In the UK eating out and drinking sector in April 2020, a total of 81 percent of business leaders had already started recovery planning for various scenarios. Others were waiting for more information, or said they do not have the capactiy to plan for recovery yet. Only one percent of respondents did not have any recovery plans at the time.

As of May 2, 2023, there were roughly 687 million global cases of COVID-19. Around 660 million people had recovered from the disease, while there had been almost 6.87 million deaths. The United States, India, and Brazil have been among the countries hardest hit by the pandemic.

The various types of human coronavirus The SARS-CoV-2 virus is the seventh known coronavirus to infect humans. Its emergence makes it the third in recent years to cause widespread infectious disease following the viruses responsible for SARS and MERS. A continual problem is that viruses naturally mutate as they attempt to survive. Notable new variants of SARS-CoV-2 were first identified in the UK, South Africa, and Brazil. Variants are of particular interest because they are associated with increased transmission.

Vaccination campaigns Common human coronaviruses typically cause mild symptoms such as a cough or a cold, but the novel coronavirus SARS-CoV-2 has led to more severe respiratory illnesses and deaths worldwide. Several COVID-19 vaccines have now been approved and are being used around the world.

These documents were produced through a collaboration between GLA, PHE London and Association of Directors of Public Health London. The wider impacts slide set pulls together a series of rapid evidence reviews and consultation conversations with key London stakeholders. The evidence reviews and stakeholder consultations were undertaken to explore the wider impacts of the pandemic on Londoners and the considerations for recovery within the context of improving population health outcomes. The information presented in the wider impact slides represents the emerging evidence available at the time of conducting the work (May-August 2020). The resource is not routinely updated and therefore further evidence reviews to identify more recent research and evidence should be considered alongside this resource. It is useful to look at this in conjunction with the ‘People and places in London most vulnerable to COVID-19 and its social and economic consequences’ report commissioned as part of this work programme and produced by the New Policy Institute. Additional work was also undertaken on the housing issues and priorities during COVID. A short report and examples of good practice are provided here. These reports are intended as a resource to support stakeholders in planning during the transition and recovery phase. However, they are also relevant to policy and decision-making as part of the ongoing response. The GLA have also commissioned the University of Manchester to undertake a rapid evidence review on inequalities in relation to COVID-19 and their effects on London.

Calderdale COVID Impact Assessment has been produced as evidence for the development and delivery for the Calderdale Inclusive Economic Recovery Plan and sets out a focus on economic recovery, but also considers the wider impacts of COVID-19 on Calderdale and its communities. Also see Inclusive Recovery and COVID Impact Assessment for more information and a range of related reports and datasets.

Business leaders within the eating and drinking out sector in the United Kingdom expected their biggest challenges for business recovery post-lockdown due to the coronavirus (COVID-19) pandemic to be operational changes and Government regulations. Challenges related to staff and supply were not considered as major.

In past 24 hours, UK, Europe had N/A new cases, N/A deaths and N/A recoveries.

The Community Engagement team at the Greater London Authority (GLA) commissioned this report to identify and examine past and present projects which involve collecting Londoners experiences of COVID-19 through a variety of creative and non-traditional materials. The purpose of the report is to: provide an overview of projects and activities which record Londoners COVID-19 stories and experiences. outline who is responsible for these projects and activities (individuals, museums, community groups, charities, community interest groups, non-profits, other institutions and organisations). analyse the voices of individuals/groups/communities targeted in the projects and activities. highlight obvious gaps in the collected data which can inform future programmes geographically map out projects and other activities which record COVID-19 stories and experiences across Greater London. The data provides insight into trends and patterns in COVID-19 collecting projects and activities that have been carried out in London from March 2020 to March 2021. Reflections and final suggestions on how to navigate these projects and activities for specific next steps in the Community-Led Recovery Programme, targeted missions, suggestions etc. will be discussed later in this report. In particular, this report provides information relevant to the London Community Story (LCS) Programme, one of the two strands of the Community-Led Recovery programme. Alongside this report is a dataset outlining 160 COVID-19 collecting projects that took place in London. The dataset gives project names, boroughs, material types, collecting organisation type and organisation names. We encourage you to use this dataset as a starting point and then do your own additional research on the 160 projects. If you are aware of a project that has not been included, please let us know and we can add it.

