Provisional counts of the number of deaths registered in England and Wales, including deaths involving coronavirus (COVID-19), by local authority, health board and place of death in the latest weeks for which data are available. The occurrence tabs in the 2021 edition of this dataset were updated for the last time on 25 October 2022.

In early-February 2020, the first cases of COVID-19 in the United Kingdom (UK) were confirmed. As of December 2023, the South East had the highest number of confirmed first episode cases of the virus in the UK with 3,180,101 registered cases, while London had 2,947,727 confirmed first-time cases. Overall, there has been 24,243,393 confirmed cases of COVID-19 in the UK as of January 13, 2023.

COVID deaths in the UK COVID-19 was responsible for 202,157 deaths in the UK as of January 13, 2023, and the UK had the highest death toll from coronavirus in western Europe. The incidence of deaths in the UK was 297.8 per 100,000 population as January 13, 2023.

Current infection rate in Europe The infection rate in the UK was 43.3 cases per 100,000 population in the last seven days as of March 13, 2023. Austria had the highest rate at 224 cases per 100,000 in the last week.

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

Provisional age-standardised mortality rates for deaths due to COVID-19 by sex, local authority and deprivation indices, and numbers of deaths by middle-layer super output area.

The number of deaths registered in England and Wales due to and involving coronavirus (COVID-19). Breakdowns include age, sex, region, local authority, Middle-layer Super Output Area (MSOA), indices of deprivation and place of death. Includes age-specific and age-standardised mortality rates.

A lookup file between 2019 Local Authority Districts to 2020 Covid Infection Survey Geography in the United Kingdom, as at 1 October 2020. (File size - 48KB) Field Names - LAD19CD, LAD19NM, CIS20CD, FIDField Types - Text, Text, Text, NumericField Lengths - 9, 35, 9FID = The FID, or Feature ID is created by the publication process when the names and codes / lookup products are published to the Open Geography portal.

A lookup file between 2018 Local Authority Districts to 2020 Covid Infection Survey Geography in the United Kingdom, as at 1 October 2020. (File size - 48KB) Field Names - LAD18CD, LAD18NM, LAD18NMW, CIS20CD, FIDField Types - Text, Text, Text, Text, NumericField Lengths - 9, 28, 28, 9FID = The FID, or Feature ID is created by the publication process when the names and codes / lookup products are published to the Open Geography portal. REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LAD18_CIS20_EN_LU_v1_5fbc82fc73e6407facd67a1c5e4cc043/FeatureServer

A lookup file between 2020 Covid Infection Survey Geography to 2020 Local Authority Districts to 2019 Regions in the United Kingdom, as at 1 October 2020. (File size - 56KB) Field Names - CIS20CD, LAD20CDS, RGN19CD, RGN19NM, FIDField Types - Text, Text, Text, Text, NumericField Lengths - 9, 99, 9, 24FID = The FID, or Feature ID is created by the publication process when the names and codes / lookup products are published to the Open Geography portal.

A lookup file between Local Authority District (2019) to 2020 Covid Infection Survey Geography in Great Britain, as at 1 October 2020. (File size - 64KB) Field Names - LAD19CD, LAD19NM, LAD19NMW, CIS20CD, FIDField Types - Text, Text, Text, Text, NumericField Lengths - 9, 35, 24, 9FID = The FID, or Feature ID is created by the publication process when the names and codes / lookup products are published to the Open Geography portal. REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LAD19_CIS20_GB_LU_ed5b75bc28e24b5d81b393cba28c48d3/FeatureServer

Laboratory confirmed cases of MRSA bacteraemia. Community-onset cases are all those that are not hospital-onset cases. Hospital-onset is determined by patient location, date of admission, date of specimen, and patient category. Hospital onset is only indicative for cases where NHS patient specimens are taken on the third day of admission onwards (e.g., day three when day one equals the day of admission) at an acute trust (including cases with unspecified specimen location) for inpatients, day patients, emergency assessment, or unspecified patient category. Records with a missing admission date (where the specimen location is acute trust or missing and the patient category is inpatient, day patient, emergency assessment, or unspecified) are also included. Other cases may have hospital onset, but not in acute trusts.

