Ready for the Post-Pandemic World?

The migrant worker dormitory clusters, although certainly a serious matter, might seem like just a blemish in an otherwise stellar record of successful crisis management by a high-capacity government responsible for developing Singapore from a "Third World” to a "First World” country in a very short period. Made up of very capable technocrats with a pragmatic outlook, this government focused on results, were quick to react to problems as they surfaced, and never took its eye away from the unsentimental task of keeping its globally embedded economy going as a vital part of national survival. Some might argue, further, that the authorities and countless other people in Singapore who volunteered their support did the best they could, in the context of an unprecedented and unpredictable pandemic of this scale and magnitude. However, the dormitory clusters and other lapses are symptoms of deeper structural problems. This is an important perspective that can constructively provide insight into whether these kinds of problems will manifest again and again in occasional eruptions and disruptions, which are painful but manageable. Or whether they will lead to more systemically destructive outcomes over time, which will either ruin Singapore eventually or create the opportunity to rebuild something better. Given Singapore's track record of swift and effective reaction to problems, one can expect economic rejuvenation at some point, accompanied by social and cultural exuberance. But will this mean returning to business-asusual? And will the deep structures shaped by authoritarian politics and market fundamentalism continue to worsen income inequality, poverty, an over-dependency on exploited migrant workers, the neglect of heterotopic spaces of otherness, and a dogmatic refusal by the government to engage more widely and in good faith with a broader range of people and perspectives outside its circle? © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

Migrant Worker Dormitories: Virus in a Neoliberal Politics of Space

In neoliberal Singapore, capitalism thrives on the exploitation of low-waged migrant workers who are attracted to Singapore to earn a living building and cleaning the city and serving its residents. Their presence in this already crowded city provokes a dualistic public response that originates from a grudging acceptance of their indispensability: on the one hand, a refusal to allow them to fully integrate with Singapore society and be treated as equal human beings;and, on the other hand, a compassionate desire to help them when they are in need. The former tendency has had the effect of making migrant workers as invisible as possible, hence the profitable solution to house large numbers of them in dormitories located in the peripheral spaces of the island. Capitalism, profit maximization, and space optimization have created conditions and practices of exploitation that are, in normal times, cloaked in invisibility. The 2020 outbreak of COVID-19 in these dormitory spaces should not be surprising, unless they had been so well-hidden in the blind spots of public conscience and policy consciousness. The outbreaks also produced dualistic public reactions: moral panic and the stigmatization of infectious foreigners as dirty and dangerous folk devils, which demands further spatial segregation;and civic activism that steps up to the service of helping the vulnerable in their time of need. The solutions going forward will likely be technical rather than normative in nature, well within the segregating and exploitative logic of neoliberal globalization, with evermore-ingenious ways to extract value from migrant-worker labour, while making them and the heterotopia in which they exist as invisible and distant as possible. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

Estimating SARS-CoV-2 infection risk in university dormitories using CO2 pulse injections

Air movement dynamics within three student dormitories were studied with simulated carbon dioxide (CO2) pulse injections to understand SARS-CoV-2 transmission risk. CO2 decay rate, proportion of shared air, and transport time were calculated from dynamic CO2 measurement data within simulated source and adjacent receptor rooms. Applying a Wells-Riley infection risk analysis with these results, the risk of SARS-CoV-2 infection in adjacent rooms ranged from 1% to 58% assuming an average emission rate of 5 quanta per hour and exposure duration of 3.5 days. Door opening status was very influential in resulting risk and vertical transport from source to above rooms was observed in all dormitories. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Measurement of Phthalates in Settled Dust in University Dormitories and Its Implications for Exposure Assessment

Six phthalates: dimethyl phthalate (DMP), diethyl phthalate (DEP), di(n-butyl) phthalate (DnBP), butyl benzyl phthalate (BBzP), di(2-ethylhexyl) phthalate (DEHP), and di(n-octyl) phthalate (DOP) in settled dust on different indoor surfaces were measured in 30 university dormitories. A Monte Carlo simulation was used to estimate college students' exposure via inhalation, non-dietary ingestion, and dermal absorption based on measured concentrations. The detection frequencies for targeted phthalates were more than 80% except for DEP (roughly 70%). DEHP was the most prevalent compound in the dust samples, followed by DnBP, DOP, and BBzP. Statistical analysis suggested that phthalate levels were higher in bedside dust than that collected from table surfaces, indicating a nonuniform distribution of dust-phase phthalates in the sleep environment. The simulation showed that the median DMP daily intake was 0.81 μg/kg/day, which was the greatest of the targeted phthalates. For the total exposures to all phthalates, the mean contribution of exposures during the daytime and sleeping time was 54% and 46%, respectively.