A joint map of resources targeted towards the remedy and recovery during and after the COVID 19 crisis. Information about resources and support services provided by a number of organisations across the city.If you are a provider of services and resources, your information can be added and made public via the form available from here.If you have any questions about this dataset please email smart@leicester.gov.uk or complete the form available from here.

This study aims to address the gap in literature by tracking the mental health of university students over a two-year period, spanning the Covid-19 pandemic and its aftermath. Further, it seeks to explore patterns of change, identify factors influencing mental health outcomes, and assess whether there are improvements in the well-being of university students as the post-pandemic period unfolds. A two-year longitudinal study surveyed a sample of university students (n=300) three times between May 2020 and June 2022. Students psychological distress, generalised anxiety, flourishing and personal wellbeing were assessed at each time point.

Context

Within the current response of a pandemic caused by the SARS-CoV-2 coronavirus, which in turn causes the disease, called COVID-19. It is necessary to join forces to minimize the effects of this disease.

Therefore, the intention of this dataset is to save data scientists time:

• Gather the data at the country level, encoding the country with its ISO code to allow easy access to other data
• Perform pre-processing of data, calculations of increments and other indicators that can facilitate modeling.
• Add the response of the governments over time so that it can be taken into account in the modeling.
• Daily update.

This dataset is not intended to be static, so suggestions for expanding it are welcome. If someone considers it important to add information, please let me know.

Content

The data contained in this dataset comes mainly from the following sources:

Source: Center for Systems Science and Engineering (CSSE) at Johns Hopkins University https://github.com/CSSEGISandData/COVID-19 Provided by Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE): https://systems.jhu.edu/

Source: OXFORD COVID-19 GOVERNMENT RESPONSE TRACKER https://www.bsg.ox.ac.uk/research/research-projects/oxford-covid-19-government-response-tracker Hale, Thomas and Samuel Webster (2020). Oxford COVID-19 Government Response Tracker. Data use policy: Creative Commons Attribution CC BY standard.

The original data is updated daily.

The features it includes are:

• Country Name

• Country Code ISO 3166 Alpha 3

• Date

• Incidence data:

  • confirmed
  • deaths
  • recoveries

• Daily increments:

  • confirmed_inc
  • deaths_inc
  • recoveries_inc

• Empirical Contagion Rate - ECR

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F3508582%2F3e90ecbcdf76dfbbee54a21800f5e0d6%2FECR.jpg?generation=1586861653126435&alt=media" alt="">

• GOVERNMENT RESPONSE TRACKER - GRTStringencyIndex

  OXFORD COVID-19 GOVERNMENT RESPONSE TRACKER - Stringency Index

• Indices from Start Contagion

  • Days since the first case of contagion is overcome
  • Days since 100 cases are exceeded

• Percentages over the country's population:

  • confirmed_PopPct
  • deaths_PopPct
  • recoveries_PopPct

The method of obtaining the data and its transformations can be seen in the notebook:

Notebook COVID-19 Data by country with Government Response

Photo by Markus Spiske on Unsplash

The biology driving individual patient responses to SARS-CoV-2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data and covering a year post-disease onset, from 215 SARS-CoV-2 infected subjects with differing disease severities. Our analyses revealed distinct “systemic recovery” profiles, with specific progression and resolution of the inflammatory, immune cell, metabolic and clinical responses. In particular, we found a strong inter- and intra-patient temporal covariation of innate immune cell numbers, kynurenine metabolites and lipid metabolites, which highlighted candidate immunologic and metabolic pathways influencing the restoration of homeostasis, the risk of death and that of long COVID. Based on these data, we identified a composite signature predictive of systemic recovery at the patient level, using a joint model on cellular and molecular parameters measured soon after disease onset. New predictions can be generated using the online tool http://shiny.mrc-bsu.cam.ac.uk/apps/covid-19-systemic-recovery-prediction-app, designed to test our findings prospectively.

Frailty is a syndrome of increased vulnerability to incomplete resolution of homeostasis (healing or return to baseline function) following a stressor event (such as an infection or fall) and it is associated with poor outcomes including increased mortality and reduced quality of life. The pathophysiology of frailty is poorly understood. Age and frailty have been proven to be independently predictive of outcomes in patients admitted with an acute illness. In COVID-19, routine frailty identification informed decision making about treatment.

