ASTRO: Reducing COVID-19 Exposure through Contact Prediction and Avoidance

The fight against the COVID-19 pandemic has highlighted the importance and benefits of recommending paths that reduce the exposure to and the spread of the SARS-CoV-2 coronavirus by avoiding crowded indoor or outdoor areas. Existing path discovery techniques are inadequate for coping with such dynamic and heterogeneous (indoor and outdoor) environments—they typically find an optimal path assuming a homogeneous and/or static graph, and hence they cannot be used to support contact avoidance. In this article, we pose the need for Mobile Contact Avoidance Navigation and propose ASTRO ( A ccessible S patio- T emporal R oute O ptimization), a novel graph-based path discovering algorithm that can reduce the risk of COVID-19 exposure by taking into consideration the congestion in indoor spaces. ASTRO operates in an A * manner to find the most promising path for safe movement within and across multiple buildings without constructing the full graph. For its path finding, ASTRO requires predicting congestion in corridors and hallways. Consequently, we propose a new grid-based partitioning scheme combined with a hash-based two-level structure to store congestion models, called CM-Structure , which enables on-the-fly forecasting of congestion in corridors and hallways. We demonstrate the effectiveness of ASTRO and the accuracy of CM-Structure ’s congestion models empirically with realistic datasets, showing up to one order of magnitude reduction in COVID-19 exposure.

Presence of SARS-CoV-2 RNA on Surfaces of Public Places and a Transportation System Located in a Densely Populated Urban Area in South America

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible RNA virus that causes COVID-19. Being aware of the presence of the virus on different types of surfaces and in different environments, and having a protocol for its detection, is important to understand the dynamics of the virus and its shedding patterns. In Ecuador, the detection of viral RNA in urban environmental samples has not been a priority. The present study analyzed samples from two densely populated neighborhoods and one public transportation system in Quito, Ecuador. Viral RNA presence was assessed using RT-LAMP. Twenty-eight out of 300 surfaces tested positive for SARS-CoV-2 RNA (9.33%). Frequently touched surfaces, especially in indoor spaces and on public transportation, were most likely to be positive for viral RNA. Positivity rate association for the two neighborhoods and for the surface type was not found. This study found viral RNA presence on urban surfaces; this information provides an insight into viral dissemination dynamics. Monitoring environmental SARS-CoV-2 could support the public health prevention strategies in Quito, Ecuador.

DESIGN OF INDOOR ROBOT PROTOTYPE GUIDED BY RFID BASED POSITIONING AND NAVIGATION SYSTEM

In this study, a robot prototype was designed for indoor spaces guided by an RFID-based positioning and navigation system. First, the work area was prepared from cardboard material and RFID cards were placed at predetermined points in the work area. The unique ID number of each RFID card was defined and the coordinates of their location in the work area are known. The RFID reader in the robot prototype reads from less than 5 cm. With a basic approach, when the robot reads an RFID card that it passes over while in motion, the position of the robot is considered the same as the position of the card it is currently reading. The route is defined for the robot prototype whose location is known before starting the movement. When the robot reads a new RFID card during movement, it must move forward or turn left or right to reach the point where the next RFID card is located according to the route. This decision was predetermined and defined according to its location. Alphabot was used as the prototype. Arduino board and additional auxiliary sensors such as gyro sensor, speed sensors, distance sensors are placed on the prototype. The prototype robot is left at any point in the work area and arrives at a target point determined by the user. The required road route to reach the destination is calculated with the shortest path algorithm depending on the road network on the working area and the route is defined. Thus, it is ensured that the prototype reaches the target without any external intervention by the user other than target determination.

A Relative Study of Contemporary Residential Landscape Architecture: From the Local to the Global Aspect

The location of residential quarters has a deep connection with the pattern of everyday life. It is not always significant for social activities; however, it is the main component in city planning. Along with the improvement of the society and economy, the landscape of residences is likewise changing. This paper aims to discuss the planning strategies of residential landscape from a socio-technical perceptive. A diverse approach was implemented for collecting data due to the uncertain situation around the world because of COVID19 including personal archival data, LDA authority, building regulations, research articles and interviews. The variables adapted for the current research are: drift from outdoor spaces to indoor spaces, orientation of design and spatial layout and practices diffusion. The study suggests that the dynamics of space and practices can normalize the unsustainable arrangements rooted in social organizations. The increased consumption of electrical appliances and specification of spaces has changed the culture into an unsuitable indoor layout planning and has neglected the use of outdoor areas in contemporary societies. This study can help to bring the implementation of house planning into a broader perspective globally as there is a comparison drawn between the local and international landscaped signing by a renowned landscape architect "Geoffrey Bawa". Keywords: architecture, contemporary and landscape, open spaces, orientation, residential planning

