(LONDON) ONS Integrated Data Report: Has launched the first stage of the Integrated Data Service (IDS), a cloud-based platform giving analysts and researchers greater access to data from a range of sources #AceNewsDesk report

#AceNewsReport – Oct.27: Launching next spring, a public beta will open the door for accredited researchers outside of government to use the new service: The private beta version will allow a selection of government analysts to compare and combine data held by the ONS and other departments, helping to unlock the full potential of data, inform policy decisions and encourage collaboration across government…..

#AceDailyNews says according to ONS Report: Launches ‘Integrated Data Service’ (IDS) to boost government collaboration on data sharing….

The three projects selected for the private beta and will focus on some of the government’s top priorities:

  • wage growth – an ONS and HM Treasury collaboration will investigate in detail how wages change across the country, helping inform the government’s “Levelling Up” policy agenda
  • energy efficiency – working with the Valuation Office Agency to provide better information on the energy efficiency of homes around the country as part of wider work to help measure the UK’s progress towards reaching net zero by 2050
  • regional issues – a collaboration with Department for Business, Energy, and Industrial Strategy to analyse how text from local news sources across the UK can be used to understand concerns of communities around the country

DCMS Minister for State Julia Lopez said: “The Integrated Data Service is a crucial part of our National Data Strategy and will make it easier and quicker for policy makers to access robust evidence for making the decisions that can improve the lives of people across the country.

“Unlocking the power of data will boost the economy, create jobs and help us build back better from the pandemic.” 

Joanna Davinson, Executive Director at the Central Digital and Data Office, said: “The Integrated Data Service will provide the public sector with secure access to high-quality data for better research and analysis.

“This is aligned to our vision of having increased availability of data for decision-makers to ensure more data driven policies. In this way, we can enable transformation of the Government’s use of data and support the delivery of efficient public services for users.”

Alison Pritchard, Deputy National Statistician for Data Capability, said: “The Service demonstrates how data held, managed and accessed in a trusted and secure environment can benefit us all by providing essential insight on social and economic factors. I am particularly looking forward to engaging widely to explain how we are protecting the data appropriately and making sure it is put to use for the public good.”

Read more about the project and its future in today’s blog.

#AceNewsDesk report ………………Published: Oct.27: 2021:

Editor says …Sterling Publishing & Media Service Agency is not responsible for the content of external site or from any reports, posts or links, and can also be found here on Telegram: https://t.me/acenewsdaily all of our posts fromTwitter can be found here: https://acetwitternews.wordpress.com/ and all wordpress and live posts and links here: https://acenewsroom.wordpress.com/and thanks for following as always appreciate every like, reblog or retweet and free help and guidance tips on your PC software or need help & guidance from our experts AcePCHelp.WordPress.Com

#data, #ids, #london, #ons

(LONDON) ONS REPORT: The number of job vacancies in the UK has hit a record high, according to the latest official figures #AceNewsDesk report

#AceNewsReport – Oct.13: The largest increase in vacancies was in the retail sector and in motor vehicle repair, it said: The UK unemployment rate was estimated at 4.5%, compared with a rate of 4% before the pandemic:

#AceDailyNews says according to the latest ONS report: UK job vacancies reach 20-year high with total of 1.1-million: The ONS said the number of employees on payrolls showed another monthly increase, rising 207,000 to a record 29.2 million in September…..

A waiter

Glossary

Vacancies

Vacancies are defined as positions for which employers are actively seeking recruits from outside their business or organisation. The estimates are based on the Vacancy Survey; this is a survey of employers designed to provide estimates of the stock of vacancies across the economy, excluding agriculture, forestry and fishing (a small sector for which the collection of estimates would not be practical).

Jobs

job is an activity performed for an employer or customer by a worker in exchange for payment, usually in cash, or in kind, or both. The number of jobs is not the same as the number of people in employment. This is because a person can have more than one job. The number of jobs is the sum of employee jobs from employer surveys, self-employment jobs from the Labour Force Survey (LFS), those in HM Forces and government-supported trainees. The number of people in employment is measured by the LFS; these estimates are available in our Employment in the UKrelease.

A more detailed glossary is available.Back to table of contents

Measuring the data

Consultation on the Code of Practice for Statistics – proposed change to 9.30am release practice

On behalf of the UK Statistics Authority, the Office for Statistics Regulation (OSR) is conducting a consultation on the Code of Practice for Statistics, proposing changes to the 9.30am release practice. Please send comments by 21 December 2021 to regulation@statistics.gov.uk.