This dataset from 01-03-2020 to 01-04-2022 of 327,346 patients admitted during all waves of the COVID pandemic both with and without COVID-19. The dataset includes granular demographics, frailty scores, physiology and vital signs, all care contacts and investigations (including imaging), all medications including dose and routes, care outcomes, length of stay and outcomes including readmission and mortality.

Geography: The West Midlands (WM) has a population of 6 million & includes a diverse ethnic & socio-economic mix. UHB is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & > 120 ITU bed capacity. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. 

Data set availability:  Data access is available via the PIONEER Hub for projects which will benefit the public or patients.  This can be by developing a new understanding of disease, by providing insights into how to improve care, or by developing new models, tools, treatments, or care processes.  Data access can be provided to NHS, academic, commercial, policy and third sector organisations.  Applications from SMEs are welcome.  There is a single data access process, with public oversight provided by our public review committee, the Data Trust Committee.  Contact pioneer@uhb.nhs.uk or visit www.pioneerdatahub.co.uk for more details. 

Available supplementary data: Matched controls; ambulance and community data. Unstructured data (images).  We can provide the dataset in OMOP and other common data models and can build synthetic data to meet bespoke requirements. 

Available supplementary support: Analytics, model build, validation & refinement; A.I. support.  Data partner support for ETL (extract, transform & load) processes.  Bespoke and “off the shelf” Trusted Research Environment (TRE) build and run.  Consultancy with clinical, patient & end-user and purchaser access/ support.  Support for regulatory requirements.  Cohort discovery. Data-driven trials and “fast screen” services to assess population size.

The increase in the extent of working-from-home determined by the COVID-19 health crisis has led to a substantial shift of economic activity across geographical areas; which we refer to as a Zoomshock. When a person works from home rather than at the office, their work-related consumption of goods and services provided by the locally consumed service industries will take place where they live, not where they work. Much of the clientèle of restaurants, coffee bars, pubs, hair stylists, health clubs, taxi providers and the like located near workplaces is transferred to establishment located near where people live. These data are our calculations of the Zoomshock at the MSOA level. They reflect estimats of the change in the number of people working in UK neighbourhoods due to home-working.

The COVID-19 shutdown is not affecting all parts of the UK equally. Economic activity in local consumer service industries (LCSI), such as retail outlets, restaurants, hairdressers, or gardeners has all but stopped; other industries are less affected. These differences among industries and their varying importance across local economies means recovery will be sensitive to local economic conditions and will not be geographically uniform: some neighbourhoods face a higher recovery risk of not being able to return to pre-shutdown levels of economic activity. This recovery risk is the product of two variables. The first is the shock, the effect of the shutdown on local household incomes. The second is the multiplier, the effect on LCSI economic activity following a negative shock to household incomes. In neighbourhoods where many households rely on the LCSI sector as a primary source of income the multiplier may be particularly large, and these neighbourhoods are vulnerable to a vicious circle of reduced spending and reduced incomes. This project will produce data measuring the shock, the multiplier, and the COVID-19 shutdown recovery risk for UK neighbourhoods. These variables will be estimated using individual and firm level information from national surveys and administrative data. The dataset, and corresponding policy report, will be made public and proactively disseminated to guide local and national policy design. Recovery inequality is likely to be substantial: absent intervention, existing regional inequalities may be exacerbated. This research will provide a timely and necessary input into designing appropriate recovery policy.

