, together with street design, allows for knowing where and when it is necessary to take tactical urbanism measures in order to maintain or improve the level of service, as well as where it is necessary to take measures to reduce pedestrian flow.

COVID-19 and urban spaces: A new integrated CFD approach for public health opportunities

Safe urban public spaces are vital owing to their impacts on public health, especially during pandemics such as the ongoing COVID-19 pandemic. Urban public spaces and urbanscape elements must be designed with the risk of viral transmission in mind. This work therefore examines how the design of urbanscape elements can be revisited to control COVID-19 transmission dynamics. Nine proposed models of urban public seating were thus presented and assessed using a transient three-dimensional computational fluid dynamics (CFD) model, with the Eulerian-Lagrangian method and discrete phase model (DPM). The proposed seating models were evaluated by their impact on the normalized air velocity, the diameter of coughing droplets, and deposition fraction. Each of the proposed models demonstrated an increase in the normalized velocity, and a decrease in the deposition fraction by >29%. Diagonal cross linear and curved triangle configurations demonstrated an improved airflow momentum and turbulent flow, which decreased the droplets deposition fraction by 68%, thus providing an improved, healthier urban public seating option.

Clinical and epidemiological characteristics of patients seeking COVID-19 testing in a private centre in Malaysia: Is there a role for private healthcare in battling the outbreak?

OBJECTIVE

This cross-sectional observational study summarized the baseline characteristics of subjects who underwent COVID-19 molecular testing in a private medical centre located in the state of Selangor in Malaysia between 1 Oct 2020 and 31 Jan 2021. We compared the baseline characteristics between subjects who were tested positive and negative of SARS-CoV-2 infection, and identified risk factors which may be predictive of SARS-CoV-2 positivity.

METHODS AND FINDINGS

A total of 36603 subjects who were tested for COVID-19 infection via molecular assays at Sunway Medical Centre between Oct 1, 2020 and Jan 31, 2021, and consented to participate in this observation study were included for analysis. Descriptive statistics was used to summarize the study cohort, whereas logistic regression analysis was used to identify risk factors associated with SARS-CoV-2 positivity. Among the reasons listed for COVID-19 screening were those who needed clearance for travelling, clearance to return to work, or clearance prior to hospital admission. They accounted for 67.7% of tested subjects, followed by the self-referred group (27.3%). Most of the confirmed cases were asymptomatic (62.6%), had no travel history (99.6%), and had neither exposure to SARS-CoV-2 confirmed cases (61.9%) nor exposure to patients under investigation (82.7%) and disease clusters (89.2%). Those who presented with loss of smell or taste (OR: 26.91; 95% CI: 14.81-48.92, p<0.001), fever (OR:3.97; 95% CI: 2.54-6.20, p<0.001), running nose (OR: 1.75; 95% CI:1.10-2.79, p = 0.019) or other symptoms (OR: 5.63; 95% CI:1.68-18.91, p = 0.005) were significantly associated with SARS-CoV-2 positivity in the multivariate logistic regression analysis.

CONCLUSION

Our study showed that majority of patients seeking COVID-19 testing in a private healthcare setting were mainly asymptomatic with low epidemiological risk. Consequently, the average positivity rate was 1.2% compared to the national cumulative positivity rate of 4.65%. Consistent with other studies, we found that loss of smell or taste, fever and running nose were associated with SARS-CoV-2 positivity. We believe that strengthening the capacity of private health institutions is important in the national battle against the COVID-19 pandemic, emphasizing the importance of public-private partnership to improve the quality of clinical care.

The Societal Influences and Quality of Life Among Healthcare Team Members During the COVID-19 Pandemic

Background: The coronavirus infection disease 2019 (COVID-19) pandemic is likely to put healthcare professionals across the world in an unprecedented situation. Methods: A total of 683 healthcare workers were recruited in this study. Short form-12 items (SF-12), Societal Influences Survey Questionnaire (SISQ), and Disaster-Related Psychological Screening Test (DRPST) were used to survey participants. Multiple linear regression and structural equation model (SEM) were used to explore the possible factors to the societal influences and quality of life. Results: After multiple linear regression analysis, female, older, more education years, married, regular intake, and posttraumatic stress disorder (PTSD) frequency had positive association with SISQ. To physical component summary (PCS) of SF-12, chronic illness, sleep score, PTSD frequency, and social distance had negative association, and exercise habits had positive association. A mental component summary (MCS) value of SF-12, age, participate in social activities, and social information had positive association, and PTSD frequency, sleep score, social anxiety, and depression had negative association. Under SEM analysis, PTSD had positive influence on SISQ. Sleep score and MCS value had negative influences on SISQ. PTSD severity, older age, sleep score, smoking, and nursing staff had negative influences on PCS value. Young age, PTSD frequency, sleep score, and depression had negative influences on MCS value. Conclusion: Healthcare team members with severe PTSD symptoms suffered more societal influences. Relative to PTSD severity, PTSD frequency was more important to the quality of life. Members of older age who frequently participate in clubs, volunteers, or charity activities had better mental life quality.

Resilient Built Environment: Critical Review of the Strategies Released by the Sustainability Rating Systems in Response to the COVID-19 Pandemic

Since the COVID-19 outbreak, buildings have been viewed as a facilitator of disease spread, where the three main transmission routes (contact, droplets, aerosols) are more likely to happen. However, with proper policies and measures, buildings can be better prepared for re-occupancy and beyond. This study reviews the strategies developed by several Sustainability Rating Systems (SRS, namely WELL, Fitwel and LEED) to respond to any infectious disease and ensure that building occupants protect and maintain their health. The best practices, that are similar between each SRS, highlight that the overall sustainability of the spaces increases if they are resilient. Results indicate that SRS promote a weak sustainability approach since they accept that economic development can reduce natural capitals. SRS are also characterized by an aggregated level of assessment of different criteria that does not allow to map different choices. However, the decomposition of the concept of sustainability in its three bottom lines (i.e., environmental, social and economic) shows that preventive strategies are likely to be systematically adopted as the state-of-the-art. Finally, even if the latest research points out the airborne transmission as the major infection route, the SRS lack analytical measures to address issues such as social distancing.

Social Distance Monitoring Approach Using Wearable Smart Tags

Coronavirus has affected millions of people worldwide, with the rate of infected people still increasing. The virus is transmitted between people through direct, indirect, or close contact with infected people. To help prevent the social transmission of COVID-19, this paper presents a new smart social distance system that allows individuals to keep social distances between others in indoor and outdoor environments, avoiding exposure to COVID-19 and slowing its spread locally and across the country. The proposed smart monitoring system consists of a new smart wearable prototype of a compact and low-cost electronic device, based on human detection and proximity distance functions, to estimate the social distance between people and issue a notification when the social distance is less than a predefined threshold value. The developed social system has been validated through several experiments, and achieved a high acceptance rate (96.1%) and low localization error (<6 m).

