Search

The disruptive effects of the COVID-19 pandemic has rapidly shifted how individuals navigate in cities. Governments are concerned that travel behavior will shift toward a car-driven and homeworking future, shifting demand away from public transport use. These concerns place the recovery of public transport in a possible crisis. A resilience perspective may aid the discussion around recovery – particularly one that deviates from pre-pandemic behavior. This paper presents an empirical study of London's public transport demand and introduces a perspective of spatial resilience to the existing body of research on post-pandemic public transport demand. This study defines spatial resilience as the rate of recovery in public transport demand within census boundaries over a period after lockdown restrictions were lifted. The relationship between spatial resilience and urban socioeconomic factors was investigated by a global spatial regression model and a localized perspective through Geographically Weighted Regression (GWR) model. In this case study of London, the analysis focuses on the period after the first COVID-19 lockdown restrictions were lifted (June 2020) and before the new restrictions in mid-September 2020. The analysis shows that outer London generally recovered faster than inner London. Factors of income, car ownership and density of public transport infrastructure were found to have the greatest influence on spatial patterns in resilience. Furthermore, influential relationships vary locally, inviting future research to examine the drivers of this spatial heterogeneity. Thus, this research recommends transport policymakers capture the influences of homeworking, ensure funding for a minimum level of service, and advocate for a polycentric recovery post-pandemic. [ABSTRACT FROM AUTHOR]

The current COVID-19 pandemic has profoundly impacted people's lifestyles and travel behaviours, which may persist post-pandemic. An effective monitoring tool that allows us to track the level of change is vital for controlling viral transmission, predicting travel and activity demand and, in the long term, for economic recovery. In this paper, we propose a set of Twitter mobility indices to explore and visualise changes in people's travel and activity patterns, demonstrated through a case study of London. We collected over 2.3 million geotagged tweets in the Great London Area (GLA) from Jan 2019 –Feb 2021. From these, we extracted daily trips, origin-destination matrices, and spatial networks. Mobility indices were computed based on these, with the year 2019 as a pre-Covid baseline. We found that in London, (1) People are making fewer but longer trips since March 2020. (2) In 2020, travellers showed comparatively reduced interest in central and sub-central activity locations compared to those in outer areas, whereas, in 2021, there is a sign of a return to the old norm. (3) Contrary to some relevant literature on mobility and virus transmission, we found a poor spatial relationship at the Middle Layer Super Output Area (MSOA) level between reported COVID-19 cases and Twitter mobility. It indicated that daily trips detected from geotweets and their most likely associated social, exercise and commercial activities are not critical causes for disease transmission in London. Aware of the data limitations, we also discuss the representativeness of Twitter mobility by comparing our proposed measures to more established mobility indices. Overall, we conclude that mobility patterns obtained from geo-tweets are valuable for continuously monitoring urban changes at a fine spatiotemporal scale. [ABSTRACT FROM AUTHOR]

The investigation of the fractal nature of financial data has been growing in the literature. The purpose of this paper is to investigate the impact of the COVID-19 pandemic on the efficiency of agricultural futures markets by using multifractal detrended fluctuation analysis (MF-DFA). To better understand the relative changes in the efficiency of agriculture commodities due to the pandemic, we split the dataset into two equal periods of seven months, i.e., 1 August 2019 to 10 March 2020 and 11 March 2020 to 25 September 2020. We used the high-frequency data at 15 min intervals of cocoa, cotton, coffee, orange juice, soybean, and sugar. The findings reveal that the COVID-19 pandemic has great but varying impacts on the intraday multifractal properties of the selected agricultural future markets. In particular, the London sugar witnessed the lowest multifractality while orange juice exhibited the highest multifractality before the pandemic declaration. Cocoa became the most efficient while the cotton exhibited the minimum efficient pattern after the pandemic. Our findings show that the highest improvement is found in the market efficiency of orange juice. Furthermore, the behavior of these agriculture commodities shifted from a persistent to an antipersistent behavior after the pandemic. The information given by the detection of multifractality can be used to support investment and policy-making decisions. [ABSTRACT FROM AUTHOR]