Data is available by Sub ICB (Integrated Care Board) location.

Rationale A long-running voluntary surveillance scheme of laboratory-reported cases of Staphylococcus aureus bacteraemia showed increasing incidence of meticillin-resistant S. aureus (MRSA) infections in England, Wales, and Northern Ireland in the 1990s. This generated both media and public interest. In response, the Department of Health (DH) in England introduced a mandatory surveillance scheme for S. aureus bacteraemias in April 2001, which included data on the number of cases that were due to MRSA. In October 2005, the mandatory surveillance scheme for MRSA bacteraemias was enhanced to collect patient-level data. Additionally, all NHS organisations reporting cases of MRSA bacteraemia from 1 April 2013 were required to complete a Post Infection Review (PIR). This process was commenced to support the delivery of zero tolerance on MRSA bacteraemia, as set out by NHS England in the Planning Guidance Everyone counts: Planning for Patients 2013/14. A PIR is undertaken after all MRSA bacteraemias with the purpose of identifying how a case occurred, to identify actions by local healthcare teams which will prevent a reoccurrence, and to identify the organisation best placed to ensure improvements are made (this is known as “assigning” a case to an organisation). From 1 April 2018, the PIR process changed from being applied by all trusts to trusts identified as having high rates of MRSA. For more information, please see MRSA Guidance: Post Infection Review. A low value is indicative of a low rate of MRSA.

Source of numerator UK Health Security Agency (UKHSA), Healthcare Associated Infection Data Capture System (HCAI DCS) Mandatory Surveillance

Source of denominator Office for National Statistics (ONS), Mid-year population estimates

Caveats These data do not provide a basis for decisions on the clinical effectiveness of infection control interventions in individual Trusts: further investigations considering potential confounders would need to be undertaken before this could be done.

Nor do these data provide a basis for comparisons between acute Trust or SICBLs. Rate information, using rate calculations as currently defined, is not appropriate for comparison. The counts of infections have not been adjusted to give a standardised rate considering factors such as organisational demographics or case mix. Rate information is of use for comparison of an individual organisation over time.

‘All reported cases’ refers to all MRSA-positive blood cultures reported by the Trust whose laboratory processes the specimen. It is important to note that this does not necessarily imply that the infection was acquired there.

Confidence intervals for rates are not currently calculated because appropriate methods for comprehensive coverage are being assessed.

Cases that the UKHSA’s HCAI Data Capture System attributes to a commissioning hub (such as the national commissioning hub, 13Q, or one of the regional Health & Justice commissioning hubs) are not featured in sub ICB Location dashboards but they do still contribute to the highest spatial level—the England national total. This means the England case total & rates may be slightly higher than the sum of all sub ICB Location cases & rates.

IMPORTANT NOTE: SICBL calculations for the period between January 2021 and January 2022 have been based on SICBL boundaries. As such some SICBLs may experience higher or lower rates than expected due to this change. Those SICBLs affected are; Bassetlaw, Glossop, East Leicestershire and Rutland, Lincolnshire, Cambridgeshire and Peterborough, Birmingham and Solihull, Black Country and West Birmingham and Oundle.

A lookup file between Local Authority Districts (2018) to 2020 Covid Infection Survey Geographys in Great Britain, as at 1 October 2020. (File size - 64KB) Field Names - LAD18CD, LAD18NM, LAD18NMW, CIS20CD, FIDField Types - Text, Text, Text, Text, NumericField Lengths - 9, 28, 24, 9FID = The FID, or Feature ID is created by the publication process when the names and codes / lookup products are published to the Open Geography portal. REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LAD18_CIS20_GB_LU_1de3fb723e594e379468decf62be9e58/FeatureServer

Live births by usual residence of mother, and General Fertility Rates (GFR), and Deaths and Standardised Mortality Ratio (SMR) by ward and local authority.