Recent research on expiratory particles in respiratory viral infection and control strategies: A review

The global spread of coronavirus disease 2019 poses a significant threat to human health. In this study, recent research on the characteristics of expiratory particles and flow is reviewed, with a special focus on different respiratory activities, to provide guidance for reducing the viral infection risk in the built environment. Furthermore, environmental influence on particle evaporation, dispersion, and virus viability after exhalation and the current methods for infection risk assessment are reviewed. Finally, we summarize promising control strategies against infectious expiratory particles. The results show that airborne transmission is a significant viral transmission route, both in short and long ranges, from infected individuals. Relative humidity affects the evaporation and trajectories of middle-sized droplets most, and temperature accelerates the inactivation of SARS-CoV-2 both on surfaces and in aerosols. Future research is needed to improve infection risk models to better predict the infection potential of different transmission routes. Moreover, further quantitative studies on the expiratory flow features after wearing a mask are needed. Systematic investigations and the design of advanced air distribution methods, portable air cleaners, and ultraviolet germicidal irradiation systems, which have shown high efficacy in removing contaminants, are required to better control indoor viral infection.

Study on ventilation rates and assessment of infection risks of COVID-19 in an outpatient building

A modified Wells-Riley model combining the airborne route and close contact route was proposed to predict the infection risks of coronavirus disease 2019 (COVID-19) in main functional spaces of an outpatient building in Shenzhen, China. The personnel densities and ventilation rates in the 20 waiting rooms, outpatient hall and hospital street were on-site measured. The average fresh air volume per person and occupant area per person in the 20 waiting rooms were 77.6 m³/h and 6.47 m²/per, satisfied with the Chinese standard. The average waiting time of the occupants was 0.69 h. Thus, assuming the proportion of infected people in the outpatient building was 2%, the daily average infection probabilities of COVID-19 in the 20 waiting rooms were 0.19–1.88% with a reasonable setting of the quanta produced by an infector (q = 45 quanta/h) and the effective exposure dose of pathogen per unit close contact time (β = 0.05 h⁻¹). The design of the semi-closed hospital street with a height of 24 m improved its natural ventilation with a fresh air volume per person of 70–185 m³/h and further dilute the viral aerosol and decreased the infection risk to a negligible level (i.e., below 0.04% with an infector proportion of 2%). The assessment method provides real-time prediction of indoor infection risk and good assist in spread control of COVID-19.

Mitigation of Particle Spread During Mastoidectomy: A Systematic Review

Our objective is to analyze the risk of particle spread through mastoidectomy during the COVID-19 pandemic with an aim to assess the tools used to mitigate the spread. A systematic review was conducted using PRISMA guidelines. Our search terms included: MASTOIDECTOMY + COVID-19 or MASTOIDECTOMY + SAR- CoV-2 or MASTOIDECTOMY + CORONAVIRUS. Studies consistent with the inclusion and exclusion criteria were included in the review. Of the 20 articles identified in the initial search, six met the inclusion criteria. The included articles were all experimental studies, with five studies using cadaver subjects and one study using live human subjects. Three studies measured droplet spread and three studies measured aerosolized particle spread. The maximum distance of particle spread ranged from 30 cm to 208 cm. Four studies assessed the use of a barrier system, with two using the OtoTent and two using a barrier drape. Two studies defined the microscope alone as a possible mitigatory tool. One study compared burr type and size to determine the effects on particle spread. During the coronavirus disease 2019 (COVID-19) pandemic, evaluation of tools to mitigate particle spread is imperative for the safety of the surgical team and the healthcare system at large. Barrier drapes, OtoTents and microscopes all have proven to mitigate particle spread; however, further research needs to be performed to compare their efficacy and develop a standard of safety.

Natural ventilation strategy and related issues to prevent coronavirus disease 2019 (COVID-19) airborne transmission in a school building

The World Health Organization (WHO) announced that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may spread through aerosols, so-called airborne transmission, especially in a poorly ventilated indoor environment. Ventilation protects the occupants against airborne transmission. Various studies have been performed on the importance of sufficient ventilation for diluting the concentration of virus and lowering any subsequent dose inhaled by the occupants. However, the ventilation situation can be problematic in public buildings and other shared spaces, such as shops, offices, schools, and restaurants. If ventilation is provided by opening windows, the outdoor airflow rate depends strongly on the specific local conditions (opening sizes, relative positions, climatic and weather conditions). This study uses field measurements to analyze the natural ventilation performance in a school building according to the window opening rates, positions, and weather conditions. The ventilation rates were calculated by the tracer gas decay method, and the infection risk was assessed using the Wells-Riley equation. Under cross-ventilation conditions, the average ventilation rates were measured at 6.51 h^-1 for 15% window opening, and 11.20 h^-1 for 30% window opening. For single-sided ventilation, the ventilation rates were reduced to about 30% of the values from the cross-ventilation cases. The infection probability is less than 1% in all cases when a mask is worn and more than 15% of the windows are open with cross-ventilation. With single-sided ventilation, if the exposure time is less than 1 h, the infection probability can be kept less than 1% with a mask. However, the infection probability exceeds 1% in all cases where exposure time is greater than 2 h, regardless of whether or not a mask is worn. Also, when the air conditioner was operated with a window opening ratio of 15%, power consumption increased by 10.2%.

Experimental study on the control effect of different ventilation systems on fine particles in a simulated hospital ward

In recent years, a large number of respiratory infectious diseases (especially COVID-19) have broken out worldwide. Respiratory infectious viruses may be released in the air, resulting in cross-infection between patients and medical workers. Indoor ventilation systems can be adjusted to affect fine particles containing viruses. This study was aimed at performing a series of experiments to evaluate the ventilation performance and assess the exposure of healthcare workers (HW) to virus-laden particles released by patients in a confined experimental chamber. In a typical ward setting, four categories (top supply and exhaust, side supply and exhaust) were evaluated, encompassing 16 different air distribution patterns. The maximum reduction in the cumulative exposure level for HW was 70.8% in ventilation strategy D (upper diffusers on the sidewall supply and lower diffusers on the same sidewall return). The minimum value of the cumulative exposure level for a patient close to the source of the contamination pertained to Strategy E (upper diffusers on the sidewall supply and lower diffusers on the opposite sidewall return). Lateral ventilation strategies can provide significant guidance for ward operation to minimizing the airborne virus contamination. This study can provide a reference for sustainable buildings to construct a healthy indoor environment.

Seesaw scenarios of lockdown for COVID-19 pandemic: Simulation and failure analysis

The ongoing COVOD-19(SARS-CoV-2) outbreak has had a devastating impact on the economy, education and businesses. In this paper, the behavior of an epidemic is simulated on different contact networks. Herein, it is assumed that the infection may be transmitted at each contact from an infected person to a susceptible individual with a given probability. The probability of transmitting the disease may change due to the individuals' social behavior or interventions prescribed by the authorities. We utilized simulation on the contact networks to demonstrate how seesaw scenarios of lockdown can curb infection and level the pandemic without maximum pressure on the poor societies. Soft scenarios consist of closing businesses 2, 3, and 4 days in between with four levels of lockdown respected by 25%, 50%, 75%, and 100% of the population. The findings reveal that the outbreak can be flattened under softer alternatives instead of a doomsday scenario of complete lockdown. More specifically, it is turned out that proposed soft lockdown strategies can flatten up to 120% of the pandemic course. It is also revealed that transmission probability has a crucial role in the course of the infection, growth rate of the infection, and the number of infected individuals.

