Borough-level COVID-19 forecasting in London using deep learning techniques and a novel MSE-Moran’s I loss function

Following its identification in late 2019, COVID-19 has spread around the globe, and been declared a pandemic. With this in mind, modelling the spread of COVID-19 remains important for responding effectively. To date research has focused primarily on modelling the spread of COVID-19 on national and regional scales with just a few studies doing so on a city and sub-city scale. However, no attempts have yet been made to design and optimize a model explicitly for accurately forecasting the spread of COVID-19 at sub-city scale. This research aimed to address this research gap by developing an experimental LSTM-ANN deep learning model. The model is largely autoregressive in nature as it considers temporally lagged borough-level COVID-19 cases data from the last 9 days, but also considers temporally lagged (i) borough-level NO2 concentration data, (ii) government stringency data, and (iii) climatic data from the last 9 days, as well as non-temporally variable borough-level urban characteristics data when modelling and forecasting the spread of the disease. The model was also encouraged to learn the spatial relationships between boroughs with regards to the spread of COVID-19 by a novel MSE-Moran's I loss function. Overall, the model's performance appears promising and so the model represents a useful tool for assisting the decision making and interventions of governing bodies within cities. A sensitivity analysis also indicated that of the non COVID-19 variables, the government stringency is particularly important in the modelling process, with this being closely followed by the climatic variables, the NO2 concentration data, and finally the urban characteristics data. Additionally, the introduction of the novel MSE-Moran's I loss function appeared to improve the model's forecasting performance, and so this research has implications at the intersection of deep learning and disease modelling. It may also have implications within spatio-temporal forecasting more generally because such a feature may have the potential to improve forecasting in other spatio-temporal applications

URBAN MOBILITY IN POST-COVID CITY: Assessing the Conflict between Safe and Sustainable Urban Mobility in Four Types of Neighbourhoods in GCR Egypt.

Covid19 pandemic gives social distance great concerns in contemporary cities especially the one related to safe urban mobility. People were asked to choose travel modes that maintain safe social distance to minimize the chance of infection while traveling safely from place to another. Accordingly, urban mobility witnessed a paradigm shift from the first sustainable urban mobility paradigm that found efficiency in mass transportation and minimizing the need for extended private motorized mobility inside cities, to the new safe urban mobility paradigm that strive for reducing the face-to-face contact by encouraging single ride mobility. Accordingly, Planners are required to shift to the new paradigm of urban mobility, and scholars are required to question health safety of the new paradigm of urban mobility at the same time to question its sustainability. The research aims to compare adopted movement behaviour across different neighbourhood models including purpose of mobility, mode choices, trip distance, and trip frequency. The paper reports, based on empirical findings, to three conclusions. Firstly, covid19 caused different levels of coping movement behavioural change across different types of neighbourhoods. Secondly, the paper observed coping ideas of reducing unnecessary trips, displace mobility from public to private modes, distribution of trips to different times of the day, providing safe walkway for keeping social distance and encouraging walkability and cyclability. Finally, the paper deduced different design guidelines for urban form design that facilitate such coping urban mobility strategies and at the same time achieve sustainability including soft mixed use, soft density, and grid street patterns to facilitate coping of safe and sustainable urban mobility

The impact of the built environment on health behaviours and disease transmission in social systems

The environment plays an important role in disease dynamics and in determining the health of individuals. Specifically, the built environment has a large impact on the prevention and containment of both chronic and infectious disease in humans and in non-human animals. The effects of the built environment on health can be direct, for example, by influencing environmental quality, or indirect by influencing behaviours that impact disease transmission and health. Furthermore, these impacts can happen at many scales, from the individual to the society, and from the design of the plates we eat from to the design of cities. In this paper, we review the ways that the built environment affects both the prevention and the containment of chronic and infectious disease. We bring examples from both human and animal societies and attempt to identify parallels and gaps between the study of humans and animals that can be capitalized on to advance the scope and perspective of research in each respective field. By consolidating this literature, we hope to highlight the importance of built structures in determining the complex dynamics of disease and in impacting the health behaviours of both humans and animals.This article is part of the theme issue 'Interdisciplinary approaches for uncovering the impacts of architecture on collective behaviour'

Making Transit Safe to Ride During a Pandemic: What Are the Risks and What Can Be Done in Response?

UC-ITS-2021-12The Covid-19 pandemic dramatically curtailed travel in the spring of 2020 and more moderately in the months that followed. Travel on public transport declined more and remains lower than on other travel modes, such as driving, biking, and walking. Although public transit operators have implemented various measures to reduce the risk of infection for both riders and employees, fear that public transport poses a high risk for transmission of the infectious disease is widespread. Since the onset of the Covid-19 pandemic, debates have raged in the popular and academic literatures regarding the safety of public transit systems and the role they may play in spreading the disease. To inform this debate, the authors review the public health literature on the spread of communicable diseases on public transport and conclude that current debates over public transit safety with regard to infection risk have tended to simplify a complex question that depends on numerous factors, many of which are well beyond the control of public transit operators. The authors draw on published studies of previous epidemics and the current pandemic to show that (1) there is a risk of infection on public transport, but the relative magnitude of the risk is often lower than in many other settings including households, workplace, schools, restaurants, and hospitals; (2) both the broader public health response and public transit agency actions can meaningfully reduce the risks of transmission; and (3) public transport (and indeed all travel modes), by moving people from one place to another, can facilitate the geographical propagation of infections, which can be effectively limited by travel restrictions. The authors highlight the multitude of risk factors that can affect infection risk on public transport, and argue that public transit systems can be made safe by actions taken by individual riders, public transit operators and, most important, by community-wide public health responses