Background: Researchers conducting cohort studies may wish to investigate the effect of episodes of COVID-19 illness on participants. A definitive diagnosis of COVID-19 is not always available, so studies have to rely on proxy indicators. This paper seeks to contribute evidence that may assist the use and interpretation of these COVID-indicators.Methods: We described five potential COVID-indicators: self-reported core symptoms, a symptom algorithm; self-reported suspicion of COVID-19; self-reported external results; and home antibody testing based on a 'lateral flow' antibody (IgG/IgM) test cassette. Included were staff and postgraduate research students at a large London university who volunteered for the study and were living in the UK in June 2020. Excluded were those who did not return a valid antibody test result. We provide descriptive statistics of prevalence and overlap of the five indicators.Results: Core symptoms were the most common COVID-indicator (770/1882 participants positive, 41%), followed by suspicion of COVID-19 (n = 509/1882, 27%), a positive symptom algorithm (n = 298/1882, 16%), study antibody lateral flow positive (n = 124/1882, 7%) and a positive external test result (n = 39/1882, 2%), thus a 20-fold difference between least and most common. Meeting any one indicator increased the likelihood of all others, with concordance between 65 and 94%. Report of a low suspicion of having had COVID-19 predicted a negative antibody test in 98%, but positive suspicion predicted a positive antibody test in only 20%. Those who reported previous external antibody tests were more likely to have received a positive result from the external test (24%) than the study test (15%).Conclusions: Our results support the use of proxy indicators of past COVID-19, with the caveat that none is perfect. Differences from previous antibody studies, most significantly in lower proportions of participants positive for antibodies, may be partly due to a decline in antibody detection over time. Subsequent to our study, vaccination may have further complicated the interpretation of COVID-indicators, only strengthening the need to critically evaluate what criteria should be used to define COVID-19 cases when designing studies and interpreting study results. [ABSTRACT FROM AUTHOR]

This paper investigates the safe haven potential of Islamic stocks within the context of the London stock market, alongside other prominent hedging assets, namely gold, Brent crude, and Bitcoin, using the M-DCC GARCH model. The study finds that Islamic finance no longer demonstrates robust safe haven characteristics but instead serves as a diversifier during periods of market stability. In contrast, gold exhibits notable hedging properties both prior to the COVID-19 pandemic and during market turmoil, outperforming all assets except Bitcoin. [ABSTRACT FROM AUTHOR]

Recent outbreaks of coronavirus disease 2019 (COVID-19) has led a global pandemic cross the world. Most countries took two main interventions: suppression like immediate lockdown cities at epicenter or mitigation that slows down but not stopping epidemic for reducing peak healthcare demand. Both strategies have their apparent merits and limitations; it becomes extremely hard to conduct one intervention as the most feasible way to all countries. Targeting at this problem, this paper conducted a feasibility study by defining a mathematical model named SEMCR, it extended traditional SEIR (Susceptible-Exposed-Infectious-Recovered) model by adding two key features: a direct connection between Exposed and Recovered populations, and separating infections into mild and critical cases. It defined parameters to classify two stages of COVID-19 control: active contain by isolation of cases and contacts, passive contain by suppression or mitigation. The model was fitted and evaluated with public dataset containing daily number of confirmed active cases including Wuhan and London during January 2020 and March 2020. The simulated results showed that 1) Immediate suppression taken in Wuhan significantly reduced the total exposed and infectious populations, but it has to be consistently maintained at least 90 days (by the middle of April 2020). Without taking this intervention, we predict the number of infections would have been 73 folders higher by the middle of April 2020. Its success requires efficient government initiatives and effective collaborative governance for mobilizing of corporate resources to provide essential goods. This mode may be not suitable to other countries without efficient collaborative governance and sufficient health resources. 2) In London, it is possible to take a hybrid intervention of suppression and mitigation for every 2 or 3 weeks over a longer period to balance the total infections and economic loss. While the total infectious populations in this scenario would be possibly 2 times than the one taking suppression, economic loss and recovery of London would be less affected. 3) Both in Wuhan and London cases, one important issue of fitting practical data was that there were a portion (probably 62.9% in Wuhan) of self-recovered populations that were asymptomatic or mild symptomatic. This finding has been recently confirmed by other studies that the seroprevalence in Wuhan varied between 3.2% and 3.8% in different sub-regions. It highlights that the epidemic is far from coming to an end by means of herd immunity. Early release of intervention intensity potentially increased a risk of the second outbreak. [ABSTRACT FROM AUTHOR]

Given the paramount impacts of COVID-19 on people's lives in the capital of the UK, London, it was foreseeable that the city's crime patterns would have undergone significant transformations, especially during lockdown periods. This study aims to testify the crime patterns' changes in London, using data from March 2020 to March 2021 to explore the driving forces for such changes, and hence propose data-driven insights for policy makers and practitioners on London's crime deduction and prevention potentiality in post-pandemic era. (1) Upon exploratory data analyses on the overall crime change patterns, an innovative BSTS model has been proposed by integrating restriction-level time series into the Bayesian structural time series (BSTS) model. This novel method allows the research to evaluate the varied effects of London's three lockdown periods on local crimes among the regions of London. (2) Based on the predictive results from the BSTS modelling, three regression models were deployed to identify the driving forces for respective types of crime experiencing significant increases during lockdown periods. (3) The findings solidified research hypotheses on the distinct factors influencing London's specific types of crime by period and by region. In light of the received evidence, insights on a modified policing allocation model and supporting the unemployed group was proposed in the aim of effectively mitigating the surges of crimes in London. [ABSTRACT FROM AUTHOR]