The births and deaths data comes from ONS Vital Statistics Table 4.
Small area data is only available directly from ONS under licence.

The general fertility rate (GFR) is the number of live births per 1,000 women aged 15-44.

SMR measures whether the population of an area has a higher or lower number of deaths than expected based on the age profile of the population (more deaths are expected in older populations). The SMR is defined as follows: SMR = (Observed no. of deaths per year)/(Expected no. of deaths per year).

Rates are provisional, they are based on the GLA 2011 based SHLAA ward projections (standard) released in January 2012. At national level, however, they are based on the mid-year population estimates.

More information is on the ONS website.

According to a survey carried out in April, 2020, almost 31 percent of hospital doctors in the UK said that due to the prioritization of patients with confirmed or possible coronavirus (COVID-19) the care available to non-coronavirus patients has significantly worsened. Furthermore, 25 percent of doctors reported that the care to patients not infected with coronavirus has slightly worsened since the pandemic started, while approximately 11 percent said it was too early to know how the patient's care has been affected.

The latest number of cases in the UK can be found here. For further information about the coronavirus pandemic, please visit our dedicated Facts and Figures page.

All children at age 12 months who have received the complete course (3 doses) of hepatitis B vaccine within each reporting area as a percentage of all the eligible population as defined in the hepatitis B chapter of the immunisation against infectious diseases "Green Book" (have maternal Hep B positive status).RationaleInfants born to hepatitis B virus (HBV) infected mothers are at high risk of acquiring HBV infection themselves. Babies born to infected mothers are given a dose of the hepatitis B vaccine after they are born. This is followed by another two doses (with a month in between each) and a booster dose 12 months later. Around 20% of people with chronic hepatitis B will go on to develop scarring of the liver (cirrhosis), which can take 20 years to develop, and around 1 in 10 people with cirrhosis will develop liver cancer.Vaccination coverage is the best indicator of the level of protection a population will have against vaccine preventable communicable diseases. Coverage is closely correlated with levels of disease. Monitoring coverage identifies possible drops in immunity before levels of disease rise.Since April 2000 it has been recommended that all pregnant women in England and Wales should be offered testing for hepatitis B through screening for HBsAg, and that all babies of HBsAg seropositive women should be immunised (HSC 1998 127). A dose of paediatric hepatitis B vaccine is recommended for all infants born to an HBV infected mother as soon as possible after birth, then at 1 and 2, and 12 months of age ( https://www.gov.uk/government/collections/hepatitis-b-guidance-data-and-analysis ). Previous evidence shows that highlighting vaccination programmes encourages improvements in uptake levels may also have relevance for NICE guidance PH21: Reducing differences in the uptake of immunisations (The guidance aims to increase immunisation uptake among those aged under 19 years from groups where uptake is low).Definition of numeratorNumber of children at age 12 months who have received the complete course (3 doses) of hepatitis B vaccine. Numerator counts for local authorities include all people registered with practices in the local authority, and no data are available to provide resident based figures.Definition of denominatorEligible population as defined in the hepatitis B chapter of the immunisation against infectious diseases "Green Book" (have maternal Hep B positive status).Denominators for local authorities include all people registered with practices in the local authority, and no data are available to provide resident based figures.CaveatsThese statistics have been published as ‘experimental statistics’ in the NHS Digital “NHS Immunisation Statistics, England” report. There are a number of issues with the hepatitis B dataset which have either impacted on data quality or have raised potential concerns around the quality of the data. Selective neonatal hepatitis B coverage data are reported by local authority (LA) responsible population for the first time in the 2015 to 2016 publication. Many LAs could not supply complete data on infants born to hepatitis B positive mothers and for a number of other LAs there were data quality issues. It has therefore not been possible to estimate figures for those LAs or describe the quality/completeness of LA data with any accuracy. (see Quality Statement for 2015 to 2016 for more information). Office of Health Improvement and Disparities has also published data for LAs that are co terminus with former PCTs but provided data by PCT rather than LA. These data were not published or validated by NHS Digital.