Behaviour of aerosols and their role in the transmission of SARS-CoV-2; a scoping review

Covid‐19 has triggered an unprecedented global health crisis. The highly contagious nature and airborne transmission route of SARS‐CoV‐2 virus requires extraordinary measures for its containment. It is necessary to know the behaviour of aerosols carrying the virus to avoid this contagion. This paper describes the behaviour of aerosols and their role in the transmission of SARS‐CoV‐2 according to published models using a scoping review based on the PubMed, Scopus, and WOS databases. From an initial 530 references, 9 papers were selected after applying defined inclusion criteria. The results reinforce the airborne transmission route as a means of contagion of the virus and recommend the use of face masks, extending social distance to more than 2 metres, and natural ventilation of enclosed spaces as preventive measures. These results contribute to a better understanding of SARS‐CoV‐2 and help design effective strategies to prevent its spread.

COVID-19 Outbreak in a Military Unit in Korea

OBJECTIVES

This study presents the response of a military unit to the COVID-19 outbreak in Gyeonggi Province. As soon as two soldiers were identified as index cases, the infectious disease investigators of the Gyeonggi Provincial Government, Korea Disease Control and Prevention Agency and the Armed Forces Epidemiologic Investigation Center, discussed the investigation and response plan for an imminent massive outbreak.

METHODS

The joint immediate response team (IRT) conducted interviews with confirmed patients with COVID-19, reviewed medical records, performed contact tracing using global positioning system (GPS), and undertook a field investigation. For risk assessment, the joint IRT visited all eight sites of the military units and the army chaplain's church to evaluate the transmission risk of each site. The evaluation items included the size of the site, the use of air conditioning, whether windows were opened, and whether masks were worn. A pooled testing was used for a low-risk population to quickly detect the spread of COVID-19 in the military base.

RESULTS

A day before the symptom onset of the index case, the lecturer and >50% of the attendees were infected with COVID-19 while attending a lecture that lasted 2 h and 30 min. Attendees were not wearing masks and were in a poorly ventilated room.

CONCLUSION

Since the disease can be spread before symptom onset, contact tracing must be performed to investigate potential exposures prior to symptom onset and manage any exposed persons.

Doctors Spreading SARS-CoV-2 Infection to Their Patients and Health Workers. What is the Likelihood of This Scenario?

Aims: In this particular study, we report our experience of eight doctors infected with SARS-CoV-2 and discuss the probability of in-hospital virus transmission to patients or the rest of the hospital personnel. The importance of PPEs is highlighted. Materials and methods:We explore the data of eight doctors who were tested positive for SARS-CoV-2 after returning from their summer vacation. More specific, we evaluated the time they spent working before they got tested after their return, the symptoms they developed and the results of their tracking through their patients and the rest of hospital workers. Results:All doctors followed their working schedule, ranging from 2-4 days after their summertime off, without knowledge of being infected. They had been keeping all suggested protection precautions, while no further virus transmission to patients and/or other healthcare workers occurred, even though they had close contact and cooperation with many of them. Conclusions:Our experience suggests that, if healthcare workers conform to established safety procedures, the likelihood of further transmission both to patients and their colleagues, even in asymptomatic state, appears to be minimal.

Indoors ventilation in times of confinement by SARS-CoV-2 epidemic: A comparative approach between Spain and Italy

With the arrival of the SARS-CoV-2 coronavirus, the scientific academia, as well as policymakers, are striving to conceive solutions as an attempt to contain the spreading of contagion. Among the adopted measures, severe lockdown restrictions were issued to avoid the diffusion of the virus in an uncontrolled way through public spaces. It can be deduced from recent literature that the primary route of transmission is via aerosols, produced mainly in poorly ventilated interior areas where infected people spend a lot of time with other people. Concerning contagion rates, accumulated incidence or number of hospitalizations due to COVID-19, Spain, and Italy have reached very high levels. In this framework, a regression analysis to assess the feasibility of the indoor ventilation measures established in Spain and Italy, with respect to the European framework, is here presented. To this aim, ten cases of housing typology were and analyzed. The results show that the measures established in the applicable regulations to prevent and control the risk of contagion by aerosols are not adequate to guarantee a healthy environment indoors. The current Italian guidelines are more restrictive than in Spain, yet the ventilation levels are still insufficient in times of pandemic.

Interactions of SARS-CoV-2 with inanimate surfaces in built and transportation environments

Understanding the interactions and transmission of pathogens with/via inanimate surfaces common in the built environment and public transport vehicles is critical to promoting sustainable and resilient urban development. Here, molecular dynamics (MD) simulations are used to study the adhesion of SARS-CoV-2 (the causative agent of COVID-19) to some of these surfaces at different temperatures (same for surfaces and ambiance) ranging from -23 to 60 °C. Surfaces simulated are aluminum, copper, copper oxide, polyethylene (PE), and silicon dioxide (SiO2). Steered MD (SMD) simulations are also used to investigate the transfer of the virus from PE and SiO2 when a contaminated surface is touched. The virus shows the lowest and highest adhesions to PE and SiO2, respectively (20 vs 534 eV). Influence of temperature is not found to be noticeable. Using simulated water molecules to represent moisture on the skin, SMD simulations show that water molecules can lift the virus from the PE surface but damage the virus when lifting it from the the SiO2 surface. The results suggest that the PE surface is a more favorable surface to transmit the virus than the other surfaces simulated in this study. The results are compared with those reported in a few experimental studies.

Detection of COVID-19 from speech signal using bio-inspired based cepstral features

The early detection of COVID-19 is a challenging task due to its deadly spreading nature and existing fear in minds of people. Speech-based detection can be one of the safest tools for this purpose as the voice of the suspected can be easily recorded. The Mel Frequency Cepstral Coefficient (MFCC) analysis of speech signal is one of the oldest but potential analysis tools. The performance of this analysis mainly depends on the use of conversion between normal frequency scale to perceptual frequency scale and the frequency range of the filters used. Traditionally, in speech recognition, these values are fixed. But the characteristics of speech signals vary from disease to disease. In the case of detection of COVID-19, mainly the coughing sounds are used whose bandwidth and properties are quite different from the complete speech signal. By exploiting these properties the efficiency of the COVID-19 detection can be improved. To achieve this objective the frequency range and the conversion scale of frequencies have been suitably optimized. Further to enhance the accuracy of detection performance, speech enhancement has been carried out before extraction of features. By implementing these two concepts a new feature called COVID-19 Coefficient (C-19CC) is developed in this paper. Finally, the performance of these features has been compared.

Moderation effect of urban density on changes in physical activity during the coronavirus disease 2019 pandemic

Various social distancing measures were carried out in many cities worldwide during the coronavirus disease 2019 pandemic (COVID-19). These measures have led to decreased physical activity levels and higher health risks among urban populations. Strong evidence has been established that built environment characteristics can stimulate physical activity and thus improve public health during non-pandemic periods. Urban density was arguably one of the most important built environment characteristics. However, little is known about whether high urban density amplifies or attenuates the decline in physical activity during the pandemic. Based on two-wave physical activity data collected before and during the pandemic (in January and May 2020, respectively), we used moderation analysis to compare the changes in physical activity levels between people living in low- and high-density neighborhoods. Our results showed that people living in low-density areas have a smaller decrease in physical activity conducted in neighborhood, compared to those living in high-density areas. Our findings suggest that a flexible and porous urban development strategy could enhance the resilience of a city during the coronavirus pandemic and beyond.