Drawing on quantitative and qualitative research in England, and more specifically in London, this article sheds light on trends in platform work during the COVID-19 crisis. While the number of platform workers grew, the proportion of their income it contributed to fell, making up less than a quarter of total earnings. Interviews with driving and delivery platform workers in London (Europe's largest platform market) shed light on these puzzling trends. New recruitment by the platforms and adjustment of their algorithms during the lockdown led to downward pressure on earnings, poorer working conditions, extended waiting times, longer working hours and negative impacts on work–life balance, health and well-being. The article concludes that the pandemic provided platforms with an opportunity to consolidate their market position, but this was achieved at the cost of growing power asymmetry in the platform labour market, with workers' attempts to organise and improve conditions undermined by over-recruitment. [ABSTRACT FROM AUTHOR]

The coronavirus pandemic that started in 2019 has had wide-ranging impacts on many aspects of people's daily lives. At the peak of the outbreak, lockdown measures and social distancing changed the ways in which cities function. In particular, they had profound impacts on urban transportation systems, with public transport being shut down in many cities. Bike share systems (BSS) were widely reported as having experienced an increase in demand during the early stages of the pandemic before returning to pre-pandemic levels. However, the studies published to date focus mainly on the first year of the pandemic, when various waves saw continual relaxing and reintroductions of restrictions. Therefore, they fall short of exploring the role of BSS as we move to the post-pandemic period. To address this gap, this study uses origin-destination (O-D) flow data from London's Santander Cycle Hire Scheme from 2019–2021 to analyze the changing use of BSS throughout the first two years of the pandemic, from lockdown to recovery. A Gaussian mixture model (GMM) is used to cluster 2019 BSS trips into three distinct clusters based on their duration and distance. The clusters are used as a reference from which to measure spatial and temporal change in 2020 and 2021. In agreement with previous research, BSS usage was found to have declined by nearly 30% during the first lockdown. Usage then saw a sharp increase as restrictions were lifted, characterized by longer, less direct trips throughout the afternoon rather than typical peak commuting trips. Although the aggregate number of BSS trips appeared to return to normal by October 2020, this was against the backdrop of continuing restrictions on international travel and work from home orders. The period between July and December 2021 was the first period that all government restrictions were lifted. During this time, BSS trips reached higher levels than in 2019. Spatio-temporal analysis indicates a shift away from the traditional morning and evening peak to a more diffuse pattern of working hours. The results indicate that the pandemic may have had sustained impacts on travel behavior, leading to a "new normal" that reflects different ways of working. [ABSTRACT FROM AUTHOR]

Introduction: Following the emergence of SARS-CoV-2 in 2020, care homes were disproportionately impacted by high mortality and morbidity of vulnerable elderly residents. Non-pharmaceutical interventions (NPIs) and improved infection control measures together with vaccination campaigns have since improved outcomes of infection. We studied the utility of past infection status, recent vaccination and anti-S antibody titres as possible correlates of protection against a newly emergent Omicron variant infection. Methods: Prospective longitudinal surveillance of nine sentinel London care homes from April 2020 onwards found that all experienced COVID-19 outbreaks due to Omicron (BA.1) during December 2021 and January 2022, despite extensive prior SARS-CoV-2 exposure and high COVID-19 vaccination rates, including booster vaccines (>70% residents, >40% staff). Results: Detailed investigation showed that 46% (133/288) of Omicron BA.1 infections were SARS-CoV-2 reinfections. Two and three COVID-19 vaccine doses were protective against Omicron infection within 2-9 weeks of vaccination, though protection waned from 10 weeks post-vaccination. Prior infection provided additional protection in vaccinated individuals, approximately halving the risk of SARS-CoV-2 infection. Discussion: Anti-S antibody titre showed a dose-dependent protective effect but did not fully account for the protection provided by vaccination or past infection, indicating that other mechanisms of protection are also involved. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has paralyzed entire social levels. Organized religion is one of those levels, having suffered a lot due to the closing of churches and the automatic physical cessation of religious services. Both the weekly practitioners and those attending church minimally (say at Easter and Christmas) felt the shock of the closing of the churches. As such, the online environment was the saving option during the pandemic. However, not all churches embraced the move of liturgical services to online from the start, and at the same time, not all churches had a rich history of using digital technologies or the Internet for religious purposes. In this context, I investigate how religious communities succeeded in dealing with the imposed governmental regulations on social distance. I follow the specific religious rituals that have suffered the most by moving liturgy online, rituals such as baptism, Eucharist, burial, etc. Because different Christian churches understand rituals and liturgical practices in different ways, I focus specifically on a succinct comparison between the Romanian Orthodox Church and the neo-Protestant environment, especially the Seventh-day Adventist Church. In addition, I briefly extend the comparison to Adventist communities from the diaspora—especially those from London, the United Kingdom. [ABSTRACT FROM AUTHOR]

