These datasets comprise the main analyses for the paper “Household Transmission of Seasonal Coronavirus Infections: Results from the Flu Watch cohort study”, published in Wellcome Open Research. Details of the statistical methods are reported in the article. Datasets are given in CSV format and, where relevant, in .dta format. Descriptions for each dataset are as follows:

Household_CoV_acquired.csv/dta – data required to compute the proportion of cases presumably acquired outside of the household versus and the proportion acquired from household transmission. Each row represents an anonymised PCR-confirmed seasonal coronavirus case.

Household_CoV_TransmissionRisk.csv/dta – data required to compute the risk of symptomatic onward household transmission following a seasonal coronavirus index case, and perform stratified descriptive analyses.

Household_CoV_SAR.csv/.dta – data required to compute the seasonal coronavirus secondary attack risk overall and by strain. Each row represents an anonymised exposed-index pair from a given outbreak.

HH Transmission Serial Interval.csv – presents available, anonymised data required to compute the median clinical-onset serial interval overall and by strain for each household outbreak

The main entity of this document is a taxonomy with accession number 233261

As the new coronavirus strain Sars-Cov-2 (Covid-19) is spreading across the world at an alarming pace, the consumer market is seeing disruptions as manufacturing and production sectors slow down, particularly in countries where the disease hit the hardest. According to a study conducted with UK retailers in the food, fashion, and health and beauty categories, retailers are positive that the Covid-19 will have a negative impact on their sales. While ** percent thought the impact would be significant, a great share of respondents thought the outbreak would have a slightly negative impact on their sales, if the virus persists.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Fact and Figures page.

In this study, we evaluated the impact of viral variant, in addition to other variables, on within-host viral burden, by analysing cycle threshold (Ct) values derived from nose and throat swabs, collected as part of the UK COVID-19 Infection Survey. Because viral burden distributions determined from community survey data can be biased due to the impact of variant epidemiology on the time-since-infection of samples, we developed a method to explicitly adjust observed Ct value distributions to account for the expected bias. By analysing the adjusted Ct values using partial least squares regression, we found that among unvaccinated individuals with no known prior exposure, viral burden was 44% lower among Alpha variant infections, compared to those with the predecessor strain, B.1.177. Vaccination reduced viral burden by 67%, and among vaccinated individuals, viral burden was 286% higher among Delta variant, compared to Alpha variant, infections. In addition, viral burden increased by 17% for every 10-year age increment of the infected individual. In summary, within-host viral burden increases with age, is reduced by vaccination, and is influenced by the interplay of vaccination status and viral variant.

This open data publication has moved to COVID-19 Statistical Data in Scotland (from 02/11/2022) Novel coronavirus (COVID-19) is a new strain of coronavirus first identified in Wuhan, China. Clinical presentation may range from mild-to-moderate illness to pneumonia or severe acute respiratory infection. This dataset provides information on demographic characteristics (age, sex, deprivation) of confirmed novel coronavirus (COVID-19) cases, as well as trend data regarding the wider impact of the virus on the healthcare system. Data includes information on primary care out of hours consultations, respiratory calls made to NHS24, contact with COVID-19 Hubs and Assessment Centres, incidents received by Scottish Ambulance Services (SAS), as well as COVID-19 related hospital admissions and admissions to ICU (Intensive Care Unit). Further data on the wider impact of the COVID-19 response, focusing on hospital admissions, unscheduled care and volume of calls to NHS24, is available on the COVID-19 Wider Impact Dashboard. There is a large amount of data being regularly published regarding COVID-19 (for example, Coronavirus in Scotland - Scottish Government and Deaths involving coronavirus in Scotland - National Records of Scotland. Additional data sources relating to this topic area are provided in the Links section of the Metadata below. Information on COVID-19, including stay at home advice for people who are self-isolating and their households, can be found on NHS Inform. All publications and supporting material to this topic area can be found in the weekly COVID-19 Statistical Report. The date of the next release can be found on our list of forthcoming publications. Data visualisation is available to view in the interactive dashboard accompanying the COVID-19 Statistical Report. Please note information on COVID-19 in children and young people of educational age, education staff and educational settings is presented in a new COVID-19 Education Surveillance dataset going forward.

The main entity of this document is a proteome with accession number UP000125413

The new strain of coronavirus, Covid-19, has led many countries to take drastic social distancing measures, and has driven consumers to supermarkets to stock up on foodstuffs, hygiene, and over-the-counter medical products such as vitamins and pain relievers. However, according to a poll conducted by Ipsos, an overwhelming majority of British consumers (61 percent) think it is not acceptable to stockpile during the Coronavirus outbreak.