A look into the future of the COVID-19 pandemic in Europe: an expert consultation

How will the coronavirus disease 2019 (COVID-19) pandemic develop in the coming months and years? Based on an expert survey, we examine key aspects that are likely to influence the COVID-19 pandemic in Europe. The challenges and developments will strongly depend on the progress of national and global vaccination programs, the emergence and spread of variants of concern (VOCs), and public responses to non-pharmaceutical interventions (NPIs). In the short term, many people remain unvaccinated, VOCs continue to emerge and spread, and mobility and population mixing are expected to increase. Therefore, lifting restrictions too much and too early risk another damaging wave. This challenge remains despite the reduced opportunities for transmission given vaccination progress and reduced indoor mixing in summer 2021. In autumn 2021, increased indoor activity might accelerate the spread again, whilst a necessary reintroduction of NPIs might be too slow. The incidence may strongly rise again, possibly filling intensive care units, if vaccination levels are not high enough. A moderate, adaptive level of NPIs will thus remain necessary. These epidemiological aspects combined with economic, social, and health-related consequences provide a more holistic perspective on the future of the COVID-19 pandemic.

COVID-19 Impact on Operation and Energy Consumption of Heating, Ventilation and Air-Conditioning (HVAC) Systems

Heating, ventilation and air-conditioning (HVAC) system is favourable for regulating indoor temperature, relative humidity, airflow pattern and air quality. However, HVAC systems may turn out to be the culprit of microbial contamination in enclosed spaces and deteriorate the environment due to inappropriate design and operation. In the context of COVID-19, significant transformations and new requirements are occurring in HVAC systems. Recently, several updated operational guidelines for HVAC systems have been issued by various institutions to control the airborne transmission and mitigate infection risks in enclosed environments. Challenges and innovations emerge in response to operational variations of HVAC systems. To efficiently prevent the spread of the pandemic and reduce infection risks, it is essential to have an overall understanding of impacts caused by COVID-19 on HVAC systems. Therefore, the objectives of this article are to: (a) provide a comprehensive review of the airborne transmission characteristics of SARS-CoV-2 in enclosed spaces and a theoretical basis for HVAC operation guideline revision; (b) investigate HVAC-related guidelines to clarify the operational variations of HVAC systems during the pandemic; (c) analyse how operational variations of HVAC systems affect energy consumption; and (d) identify the innovations and research trends concerning future HVAC systems. Furthermore, this paper compares the energy consumption of HVAC system operation during the normal times versus pandemic period, based on a case study in China, providing a reference for other countries around the world. Results of this paper offer comprehensive insights into how to keep indoor environments safe while maintaining energy-efficient operation of HVAC systems.

ATR-FTIR and LC-Q-ToF-MS analysis of indoor dust from different micro-environments located in a tropical metropolitan area

Indoor dust is an important matrix that exposes humans to a broad spectrum of chemicals. The information on the occurrence of contaminants of emerging concern (CECs), their metabolites, and re-emerging contaminants in indoor dust is rather limited. As the indoor environment is exposed to various chemicals from personal care products, furniture, building materials, machineries and cooking/cleaning products, there is a high chance of the presence of hazardous contaminants in indoor dust. In the present study, dust samples were collected from four different micro indoor environments (photocopying centres, residential houses, classrooms, and ATM cabins) located in an urban environment located in India's southwestern part. The collected samples were subjected to ATR - FTIR and LC-Q-ToF-MS analyses. The ATR - FTIR analysis indicated the presence of aldehydes, anhydrides, carboxylic acids, esters, sulphonic acids, and asbestos - a re-emerging contaminant. A total of 19 compounds were identified from the LC-Q-ToF-MS analysis. These compounds belonged to various classes such as plasticisers, plasticiser metabolites, photoinitiators, personal care products, pharmaceutical intermediates, surfactants, and pesticides. To the best of our knowledge, this is the first report regarding the presence of CECs in indoor environments in Kerala and also the suspected occurrence of pesticides (metaldehyde and ethofumesate) in classroom dust in India. Another important highlight of this work is the demonstration of ATR-FTIR as a complementary technique for LC-Q-ToF-MS in the analysis of indoor pollution while dealing with totally unknown pollutants. These results further highlight the occurrence of probable chemically modified metabolites in the tropical climatic conditions in a microenvironment.

Safety and Reverence: How Roman Catholic Liturgy Can Respond to the COVID-19 Pandemic

The current COVID-19 pandemic is a major challenge for many religious denominations. The Roman Catholic Church strongly depends on physical communal worship and sacraments. Disagreements grow concerning the best balance between safety and piety. To address this issue, I review the major transmission risks for the SARS-CoV-2 virus and list certain measures to enhance the safety of the Roman Catholic Liturgy without compromising its intrinsic beauty and reverent spiritual attitude. This can be achieved through assimilation of several traditional elements into the modern liturgy. I emphasize that religious leadership and decision-making should be transparent and based on inclusiveness, pluralism, best scientific evidence and voluntary cooperation.

SNS Big Data Analysis Framework for COVID-19 Outbreak Prediction in Smart Healthy City

Nowadays, the world is experiencing a pandemic crisis due to the spread of COVID-19, a novel coronavirus disease. The contamination rate and death cases are expeditiously increasing. Simultaneously, people are no longer relying on traditional news channels to enlighten themselves about the epidemic situation. Alternately, smart cities citizens are relying more on Social Network Service (SNS) to follow the latest news and information regarding the outbreak, share their opinions, and express their feelings and symptoms. In this paper, we propose an SNS Big Data Analysis Framework for COVID-19 Outbreak Prediction in Smart Sustainable Healthy City, where Twitter platform is adopted. Over 10000 Tweets were collected during two months, 38% of users aged between 18 and 29, while 26% are between 30 and 49 years old. 56% of them are males and 44% are females. The geospatial location is USA, and the used language is English. Natural Language Processing (NLP) is deployed to filter the tweets. Results demonstrated an outbreak cluster predicted seven days earlier than the confirmed cases with an indicator of 0.989. Analyzing data from SNS platforms enabled predicting future outbreaks several days earlier, and scientifically reduce the infection rate in a smart sustainable healthy city environment.

Estimation of the SARS-CoV-2 transmission probability in confined traffic space and evaluation of the mitigation strategies

Public transport is a fundamental service for the resumption of work and production, but the enclosed environment and dense population create very favorable conditions for the spread of epidemic infections. Thus, effective public health interventions are urgently introduced. The objective of this paper is to quantitatively estimate the SARS-CoV-2 transmission probability and evaluate the influence of environmental parameters and individual intervention on the epidemic prevention. For this purpose, (1) we estimate the virus emission rate with Diamond Princess Cruise Ship infection data by Monte Carlo simulation and the improved Wells-Riley model, and (2) employ the reproductive number R to quantify diverse mitigation strategies. Different determinants are examined such as the duration of exposure, the number of passengers combined with individual interventions such as mask type and mask-wearing rate. The results show that the SARS-CoV-2 quantum generation rate is 185.63. The R shows a stronger positive correlation with the exposure time comparing to the number of passengers. In this light, reducing the frequency of long-distance journeys on crowded public transportation may be required to reduce the spread of the virus during the pandemic. N95 mask and surgical mask can reduce the transmission risk by 97 and 84%, respectively, and even homemade mask can reduce the risk by 67%, which indicates that it is necessary to advocate wearing masks on public transportation.