Background: To minimise infection during COVID-19, the clozapine haematological monitoring interval was extended from 4-weekly to 12-weekly intervals in South London and Maudsley NHS Foundation Trust. Aims: To investigate the impact of this temporary policy change on clinical and safety outcomes. Method: All patients who received clozapine treatment with extended (12-weekly) monitoring in a large London National Health Service trust were included in a 1-year mirror-image study. A comparison group was selected with standard monitoring. The proportion of participants with mild to severe neutropenia and the proportion of participants attending the emergency department for clozapine-induced severe neutropenia treatment during the follow-up period were compared. Psychiatric hospital admission rates, clozapine dose and concomitant psychotropic medication in the 1 year before and the 1 year after extended monitoring were compared. All-cause clozapine discontinuation at 1-year follow-up was examined. Results: Of 569 participants, 459 received clozapine with extended monitoring and 110 controls continued as normal. The total person-years were 458 in the intervention group and 109 in the control group, with a median follow-up time of 1 year in both groups. During follow-up, two participants (0.4%) recorded mild to moderate neutropenia in the intervention group and one (0.9%) in the control group. There was no difference in the incidence of haematological events between the two groups (IRR = 0.48, 95% CI 0.02–28.15, P = 0.29). All neutropenia cases in the intervention group were mild, co-occurring during COVID-19 infection. The median number of admissions per patient during the pre-mirror period remained unchanged (0, IQR = 0) during the post-mirror period. There was one death in the control group, secondary to COVID-19 infection. Conclusions: There was no evidence that the incidence of severe neutropenia was increased in those receiving extended monitoring. [ABSTRACT FROM AUTHOR]

Background: Maternal vaccinations against Influenza, Pertussis, and Covid-19 are recommended in the UK, and vaccines against further infections may become available soon. However, many pregnant women, especially in socially and ethnically diverse areas, have low vaccine uptake. Qualitative studies on the reasons and possible solutions are needed that are inclusive of disadvantaged and minority ethnic groups. We therefore aimed to understand the complex interplay between structural and behavioural factors contributing to the low maternal vaccine uptake in socially and ethnically diverse areas in London in the Covid-19 context. Methods: In 2022, we conducted semi-structured interviews and a focus group discussion among a purposive sample of 38 pregnant/recently pregnant women and 20 health service providers, including 12 midwives. Participants were recruited in ethnically diverse London boroughs. We followed a critical realist paradigm and used a thematic analysis approach. Results: The sample included participants who took all, some or none of the maternal vaccines, with some participants unsure whether they had taken or been offered the vaccines. Decision-making was passive or active, with the expectation for pregnant women to do their 'own research'. Participants described various individual, social and contextual influences on their decision-making as they navigated the antenatal care system. Missing or conflicting information from providers meant knowledge gaps were sometimes filled with misinformation from unreliable sources that increased uncertainties and mistrust. Both pregnant women and providers described structural and organisational factors that hindered access to information and vaccinations, including lack of training, time and resources, and shortcomings of health information systems and apps. Some participants described factors that facilitated vaccination uptake and many made recommendations for improvements. Conclusions: Our study showed how structural and organisational factors can compound uncertainties around maternal vaccination among socially and ethnically diverse populations. Results highlight the need for more reliable resources, streamlined workflows, improved electronic information systems and training in their use. Roles and responsibilities should be clarified with potential greater involvement of nurses and pharmacists in vaccine provision. Education and communication should consider individual (language/digital) skills and needs for information and reassurance. Further research is needed to co-produce solutions with service users and providers. [ABSTRACT FROM AUTHOR]