Psychological State and Subjective Environmental Perception of College Students Residing in Dormitories during Quarantine: A Case Study

Quarantine is one of the effective approaches to control the spread of COVID-19. However, prolonged isolation may harm the health of residents, especially students, who are quarantined in dormitories. This study surveyed students' behaviors, living environment, and psychological state through an online questionnaire. The results showed that during the isolation period, the participants' discomfort mainly came from high temperatures, high humidity, loud sounds, and dark lighting. Moreover, about half of the students experienced severe anxiety or depression, with poor sleep and an unclear mind being the most common problems. Additionally, this study focused on exploring the correlations between environmental perceptions and the psychological state of isolated students, that were identified to be significant. Furthermore, as isolation time was prolonged, the psychological state of isolated students worsened, and the most significant factor changed from thermal sensations to acoustic sensations. Interestingly, the psychological state of males was worse than females, and they were more easily affected by their thermal and acoustic environments. Therefore, keeping the environment comfortable has a positive influence on maintaining the good psychological condition of people in isolation. This study can provide suggestions for the improvement of indoor environments and for the mental health of people in isolation and in other similar situations.

Investigation of the Impacts of COVID-19 on the Electricity Consumption of a University Dormitory Using Weather Normalization

This study investigated the impacts of the COVID-19 pandemic on the electricity consumption of a university dormitory building in the southern US. The historical electricity consumption data of this university dormitory building and weather data of an on-campus weather station, which were collected from January 1st, 2017 to July 31st, 2020, were used for analysis. Four inverse data-driven prediction models, i.e, Artificial Neural Network, Long Short-Term Memory Recurrent Neural Network, eXtreme Gradient Boosting, and Light Gradient Boosting Machine, were exploited to account for the influence of the weather conditions. The results suggested that the total electricity consumption of the objective building decreased by nearly 41% (about 276,000 kWh (942 MMBtu)) compared with the prediction value during the campus shutdown due to the COVID-19. Besides, the daily load ratio (DTR) varied significantly as well. In general, the DTR decreased gradually from 80% to nearly 40% in the second half of March 2020, maintained on a relatively stable level between 30% to 60% in April, May, and June 2020, and then slowly recovered to 80% of the normal capacity in July 2020.

COVID-19 Cross Contamination through Energy Recovery Ventilation Devices

Airborne diseases are a current concern. Infections can spread through the air even when a disease may not be characterized as "airborne" in medical terms. Some installed HVAC systems can spread infectious agents to those who are not currently infected. Cross contamination through leakage in energy recovery ventilation (ERV) devices can provide a pathway for infection. Energy recovery devices are currently required in many new buildings codes and standards. They are often installed in retrofit projects in older buildings in order to save energy. The risk from cross-contamination can be estimated using the Wells-Riley infection model. Energy recovery ventilation device applications can be designed, specified, and installed to effectively eliminate the risk of cross contamination in new systems using current technology so this is an avoidable risk.. A framework for evaluating currently installed ERV systems is providedfor facilities managers and HVAC systems operators to identify and minimize cross contamination infection risk.

My will to live

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GREEN MANAGEMENT IMPLEMENTATION: A CASE OF THE BULGARIAN HOTEL MARKET

This research article focuses on the ecological operation of accommodation services in Bulgaria. The aim of this article is to evaluate the application of various green management elements and measures in selected hotels in Bulgaria, namely in the cities of Sofia and Varna. The research will pay attention to the implementation of individual green measures in hotel operations as well as a comparison between hotel categories and hotels in the two cities in terms of the application of green measures. Running an environmentally friendly hotel can have several positive effects, it significantly manifests itself in the area of marketing - it creates an image, has an effect on current and prospective guests, and defines the positioning of the hotel. It also impacts the economic and operational aspects, with ecological elements having the potential to reduce hotels' operating costs. The societal impact of running hotels in an environmentally friendly fashion lies in resource conservation and ensuring environmental sustainability. This research was carried out using mixed research methods, combining semi-structured interviews with hotel management staff in Varna (n = 90) and Sofia (n = 96). The total sample of participating hotels represented 81.6% of hotels in the two cities. The interviews were complemented with a questionnaire survey, which focused on the application of environmentally friendly solutions in hotel operations. In the data analysis stage, the methods of correspondence analysis, the ANOVA test and the Kruškal-Wallis test were used. The results suggest that the higher the hotel category, the stronger the trend to use environmentally friendly methods in running hotels. The research also found that there were differences between the level at which green measures were applied in hotel operations in the two cities. The research results are applicable in practice by national professional associations that support resource conservation and thus affect the entire hospitality industry.