Fluid dynamics of respiratory droplets in the context of COVID-19: Airborne and surfaceborne transmissions

The World Health Organization has declared COVID-19 a global pandemic. Several countries have experienced repeated periods of major spreading over the last two years. Many people have lost their lives, employment, and the socioeconomic situation has been severely impacted. Thus, it is considered to be one of the major health and economic disasters in modern history. Over the last two years, several researchers have contributed significantly to the study of droplet formation, transmission, and lifetime in the context of understanding the spread of such respiratory infections from a fluid dynamics perspective. The current review emphasizes the numerous ways in which fluid dynamics aids in the comprehension of these aspects. The biology of the virus, as well as other statistical studies to forecast the pandemic, is significant, but they are not included in this review.

A systematic approach to estimating the effectiveness of multi-scale IAQ strategies for reducing the risk of airborne infection of SARS-CoV-2

The unprecedented coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has made more than 125 million people infected and more than 2.7 million people dead globally. Airborne transmission has been recognized as one of the major transmission routes for SARS-CoV-2. This paper presents a systematic approach for evaluating the effectiveness of multi-scale IAQ control strategies in mitigating the infection risk in different scenarios. The IAQ control strategies across multiple scales from a whole building to rooms, and to cubical and personal microenvironments and breathing zone, are introduced, including elevated outdoor airflow rates, high-efficiency filters, advanced air distribution strategies, standalone air cleaning technologies, personal ventilation and face masks. The effectiveness of these strategies for reducing the risk of COVID-19 infection are evaluated for specific indoor spaces, including long-term care facility, school and college, meat plant, retail stores, hospital, office, correctional facility, hotel, restaurant, casino and transportation spaces like airplane, cruise ship, subway, bus and taxi, where airborne transmission are more likely to occur due to high occupancy densities. The baseline cases of these spaces are established according to the existing standards, guidelines or practices. Several integrated mitigation strategies are recommended and classified based on their relative cost and effort of implementation for each indoor space. They can be applied to help meet the current challenge of ongoing COVID-19, and provide better preparation for other possible epidemics and pandemics of airborne infectious diseases in the future.

Risk assessment of airborne COVID-19 exposure in social settings

The COVID-19 pandemic has led to many countries oscillating between various states of lock-down as they seek to balance keeping the economy and essential services running and minimizing the risk of further transmission. Decisions are made about which activities to keep open across a range of social settings and venues guided only by ad hoc heuristics regarding social distancing and personal hygiene. Hence, we propose the dual use of computational fluid dynamic simulations and surrogate aerosol measurements for location-specific assessment of risk of infection across different real-world settings. We propose a 3-tiered risk assessment scheme to facilitate classification of scenarios into risk levels based on simulations and experiments. Threshold values of <54 and >840 viral copies and <5% and >40% of original aerosol concentration are chosen to stratify low, medium, and high risk. This can help prioritize allowable activities and guide implementation of phased lockdowns or re-opening. Using a public bus in Singapore as a case study, we evaluate the relative risk of infection across scenarios such as different activities and passenger positions and demonstrate the effectiveness of our risk assessment methodology as a simple and easily interpretable framework. For example, this study revealed that the bus's air-conditioning greatly influences dispersion and increases the risk of certain seats and that talking can result in similar relative risk to coughing for passengers around an infected person. Both numerical and experimental approaches show similar relative risk levels with a Spearman's correlation coefficient of 0.74 despite differing observables, demonstrating applicability of this risk assessment methodology to other scenarios.

Application of Portable Air Purifiers for Mitigating COVID-19 in Large Public Spaces

This study investigated, using validated computational fluid dynamics techniques, the actual performance of portable air purifiers for reducing the infection risks of airborne respiratory diseases such as COVID-19, by properly installing air purifiers in complicated large public spaces of primary concern, such as restaurants and ballrooms. The research results reveal that portable air purifiers with HEPA filtration provide an effective solution to help mitigate virus-carrying particles/droplets in large spaces where the central air conditioning system with HEPA filtration may not provide adequate dilution and/or effective ventilation. Deploying portable air purifier changes the local flow directions, and thus, reduces the cross-table airflows that may enhance the possibility of cross-infection. A field experiment was further conducted in a restaurant and a ballroom to verify the on-site performance. This study indicates that each space is unique in furniture, occupant and system layouts and capacities, and thus, requires individualized investigation of appropriate purifier number, capacities, and locations. Flexible solutions such as portable air purifiers are important and low-cost supplements to more elaborate solutions installed in central air systems.

Spatial distributive effects of public green space and COVID-19 infection in London

While public green spaces (PGS) are opined to be central in the pandemic recovery, higher accessibility to PGS also mean a higher risk of infection spread from the raised possibility of people encountering each other. This study explores the distributive effects of accessibility of PGS on the COVID-19 cases distribution using a geo-spatially varying network-based risk model at the borough level in London. The coupled effect of social deprivation with accessibility of the PGS was used as an adjustment factor to identify vulnerability. Results indicate that highly connected green spaces with high choice measure were associated with high risk of infection transmission. Socially deprived areas demonstrated higher possibility of infection spread even with moderate connectivity of the PGS. The study demonstrated that only applying a uniform social distancing measure without characterising the infrastructure and social conditions may lead to higher infection transmission.

Indoor air quality improvement in COVID-19 pandemic: Review

INTRODUCTION

The advent of COVID-19 has impinged millions of people. The increased concern of the virus spread in confined spaces due to meteorological factors has sequentially fostered the need to improve indoor air quality.

OBJECTIVE

This paper aims to review control measures and preventive sustainable solutions for the future that can deliberately help in bringing down the impact of declined air quality and prevent future biological attacks from affecting the occupant's health.

METHODOLOGY

Anontology chart is constructed based on the set objectives and review of all the possible measures to improve the indoor air quality taking into account the affecting parameters has been done.

OBSERVATIONS

An integrated approach considering non-pharmaceutical and engineering control measures together for a healthy indoor environment should be contemplated rather than discretizing the available solutions. Maintaining social distance by reducing occupant density and implementing a modified ventilation system with advance filters for decontamination of viral load can help in sustaining healthy indoor air quality.

CONCLUSION

The review paper in the main, provides a brief overview of all the improvement techniques bearing in mind thermal comfort and safety of occupants and looks for a common ground for all the technologies based on literature survey and offers recommendation for a sustainable future.

COVID-19: Research Directions for Non-Clinical Aerosol-Generating Facilities in the Built Environment

Physical contact and respiratory droplet transmission have been widely regarded as the main routes of COVID-19 infection. However, mounting evidence has unveiled the risk of aerosol transmission of the virus. Whereas caution has been taken to avoid this risk in association with clinical facilities, facilities such as spa pools and Jacuzzis, which are characterized by bubble-aerosol generation, high bather loads, and limited turnover rates, may promote aerosol transmission. Focusing on these non-clinical facilities in the built environment, a review study was undertaken. First, the typical water disinfection and ventilation-aided operations for the facilities were illustrated. Second, cross comparisons were made between the applicable standards and guidelines of the World Health Organization and countries including Australia, Canada, China, the United Kingdom, and the United States. The similarities and differences in their water quality specifications, ventilation requirements, and air quality enhancement measures were identified; there were no specific regulations for preventing aerosol transmission at those aerosol-generating facilities. Third, a qualitative review of research publications revealed the emergence of studies on potential air-borne transmission of COVID-19, but research on built facilities posing high risks of aerosol transmission remains scant. This study’s results inform key directions for future research on abating aerosol transmission of COVID-19: the development of bespoke personal protective equipment and engineering and management controls on water quality, ventilation, and air quality.