Due to changes in the collection and availability of data on COVID-19 this page will no longer be updated. The webpage will no longer be available as of 11 May 2023. On-going, reliable sources of data for COVID-19 are available via the COVID-19 dashboard, Office for National Statistics, and the UKHSA This page provides a weekly summary of data on deaths related to COVID-19 published by NHS England and the Office for National Statistics. More frequent reporting on COVID-19 deaths is now available here, alongside data on cases, hospitalisations, and vaccinations. This update contains data on deaths related to COVID-19 from: NHS England COVID-19 Daily Deaths - last updated on 28 June 2022 with data up to and including 27 June 2022. ONS weekly deaths by Local Authority - last updated on 16 August 2022 with data up to and including 05 August 2022. Summary notes about each these sources are provided at the end of this document. Note on interpreting deaths data: statistics from the available sources differ in definition, timing and completeness. It is important to understand these differences when interpreting the data or comparing between sources. Weekly Key Points An additional 24 deaths in London hospitals of patients who had tested positive for COVID-19 and an additional 5 where COVID-19 was mentioned on the death certificate were announced in the week ending 27 June 2022. This compares with 40 and 3 for the previous week. A total of 306 deaths in hospitals of patients who had tested positive for COVID-19 and 27 where COVID-19 was mentioned on the death certificate were announced for England as whole. This compares with 301 and 26 for the previous week. The total number of COVID-19 deaths reported in London hospitals of patients who had tested positive for COVID-19 is now 19,102. The total number of deaths in London hospitals where COVID-19 was mentioned on the death certificate is now 1,590. This compares to figures of 119,237 and 8,197 for English hospitals as a whole. Due to the delay between death occurrence and reporting, the estimated number of deaths to this point will be revised upwards over coming days These figures do not include deaths that occurred outside of hospitals. Data from ONS has indicated that the majority (79%) of COVID-19 deaths in London have taken place in hospitals. Recently announced deaths in Hospitals 21 June 22 June 23 June 24 June 25 June 26 June 27 June London No positive test 0 0 1 4 0 0 0 London Positive test 3 7 2 10 0 0 2 Rest of England No positive test 2 6 4 4 0 0 6 Rest of England Positive test 47 49 41 58 6 0 81 16 May 23 May 30 May 06 June 13 June 20 June 27 June London No positive test 14 3 4 0 4 3 5 London Positive test 45 34 55 20 62 40 24 Rest of England No positive test 41 58 33 23 47 23 22 Rest of England Positive test 456 375 266 218 254 261 282 Deaths by date of occurrence 21 June 22 June 23 June 24 June 25 June 26 June 27 June London 20,683 20,686 20,690 20,691 20,692 20,692 20,692 Rest of England 106,604 106,635 106,679 106,697 106,713 106,733 106,742 Interpreting the data The data published by NHS England are incomplete due to: delays in the occurrence and subsequent reporting of deaths deaths occurring outside of hospitals not being included The total deaths reported up to a given point are therefore less than the actual