Coronavirus

For more information on how labour market data sources are affected by the coronavirus (COVID-19) pandemic, see the article published on 6 May 2020, which details some of the challenges that we have faced in producing estimates at this time.

An article, published on 11 December 2020, compares our labour market data sources and discusses some of the main differences.

Workforce Jobs estimates include data from the Labour Force Survey (LFS). From the 15 July 2021 an improved LFS weighting methodology, better accounting for population changes through the COVID-19 pandemic was implemented, affecting periods from January to March 2020 onwards. This publication of Workforce Jobs statistics is the first to take on these revised LFS estimates. For more information on the changes to LFS weighting methodology through the pandemic please see our article on the LFS Survey weighting methodology.

Impact on production of vacancy and workforce job estimates

Because of social distancing measures leading to the temporary closure of businesses across the UK, there have been some difficulties in collecting data using the Vacancy Survey and the Short-Term Employment Surveys.

Survey response rates were lower than is typical. To protect the quality of our output, we have used alternative sources where possible to inform data. We have used Standard Industrial Classification (SIC) section-level indications from the Business Insights and Conditions Survey (BICS), as well as survey contributor-level comments provided to us over the telephone or electronically, as a guide on whether businesses are operational and likely, or not, to be actively recruiting and to confirm employment figures.

Sources

The data in this bulletin come from surveys of businesses. It is not feasible to survey every business in the UK, so these statistics are estimates based on samples, not precise figures.

Vacancies

Estimates of vacancies are obtained from the Vacancy Survey, a survey of employers. Adzuna Online job advert estimates are also published as part of the Coronavirus and the latestindicators for the UK economy release.

Jobs

Estimates of jobs are compiled from a number of sources, including Short-Term Employment Surveys (STES), the Quarterly Public Sector Employment Survey (QPSES) and the Labour Force Survey (LFS). STES is a group of surveys that collect employment and turnover information from private sector businesses. In December of each year, the jobs estimates are “benchmarked” to the latest estimates from the Business Register and Employment Survey (BRES).

The STES estimates are drawn for a specified date early in the last month of each calendar quarter. The March 2020 data were from 13 March 2020 before the start of coronavirus (COVID-19) social distancing measures.

For more information on how jobs data are measured, please see the Measuring the Data section in our previous release

More quality and methodology information on strengths, limitations, appropriate uses, and how the data were created is available in the Vacancy Survey QMI and Workforce jobs QMI.

Sampling variability

The sampling variability of the three-month average vacancies level is around plus or minus 1.5% of that level expressed as a coefficient of variation, giving a 95% confidence interval for estimates of approximately plus or minus 20,000.

The sampling variability of the three-month average vacancies level, for a typical industrial sector is around plus or minus 6% of that level.Back to table of contents

#AceHealthDesk report ……………………Published: Oct.13: 2021:

Editor says …Sterling Publishing & Media Service Agency is not responsible for the content of external site or from any reports, posts or links, and can also be found here on Telegram: https://t.me/acenewsdaily all of our posts fromTwitter can be found here: https://acetwitternews.wordpress.com/ and all wordpress and live posts and links here: https://acenewsroom.wordpress.com/and thanks for following as always appreciate every like, reblog or retweet and free help and guidance tips on your PC software or need help & guidance from our experts AcePCHelp.WordPress.Com

#employment, #jobs, #london, #ons, #unemployment, #vacancies

(LONDON) ONS Breakthrough Cases Report: Where infection occurs in people ‘fully vaccinated’ and deaths involving #COVID19 who also had first positive PCR Test at least 14-days after 2nd vaccine dose #AceHealthDesk report

#AceHealthReport – Sept.18: “ Breakthrough cases” are where infection has occurred in someone who is fully vaccinated. We define a “breakthrough death” as a death involving coronavirus (COVID-19) that occurred in someone who had received both vaccine doses, and had a first positive PCR test at least 14 days after the second vaccination dose. In total, there were 256 breakthrough deaths between 2 January and 2 July 2021 (Table 2)….

#CoronavirusNewsDesk says this is an ONS report from Jan.02 – July.02: 2021: On Cases of people who have received two doses of vaccine and showed 256 breakthrough deaths between those dates above ….