Speech-Language Pathology and Audiology in South Africa: Clinical Training and Service in the Era of COVID-19

INTRODUCTION AND PURPOSE

The novel coronavirus (COVID-19) presented new and unanticipated challenges to the provision of clinical services, from student training to the care of patients with speech-language and hearing (SLH) disorders. Prompt changes in information and communication technologies (ICT), were required to ensure that clinical training continued to meet the Health Professions Council of South Africa's regulations and patients received effective clinical care. The purpose of this study was to investigate online clinical training and supervision to inform current and future training and clinical care provision in SLH professions.

METHODOLOGY

A scoping review was conducted using the Arksey and O'Malley (2005) framework. The electronic bibliographic databases Science Direct, PubMed, Scopus, MEDLINE, and ProQuest were searched to identify publications about online clinical training and supervision and their impact on clinical service during COVID-19. Selection and analysis were performed by three independent reviewers using pretested forms.

RESULTS AND CONCLUSIONS

The findings revealed important benefits of teletraining and telepractice with potential application to South African clinical training and service provision. Five themes emerged: (1) practice produces favorable outcomes, (2) appreciation for hybrid models of training and service delivery, (3) cost effectiveness is a "big win" (4) internationalization of remote clinical training and service provision, and (5) comparable modality outcomes. These findings may have significant implications for teletraining and telepractice in low-and-middle income countries (LMICs) in the COVID-19 era and beyond, wherein demand versus capacity challenges (e.g., in human resources) persist. Current findings highlight the need for SLH training programmes to foster a hybrid clinical training model. Few studies were conducted in LMICs, indicating a gap in such research.

Virology features of a family cluster of SARS-CoV-2 infections in Shanghai, China

The global spread of SARS-CoV-2 is currently continuing, and the World Health Organization has announced the risk assessment of the viruses as high. In this study, we analyzed virology features of SARS-CoV-2 causing a family cluster outbreak. Among the six family members, five have been laboratory-confirmed infection of SARS-CoV-2 viruses. A total of five SARS-CoV-2 viruses have been isolated from the nasopharyngeal swabs. The complete genome of the viruses exhibited 100% nucleotide identity with each other. Only two nucleotide differences have been observed between genomes of the isolated viruses and the HCoV/Wuhan/ IVDC-HB-01/2019 strain. Therefore, SARS-CoV-2 has been confirmed as the causation of the family cluster infections.

Social distance monitoring framework using deep learning architecture to control infection transmission of COVID-19 pandemic

The recent outbreak of the COVID-19 affected millions of people worldwide, yet the rate of infected people is increasing. In order to cope with the global pandemic situation and prevent the spread of the virus, various unprecedented precaution measures are adopted by different countries. One of the crucial practices to prevent the spread of viral infection is social distancing. This paper intends to present a social distance framework based on deep learning architecture as a precautionary step that helps to maintain, monitor, manage, and reduce the physical interaction between individuals in a real-time top view environment. We used Faster-RCNN for human detection in the images. As the human's appearance significantly varies in a top perspective; therefore, the architecture is trained on the top view human data set. Moreover, taking advantage of transfer learning, a new trained layer is fused with a pre-trained architecture. After detection, the pair-wise distance between peoples is estimated in an image using Euclidean distance. The detected bounding box's information is utilized to measure the central point of an individual detected bounding box. A violation threshold is defined that uses distance to pixel information and determines whether two people violate social distance or not. Experiments are conducted using various test images; results demonstrate that the framework effectively monitors the social distance between peoples. The transfer learning technique enhances the overall performance of the framework by achieving an accuracy of 96% with a False Positive Rate of 0.6%.

COVID-19 recovery for the Nigerian construction sites: The role of the fourth industrial revolution technologies

Fourth industrial revolution (4IR) technologies have been proved as successful platforms to communicate and visualise construction projects within team meetings. These techniques possibly can enhance compliance with Covid-19 rules on sites. How far concerning Nigerian construction contractors in the use of 4IR technologies are yet to receive in-depth studies. Therefore, this paper offers a collective insight into the issues affecting construction firms from Covid-19 regarding lockdown rules and the role of 4IR technologies. Given the unexplored nature of the problem, a virtual face-to-face type of qualitative research method was employed. Twelve semi-structured interviews from selected construction firms and consultant experts were engaged and collated data analysed via a thematic approach. Findings group the 4IR technologies into smart construction site, simulation and modelling, and digitisation and virtualisation in Nigeria's context, and majority of the 4IR technologies can be useful to enhance Covid-19 compliance. Reluctant to adopt, high implementation cost, inadequate knowledge management, resistance to change, among others emerged as the factors hindering 4IR technologies usage. Findings will strengthen and provide a rich insight into the impact of Covid-19 on construction sites and contribute towards informing key stakeholders to create an enabling environment for the implementation of 4IR technologies on site.

Occupant-density-detection based energy efficient ventilation system: Prevention of infection transmission

Ventilation plays an important role in prevention and control of COVID-19 in enclosed indoor environment and specially in high-occupant-density indoor environments (e.g., underground space buildings, conference room, etc.). Thus, higher ventilation rates are recommended to minimize the infection transmission probability, but this may result in higher energy consumption and cost. This paper proposes a smart low-cost ventilation control strategy based on occupant-density-detection algorithm with consideration of both infection prevention and energy efficiency. The ventilation rate can be automatically adjusted between the demand-controlled mode and anti-infection mode with a self-developed low-cost hardware prototype. YOLO (You Only Look Once) algorithm was applied for occupancy detection based on video frames from surveillance cameras. Case studies show that, compared with a traditional ventilation mode (with 15% fixed fresh air ratio), the proposed ventilation control strategy can achieve 11.7% energy saving while lowering the infection probability to 2%. The developed ventilation control strategy provides a feasible and promising solution to prevent transmission of infection diseases (e.g., COVID-19) in public and private buildings, and also help to achieve a healthy yet sustainable indoor environment.

Leveraging artificial intelligence to analyze the COVID-19 distribution pattern based on socio-economic determinants

The spatialization of socioeconomic data can be used and integrated with other sources of information to reveal valuable insights. Such data can be utilized to infer different variations, such as the dynamics of city dwellers and their spatial and temporal variability. This work focuses on such applications to explore the underlying association between socioeconomic characteristics of different geographical regions in Dublin, Ireland, and the number of confirmed COVID cases in each area. Our aim is to implement a machine learning approach to identify demographic characteristics and spatial patterns. Spatial analysis was used to describe the pattern of interest in electoral divisions (ED), which are the legally defined administrative areas in the Republic of Ireland for which population statistics are published from the census data. We used the most informative variables of the census data to model the number of infected people in different regions at ED level. Seven clusters detected by implementing an unsupervised neural network method. The distribution of people who have contracted the virus was studied.