BackgroundThere is an urgent need to better understand the factors that predict mental wellbeing in vocationally active adults during globally turbulent times.AimTo explore the relationship between psychological detachment from work (postulated as a key recovery activity from work) in the first national COVID-19 lockdown with health, wellbeing, and life satisfaction of working age-adults one year later, within the context of a global pandemic.MethodsWellbeing of the Workforce (WoW) was a prospective longitudinal cohort study, with two waves of data collection (Time 1, April-June 2020: T1 n = 337; Time 2, March-April 2021: T2 = 169) corresponding with the first and third national COVID-19 lockdowns in the UK. Participants were >18 years, who were employed or self-employed and working in the UK. Descriptive and parametric (t-tests and linear regression) and nonparametric (chi square tests) inferential statistics were employed.ResultsRisk for major depression (T1: 20.0% to T2: 29.0%, p = .002), poor general health (T1: 4.7% to T2: 0%, p = .002) and poor life satisfaction (T1: 15.4% to T2: 25.4%, p = .002) worsened over time, moderate-to-severe anxiety remained stable (T1: 26.1% to T2: 30.2%, p = .15). Low psychological detachment from work was more prevalent in the first wave (T1: 21.4% and T2: 16.0%), with a moderate improvement observed from T1 to T2 (t (129) = -7.09, p < .001). No differences were observed with work status (employed/self-employed), except for self-employed workers being more likely to report poor general health at T1 (16.1%, p = .002). Better psychological wellbeing, lower anxiety and higher life satisfaction at T2 were observed in those who reported better psychological detachment from work at T1 (β = .21, p = .01; β = -.43, p < .001; β = .32, p = .003, respectively), and in those who improved in this recovery activity from T1 to T2 (β = .36, p < .001; β = -.27, p < .001; β = .27, p = .008, respectively), controlling for age, gender and ethnicity.ConclusionThe ability to psychologically detach from work during the first pandemic lockdown, and improvement in this recovery activity over time, predicted better mental wellbeing and quality of life in vocationally active adults after one year of a global crisis, irrespective of work status. Interventions to encourage workers to psychologically detach from work may help to support employee wellbeing at all times, not only in the extreme circumstances of pandemics and economic uncertainty.

The Healthy Ageing in Scotland (HAGIS): COVID-19 Impact and Recovery Study, 2021-2022 is a multidisciplinary large-scale study of older adults (aged 50 and over) living in Scotland. The study was established to explore the spectrum of COVID-19 concerns in older adults and its impact on their willingness to (re)engage across health, social, and economic domains as Scotland's economy and society emerged from the pandemic. The survey data were collected between October 2021 and January 2022 using electronic, postal self-completion interviews and telephone-assisted personal interviews. From a target sample of 15,674 older adults, drawn from two existing Scottish longitudinal studies and a predefined panel, 3,373 individuals (59 percent women and 41 percent men) completed the survey.

The data provide a wealth of information on older adults' socio-demographics, COVID-19-induced fear, worries and concerns, health domains, social capital and participation, economic and consumption behaviours, return to workplace experiences and preferences.

Further information is available HAGIS COVID-19 Impact and Recovery Study webpage.

he aim of RESISTIRÉ (https://resistire-project.eu/) is to understand the unequal impacts that the COVID-19 pandemic and its policy responses had on behavioural, social, and economic inequalities in 31 countries (the EU 27 along with Iceland, Serbia, Turkey, and the UK) and to work towards individual and societal resilience. RESISTIRÉ does so by collecting and analysing policy data, quantitative data, and qualitative data, and by translating these into insights to be used for designing, devising, and piloting solutions for improved policies and social innovations that can be deployed by policymakers, stakeholders and actors in relevant policy domains. The project relies on a ten-partner multidisciplinary and multisectoral European consortium and a well-established network of researchers in the 31 countries. The data were generated by 30 national researchers (NRs), representing EU27 countries (minus Malta), along with Iceland, the UK, Serbia, and Turkey. Most of them are researchers and experts in gender studies and inequality studies. The NRs were asked to analyse policies designed to stimulate and support the socioeconomic process of recovering from the pandemic in their respective countries.

Mass Spectrometry identifies temporal changes and hallmarks of Delayed Recovery in the COVID19 Neutrophil proteomes MTD project_description High-resolution mass spectrometry and the parallel quantitative evaluation of thousands of proteins has been used to characterise the proteomes of peripheral blood neutrophils from >200 individuals. This work has comprehensively mapped neutrophil molecular changes associated with mild versus severe COVID19 and identified significant quantitative changes in more than 1700 proteins in neutrophils from patients hospitalised with COVID19 versus patients with non-COVID19 acute respiratory infections. The study identifies neutrophil protein signatures associated with COVID19 disease severity. The data also show that alterations in neutrophil proteomes can persist in fully recovered patients and identify distinct neutrophil proteomes in recovered versus non recovered patients. Our study provides novel insights into neutrophil responses during acute COVID-19 and reveal that altered neutrophil phenotypes persist in convalescent COVID19 infections.