High Sensitivity and Specificity of Dormitory-Level Wastewater Surveillance for COVID-19 during Fall Semester 2020 at Syracuse University, New York.

A residential building's wastewater presents a potential non-invasive method of surveilling numerous infectious diseases, including SARS-CoV-2. We analyzed wastewater from 16 different residential locations at Syracuse University (Syracuse, NY, USA) during fall semester 2020, testing for SARS-CoV-2 RNA twice weekly and compared the presence of clinical COVID-19 cases to detection of the viral RNA in wastewater. The sensitivity of wastewater surveillance to correctly identify dormitories with a case of COVID-19 ranged from 95% (95% confidence interval [CI] = 76-100%) on the same day as the case was diagnosed to 73% (95% CI = 53-92%), with 7 days lead time of wastewater. The positive predictive value ranged from 20% (95% CI = 13-30%) on the same day as the case was diagnosed to 50% (95% CI = 40-60%) with 7 days lead time. The specificity of wastewater surveillance to correctly identify dormitories without a case of COVID-19 ranged from 60% (95% CI = 52-67%) on the day of the wastewater sample to 67% (95% CI = 58-74%) with 7 days lead time. The negative predictive value ranged from 99% (95% CI = 95-100%) on the day of the wastewater sample to 84% (95% CI = 77-91%) with 7 days lead time. Wastewater surveillance for SARS-CoV-2 at the building level is highly accurate in determining if residents have a COVID-19 infection. Particular benefit is derived from negative wastewater results that can confirm a building is COVID-19 free.

Enumerating asymptomatic COVID-19 cases and estimating SARS-CoV-2 fecal shedding rates via wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) was utilized to monitor SARS-CoV-2 RNA in sewage collected from manholes specific to individual student dormitories (dorms) at the University of Arizona in the fall semester of 2020, which led to successful identification and reduction of SARS-CoV-2 transmission events. Positive wastewater samples triggered clinical testing of residents within that dorm; thus, SARS-CoV-2 infected individuals were identified regardless of symptom expression. This current study examined clinical testing data to determine the abundance of asymptomatic versus symptomatic cases in these defined communities. Nasal and nasopharyngeal swab samples processed via antigen and PCR tests indicated that 79.2% of SARS-CoV-2 infections were asymptomatic, and only 20.8% of positive cases reported COVID-19 symptoms at the time of testing. Clinical data was paired with corresponding wastewater virus concentrations, which enabled calculation of viral shedding rates in feces per infected person. Mean shedding rates averaged from positive wastewater samples across all dorms were 7.30 ± 0.67 log10 genome copies per gram of feces (gc/g-feces) based on the N1 gene. Quantification of SARS-CoV-2 fecal shedding rates from infected individuals has been the critical missing component necessary for WBE models to measure and predict SARS-CoV-2 infection prevalence in communities. The findings from this study can be utilized to create models that can be used to inform public health prevention and response actions.

Singapore's Pandemic Preparedness: An Overview of the First Wave of COVID-19.

A global response to the rapid spread of the 2019 novel coronavirus disease (COVID-19) is imperative in order to reduce mortality and morbidity as well as preventing a country's health system from collapse. Singapore showed exceptional leadership in the containment of the spread of the virus, however through April 2020 the country experienced exponential growth in the number of infections, particularly migrant workers living in dormitories. The following historical case study provides an overview of Singapore's country profile, their healthcare system and the country's non pharmaceutical measures taken to mitigate and contain the spread of COVID-19 in the first few months of the pandemic. We explore the impact COVID-19 had on Singapore's economy at that time and the implications of the resultant social and political disruptions. We conclude our study by using mathematical modelling to explore confirmed COVID-19 cases in Singapore's local community and those living in dormitories and use this data to forecast the progression of the epidemic in Singapore given the non-pharmaceutical interventions in place at that time. Our results indicate the COVID-19 outbreak in Singapore increased 3-fold the initial doubling rate of 22.5 days in the first 2 months of the outbreak to 6.7 days in the 5th month; We note a faster doubling rate of 4.9 days for those living in dormitories compared to a doubling rate of 13.5 days for the rest of the community.