number that have occurred by the same point. Delays in reporting NHS provide the following guidance regarding the delay between occurrence and reporting of deaths: Confirmation of COVID-19 diagnosis, death notification and reporting in central figures can take up to several days and the hospitals providing the data are under significant operational pressure. This means that the totals reported at 5pm on each day may not include all deaths that occurred on that day or on recent prior days. The data published by NHS England for reporting periods from April 1st onward includes both date of occurrence and date of reporting and so it is possible to illustrate the distribution of these reporting delays. This data shows that approximately 10% of COVID-19 deaths occurring in London hospitals are included in the reporting period ending on the same day, and that approximately two-thirds of deaths were reported by two days after the date of occurrence. Deaths outside of hospitals The data published by NHS England does not include deaths that occur outside of hospitals, i.e. those in homes, hospices, and care homes. ONS have published data for deaths by place of occurrence. This shows that, up to 05 August, 79% of deaths in London recorded as involving COVID-19 occurred in hospitals (this compares with 44% for all causes of death). This would suggest that the NHS England data may underestimate overall deaths from COVID-19 by around 20%. Number of deaths Proportion of deaths Week ending Hospital Care home Home Other Hospital Care home Home Other 06 Mar 2020 1 1 0 0 50% 50% 0% 0% 13 Mar 2020 13 0 4 0 76% 0% 24% 0% 20 Mar 2020 148 9 11 0 88% 5% 7% 0% 27 Mar 2020 610 45 53 14 84% 6% 7% 2% 03 Apr 2020 1,215 132 143 27 80% 9% 9% 2% 10 Apr 2020 1,495 282 162 32 76% 14% 8% 2% 17 Apr 2020 1,076 295 101 29 72% 20% 7% 2% 24 Apr 2020 669 210 72 35 68% 21% 7% 4% 01 May 2020 348 125 43 15 66% 24% 8% 3% 08 May 2020 261 93 29 16 65% 23% 7% 4% 15 May 2020 152 51 22 5 66% 22% 10% 2% 22 May 2020 93 51 10 3 59% 32% 6% 2% 29 May 2020 62 25 7 6 62% 25% 7% 6% 05 Jun 2020 53 23 4 1 65% 28% 5% 1% 12 Jun 2020 27 11 9 3 54% 22% 18% 6% 19 Jun 2020 22 7 6 2 59% 19% 16% 5% 26 Jun 2020 14 14 5 1 41% 41% 15% 3% 03 Jul 2020 10 5 2 5 45% 23% 9% 23% 10 Jul 2020 15 3 0 1 79% 16% 0% 5% 17 Jul 2020 8 7 2 0 47% 41% 12% 0% 24 Jul 2020 15 1 0 2 83% 6% 0% 11% 31 Jul 2020 6 2 1 0 67% 22% 11% 0% 07 Aug 2020 6 2 0 1 67% 22% 0% 11% 14 Aug 2020 7 4 2 1 50% 29% 14% 7% 21 Aug 2020 4 0 0 0 100% 0% 0% 0% 28 Aug 2020 1 2 0 0 33% 67% 0% 0% 04 Sep 2020 3 0 1 0 75% 0% 25% 0% 11 Sep 2020 7 2 0 1 70% 20% 0% 10% 18 Sep 2020 9 2 1 0 75% 17% 8% 0% 25 Sep 2020 23 3 3 0 79% 10% 10% 0% 02 Oct 2020 27 3 2 0 84% 9% 6% 0% 09 Oct 2020 36 3 3 0 86% 7% 7% 0% 16 Oct 2020 41 0 2 0 95% 0% 5% 0% 23 Oct 2020 47 4 4 0 85% 7% 7% 0% 30 Oct 2020 91 3 5 1 91% 3% 5% 1% 06 Nov 2020 93 7 5 2 87% 7% 5% 2% 13 Nov 2020 109 11 10 2 83% 8% 8% 2% 20 Nov 2020 162 5 8 4 91% 3% 4% 2% 27 Nov 2020 175 8 14 5 87% 4% 7% 2% 04 Dec 2020 190 10 13 10 85% 4% 6% 4% 11 Dec 2020 199 9 13 6 88% 4% 6% 3% 18 Dec 2020 267 15 25 4 86% 5% 8% 1% 25 Dec 2020 403 30 43 7 83% 6% 9% 1% 01 Jan 2021 677 35 109 28 80% 4% 13% 3% 08 Jan 2021 959 73 167 36 78% 6% 14% 3% 15 Jan 2021 1,125 84 165 39 80% 6% 12% 3% 22 Jan 2021 1,163 96 142 43 81% 7% 10% 3% 29 Jan 2021 863 82 101 28 80% 8% 9% 3% 05 Feb 2021 