As Covid-19 continues to impact governments and communities worldwide, new data emerging on the virus are helping individuals to stay on top of the situation and protect themselves and those around them. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

This publication was archived on 12 October 2023. Please see the Viral Respiratory Diseases (Including Influenza and COVID-19) in Scotland publication for the latest data. This dataset provides information on number of new daily confirmed cases, negative cases, deaths, testing by NHS Labs (Pillar 1) and UK Government (Pillar 2), new hospital admissions, new ICU admissions, hospital and ICU bed occupancy from novel coronavirus (COVID-19) in Scotland, including cumulative totals and population rates at Scotland, NHS Board and Council Area levels (where possible). Seven day positive cases and population rates are also presented by Neighbourhood Area (Intermediate Zone 2011). Information on how PHS publish small are COVID figures is available on the PHS website. Information on demographic characteristics (age, sex, deprivation) of confirmed novel coronavirus (COVID-19) cases, as well as trend data regarding the wider impact of the virus on the healthcare system is provided in this publication. Data includes information on primary care out of hours consultations, respiratory calls made to NHS24, contact with COVID-19 Hubs and Assessment Centres, incidents received by Scottish Ambulance Services (SAS), as well as COVID-19 related hospital admissions and admissions to ICU (Intensive Care Unit). Further data on the wider impact of the COVID-19 response, focusing on hospital admissions, unscheduled care and volume of calls to NHS24, is available on the COVID-19 Wider Impact Dashboard. Novel coronavirus (COVID-19) is a new strain of coronavirus first identified in Wuhan, China. Clinical presentation may range from mild-to-moderate illness to pneumonia or severe acute respiratory infection. COVID-19 was declared a pandemic by the World Health Organisation on 12 March 2020. We now have spread of COVID-19 within communities in the UK. Public Health Scotland no longer reports the number of COVID-19 deaths within 28 days of a first positive test from 2nd June 2022. Please refer to NRS death certificate data as the single source for COVID-19 deaths data in Scotland. In the process of updating the hospital admissions reporting to include reinfections, we have had to review existing methodology. In order to provide the best possible linkage of COVID-19 cases to hospital admissions, each admission record is required to have a discharge date, to allow us to better match the most appropriate COVID positive episode details to an admission. This means that in cases where the discharge date is missing (either due to the patient still being treated, delays in discharge information being submitted or data quality issues), it has to be estimated. Estimating a discharge date for historic records means that the average stay for those with missing dates is reduced, and fewer stays overlap with records of positive tests. The result of these changes has meant that approximately 1,200 historic COVID admissions have been removed due to improvements in methodology to handle missing discharge dates, while approximately 820 have been added to the cumulative total with the inclusion of reinfections. COVID-19 hospital admissions are now identified as the following: A patient's first positive PCR or LFD test of the episode of infection (including reinfections at 90 days or more) for COVID-19 up to 14 days prior to admission to hospital, on the day of their admission or during their stay in hospital. If a patient's first positive PCR or LFD test of the episode of infection is after their date of discharge from hospital, they are not included in the analysis. Information on COVID-19, including stay at home advice for people who are self-isolating and their households, can be found on NHS Inform. Data visualisation of Scottish COVID-19 cases is available on the Public Health Scotland - Covid 19 Scotland dashboard. Further information on coronavirus in Scotland is available on the Scottish Government - Coronavirus in Scotland page, where further breakdown of past coronavirus data has also been published.

Key demographics, ventilation parameters, treatment and disease severity scores, by UK pandemic wave.