5. Characteristics of breakthrough deaths

We used the Public Health Data Asset (PHDA) to investigate the characteristics of breakthrough cases, leveraging information from the General Practice Extraction Service (GPES) data for coronavirus (COVID-19) pandemic planning and research and Hospital Episode Statistics (HES). The linked data includes 252 breakthrough deaths and 43,956 total deaths involving COVID-19, 98.4% and 85.7% respectively of all breakthrough and total deaths involving COVID-19 that occurred between 2 January and 2 July 2021.

Table 3 shows some characteristics of these deaths.

Notes:
  1. Office for National Statistics (ONS) figures based on death registrations up to 28 July 2021 for deaths that occurred between 2 January and 2 July 2021 (Week 1 – Week 26).
  2. Statistics are calculated using the Public Health Data Asset, a linked dataset of people resident in England who could be linked to the 2011 Census and GP Patient Register.
  3. Deaths were defined using the International Classification of Diseases, tenth revision (ICD-10). Deaths involving the coronavirus (COVID-19) are defined as those with an underlying cause, or any mention of, ICD-10 codes U07.1 (COVID-19 virus identified) or U07.2 (COVID-19, virus not identified). Please note, this differs from the definition used in the majority of mortality outputs (see Glossary).
  4. Age is defined on the date of death.
  5. See Glossary for definitions of health-related variables.

The median age for breakthrough deaths was 84 and 61.1% of the deaths occurred in males, despite there being more elderly women than men, and therefore initially more fully vaccinated women who could experience a breakthrough death. For all other deaths involving COVID-19 occurring between 2 January and 2 July 2021 in the PHDA dataset, the median age was 82 and 52.2% were male.

13.1% of the breakthrough deaths occurred in people who were immunocompromised, compared to 5.4% for other deaths involving COVID-19. Individuals were identified as immunocompromised if they had experienced a hospital episode since 1 January 2019 where the diagnosis or procedure code corresponded to an immunocompromised condition, or who had died and a condition corresponding to being immunocompromised was listed on the death certificate (see Measuring the data).

A greater proportion of breakthrough deaths occurred in those who were clinically extremely vulnerable (76.6%, 193 deaths), than other COVID-19 deaths (74.5%, 32,567 deaths) or non-COVID-19 deaths (69.7%, 128,454 deaths). A similar trend is observed for disability and long-term health problem status, with proportions of deaths among people self-reporting that they are “limited a lot” on the 2011 Census as 31.7%, 27.8% and 24.2% for breakthrough deaths, other deaths involving COVID-19 and non-COVID-19 deaths respectively. However, the characteristics of breakthrough deaths can reflect the characteristics of the population that is more likely to be double vaccinated as well as having an increased risk of a breakthrough death, and numbers are relatively low and should therefore be interpreted with caution.Back to table of contents

6. Glossary

Age standardised mortality rates

Age-standardised mortality rates (ASMRs) are used to allow comparisons between populations that may contain different proportions of people of different ages and sex. The 2013 European Standard Population is used to standardise rates. In this bulletin, the ASMRs are calculated for each week. For more information see Section 7: Measuring the data.

Coronaviruses

The World Health Organization (WHO) defines coronaviruses as “a large family of viruses that are known to cause illness ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS)”. Between 2001 and 2018, there were 12 deaths in England and Wales due to a coronavirus infection, with a further 13 deaths mentioning the virus as a contributory factor on the death certificate.

Coronavirus (COVID-19)

COVID-19 refers to the “coronavirus disease 2019” and is a disease that can affect the lungs and airways. It is caused by a type of coronavirus. Further information is available from the World Health Organization (WHO).

Statistical significance

The term “significant” refers to statistically significant changes or differences. Significance has been determined using the 95% confidence intervals, where instances of non-overlapping confidence intervals between estimates indicate the difference is unlikely to have arisen from random fluctuation.

95% confidence intervals

A confidence interval is a measure of the uncertainty around a specific estimate. If a confidence interval is 95%, it is expected that the interval will contain the true value on 95 occasions if repeated 100 times. As intervals around estimates widen, the level of uncertainty about where the true value lies increases. The size of the interval around the estimate is strongly related to the number of deaths, prevalence of health states and the size of the underlying population. At a national level, the overall level of error will be small compared with the error associated with a local area or a specific age and sex breakdown. More information is available on our uncertainty pages.