Does historical data still count? Exploring the applicability of smart building applications in the post-pandemic period

The emergence of COVID-19 pandemic is causing tremendous impact on our daily lives, including the way people interact with buildings. Leveraging the advances in machine learning and other supporting digital technologies, recent attempts have been sought to establish exciting smart building applications that facilitates better facility management and higher energy efficiency. However, relying on the historical data collected prior to the pandemic, the resulting smart building applications are not necessarily effective under the current ever-changing situation due to the drifts of data distribution. This paper investigates the bidirectional interaction between human and buildings that leads to dramatic change of building performance data distributions post-pandemic, and evaluates the applicability of typical facility management and energy management applications against these changes. According to the evaluation, this paper recommends three mitigation measures to rescue the applications and embedded machine learning algorithms from the data inconsistency issue in the post-pandemic era. Among these measures, incorporating occupancy and behavioural parameters as independent variables in machine learning algorithms is highlighted. Taking a Bayesian perspective, the value of data is exploited, historical or recent, pre- and post-pandemic, under a people-focused view.

Identification of the high-risk residence communities and possible risk factors of COVID-19 in Wuhan, China☆

The coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern. It is important to identify high-risk residence communities and the risk factors for decision making on targeted prevention and control measures. In this paper, the number of confirmed and suspected cases of COVID-19 in the residence communities in Wuhan, China was collected together with the characteristic variables of the residence communities and the distances between the residence communities and nearby crowded places. The correlation analysis was conducted between the number of confirmed cases and the characteristic/distance variables. Concerning the characteristic variables, there are significant positive correlations between the number of COVID-19 confirmed cases and the construction area, covered area, total number of houses, total number of buildings, volume ratio, property charge, and number of second-hand houses in the residence communities in Wuhan, while minor or no correlation is observed for the average price of houses, construction year, greening ratio, or number of sold houses. Concerning the distance variables, there are significant negative correlations between the number of confirmed cases and the distances from the residence communities to the nearest universities, business clusters, and railway stations, while minor or no correlation is observed for the Huanan Seafood Wholesale Market, kindergartens, primary schools, middle schools, shopping malls, cinemas, subway stations, bus stops, inter-city bus stations, airport, general hospitals, or appointed hospitals for COVID-19 pandemic. Therefore, the residence communities which are newly-built, where the volume ratio or property charge is high or the construction area, covered area, or total number of houses, buildings, second-hand houses, or sold houses is large, or which are close to universities, business clusters, subway stations, or railway stations are the high-risk ones where strict measures should be taken. This study provides the authorities with a valuable reference for precise disease prevention and control on the residence community level in similar cities in the world.

Working Women, Delhi Metro and Covid-19: A Case Study in Delhi-NCR

Availability of safe, reliable and affordable public transport facilitates access to work opportunities. This relationship between transport and economic independence is not gender neutral. Delhi's Metro Rail Network marked a milestone in this regard as it provided a gender-sensitive means of mass transit with specific facilities for women passengers. However, the onset of Covid-19 pandemic, followed by restrictions on mobility and change in working habits, brought the urban public transport network to a standstill. Given this background, the paper explores the impact of Metro Rail Network on the commuting pattern and preferences of working women in Delhi-NCR region as well as the travel-related challenges faced by women that were magnified during the pandemic.

Peering inside a cough or sneeze to explain enhanced airborne transmission under dry weather

High-fidelity simulations of coughs and sneezes that serve as virtual experiments are presented, and they offer an unprecedented opportunity to peer into the chaotic evolution of the resulting airborne droplet clouds. While larger droplets quickly fall-out of the cloud, smaller droplets evaporate rapidly. The non-volatiles remain airborne as droplet nuclei for a long time to be transported over long distances. The substantial variation observed between the different realizations has important social distancing implications, since probabilistic outlier-events do occur and may need to be taken into account when assessing the risk of contagion. Contrary to common expectations, we observe dry ambient conditions to increase by more than four times the number of airborne potentially virus-laden nuclei, as a result of reduced droplet fall-out through rapid evaporation. The simulation results are used to validate and calibrate a comprehensive multiphase theory, which is then used to predict the spread of airborne nuclei under a wide variety of ambient conditions.

Could thermodynamics and heat and mass transfer research produce a fundamental step advance toward and significant reduction of SARS-COV-2 spread?

We are living an extraordinary season of uncertainty and danger, which is caused by SARS-Cov-2 infection and consequent COVID-19 infection. This preliminary study comes from both a mix of entrepreneurial experience and scientific research. It is aimed by the exigency to reach a new and more effective analysis of the risks on the filed and to reduce them inside a necessary cooperation process which may regard both research and some of the economic activities which are damaged by passive protection measures such as indiscriminate lockdowns. This global emergency requires specific efforts by any discipline that regards specific problems which need to be solved urgently. The characteristic airborne diffusion patterns of COVID-19 shows that the airborne presence of viruses depends on multiple factors which include the dimension of microdroplets emitted by a contagious person, the atmospheric temperature and humidity, the presence of atmospheric particulate and pollution, which may act as a transport vehicle for the virus. The pandemic diffusion shows a particular correlation with the air quality and levels of atmospheric pollution. Specific problems need to solved to understand better the virus, its reliability, diffusion, replication, how it attacks the persons and the conditions, which drives to both positive and deadly evolution of the illness. Most of these problems may benefit from the contribution from both heat and mass transfer and the unsteady thermodynamics of living systems which evolves according to constructal law. After the bibliographic research on the virus, emissive and spread modes, and consequent today adopted protection, a detailed analysis of the contributions which may be assessed by research in thermodynamics, heat and mass transfer, technical and chemical physics. Some possible areas of research have been identified and discussed to start an effective mobilization which may support the effort of the research toward a significant reduction of the impacts of the pandemic infection and the economic risks of new generalized lockdowns.

Exploring spatiotemporal effects of the driving factors on COVID-19 incidences in the contiguous United States

Since December 2019, the world has witnessed the stringent effect of an unprecedented global pandemic, coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of January 29,2021, there have been 100,819,363 confirmed cases and 2,176,159 deaths reported. Among the countries affected severely by COVID-19, the United States tops the list. Research has been conducted to discuss the causal associations between explanatory factors and COVID-19 transmission in the contiguous United States. However, most of these studies focus more on spatial associations of the estimated parameters, yet exploring the time-varying dimension in spatial econometric modeling appears to be utmost essential. This research adopts various relevant approaches to explore the potential effects of driving factors on COVID-19 counts in the contiguous United States. A total of three global spatial regression models and two local spatial regression models, the latter including geographically weighted regression (GWR) and multiscale GWR (MGWR), are performed at the county scale to take into account the scale effects. For COVID-19 cases, ethnicity, crime, and income factors are found to be the strongest covariates and explain most of the variance of the modeling estimation. For COVID-19 deaths, migration (domestic and international) and income factors play a critical role in explaining spatial differences of COVID-19 deaths across counties. Such associations also exhibit temporal variations from March to July, as supported by better performance of MGWR than GWR. Both global and local associations among the parameters vary highly over space and change across time. Therefore, time dimension should be paid more attention to in the spatial epidemiological analysis. Among the two local spatial regression models, MGWR performs more accurately, as it has slightly higher Adj. R2 values (for cases, R2 = 0.961; for deaths, R2 = 0.962), compared to GWR's Adj. R2 values (for cases, R2 = 0.954; for deaths, R2 = 0.954). To inform policy-makers at the nation and state levels, understanding the place-based characteristics of the explanatory forces and related spatial patterns of the driving factors is of paramount importance. Since it is not the first time humans are facing public health emergency, the findings of the present research on COVID-19 therefore can be used as a reference for policy designing and effective decision making.

