New urban habits in Stockholm following COVID-19.

During the COVID-19 pandemic, physical distancing, mobility restrictions and self-isolation measures were implemented around the world as the primary intervention to prevent the virus from spreading. Urban life has undergone sweeping changes, with people using spaces in new ways. Stockholm is a particularly relevant case of this phenomenon since most facilities, such as day care centres and schools, have remained open, in contrast to cities with a broader lockdown. In this study, we use Twitter data and an online map survey to study how COVID-19 restrictions have impacted the use of different locations, services and amenities in Stockholm. First, we compare the spatial distribution of 87,000 geolocated tweets pre-COVID-19 and during the COVID-19 pandemic. Second, we analyse 895 survey responses asking people to identify places they 'still visit', 'use more', 'avoid' and self-report reasons for using locations. The survey provides a nuanced understanding of whether and how restrictions have affected people. Service and seclusion were found to be important; therefore, the accessibility of such amenities was analysed, demonstrating how changes in urban habits are related to conditions of the local environment. We find how different parts of the city show different capacities to accommodate new habits and mitigate the effects of restrictions on people's use of urban spaces. In addition to the immediate relevance to COVID-19, this paper thus contributes to understanding how restrictions on movement and gathering, in any situation, expose more profound urban challenges related to segregation and social inequality.

MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes.

The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples for early detection, prevalence monitoring, and variant identification of human diseases in large populations. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we show that taxon abundance and sub-species diversisty in gut-associated microbiomes are new feature space to utilize for human population estimation. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships with respect to human population size. Here and throughout this paper, the human population size is essentially the sample size from the wastewater sample. We present a new algorithm, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxa's relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. New theorems are provided to justify our approach. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome.

Demand for Social Interactions: Evidence from the Restaurant Industry during the COVID-19 Pandemic

We study the heterogeneous impacts of COVID-19 on restaurants in the post-lockdown United States, from lens of social interactions. We use the data structure of chain restaurants to disentangle restaurant attributes such as food and service types (which vary across chains) and local market conditions such as infection risks (which vary with each establishment's geographical location). We find that visits to chains with higher social indices experienced larger drops as local new cases increased in 2020, but also faster recovery later when vaccination programs expanded. Moreover, demand for restaurants in city centers recovered faster than demand for those in suburbs. This article is protected by copyright. All rights reserved.

From SARS to COVID-19: Digital infrastructures of surveillance and segregation in exceptional times.

The COVID-19 pandemic, an exceptional crisis, sparked the introduction of new digital infrastructure to halt the novel coronavirus's spread. This paper explores how such digital infrastructure's impact might reverberate over the long term, by comparing Singapore, Hong Kong, and mainland China's utilization of digital technology in response to the 2003 SARS outbreak, and their responses to the 2020 COVID-19 pandemic. We find that advancements in digital technology since 2003 have boosted governments' surveillance and segregation abilities substantially-most dramatically so in China. Even though some of these new digital interventions are ostensibly designed to be temporary ones to address the needs of the immediate crisis, we argue that the resultant extensions of state power experienced during COVID-19 are likely to have profound long-term effects because they fundamentally affect sociopolitical contexts, institutional capabilities, and digital cultures. We also find that the extent to which governments can extend digital surveillance and segregation abilities during the pandemic is contingent on their respective sociopolitical, institutional, and digital cultural contexts.

Cities and infectious diseases: Assessing the exposure of pedestrians to virus transmission along city streets

As cities resume life in public space, they face the difficult task of retaining outdoor activity while decreasing exposure to airborne viruses, such as the novel coronavirus. Even though the transmission risk is higher in indoor spaces, recent evidence suggests that physical contact outdoors also contributes to an increased virus exposure. Given that streets constitute the largest percentage of public space in cities, there is an increasing need to prioritise their use to minimise transmission risk. However, city officials currently lack the assessment tools to achieve this. This article evaluates the extent to which street segments are associated with spatiotemporal variations of potential exposures of pedestrians to virus transmission. We develop a multi-component risk score that considers both urban form and human activity along streets over time, including (a) an assessment of pedestrian infrastructure according to the average width of pavements, (b) a measure of accessibility for each street based on its position in the street network, (c) an activity exposure score that identifies places along streets where exposure could be higher and (d) an estimate of the number of pedestrians that will pass through each street during weekdays and weekends. We use Amsterdam in the Netherlands as a case study to illustrate how our score could be used to assess the exposure of pedestrians to virus transmission along streets. Our approach can be replicated in other cities facing a similar challenge of bringing life back to the streets while minimising transmission risks.

Can Open Source Hardware Mechanical Ventilator (OSH-MVs) initiatives help cope with the COVID-19 health crisis? Taxonomy and state of the art.

The field of Open Source Hardware Mechanical Ventilators (OSH-MVs) has seen a steep rise of contributions during the 2020 COVID-19 pandemic. As predictions showed that the number of patients would exceed current supply of hospital-grade ventilators, a number of formal (academia, the industry and governments) and informal (fablabs and startups) entities raced to develop cheap, easy-to-fabricate mechanical ventilators. The presence of actors with very diverse modus operandi as well as the speed at which the field has grown, led to a fragmented design space characterized by a lack of clear design patterns, projects not meeting the minimum functional requirements or showing little-to-no innovation; but also valid alternatives to hospital-grade devices. In this paper we provide a taxonomic system to help researchers with no background in biomedical engineering to read, understand and contribute to the OSH-MV field. The taxonomy is composed of ten properties that are read through the lenses of three reflection criteria: buildability, adoptability and scalability. We applied the taxonomy to the analysis of seventeen OSH-MV projects, which are representative of the current landscape of possibilities available for COVID-19 patients. We discuss the different design choices adopted by each project highlighting strengths and weaknesses and we suggest possible directions for the development of the OSH-MV field.