Deaths involving COVID-19

For this analysis we define a death as involving COVID-19 if either of the ICD-10 codes U07.1 (COVID-19, virus identified) or U07.2 (COVID-19, virus not identified) is mentioned on the death certificate. In contrast to the definition used in the weekly deaths release, deaths where the ICD-10 code U09.9 (post-COVID condition, where the acute COVID-19 had ended before the condition immediately causing death occurred) is mentioned on the death certificate and neither of the other two COVID-19 codes are mentioned are not included, as they are likely to be the result of an infection caught a long time previously, and therefore not linked to the vaccination status of the person at date of death. Deaths involving U10.9 (multisystem inflammatory syndrome associated with COVID-19) where U07.1 or U07.2 are mentioned are also excluded. This is a rare complication affecting children, and there are no such deaths in our dataset for the data released in Deaths involving COVID-19 by vaccination status, England: deaths occurring between 2 January and 2 July 2021. 

Limitation by a long-term health problem of disability

Limitation by a long-term health problem or disability is self-reported on the 2011 Census for the question, “Are your day-to-day activities limited because of a health problem or disability which has lasted, or is expected to last, at least 12 months?”. Answers are one of, “Yes, limited a lot”, “Yes, limited a little”, or “No”.

Clinical vulnerability

Clinical vulnerability is determined according to the QCOVID risk model for health conditions that result in a higher risk of COVID-19. Health conditions are determined using the General Practice Extraction Service (GPES) and Hospital Episode Statistics (HES) data.

Immunocompromised

A person was identified as immunocompromised if they had a hospital episode recorded in the Hospital Episode Statistics dataset (HES) Admitted Patient Care dataset that started on or after 1 January 2019, with a diagnosis code (ICD-10) or procedure code (OPCD) corresponding to a condition that is associated with either primary or secondary immunosuppression. A person was also flagged as immunocompromised if they died and at least one of these ICD-10 diagnosis codes was mentioned on the death certificate or if they had SNOMED codes recorded in the General Practice Extraction Service dataset corresponding to a prescription of immunosuppressants.

The ICD-10 diagnosis codes included are based on the Immunocompromised State Diagnosis codes from the US Agency for Healthcare Research and Quality. These are ICD-10-CM codes, therefore we used only those codes that were up to 4 digits long to correspond to ICD-10 codes. 

The OPCS-4 procedure codes are based on the OPCS-4 codes listed in the NHS shielding list published by NHS Digital for the following disease groups: transplant, or cancer undergoing active chemo or radiotherapy.

Full lists of the ICD-10 codes and OPCS-4 codes used are given in the reference tables.

Date infected with COVID-19

The first positive test date of the most recent COVID-19 infection recorded in Test and Trace data is used to determine when a person who died from COVID-19 was infected relative to their vaccination data. The absence of a positive test can be either due to a linkage failure (the person was tested but we could not find them in the Test and Trace dataset) or to infection having occurred either not in England or before mass testing was available.

A COVID-19 infection can have multiple positive test results, and a person may be reinfected at a later period. The first positive test result was taken as the start of the first infection, and subsequent infections were determined as starting on the first positive test date that occurred >90 days after the start of the previous infection. The most recent infection is then defined as the start of the last recorded infection.

NOTE: This data is subject to change or fluctuation

#AceHealthDesk report ……..Published: Sept.18: 2021:

Editor says …Sterling Publishing & Media Service Agency is not responsible for the content of external site or from any reports, posts or links, and can also be found here on Telegram: https://t.me/acenewsdaily all of our posts fromTwitter can be found here:  https://acetwitternews.wordpress.com/ and all wordpress and live posts and links here: https://acenewsroom.wordpress.com/and thanks for following as always appreciate every like, reblog or retweet and free help and guidance tips on your PC software or need help & guidance from our experts AcePCHelp.WordPress.Com

#covid19, #london, #ons, #pcr-test, #vaccine

(LONDON) ONS REPORT: In England, it is estimated that over 9 in 10 adults, or 94.2% of the adult population (95% credible interval: 93.2% to 95.1%) would have tested positive for antibodies against SARS-CoV-2, the specific virus that causes coronavirus (COVID-19) FULL DETAILS BELOW: #AceHealthDesk report

#AceHealthDesk says that 9 in 10 adults were estimated to have #COVID19 antibodies across U.K. (not living in care homes, hospitals or other institutional settings) Week beginning 26th July 2021 ….