Dilution-based evaluation of airborne infection risk - Thorough expansion of Wells-Riley model

Evaluation of airborne infection risk with spatial and temporal resolutions is indispensable for the design of proper interventions fighting infectious respiratory diseases (e.g., COVID-19), because the distribution of aerosol contagions is both spatially and temporally non-uniform. However, the well-recognized Wells-Riley model and modified Wells-Riley model (i.e., the rebreathed-fraction model) are limited to the well-mixed condition and unable to evaluate airborne infection risk spatially and temporally, which could result in overestimation or underestimation of airborne infection risk. This study proposes a dilution-based evaluation method for airborne infection risk. The method proposed is benchmarked by the Wells-Riley model and modified Wells-Riley model, which indicates that the method proposed is a thorough expansion of the Wells-Riley model for evaluation of airborne infection risk with both spatial and temporal resolutions. Experiments in a mock hospital ward also demonstrate that the method proposed effectively evaluates the airborne infection risk both spatially and temporally. The proposed method is convenient to implement for the development of healthy built environments.

Dilution-based evaluation of airborne infection risk - Thorough expansion of Wells-Riley model

Evaluation of airborne infection risk with spatial and temporal resolutions is indispensable for the design of proper interventions fighting infectious respiratory diseases (e.g., COVID-19), because the distribution of aerosol contagions is both spatially and temporally non-uniform. However, the well-recognized Wells-Riley model and modified Wells-Riley model (i.e., the rebreathed-fraction model) are limited to the well-mixed condition and unable to evaluate airborne infection risk spatially and temporally, which could result in overestimation or underestimation of airborne infection risk. This study proposes a dilution-based evaluation method for airborne infection risk. The method proposed is benchmarked by the Wells-Riley model and modified Wells-Riley model, which indicates that the method proposed is a thorough expansion of the Wells-Riley model for evaluation of airborne infection risk with both spatial and temporal resolutions. Experiments in a mock hospital ward also demonstrate that the method proposed effectively evaluates the airborne infection risk both spatially and temporally. The proposed method is convenient to implement for the development of healthy built environments.

A novel social distancing analysis in urban public space: A new online spatio-temporal trajectory approach

Social distancing in public spaces plays a crucial role in controlling or slowing down the spread of coronavirus during the COVID-19 pandemic. Visual Social Distancing (VSD) offers an opportunity for real-time measuring and analysing the physical distance between pedestrians using surveillance videos in public spaces. It potentially provides new evidence for implementing effective prevention measures of the pandemic. The existing VSD methods developed in the literature are primarily based on frame-by-frame pedestrian detection, addressing the VSD problem from a static and local perspective. In this paper, we propose a new online multi-pedestrian tracking approach for spatio-temporal trajectory and its application to multi-scale social distancing measuring and analysis. Firstly, an online multi-pedestrian tracking method is proposed to obtain the trajectories of pedestrians in public spaces, based on hierarchical data association. Then, a new VSD method based on spatio-temporal trajectories is proposed. The proposed method not only considers the Euclidean distance between tracking objects frame-by-frame but also takes into account the discrete Fréchet distance between trajectories, hence forms a comprehensive solution from both static and dynamic, local and holistic perspectives. We evaluated the performance of the proposed tracking method using the public dataset MOT16 benchmark. We also collected our own pedestrian dataset "SCU-VSD" and designed a multi-scale VSD analysis scheme for benchmarking the performance of the social distancing monitoring in the crowd. Experiments have demonstrated that the proposed method achieved outstanding performance on the analysis of social distancing.

A hover view over effectual approaches on pandemic management for sustainable cities - The endowment of prospective technologies with revitalization strategies

The COVID-19 pandemic affects all of society and hinders day-to-day activities from a straightforward perspective. The pandemic has an influential impact on almost everything and the characteristics of the pandemic remain unclear. This ultimately leads to ineffective strategic planning to manage the pandemic. This study aims to elucidate the typical pandemic characteristics in line with various temporal phases and its associated measures that proved effective in controlling the pandemic. Besides, an insight into diverse country's approaches towards pandemic and their consequences is provided in brief. Understanding the role of technologies in supporting humanity gives new perspectives to effectively manage the pandemic. Such role of technologies is expressed from the viewpoint of seamless connectivity, rapid communication, mobility, technological influence in healthcare, digitalization influence, surveillance and security, Artificial Intelligence (AI), and Internet of Things (IoT). Furthermore, some insightful scenarios are framed where the full-fledged implementation of technologies is assumed, and the reflected pandemic impacts in such scenarios are analyzed. The framed scenarios revolve around the digitalized energy sector, an enhanced supply chain system with effective customer-retailer relationships to support the city during the pandemic scenario, and an advanced tracking system for containing virus spread. The study is further extended to frame revitalization strategies to highlight the expertise where significant attention needs to be provided in the post-pandemic period as well as to nurture sustainable development. Finally, the current pandemic scenario is analyzed in terms of occurred changes and is mapped into SWOT factors. Using Fuzzy Technique for Order of Preference by Similarity to Ideal Solution based Multi-Criteria Decision Analysis, these SWOT factors are analyzed to determine where prioritized efforts are needed to focus so as to traverse towards sustainable cities. The results indicate that the enhanced crisis management ability and situational need to restructure the economic model emerges to be the most-significant SWOT factor that can ultimately support humanity for making the cities sustainable.

Social distancing enhanced automated optimal design of physical spaces in the wake of the COVID-19 pandemic

As the COVID-19 pandemic unfolds, manually enhanced ad-hoc solutions have helped the physical space designers and decision makers to cope with the dynamic nature of space planning. Due to the unpredictable nature by which the pandemic is unfolding, the standard operating procedures also change, and the protocols for physical interaction require continuous reconsideration. Consequently, the development of an appropriate technological solution to address the current challenge of reconfiguring common physical environments with prescribed physical distancing measures is much needed. To do this, we propose a design optimization methodology which takes the dimensions, as well as the constraints and other necessary requirements of a given physical space to yield optimal redesign solutions on the go. The methodology we propose here utilizes the solution to the well-known mathematical circle packing problem, which we define as a constrained mathematical optimization problem. The resulting optimization problem is solved subject to a given set of parameters and constraints - corresponding to the requirements on the social distancing criteria between people and the imposed constraints on the physical spaces such as the position of doors, windows, walkways and the variables related to the indoor airflow pattern. Thus, given the dimensions of a physical space and other essential requirements, the solution resulting from the automated optimization algorithm can suggest an optimal set of redesign solutions from which a user can pick the most feasible option. We demonstrate our automated optimal design methodology by way of a number of practical examples, and we discuss how this framework can be further taken forward as a design platform that can be implemented practically.