Study of COVID-19 pandemic in London (UK) from urban context

Abstract

COVID-19 transmission in London city was discussed in this work from an urban context. The association between COVID-19 cases and climate indicators in London, UK were analysed statistically employing published data from national health services, UK and Time and Date AS based weather data. The climatic indicators included in the study were the daily averages of maximum and minimum temperatures, humidity, and wind speed. Pearson, Kendall, and Spearman rank correlation tests were selected for data analysis. The data was considered up to two different dates to study the climatic effect (10th May in the first study and then updated up to 16th of July in the next study when the rest of the data was available). The results were contradictory in the two studies and it can be concluded that climatic parameters cannot solely determine the changes in the number of cases in the pandemic. Distance from London to four other cities (Birmingham, Leeds, Manchester, and Sheffield) showed that as the distance from the epicentre of the UK (London) increases, the number of COVID-19 cases decrease. What should be the necessary measure to be taken to control the transmission in cities have been discussed.

Association of built environment attributes with the spread of COVID-19 at its initial stage in China

“…Raj, Velraj, & Haghighat (2020) investigated the relationships between virus viability and populating density, climate severity, the volume of indoor spaces and air-conditioning usage in India, through correlation analyses. Traffic volumes on road and travel distance are identified as important factors to explain newly confirmed cases of COVID-19, by Lee et al (2020) who focused on Incheon, South Korea and estimated a linear regression model, and by Ghosh et al (2020) who focused on four UK cities and estimated a mixed-effects model, respectively. Through a bivariate logistic regression model, the household crowding, number of residential units per building, and household structure are found to be associated with COVID-19 transmission in New York ( Emeruwa et al, 2020 ).…”

“… Hamidi et al, 2020 Metropolitan population, activity density (population & employment per square mile), ICU beds per 10,000 population, primary care physicians per 10,000 population Multi-level linear model 1,165 metropolitan counties in the USA Larger metropolitan areas lead to significantly higher COVID-19 infection rates and higher mortality rates Lee et al, 2020 Traffic volumes on roads Single linear regression 6,307 vehicle detection systems (VDS) in South Korea In Incheon there was a positive, but insignificant, linear relationship between the increasing numbers of newly confirmed cases and increasing traffic. Ghosh et al, 2020 Travel distance to London, population density Mixed-effects model Distance from London to four other cities (Birmingham, Leeds, Manchester and Sheffield) As the distance from London increases, the number of COVID-19 cases decreases. Mizumoto & Chowell, 2020 Occupant density on the Diamond Princess cruise ship Mathematical modeling 621epidemiological incidence cases The increased exposure risks associated with high occupant density were demonstrated in the COVID-19 outbreak that occurred on the ship.…”

“…However, only a few BE attributes were targeted in each study and very limited studies have captured the BE from both inter-city and intra-city perspectives. For inter-city BE attributes, the contributions of travel distance are explored ( Ghosh et al, 2020 ), as well airlines or train flows ( Lau et al, 2020 ). However, no study can be found to deal with the number of trains, the number of flights and population flows across cities at the same time, as done in this study.…”

Spatiotemporal variability of COVID-19 pandemic in relation to air pollution, climate and socioeconomic factors in Pakistan

“…The atmospheric factors such as humidity, temperature, or solar irradiation perform inversely to COVID-19 survival. For instance, some recent studies show that COVID-19 transmission is favored by cold and dry weather conditions ( Casanova et al, 2010 ; Ghosh et al, 2020a ). Regarding COVID-19 pandemic transmission, Huang et al (2020) found that the COVID-19 is facilitated in the temperature range from 5 and 15 °C.…”

Towards an antifragile urban form: a research agenda for advancing resilience in the built environment

“…The increased speed of global movements, supported by technological progress, provides new opportunities to vira. Pathogens make their way from animals to humans locally in rural areas and spread to more urbanised regions thanks to global networks moving large numbers of people, animals and goods quickly across the globe on a daily basis (United Nations 2020; Ghosh et al 2020). Viewed from this angle, beyond its novelty, COVID-19 does not look exceptional; neither in its ability to spread in space nor in terms of the speed it travels.…”