605 70 59 38 78% 9% 8% 5% 12 Feb 2021 439 29 49 14 83% 5% 9% 3% 19 Feb 2021 338 29 33 12 82% 7% 8% 3% 26 Feb 2021 214 19 19 11 81% 7% 7% 4% 05 Mar 2021 141 11 19 5 80% 6% 11% 3% 12 Mar 2021 99 9 7 1 85% 8% 6% 1% 19 Mar 2021 65 10 1 1 84% 13% 1% 1% 26 Mar 2021 41 9 4 2 73% 16% 7% 4% 02 Apr 2021 35 5 4 0 80% 11% 9% 0% 09 Apr 2021 29 2 3 0 85% 6% 9% 0% 16 Apr 2021 24 6 2 0 75% 19% 6% 0% 23 Apr 2021 14 1 0 0 93% 7% 0% 0% 30 Apr 2021 13 1 1 0 87% 7% 7% 0% 07 May 2021 14 3 0 0 82% 18% 0% 0% 14 May 2021 6 2 0 0 75% 25% 0% 0% 21 May 2021 8 1 1 0 80% 10% 10% 0% 28 May 2021 11 1 2 1 73% 7% 13% 7% 04 Jun 2021 9 0 0 0 100% 0% 0% 0% 11 Jun 2021 11 3 0 0 79% 21% 0% 0% 18 Jun 2021 11 4 2 1 61% 22% 11% 6% 25 Jun 2021 10 0 0 1 91% 0% 0% 9% 02 Jul 2021 14 1 2 0 82% 6% 12% 0% 09 Jul 2021 12 1 4 1 67% 6% 22% 6% 16 Jul 2021 18 3 2 0 78% 13% 9% 0% 23 Jul 2021 48 0 7 1 86% 0% 12% 2% 30 Jul 2021 49 2 4 4 83% 3% 7% 7% 06 Aug 2021 66 1 9 1 86% 1% 12% 1% 13 Aug 2021 60 1 12 1 81% 1% 16% 1% 20 Aug 2021 84 1 5 1 92% 1% 5% 1% 27 Aug 2021 78 3 10 3 83% 3% 11% 3% 03 Sep 2021 85 3 7 1 89% 3% 7% 1% 10 Sep 2021 83 2 10 2 86% 2% 10% 2% 17 Sep 2021 65 2 9 1 84% 3% 12% 1% 24 Sep 2021 76 5 5 0 88% 6% 6% 0% 01 Oct 2021 88 2 15 1 83% 2% 14% 1% 08 Oct 2021 65 2 7 1 87% 3% 9% 1% 15 Oct 2021 62 1 9 4 82% 1% 12% 5% 22 Oct 2021 64 2 11 2 81% 3% 14% 3% 29 Oct 2021 66 3 11 1 81% 4% 14% 1% 05 Nov 2021 67 3 10 5 79% 4% 12% 6% 12 Nov 2021 84 2 12 1 85% 2% 12% 1% 19 Nov 2021 63 2 2 0 94% 3% 3% 0% 26 Nov 2021 68 2 8 0 87% 3% 10% 0% 03 Dec 2021 72 2 10 1 85% 2% 12% 1% 10 Dec 2021 81 3 12 4 81% 3% 12% 4% 17 Dec 2021 91 1 12 3 85% 1% 11% 3% 24 Dec 2021 101 8 15 3 80% 6% 12% 2% 31 Dec 2021 129 11 19 6 78% 7% 12% 4% 07 Jan 2022 178 18 19 4 81% 8% 9% 2% 14 Jan 2022 194 23 16 14 79% 9% 6% 6% 21 Jan 2022 165 25 11 4 80% 12% 5% 2% 28 Jan 2022 119 20 13 5 76% 13% 8% 3% 04 Feb 2022 97 13 8 2 81% 11% 7% 2% 11 Feb 2022 51 10 6 6 70% 14% 8% 8% 18 Feb 2022 62 6 9 3 78% 8% 11% 4% 25 Feb 2022 55 2 2 1 92% 3% 3% 2% 04 Mar 2022 47 2 2 2 89% 4% 4% 4% 11 Mar 2022 48 3 4 0 87% 5% 7% 0% 18 Mar 2022 60 7 8 4 76% 9% 10% 5% 25 Mar 2022 51 11 5 2 74% 16% 7% 3% 01 Apr 2022 60 8 5 2 80% 11% 7% 3% 08 Apr 2022 78 4 7 3 85% 4% 8% 3% 15 Apr 2022 74 6 6 3 83% 7% 7% 3% 22 Apr 2022 58 10 7 6 72% 12% 9% 7% 29 Apr 2022 39 8 3 4 72% 15% 6% 7% 06 May 2022 44 3 4 0 86% 6% 8% 0% 13 May 2022 29 2 4 2 78% 5% 11% 5% 20 May 2022 16 4 0 2 73% 18% 0% 9% 27 May 2022 34 3 3 1 83% 7% 7% 2% 03 Jun 2022 18 1 1 0 90% 5% 5% 0% 10 Jun 2022 18 1 3 0 82% 5% 14% 0% 17 Jun 2022 22 1 2 0 88% 4% 8% 0% 24 Jun 2022 33 2 3 1 85% 5% 8% 3% 01 Jul 2022 33 2 2 0 89% 5% 5% 0% 08 Jul 2022 51 4 4 4 81% 6% 6% 6% 15 Jul 2022 60 5 4 2 85% 7% 6% 3% 22 Jul 2022 71 9 10 3 76% 10% 11% 3% 29 Jul 2022 48 7 9 0 75% 11% 14% 0% 05 Aug 2022 35 1 3 4 81% 2% 7% 9% Total 18,924 2,390 2,152 634 79% 10% 9% 3% Comparison with all cause mortality Comparison of data sources Note on data sources NHS England provides numbers of patients who have died in hospitals in England and had tested positive for COVID-19, and from 25 April, the number of patients where COVID-19 is mentioned on the death certificate and no positive COVID-19 test result was received. Figures are updated each day at 2pm with deaths reported up to 5pm the previous day. There is a delay between the occurrence of a death to it being captured in the