Beyond well-mixed: a simple probabilistic model of airborne disease transmission in indoor spaces

We develop a simple model for assessing risk of airborne disease transmission that accounts for non-uniform mixing in indoor spaces and is compatible with existing epidemiological models. A database containing 174 high-resolution simulations of airflow in classrooms, lecture halls, and buses is generated and used to quantify the spatial distribution of expiratory droplet nuclei for a wide range of ventilation rates, exposure times, and room configurations. Imperfect mixing due to obstructions, buoyancy, and turbulent dispersion results in concentration fields with significant variance. The spatial non-uniformity is found to be accurately described by a shifted lognormal distribution. A well-mixed mass balance model is used to predict the mean, and the standard deviation is parameterized based on ventilation rate and room geometry. When employed in a dose-response function risk model, infection probability can be estimated considering spatial heterogeneity that contributes to both short- and long-range transmission.

Risk of COVID-19 Infection in Public Transportation: The Development of a Model

South Korea’s social distancing policies on public transportation only involve mandatory wearing of masks and prohibition of food intake, similar to policies on other indoor spaces. This is not because public transportation is safe from coronavirus disease 2019 (COVID-19), but because no suitable policies based on accurate data have been implemented. To relieve fears regarding contracting COVID-19 infection through public transportation, the government should provide accurate information and take appropriate measures to lower the risk of COVID-19. This study aimed to develop a model for determining the risk of COVID-19 infection on public transportation considering exposure time, mask efficiency, ventilation rate, and distance. The risk of COVID-19 infection on public transportation was estimated, and the effectiveness of measures to reduce the risk was assessed. The correlation between the risk of infection and various factors was identified through sensitivity analysis of major factors. The analysis shows that, in addition to the general indoor space social distancing policy, ventilation system installation, passenger number reduction in a vehicle, and seat distribution strategies were effective. Based on these results, the government should provide accurate guidelines and implement appropriate policies.

A General Computational Framework for COVID-19 Modelling with Applications to Testing Varied Interventions in Education Environments

We construct a spatially-compartmental, individual-based model of the spread of SARS-CoV-2 in indoor spaces. The model can be used to predict the infection rates in a variety of locations when various non-pharmaceutical interventions (NPIs) are introduced. Tasked by the Welsh Government, we apply the model to secondary schools and to Further and Higher Education environments. Specifically, we consider student populations mixing in a classroom and in halls of residence. We focus on assessing the potential efficacy of Lateral Flow Devices (LFDs) when used in broad-based screens for asymptomatic infection or in ‘test-to-release’ scenarios in which individuals who have been exposed to infection are released from isolation after a negative LFD result. LFDs are also compared to other NPIs; we find that, although LFD testing can be used to mitigate the spread of SARS-CoV-2, it is more effective to invest in personal protective equipment, e.g., masks, and in increasing ventilation quality. In addition, we provide an open-access and user-friendly online applet that simulates the model, complete with user tutorials to encourage the use of the model to aid educational policy decisions as input infection data becomes available.

Metagenomic insights into the microbial communities of inert and oligotrophic outdoor pier surfaces of a coastal city

Background Studies of the microbiomes on surfaces in built environment have largely focused on indoor spaces, while outdoor spaces have received far less attention. Piers are engineered infrastructures commonly found in coastal areas, and due to their unique locations at the interface between terrestrial and aquatic ecosystems, pier surfaces are likely to harbor interesting microbiology. In this study, the microbiomes on the metal and concrete surfaces at nine piers located along the coastline of Hong Kong were investigated by metagenomic sequencing. The roles played by different physical attributes and environmental factors in shaping the taxonomic composition and functional traits of the pier surface microbiomes were determined. Metagenome-assembled genomes were reconstructed and their putative biosynthetic gene clusters were characterized in detail. Results Surface material was found to be the strongest factor in structuring the taxonomic and functional compositions of the pier surface microbiomes. Corrosion-related bacteria were significantly enriched on metal surfaces, consistent with the pitting corrosion observed. The differential enrichment of taxa mediating biodegradation suggests differences between the metal and concrete surfaces in terms of specific xenobiotics being potentially degraded. Genome-centric analysis detected the presence of many novel species, with the majority of them belonging to the phylum Proteobacteria. Genomic characterization showed that the potential metabolic functions and secondary biosynthetic capacity were largely correlated with taxonomy, rather than surface attributes and geography. Conclusions Pier surfaces are a rich reservoir of abundant novel bacterial species. Members of the surface microbial communities use different mechanisms to counter the stresses under oligotrophic conditions. A better understanding of the outdoor surface microbiomes located in different environments should enhance the ability to maintain outdoor surfaces of infrastructures.