How does the COVID-19 pandemic affect interpersonal trust? Most evidence shows that natural disasters reinforce trust and cooperation, but the COVID-19 virus differs from other calamities, since it spreads through contact with people, potentially increasing suspicion and distrust, as, according to contemporaneous writers' accounts, seems to have been the case with the Black Death, the London plague, and the Spanish influenza. We investigate the link between interpersonal trust and individuals exposed to COVID-19, either vicariously through their community or networks or directly by becoming infected. We rely on an original panel survey, including a survey experiment, with a representative sample of adults in Italy, one of the countries hardest struck by the pandemic. Our experimental findings reveal that priming people about the risk that the pandemic poses to their health leads to a substantial increase in their trust in strangers. Our panel data analysis of within-individual effects shows that those who become infected trust strangers more than those who are not infected. Our findings could be explained by people observing higher than expected altruistic behavior or becoming more dependent on other people's support, consistent with the "emancipation theory of trust." When people recover from COVID-19, however, they drop to trusting strangers as much as those who were not directly exposed to the virus, an indication that the positive effects on trust during the pandemic have an emotional source. Nonetheless, the evidence suggests that, in the aggregate, there has been a small but significant increase in trust among the general population relative to prepandemic levels. [ABSTRACT FROM AUTHOR]

In this article we construct a number of early housing-market indicators from daily-scraped list-price data and investigate how they inform on housing-market trends prior to the release of official transaction data. We minimize the impact of non-market conform list prices by our data selection- and cleaning routine and thereby improve the overlap between list and transaction data. In addition to some well-known real-estate indicators (price and rent indices, price-rent ratios, market volume, time-on-market, and market turnover) we develop a new market sentiment indicator which we construct from the direction and frequency of online price changes for individual listings. We then use this group of indicators to investigate how housing markets in London and Vienna react to the COVID-19 pandemic during 2020. For London these indicators show high volatility during much of 2020 and we find that the sales and rental markets drift apart: The sales market shows an overall positive price trend, while the rental market becomes significantly weaker after the onset of the COVID-19 crisis. For Vienna we find that all indicators signal positive market developments for the first eight months after the start of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Crossing Cultures is a university-based research initiative that is part of London Metropolitan’s Centre for Urban and Built Ecologies (CUBE) which aims to develop a new pedagogical model. The focus is to provide an inclusive learning environment that facilitates intercultural relationships and group learning, equipping students with essential skills for a globally connected world beyond the subject of architecture. We have paired the design studio activities in London with a field experience of live engagement in southern Italy, in a region suffering from depopulation, while simultaneously experiencing the arrival of asylum seekers. The confluence of these opposing developments creates a need to rebuild local communities and presents an exceptional opportunity for our students to become agents of change. The article outlines how, through the creation of an additional teaching and learning platform for multi-disciplinary research outside the boundaries of the university campus, this teaching practice is raising social capital by attracting and integrating students and asylum seekers alike, adding to population and economic growth. The article concludes by highlighting the unique opportunity to scale up this hybrid studio/field study model, which has arisen because of the COVID-19 pandemic. What is proposed is that now, as universities are developing blended learning delivery models, our observations could feed into a new, expansive model for studying architecture as a student-in-residence mode of study. [ABSTRACT FROM AUTHOR]

The unprecedented lockdowns resulting from COVID-19 in spring 2020 triggered changes in human activities in public spaces. A predictive modeling approach was developed to characterize the changes in the perception of the sound environment when people could not be surveyed. Building on a database of soundscape questionnaires (N = 1,136) and binaural recordings (N = 687) collected in 13 locations across London and Venice during 2019, new recordings (N = 571) were made in the same locations during the 2020 lockdowns. Using these 30-s-long recordings, linear multilevel models were developed to predict the soundscape pleasantness ( R 2 = 0.85) and eventfulness ( R 2 = 0.715) during the lockdown and compare the changes for each location. The performance was above average for comparable models. An online listening study also investigated the change in the sound sources within the spaces. Results indicate (1) human sounds were less dominant and natural sounds more dominant across all locations; (2) contextual information is important for predicting pleasantness but not for eventfulness; (3) perception shifted toward less eventful soundscapes and to more pleasant soundscapes for previously traffic-dominated locations but not for human- and natural-dominated locations. This study demonstrates the usefulness of predictive modeling and the importance of considering contextual information when discussing the impact of sound level reductions on the soundscape. [ABSTRACT FROM AUTHOR]