IntroductionPathogens causing diabetic foot infections (DFIs) vary by region globally; however, knowledge of the causative organism is essential for effective empirical treatment. We aimed to determine the incidence and antibiotic susceptibility of DFI pathogens worldwide, focusing on Asia and China.MethodsThrough a comprehensive literature search, we identified published studies on organisms isolated from DFI wounds from January 2000 to December 2020.ResultsBased on our inclusion criteria, we analyzed 245 studies that cumulatively reported 38,744 patients and 41,427 isolated microorganisms. DFI pathogens varied according to time and region. Over time, the incidence of Gram-positive and Gram-negative aerobic bacteria have decreased and increased, respectively. America and Asia have the highest (62.74%) and lowest (44.82%) incidence of Gram-negative bacteria, respectively. Africa has the highest incidence (26.90%) of methicillin-resistant Staphylococcus aureus. Asia has the highest incidence (49.36%) of Gram-negative aerobic bacteria with species infection rates as follows: Escherichia coli, 10.77%; Enterobacter spp., 3.95%; and Pseudomonas aeruginosa, 11.08%, with higher local rates in China and Southeast Asia. Linezolid, vancomycin, and teicoplanin were the most active agents against Gram-positive aerobes, while imipenem and cefoperazone-sulbactam were the most active agents against Gram-negative aerobes.DiscussionThis systematic review showed that over 20 years, the pathogens causing DFIs varied considerably over time and region. This data may inform local clinical guidelines on empirical antibiotic therapy for DFI in China and globally. Regular large-scale epidemiological studies are necessary to identify trends in DFI pathogenic bacteria.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42023447645.