Aug.20, 2021: @acenewsservices

ONS REPORT:

1. Main points

  • In England, it is estimated that over 9 in 10 adults, or 94.2% of the adult population (95% credible interval: 93.2% to 95.1%) would have tested positive for antibodies against SARS-CoV-2, the specific virus that causes coronavirus (COVID-19), on a blood test in the week beginning 26 July 2021, suggesting they had the infection in the past or have been vaccinated.
  • In Wales, it is estimated that over 9 in 10 adults, or 93.2% of the adult population (95% credible interval: 91.8% to 94.5%) would have tested positive for antibodies against SARS-CoV-2 on a blood test in the week beginning 26 July 2021, suggesting they had the infection in the past or have been vaccinated.
  • In Northern Ireland, it is estimated that around 9 in 10 adults, or 89.1% of the adult population (95% credible interval: 85.0% to 92.0%) would have tested positive for antibodies against SARS-CoV-2 on a blood test in the week beginning 26 July 2021, suggesting they had the infection in the past or have been vaccinated.
  • In Scotland, it is estimated that over 9 in 10 adults, or 93.5% of the adult population (95% credible interval: 92.2% to 94.6%) would have tested positive for antibodies against SARS-CoV-2 on a blood test in the week beginning 26 July 2021, suggesting they had the infection in the past or have been vaccinated.
  • Across all four countries of the UK, there is a clear pattern between vaccination and testing positive for COVID-19 antibodies but the detection of antibodies alone is not a precise measure of the immunity protection given by vaccination.

About this bulletin

In this bulletin, we refer to the following.

Antibodies

We measure the presence of antibodies in the community population to understand who has had coronavirus (COVID-19) in the past, and the impact of vaccinations. It takes between two and three weeks after infection or vaccination for the body to make enough antibodies to fight the infection. Having antibodies can help to prevent individuals from getting the same infection again, or if they do get infected, they are less likely to have severe symptoms. Once infected or vaccinated, antibodies remain in the blood at low levels and can decline over time. The length of time antibodies remain at detectable levels in the blood is not fully known.

Community population

In this instance, community population refers to private residential households, and excludes those in hospitals, care homes and/or other institutional settings.

SARS-CoV-2

This is the scientific name given to the specific virus that causes COVID-19.

Data in this bulletin

The analysis on antibodies in this bulletin is based on blood test results taken from a randomly selected subsample of individuals aged 16 years and over, which are used to test for antibodies against SARS-CoV-2. We also present data on the percentage of people aged 16 years and over who report they have received one or more doses of a COVID-19 vaccine since 14 December 2020, and the percentage of people aged 16 years and over who are fully vaccinated since 15 February 2021.

Our antibodies and vaccination estimates are based on modelling of the people visited in the Coronavirus (COVID-19) Infection Survey in the community. Further information on our method to model antibodies and vaccinations can be found in our methods article.

We produce weekly modelled estimates using standard calendar weeks starting Monday. To provide the most timely and accurate estimates possible for antibody positivity, the model will include data for the first four to seven days of the most recent week available, depending on the availability of test results. The antibody estimate for the most recent week in this publication includes data from 26 to 29 July 2021.

We are presenting weekly modelled antibody estimates for adults by country, grouped age and single year of age for England, Wales, Northern Ireland and Scotland. We present the same analysis for vaccine estimates of adults who reported they have received one or more doses of a COVID-19 vaccine, and for adults who report they are fully vaccinated.

Modelled vaccine estimates are produced to provide context alongside our antibodies estimates and do not replace the official government figures on vaccinations, which are a more precise count of total vaccines issued. While we would expect the overall trend of our estimated number of people who have received vaccines to increase, it is possible that in some weeks, the estimate may remain the same or decrease as a result of sampling variability (for example, we may have a lower number of participants recording a vaccination in the latest week compared with an earlier week).Back to table of contents

2. Understanding antibodies, immunity and vaccination estimates

This bulletin presents analysis on past infection and/or vaccination – which we define as testing positive for antibodies to SARS-CoV-2 – for England, Wales, Northern Ireland and Scotland based on findings from the Coronavirus (COVID-19) Infection Survey in the UK. For context, we include estimates from our survey on the percentage of people who reported they have received at least one dose of a vaccine against SARS-CoV-2, as well as those who have been fully vaccinated against SARS-CoV-2.

It is not yet known how having detectable antibodies, now or at some time in the past, affects the chance of becoming infected or experiencing symptoms, as other parts of the immune system (T cell response) will offer protection. Antibody positivity is defined by a fixed amount of antibodies in the blood. A negative test result will occur if there are no antibodies or if antibody levels are too low to reach this threshold.

It is important to draw the distinction between testing positive for antibodies and having immunity. Following infection or vaccination, antibody levels can vary and sometimes increase but can still be below the level identified as “positive” in our test, and other tests. This does not mean that a person has no protection against COVID-19, as an immune response does not rely on the presence of antibodies alone.