The face behind the Covid-19 mask ??? A comprehensive review

The threat of epidemic outbreaks like SARS-CoV-2 is growing owing to the exponential growth of the global population and the continual increase in human mobility. Personal protection against viral infections was enforced using ambient air filters, face masks, and other respiratory protective equipment. Available facemasks feature considerable variation in efficacy, materials usage and characteristic properties. Despite their widespread use and importance, face masks pose major potential threats due to the uncontrolled manufacture and disposal techniques. Improper solid waste management enables viral propagation and increases the volume of associated biomedical waste at an alarming rate. Polymers used in single-use face masks include a spectrum of chemical constituents: plasticisers and flame retardants leading to health-related issues over time. Despite ample research in this field, the efficacy of personal protective equipment and its impact post-disposal is yet to be explored satisfactorily. The following review assimilates information on the different forms of personal protective equipment currently in use. Proper waste management techniques pertaining to such special wastes have also been discussed. The study features a holistic overview of innovations made in face masks and their corresponding impact on human health and environment. Strategies with SDG3 and SDG12, outlining safe and proper disposal of solid waste, have also been discussed. Furthermore, employing the CFD paradigm, a 3D model of a face mask was created based on fluid flow during breathing techniques. Lastly, the review concludes with possible future advancements and promising research avenues in personal protective equipment

Improving SARS-CoV-2 surveillance, mitigation and control measures in low- and middle-income countries using mobility data and rapid diagnostic tests

The SARS-CoV-2 pandemic has infected millions of people globally and continues to spread rapidly in many countries. As global vaccine access remains limited, SARS-CoV-2 transmission can be reduced through non-pharmaceutical interventions (NPIs), such as social distancing and lockdown measures that limiting human contact by restricting human mobility, and diagnostic testing strategies that rapidly identify and isolate infectious individuals. In this dissertation, I conducted three studies that inform SARS-CoV-2 surveillance and control policies in low- and middle-income countries (LMICs). The first study focuses in South Africa, where there have been multiple lockdowns and COVID-19 resurgences since the start of the pandemic.1 I assessed the association between mobility, as measured by smartphone data, and SARS-CoV-2 case positivity in South African provinces and districts at the ecological-level using regression, cross-correlation and interrupted time series analysis. I found that increases in mobility were positively associated with future COVID-19 incidence aggregated at both the province and district-level, and the association of mobility and COVID-19 incidence remained even when adjusted for district-level confounders. The second and third studies focus on rapid antigen testing (Ag-RDTs) in general LMIC settings. The main outcomes for these two studies include impact, defined as the percentage of infections averted compared to the base case scenario for each use case, and efficiency, defined as the number of tests needed to avert one infection compared to the base case scenario across use cases. In the second study, I quantified impact and efficiency of Ag-RDTs for population-level community testing using a compartmental model in a general population of 10 million people. This study adds to the literature that Ag-RDTs can be a valuable tool for population-level SARS-CoV-2 surveillance and case detection when testing is frequent and widespread, and diagnosis must be accompanied by corresponding reduction in post-diagnosis contacts in order for testing to be effective. I also identified that community testing is most useful when an epidemic is waning or before an epidemic wave, which is when SARS-CoV-2 prevalence and Rt are low. Finally, the third study assessed efficiency and impact of SARS-CoV-2 Ag-RDT testing strategies by comparing eight mathematical models across several scenarios, hereafter referred to as “use cases”. There was a clear trade-off between impact and efficiency; increasing test frequency (and/or more widespread testing of a community) increased impact, but consequently decreased efficiency. Additionally, testing strategies across most scenarios had the greatest impact when Rt and/or infection prevalence were low, but were least efficient. The findings from this dissertation provide further evidence of the importance of public health mitigation and control measures that reduce SARS-CoV-2 spread, such as NPIs and diagnostic testing, particularly in LMICs that have limited access to COVID-19 vaccines. The evidence generated from these studies can be used for future SARS-CoV-2 resurgences, whether from currently circulating variants, emergence of new SARS-CoV-2 variant strains or adaptation for use in future infectious disease outbreaks

Stadt der Zukunft - Gesund und nachhaltig: Brückenbau zwischen Disziplinen und Sektoren

Am gesellschaftlichen Einsatz für Förderung, Schutz und Wiederherstellung von Gesundheit sind im städtischen Leben zahlreiche Sektoren beteiligt. Während soziale Benachteiligungen von vielen Seiten als wichtige Größe wahrgenommen werden, ist die Aufmerksamkeit für ökologische Tragfähigkeit im Zusammenhang mit dem Thema Gesundheit bisher viel geringer. Es ist jedoch sinnvoll, diese Themen als Beitrag für eine sozial gerechte und ökologisch nachhaltige Stadtkultur zu verknüpfen. Ausgehend von einer "Welt im Wandel" entwickeln die Autor*innen ein Konzept Nachhaltiger StadtGesundheit als Erkenntnis- und Handlungsansatz. Leitprinzipien sind dabei eine "Blickfelderweiterung" auch in Richtung Zukunftsvorsorge und Nachhaltigkeit sowie ein entschlossener "Brückenbau" zur Überwindung von Barrieren, die noch allzu oft zwischen wissenschaftlichen Disziplinen und gesellschaftlichen Sektoren existieren