Social distancing measures implemented by governments worldwide during the COVID-19 pandemic have proven an effective intervention to control the transmission of SARS-CoV-2. There is a growing literature on predictors of adherence behaviours to social distancing measures, however, there are no comprehensive insights into the nature and types of non-adherence behaviours. To address this gap in the literature, we studied non-adherence in terms of counts of infringements and people's accounts on their behaviours in a sample of North London residents. We focused on the following social distancing rules: keeping 2 mts. distancing, meeting family and friends, and going out for non-essential reasons. A mixed-methods explanatory sequential design was used comprising an online survey (May 1–31, 2020) followed by semi-structured in-depth interviews held with a purposive sample of survey respondents (August 5 –September 21, 2020). A negative binomial regression model (quantitative) and Framework Analysis (qualitative) were undertaken.681 individuals completed the survey, and 30 individuals were interviewed. We integrated survey and interview findings following three levels of the Social Ecological model: individual, interpersonal and community levels. We identified non-adherence behaviours as unintentional (barriers beyond individual's control) and intentional (deliberate decision). Unintentional adherence was reported by interviewees as, lack of controllability in keeping 2 mts. distancing, environmental constraints, social responsibility towards the community and feeling low risk. Intentional non-adherence was statistically associated with and reported as lack of trust in Government, support from friends, and lack of knowledge about rules. In addition, interviewees reported individual risk assessment and decision making on the extent to following the rules, and perceived lack of adherence in the local area. Our findings indicate that unintentional and intentional non-adherence should be improved by Government partnerships with local communities to build trust in social distancing measures; tailored messaging to young adults emphasising the need of protecting others whilst clarifying the risk of transmission; and ensuring COVID-secured environments by working with environmental health officers. [ABSTRACT FROM AUTHOR]

England has been heavily affected by the SARS-CoV-2 pandemic, with severe 'lockdown' mitigation measures now gradually being lifted. The real-time pandemic monitoring presented here has contributed to the evidence informing this pandemic management throughout the first wave. Estimates on the 10 May showed lockdown had reduced transmission by 75%, the reproduction number falling from 2.6 to 0.61. This regionally varying impact was largest in London with a reduction of 81% (95% credible interval: 77-84%). Reproduction numbers have since then slowly increased, and on 19 June the probability of the epidemic growing was greater than 5% in two regions, South West and London. By this date, an estimated 8% of the population had been infected, with a higher proportion in London (17%). The infection-to-fatality ratio is 1.1% (0.9-1.4%) overall but 17% (14-22%) among the over-75s. This ongoing work continues to be key to quantifying any widespread resurgence, should accrued immunity and effective contact tracing be insufficient to preclude a second wave. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'. [ABSTRACT FROM AUTHOR]

During the first wave of the global COVID-19 pandemic the clinical utility and indications for SARS-CoV-2 serological testing were not clearly defined. The urgency to deploy serological assays required rapid evaluation of their performance characteristics. We undertook an internal validation of a CE marked lateral flow immunoassay (LFIA) (SureScreen Diagnostics) using serum from SARS-CoV-2 RNA positive individuals and pre-pandemic samples. This was followed by the delivery of a same-day named patient SARS-CoV-2 serology service using LFIA on vetted referrals at central London teaching hospital with clinical interpretation of result provided to the direct care team. Assay performance, source and nature of referrals, feasibility and clinical utility of the service, particularly benefit in clinical decision-making, were recorded. Sensitivity and specificity of LFIA were 96.1% and 99.3% respectively. 113 tests were performed on 108 participants during three-week pilot. 44% participants (n = 48) had detectable antibodies. Three main indications were identified for serological testing; new acute presentations potentially triggered by recent COVID-19 e.g. pulmonary embolism (n = 5), potential missed diagnoses in context of a recent COVID-19 compatible illness (n = 40), and making infection control or immunosuppression management decisions in persistently SARS-CoV-2 RNA PCR positive individuals (n = 6). We demonstrate acceptable performance characteristics, feasibility and clinical utility of using a LFIA that detects anti-spike antibodies to deliver SARS-CoV-2 serology service in adults and children. Greatest benefit was seen where there is reasonable pre-test probability and results can be linked with clinical advice or intervention. Experience from this pilot can help inform practicalities and benefits of rapidly implementing new tests such as LFIAs into clinical service as the pandemic evolves. [ABSTRACT FROM AUTHOR]