We also do not yet know exactly how much antibodies need to rise to give protection. A person’s T cell response will provide protection but is not detected by blood tests for antibodies. A person’s immune response is affected by a number of factors, including health conditions and age. Our blog gives further information on the link between antibodies and immunity and the vaccine programme.

While the daily official government figures provide the recorded actual numbers of vaccines against SARS-CoV-2 issued, our vaccination estimates are likely to be different from the official figures. This is because they are estimates based on a sample survey of reported vaccine status and are provided for context alongside our antibodies estimates. We control for the effect of ethnicity by post-stratifying our analysis by White and non-White ethnic groups, rather than individual ethnicities, because of our current sample size. This could result in differences between our survey estimates and the government figures in the numbers of vaccines received for some ethnic minority groups.

Importantly, our survey collects information from the population living in private households and does not include people living in communal establishments such as care homes, hospitals or prisons. The value of showing our estimates of vaccines alongside our estimates of people testing positive for antibodies is to illustrate the relationship between the two.

Differences between official figures and the estimates from this survey differ in scale across each of the four UK nations (some survey estimates are closer to the official reported figures than others) because of differences in reporting dates and the inclusion of National Immunisation Management System (NIMS)1 data for England. In addition, our sampling method for Northern Ireland is different to the other nations, inviting only people who have previously participated in a Northern Ireland Statistics and Research Agency (NISRA) survey, which could result in a sample of individuals who are more likely to get vaccinated. This should be taken into consideration if comparing vaccine and antibody estimates across the four nations, as vaccine status and antibody positivity are related.

In addition, as our analysis develops, our survey-based estimates will enable possible future analysis of people who have received a vaccine with other characteristics collected in the survey. Our blog provides more information on what the Office for National Statistics (ONS) can tell you about the COVID-19 vaccine programme.

Our methodology article provides further information around the survey design, how we process data, and how data are analysed. The study protocol specifies the research for the study. The Quality and Methodology Information details the strength and limitations of the data.

Notes for: Understanding antibodies, immunity and vaccination estimates

  1. National Immunisation Management System (NIMS) administrative data are used to validate Coronavirus (COVID-19) Infection Survey self-reported records of vaccination for England. The equivalent of this is currently not included for other countries meaning the estimates for Wales, Northern Ireland and Scotland are produced only from Coronavirus (COVID-19) Infection Survey self-reported records of vaccination.

#AceNewsDesk report ………Published: Aug.20: 2021:

Editor says …Sterling Publishing & Media Service Agency is not responsible for the content of external site or from any reports, posts or links, and can also be found here on Telegram: https://t.me/acenewsdaily all of our posts fromTwitter can be found here: https://acetwitternews.wordpress.com/ and all wordpress and live posts and links here: https://acenewsroom.wordpress.com/and thanks for following as always appreciate every like, reblog or retweet and free help and guidance tips on your PC software or need help & guidance from our experts AcePCHelp.WordPress.Com

#health, #london, #northern-ireland, #ons, #scotland, #wales

(LONDON) Employment & Inflation Report: Job vacancies in the U.K. hit a record high last month and wages soared by 7.4% between April & June, adding to fears of a prolonged period of rising prices as companies pass on higher costs to consumers #AceNewsDesk report

#AceNewsReport – Aug.18: There were a record 953,000 vacancies in the United Kingdom on average over the three months to July — 168,000 more than the first quarter of 2020 before coronavirus restrictions were introduced…

#AceDailyNews says that one million vacancies and soaring wages fuel UK inflation fears and the strong recovery in the labor market was highlighted in data published Tuesday by the Office for National Statistics and it could further fuel inflationary pressures in the UK economy. That could prompt the central bank to hike interest rates as early as May 2022, according to some economists.

For July alone, vacancies may have exceeded one million for the first time based on early survey figures, according to Jonathan Athow, ONS deputy national statistician for economic statistics.Vacancies in all industries increased, with arts, entertainment and recreation posting the fastest rate of growth following the lifting of all remaining social distancing restrictions in England on July 19.

Worker shortage is forcing UK businesses to close as Covid cases spike

“The world of work continues to rebound robustly from the effects of the pandemic,” Athow said in a statement.

The unemployment rate fell 0.2 percentage points to 4.7%, according to the ONS. Athow said that there were no signs of redundancies starting to pick up ahead of the end of the government’s furlough program, which supports wages, at the end of next month.