The data collection consists of 40 qualitative interviews with Polish migrant essential workers living in the UK and 10 in-depth expert interviews with key stakeholders providing information and support to migrant workers in the UK. All migrant interviews are in Polish. Six of the expert interviews with key stakeholders are in English and four are in Polish. Fieldwork was conducted fully online during the Covid-19 pandemic between March and August 2021, following the third UK-wide Covid-19 lockdown. Restrictions were still in place in some localities. Interviews took place shortly after the end of the transition period concluding the UK’s European Union exit on 1 January 2021. All Polish migrant worker interviewees entered the UK before 1 January 2021 and had the option to apply to the EU Settlement Scheme. The objectives of the qualitative fieldwork were to: 1. To synthesise empirical and theoretical knowledge on the short- and long-term impacts of COVID-19 on migrant essential workers. 2. To establish how the pandemic affected Polish migrant essential worker's lives; and expert interviews with stakeholders in the public and third/voluntary sector to investigate how to best support and retain migrant essential workers in COVID-19 recovery strategies. The project also involved: - co-producing policy outputs with partner organisations in England and Scotland; and - an online survey to measure how Polish migrant essential workers across different roles and sectors were impacted by COVID-19 in regard to health, social, economic and cultural aspects, and intentions to stay in the UK/return to Poland (deposited separately to University of Sheffield). Key findings included significant new knowledge about the health, social, economic and cultural impacts of Covid-19 on migrant essential workers. Polish essential workers were severely impacted by the pandemic with major mental health impacts. Mental health support was insufficient throughout the UK. Those seeking support typically turned to private (online) services from Poland as they felt they could not access them in the UK because of language or cultural barriers, lack of understanding of the healthcare system and pathways to mental health support, support being offered during working hours only, or fear of the negative impact of using mental health services on work opportunities. Some participants were in extreme financial hardship, especially those with pre-settled status or those who arrived in the UK during the pandemic. The reasons for financial strain varied but there were strong patterns linked to increased pressure at work, greater exposure to Covid-19 as well as redundancies, pay cuts and rejected benefit applications. There was a tendency to avoid applying for state financial support. These impacts were compounded by the sense of isolation, helplessness, or long-distance grief due to inability to visit loved ones in Poland. Covid-19 impacted most detrimentally on women with caring responsibilities, single parents and people in the health and teaching sectors. The most vulnerable Polish migrant essential workers - e.g. those on lower income, with pre-existing health conditions, restricted access to support and limited English proficiency - were at most risk. Discrimination was reported, including not feeling treated equally in the workplace. The sense of discrimination two-fold: as essential workers (low-paid, low-status, unsafe jobs) and as Eastern Europeans (frequent disciplining practices, treated as threat, assumed to be less qualified). In terms of future plans, some essential workers intended to leave the UK or were unsure about their future place of residence. Brexit was a major reason for uncertain settlement plans. Vaccine hesitancy was identified, based on doubts about vaccination, especially amongst younger respondents who perceived low risks of Covid-19 for their own health, including women of childbearing age, who may have worries over unknown vaccine side-effects for fertility. Interview participants largely turned to Polish language sources for vaccination information, especially social media, and family and friends in Poland. This promoted the spread of misinformation as Poland has a strong anti-vaccination movement.

Description of additional variables and parameters used in calculation of adjusted Ct values.

Raw diffraction data for mpro-x0390 / PDB ID 5REC (see: https://www.ebi.ac.uk/pdbe/entry/pdb/5REC) - SARS-CoV-2 main protease in complex with Z1587220559 (SMILES:OC=1C=CC=CC1CNC2=NC=3C=CC=CC3N2) collected as part of an XChem crystallographic fragment screening campaign on beamline i04-1 at Diamond Light Source. The deposited structure was automatically processed with standard Diamond tools and PanDDA, however the raw data are being made available to allow reanalysis by any interested party.

For more details see: https://www.diamond.ac.uk/covid-19/for-scientists/Main-protease-structure-and-XChem.html

The main entity of this document is a structure with accession number 5jil

Raw diffraction data for mpro-x1382 / PDB ID 5RFP (see: https://www.ebi.ac.uk/pdbe/entry/pdb/5RFP) - SARS-CoV-2 main protease in complex with PCM-0102190 (SMILES:CC(NC(=O)CCl)c1cccc(Cl)c1) collected as part of an XChem crystallographic fragment screening campaign on beamline i04-1 at Diamond Light Source. The deposited structure was automatically processed with standard Diamond tools and PanDDA, however the raw data are being made available to allow reanalysis by any interested party.

For more details see: https://www.diamond.ac.uk/covid-19/for-scientists/Main-protease-structure-and-XChem.html

Since the start of COVID-19 pandemic the Republic of Djibouti, in the horn of Africa, has experienced two epidemic waves of the virus between April and August 2020 and between February and May 2021. By May 2021, COVID-19 had affected 1.18% of the Djiboutian population and caused 152 deaths. Djibouti hosts several foreign military bases which makes it a potential hot-spot for the introduction of different SARS-CoV-2 strains. We genotyped fifty three viruses that have spread during the two epidemic waves. Next, using spike sequencing of twenty-eight strains and whole genome sequencing of thirteen strains, we found that Nexstrain clades 20A and 20B with a typically European D614G substitution in the spike and a frequent P2633L substitution in nsp16 were the dominant viruses during the first epidemic wave, while the clade 20H South African variants spread during the second wave characterized by an increase in the number of severe forms of COVID-19.

A breakdown of sample sizes, by category is also provided. *based upon a Ct value decrease of 3 being equivalent to a 10-fold increase in viral load [34].

Demographic and epidemiological characteristics of laboratory-confirmed COVID-19 cases in Vietnam.

Cox proportional risk analysis for mortality of all intubated and ventilated patients across both UK waves of the Sars-Cov-2 pandemic.

Mutations in SARS-CoV-2 genomes and their detection in the GISAID database: Nucleotide variants and amino acid changes.