Background: The outbreak of SARS-CoV-2 (coronavirus, COVID-19), declared a pandemic by the World Health Organization (WHO), is a global health problem with ever-increasing attributed deaths. Vital sign trends are routinely used to monitor patients with changes in these parameters often preceding an adverse event. Wearable sensors can measure vital signs continuously (e.g. heart rate, respiratory rate, temperature) remotely and can be utilised to recognise early clinical deterioration. Methods: We describe the protocol for a pilot, proof-of-concept, observational study to be conducted in an engineered hotel near London airports, UK. The study is set to continue for the duration of the pandemic. Individuals arriving to London with mild symptoms suggestive of COVID-19 or returning from high-risk areas requiring quarantine, as recommended by the Public Health England, or healthcare professionals with symptoms suggestive of COVID-19 unable to isolate at home will be eligible for a wearable patch to be applied for the duration of their stay. Notifications will be generated should deterioration be detected through the sensor and displayed on a central monitoring hub viewed by nursing staff, allowing for trend deterioration to be noted. The primary objective is to determine the feasibility of remote monitoring systems in detecting clinical deterioration for quarantined individuals in a hotel. Discussion: This trial should prove the feasibility of a rapidly implemented model of healthcare delivery through remote monitoring during a global pandemic at a hotel, acting as an extension to a healthcare trust. Potential benefits would include reducing infection risk of COVID-19 to healthcare staff, with earlier recognition of clinical deterioration through ambulatory, continuous, remote monitoring using a discrete wearable sensor. We hope our results can power future, robust randomised trials. Trial registration: ClinicalTrials.gov Identifier: NCT04337489. [ABSTRACT FROM AUTHOR]

Background: The coronavirus disease 19 (COVID-19) pandemic has presented modern healthcare with an unprecedented challenge. At the peak of the pandemic, trauma and orthopaedic services at our institutions undertook internal restructuring, diverting resources to frontline medical care. Consequently, we sought to assess the impact on the elderly and comorbid patients presenting with femoral neck fractures, with a particular focus on 30-day mortality, length of stay, multidisciplinary team involvement and departmental structuring. Method: A retrospective analysis of patients presenting with femoral neck fractures at three separate West London NHS Trusts was undertaken between March 11, 2020, to April 30, 2020. Length of stay, 30-day mortality and adherence to parameters constituting the best care evidence-based practice tariffs were compared between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive and negative patients. A similar comparison was also conducted between our cohort and the equivalent period in 2018 using data from the National Hip Fracture Database. Results: A total of 68 patients presenting with femoral neck fractures were identified, mean age 81 (range 38–98), 73% female. There were 10 confirmed/suspected cases of COVID-19 on admission and a further seven confirmed as inpatients. The 30-day mortality within our cohort was 11.76% compared to 6% nationally in 2018 (p = 0.045). Orthogeriatric reviews occurred within 72 h in 71% of cases compared to 88% in the equivalent 2018 period. Within the cohort, mean length of stay was 17.13 days (SD 5.6, range 8-27 days) for SARS-CoV-2 positive patients compared to 10 days (SD 8.7, range 1–53 days) for negative patients (p < 0.05). Thirty-two patients (47%) required increased packages of care on discharge or rehabilitation. Conclusions: The increase in 30-day mortality for SARS-CoV-2 positive patients presenting with femoral neck fractures is multifactorial, resulting from a combination of the direct effects of COVID-19 pneumonia as well as changes to the delivery of orthopaedic services. The provision of multidisciplinary care was directly affected by staff redeployment, particularly reorganisation of orthogeriatric services and lack of continuity of ward based clinical care. Our experiences have re-directed efforts towards the management of theatre teams, patient services and staffing, should we be faced with either a resurgence of COVID-19 or a future pandemic. [ABSTRACT FROM AUTHOR]

We report changes in surface nitrogen dioxide (NO2) across the UK during the COVID-19 pandemic when large and rapid emission reductions accompanied a nationwide lockdown (23 March–31 May 2020, inclusively), and compare them with values from an equivalent period over the previous 5 years. Data are from the Automatic Urban and Rural Network (AURN), which forms the basis of checking nationwide compliance with ambient air quality directives. We calculate that NO2 reduced by 42%±9.8% on average across all 126 urban AURN sites, with a slightly larger (48%±9.5%) reduction at sites close to the roadside (urban traffic). We also find that ozone (O3) increased by 11 % on average across the urban background network during the lockdown period. Total oxidant levels (Ox=NO2+O3) increased only slightly on average (3.2%±0.2%), suggesting the majority of this change can be attributed to photochemical repartitioning due to the reduction in NOx. Generally, we find larger, positive Ox changes in southern UK cities, which we attribute to increased UV radiation and temperature in 2020 compared to previous years. The net effect of the NO2 and O3 changes is a sharp decrease in exceedances of the NO2 air quality objective limit for the UK, with only one exceedance in London in 2020 up until the end of May. Concurrent increases in O3 exceedances in London emphasize the potential for O3 to become an air pollutant of concern as NOx emissions are reduced in the next 10–20 years. [ABSTRACT FROM AUTHOR]