Worker shortages could place a drag on the recovery, however. Some pubs and grocery stores had to close last month because of the number of employees required to quarantine after coming into contact with someone who had tested positive for Covid-19. 

The UK government has since scrapped this rule for people who are fully vaccinated, but the impact of the pandemic and Brexit has meant fewer EU citizens to fill jobs in industries such as retail, farming and logistics.

“Although the changes to self-isolation rules will help, with many firms facing a more deep-rooted squeeze on labor supply from the impact of Covid and Brexit, staff shortages may persistently weigh on economic activity,” head of economics at the British Chambers of Commerce, Suren Thiru said in a statement on Tuesday.

Rising inflation concerns

There are already signs that a shortage of workers is placing upward pressure on wages. According to the ONS, growth in average total pay excluding bonuses was 7.4% in the three months to June compared with the same period in 2020. 

Even after stripping out factors such as the fall in the number of lower-paid jobs, the ONS data suggest that annual wage inflation was running between 3.5% and 4.9% in June, according to Berenberg senior economist Kallum Pickering.

“It remains well above the mere 2% average rate from 2009-2019,” Pickering wrote in a research note. “With unemployment falling from an already low level and labor demand surging to well past previous record highs, the risks to the wage growth outlook look skewed to the upside,” he added.

Rising wage pressures come as businesses are already contending with higher costs in their supply chains from raw materials shortages and soaring shipping rates. 

“Together, these factors point to further inflation pressures ahead as firms try to pass on cost rises to consumers,” Pickering said. 

The Bank of England said earlier this month that it expects inflation to rise even further above its 2% target in the coming months and that it will set interest rates to ensure inflation returns to that level.

“We continue to look for the first rate hike in August 2022. But the strengthening inflation dynamic and strong recovery in domestic demand suggest the risks are tilted towards a hike even sooner that — perhaps as early as May 2022,” Pickering added.

#AceNewsDesk report ……Published: Aug.18: 2021:

Editor says …Sterling Publishing & Media Service Agency is not responsible for the content of external site or from any reports, posts or links, and can also be found here on Telegram: https://t.me/acenewsdaily all of our posts fromTwitter can be found here: https://acetwitternews.wordpress.com/ and all wordpress and live posts and links here: https://acenewsroom.wordpress.com/and thanks for following as always appreciate every like, reblog or retweet and free help and guidance tips on your PC software or need help & guidance from our experts AcePCHelp.WordPress.Com

Editor says …Sterling Publishing & Media Service Agency is not responsible for the content of external site or from any reports, posts or links, and can also be found here on Telegram: https://t.me/acenewsdaily all of our posts fromTwitter can be found here: https://acetwitternews.wordpress.com/ and all wordpress and live posts and links here: https://acenewsroom.wordpress.com/and thanks for following as always appreciate every like, reblog or retweet and free help and guidance tips on your PC software or need help & guidance from our experts AcePCHelp.WordPress.Com

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(LONDON) #Coronavirus ONS Report: #COVID19 Related deaths by ethnic group under revised ‘ Race Disparity Audit (RDA) ‘ since 2018 including socio-economic position, area context, access to housing and living arrangements across the U.K. updated Feb.07:2020: PDF Link Below: #AceHealthDesk reports

#AceHealthReport – May.11: Following a request by numbers of ethnic groups and organisations over BAME deaths of frontline #NHS and Social Care Workers ‘ and Public Health England (PHE) have commenced an investigation into reasons and causal affect behind them in the community:

#ONS Report: How ethnic groups vary across some of the social determinants of health: Last Update: 07/05/2020:

The revised Race Disparity Audit (RDA) published in March 2018 found disparities between ethnic groups in various aspects of public life, some of which were pronounced, influencing relative life chances and quality of life. A report by Public Health England showed that the Bangladeshi and Pakistani ethnicities stood out as having particularly poor health outcomes:

While the shared cultural practices associated with ethnic heritage is an important determinant of health, there are also important interconnections between ethnic group membership and other determinants of health such as:

  • socio-economic position
  • area context
  • access to housing
  • living arrangements

An important question in examining risk of coronavirus (COVID-19)-related death is how much variation can be explained independently by ethnicity and how much by variation in experience and intensity of disadvantage? As there is a social gradient in general mortality risk, it is important to illustrate how indicators of disadvantage are distributed across ethnic groups.