BackgroundThe COVID-19 pandemic has resulted in significant morbidity and mortality worldwide, with cytokine storm leading to exaggerating immune response, multi-organ dysfunction and death. Melatonin has been shown to have anti-inflammatory and immunomodulatory effects and its effect on COVID-19 clinical outcomes is controversial. This study aimed to conduct a meta-analysis to evaluate the impact of melatonin on COVID-19 patients.MethodsPubMed, Embase, and Cochrane Central Register of Controlled Trials were searched without any language or publication year limitations from inception to 15 Nov 2022. Randomized controlled trials (RCTs) using melatonin as therapy in COVID-19 patients were included. The primary outcome was mortality, and the secondary outcomes included were the recovery rate of clinical symptoms, changes in the inflammatory markers like C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and neutrophil to lymphocyte ratio (NLR). A random-effects model was applied for meta-analyses, and further subgroup and sensitivity analyses were also conducted.ResultsA total of nine RCTs with 718 subjects were included. Five studies using melatonin with the primary outcome were analyzed, and the pooled results showed no significant difference in mortality between melatonin and control groups with high heterogeneity across studies identified (risk ratio [RR] 0.72, 95% confidence interval [CI] 0.47–1.11, p = 0.14, I2 = 82%). However, subgroup analyses revealed statistically significant effects in patients aged under 55 years (RR 0.71, 95% CI 0.62–0.82, p < 0.01) and in patients treated for more than 10 days (RR 0.07, 95% CI 0.01–0.53, p = 0.01). The recovery rate of clinical symptoms and changes in CRP, ESR, and NLR were not statistically significant. No serious adverse effects were reported from melatonin use.ConclusionIn conclusion, based on low certainty of evidence, the study concluded that melatonin therapy does not significantly reduce mortality in COVID-19 patients, but there are possible benefits in patients under 55 years or treated for more than 10 days. With a very low certainty of evidence, we found no significant difference in the recovery rate of COVID-19 related symptoms or inflammatory markers in current studies. Further studies with larger sample sizes are warranted to determine the possible efficacy of melatonin on COVID-19 patients.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42022351424.

The Scottish economy, such as the United Kingdom (UK) economy, has been exposed to several adverse shocks over the past 5 years. Examples of these are the effect of the United Kingdom exiting the European Union (Brexit), the effects of the COVID-19 pandemic, and more recently Russia–Ukraine war, which can result in adverse direct and indirect economic losses across various sectors of the economy. These shocks disrupted the food and drink supply chains. The purpose of this article is 3-fold: (1) to explore the degree of resilience of the Scottish food and drink sector, (2) to estimate the effects on interconnected sectors of the economy, and (3) to estimate the economic losses, which is the financial value associated with the reduction in output. This article focuses on the impact that the sudden contraction that the “accommodation and food service activities”, resulting from the pandemic, had on the food and drink sectors. For this analysis, the study relied on the dynamic inoperability input–output model (DIIM), which takes into account the relationships across the different sectors of the Scottish economy over time. The results indicate that the accommodation and food service sector was the most affected by the COVID-19 pandemic lockdown contracting by approximately 60%. The DIIM shows that the disruption to this sector had a cascading effect on the remaining 17 sectors of the economy. The processed and preserved fish, fruits, and vegetable sector is the least resilient, while preserved meat and meat product sector is the most resilient to the final demand disruption in the accommodation and food service sector. The least economically affected sector was the other food product sector, while the other service sector had the highest economic loss. Although the soft drink sector had a slow recovery rate, economic losses were lower compared to the agricultural, fishery, and forestry sectors. From the policy perspective, stakeholders in the accommodation and food service sector should re-examine the sector and develop capacity against future pandemics. In addition, it is important for economic sectors to collaborate either vertically or horizontally by sharing information and risk to reduce the burden of future disruptions. Finally, the most vulnerable sectors of the economy, i.e., other service sectors should form a major part of government policy decision-making when planning against future pandemics.