Historical records reveal the temporal patterns of a sequence of plague epidemics in London, United Kingdom, from the 14th to 17th centuries. Analysis of these records shows that later epidemics spread significantly faster ("accelerated"). Between the Black Death of 1348 and the later epidemics that culminated with the Great Plague of 1665, we estimate that the epidemic growth rate increased fourfold. Currently available data do not provide enough information to infer the mode of plague transmission in any given epidemic; nevertheless, order-of-magnitude estimates of epidemic parameters suggest that the observed slow growth rates in the 14th century are inconsistent with direct (pneumonic) transmission. We discuss the potential roles of demographic and ecological factors, such as climate change or human or rat population density, in driving the observed acceleration. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic is imposing a profound negative impact on the health and wellbeing of societies and individuals, worldwide. One concern is the effect of social isolation as a result of social distancing on the mental health of vulnerable populations, including older people. Within six weeks of lockdown, we initiated the CHARIOT COVID-19 Rapid Response Study, a bespoke survey of cognitively healthy older people living in London, to investigate the impact of COVID-19 and associated social isolation on mental and physical wellbeing. The sample was drawn from CHARIOT, a register of people over 50 who have consented to be contacted for aging related research. A total of 7,127 men and women (mean age=70.7 [SD=7.4]) participated in the baseline survey, May–July 2020. Participants were asked about changes to the 14 components of the Hospital Anxiety Depression scale (HADS) after lockdown was introduced in the UK, on 23rd March. A total of 12.8% of participants reported feeling worse on the depression components of HADS (7.8% men and 17.3% women) and 12.3% reported feeling worse on the anxiety components (7.8% men and 16.5% women). Fewer participants reported feeling improved (1.5% for depression and 4.9% for anxiety). Women, younger participants, those single/widowed/divorced, reporting poor sleep, feelings of loneliness and who reported living alone were more likely to indicate feeling worse on both the depression and/or anxiety components of the HADS. There was a significant negative association between subjective loneliness and worsened components of both depression (OR 17.24, 95% CI 13.20, 22.50) and anxiety (OR 10.85, 95% CI 8.39, 14.03). Results may inform targeted interventions and help guide policy recommendations in reducing the effects of social isolation related to the pandemic, and beyond, on the mental health of older people. [ABSTRACT FROM AUTHOR]

Quantitative efforts to understand the emergence of the COVID-19 pandemic need to be viewed through the lens of social construction. I begin by comparing the efforts to quantitatively measure the plague in London in 1665. Then I develop five propositions for studying the social construction of statistics: (1) facts are social constructions; (2) measuring involves making decisions, (3) counting is not straightforward; (4) all comparisons involve choices; and (5) social patterns shape numbers. After examining how these propositions affect what we know about COVID-19, I consider their implications for moving beyond mathematics when approaching numeracy. [ABSTRACT FROM AUTHOR]

COVID-19 containment policies are not only curbing the spread of COVID-19 but also changing human behavior. According to the routine activity theory, owing to lockdown, the closure of entertainment sites (e.g., pubs and bars), an increase in stay-at-home time, and an increase in police patrols are likely to influence chance of committing a crime. In this study, we aimed to further examine the spatial association of COVID-19 infection rate and crime rate. Particularly, we empirically validated the speculation that increase in COVID-19 cases is likely to reduce crime rate. In the empirical study, we investigated whether and how COVID-19 infection rate is spatially associated with crime rate in London. As the spatial data used are mainly areal data, we adopted a spatial regression mode (i.e., the "random effects eigenvector spatial filtering model") to investigate the spatial associations after controlling for the socioeconomic factors. More specifically, we investigated the associations for all the four crime categories in three consequent months (March, April, and May of 2020). The empirical results indicate that 1) crime rates of the four categories have no statistically significant associations with COVID-19 infection rate in March; 2) violence-against-the-person rate has no statistically significant association with COVID-19 infection rate; and 3) robbery rate, burglary rate, and theft and handling rate have a statistically significant and negative association with COVID-19 infection rate in both April and May. [ABSTRACT FROM AUTHOR]

The virus is the only news; it is the primary topic of conversation, which is mostly fearful speculation in the absence of any real data, or any visible concern on the part of the government. This must include clinicians, epidemiologists, immunologists, virologists, experts on vaccines and clinical pharmacologists from our eminent teaching institutes. ANNA RUDDOCK Letter from Mumbai THE IMPENDING CORONA VIRUS EPIDEMIC The first patients harbouring the corona virus (since named Corona Virus 2019 or Covid-19) were identified in Wuhan, China in December 2019. [Extracted from the article]