Towards the end of the 1880s, a localized smallpox epidemic had broken out in the North of England, and had infected thousands in the region; with one news report claiming that Sheffield was responsible for three quarters of all smallpox cases in England at this time; just under 500 people died from smallpox in this pandemic. Of the entire population of Sheffield, 98 percent claimed to have been vaccinated, and (assuming these figures are correct) the death rate among cases of vaccinated people was below five percent. In stark contrast to this, cases among unvaccinated patients resulted in fatalities almost fifty percent of the time, meaning that infected persons who were not vaccinated were ten times more likely to succumb to the disease than those who had been. This ratio is similar among the infected aged above ten years, however vaccinated patients below the age of ten were 25 times more likely to survive.

This trial outlines a unique time limited opportunity to conduct the first ever randomised controlled trial in the UK, to evaluate the feasibility and acceptability of randomising participants to Settled Accommodation (SA) or Temporary Accommodation (TA) with the aim of preventing COVID-19 infection and reducing housing instability.

The study’s primary objectives were to assess the following: 1. The feasibility of recruiting local authorities and eligible participants to the study. 2. Recruitment rates of participants and retention through 3 months and 6 months post randomisation follow-up data collection. 3. The acceptability of the study and its processes, including randomisation, to single homeless households and local authorities and their willingness to participate in a definitive trial.

In addition, the study also aims to assess the following Secondary objectives: 1. Adherence to the study allocation, reach and fidelity (i.e. whether SA is delivered as intended, works as hypothesized, is scalable and sustainable). 2. The feasibility and acceptability of proposed outcome measures for a definitive trial, including resource use and health-related quality of life data, as methods to measure effectiveness of the intervention and to conduct an embedded health economic evaluation within a definitive RCT. 3. The feasibility and acceptability of linkage to routinely collected data within a definitive RCT by assessing whether (a) participants are willing to consent for their data to be linked and (b) personal identifiers can be linked to NHS Digital routine datasets.

Quantitative data was collected at baseline and follow-up at 3 and 6 months. 50 participants were invited to complete outcome measures. These participants completed the questionnaire over the telephone with trained members of staff based at the University. Data was entered into Qualtrics application system and used to collect consent and questionnaire response data. The trial explored past and current experiences of homeless individuals in relation to a range of life domains, including; housing, health, adverse life experiences such as imprisonment, and substance misuse. Participants were also invited to take part in qualitative interviews to discuss the acceptability of the study and its processes, including randomisation, and their willingness to participate in a definitive trial. They were also asked about their experience of services and provision. Data from 14 participants and 1 researcher in the Moving On Study was gathered.

As part of the government's response to COVID-19, 15,000 rough sleepers have now been offered self-contained temporary accommodation in England, mainly in hotels. This approach, which has involved the decanting of hostels, shelters and similar shared provision for rough sleepers, is a short-term response.

When the lockdown ends, decisions will need to be taken about how to house former rough sleepers in line with the UK government's commitment to prevent people from going back to the streets - including, potentially, through the re-opening of shelter-type accommodation. Existing temporary accommodation with shared facilities might make it impossible for people to comply with government social distancing advice. So these decisions will impact on the risk of a second wave of infection from COVID-19 and possibly any mutations.

This proposal outlines a unique time limited opportunity to conduct the first ever randomised controlled trial in the UK, to evaluate the effectiveness and cost-effectiveness of permanent housing on the risk of COVID-19 infection and housing stability for people experiencing homelessness.

That many homeless people are currently waiting to be housed means they can be randomly allocated to different housing solutions at scale quickly. The insights drawn from the short-term impacts of permanent housing can be used to inform other local authorities' responses to the challenges of COVID-19 and the cost-effectiveness of accommodation alternatives more broadly.