At the time of the 2011 Census, there was considerable variability between ethnic groups in the proportion of their respective populations assigned to the most advantaged Higher Managerial and Professional socio-economic class. For example, people with Indian ethnicity were twice as likely to be classified to this class than those with either Bangladeshi or Pakistani ethnicity. Those of Black or Mixed ethnicity had a smaller percentage of their respective populations assigned to this class than those with White ethnicity.

As occupation may change over time, since the 2011 UK Census an analysis of 2019 Annual Population Survey data suggested the Bangladeshi and Pakistani community has increased by approximately 17%, and the Black community by 19%. This is in contrast with the increase in the White population being under 1%. In all three of these groups, the percentage of the population in higher managerial and professional occupations has remained relatively constant, implying little social mobility since the census.

For those with no occupation information to classify from their census record, the Bangladeshi and Pakistani ethnic groups were the most likely to be classified as “never worked or long-term unemployed1, substantially higher than those of White, Indian or Chinese ethnicity.

Another indicator of social disadvantage is living in an overcrowded household (defined as having fewer bedrooms than needed to avoid undesirable sharing). Analysis of the English Housing Survey showed that between 2014 and 2017, around 679,000 (3%) of the estimated 23 million households in England were overcrowded; however, there were marked contrasts between ethnic groups. While only 2% of White British households experienced overcrowding, it was 30% of Bangladeshi households (the highest percentage), 16% of Pakistani households and 12% of Black households.

There is also a contrast in the propensity to live in a multi-family household. An unpublished analyses of Labour Force Survey data showed that in 2018, those with a Bangladeshi and Pakistani ethnicity were much more likely than any other ethnic group to live in a multi-family household, concurring with the overcrowded household contrast reported previously in this section.

In 2018 the percentage of economically active people who were unemployed also varied sizably by ethnicity. While 4% of the White and Indian ethnic populations were unemployed, it was 8% among those of Bangladeshi or Pakistani ethnicity and 9% of those with Black ethnicity.

Occupations involving close contact with the public are deemed to be a risk factor for COVID-19 infection. Figure 1 shows how ethnicities are distributed when working in occupations classified to the transport and drivers and operatives standard occupational classification sub-major group, which encompasses bus, coach and taxi drivers and those driving other types of industrial and agricultural vehicles.

Figure 1: A higher percentage of the workforce classified to the transport and drivers and operative sub-major group were from the Bangladeshi and Pakistani ethnicity group

Percentage of workforce classified to the transport and drivers and operatives sub-major group of the standard occupational classification 2010, UK, 2018 to 2019
Source: Annual Population Survey 2018 to 2019
Notes:
  1. Other ethnic group encompasses Asian other, Arab and other ethnic group categories in the classification.
  2. ‘Mixed’ encompasses White and Black Caribbean; White and Asian; White and Black African; and Other Mixed ethnic group categories in the classification.
  3. ‘Black’ encompasses Black Caribbean; Black African; and Black Other ethnic group categories in the classification.
Download this chart

Image .csv .xls

There is a noticeably greater propensity for those with a Bangladeshi and Pakistani ethnicity to be working in these occupations. In fact, these ethnicities were twice as likely as others to be working in such occupations. In contrast those classified to the Chinese ethnicity were least likely to be working in these jobs.

The brief overview in this section gives a flavour of the differences in the social determinants of health across ethnic groups, with those of Bangladeshi, Pakistani and Black ethnicities experiencing greater levels of social disadvantage than those of White, Indian or Chinese ethnicities.

Notes for: How ethnic groups vary across some of the social determinants of health:

  1. Never worked or long-term unemployed contains those aged 16 to 74 years who have never worked or are economically active and have not worked since 2009. The category excludes full-time students.

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4. Logistic regression method

By using logistic regression models, we can estimate whether the risk of dying from the coronavirus (COVID-19) is greater among Black, Asian and minority ethnic (BAME) groups than the White population, once we adjust for a range of geographical, demographic and socio-economic factors.

The dependent variable is a binary variable equal to one if the individual died from COVID-19 between 2 March 2020 and 10 April 2020, otherwise it is equal to zero. In our analytical dataset, we include all those who died from COVID-19 in this period and a weighted 1% random sample of those who did not. The regression estimates are weighted using the probability not to have migrated between 2011 and 2020.

We estimate separate models for males and females, as the risk of COVID-19 death differs markedly across gender. In our baseline model, we only adjust for age, using five-year age groups. We then adjust for geographical, demographic and socio-economic characteristics that are likely to influence the risk of dying from COVID-19 and differ across ethnic groups separately for males and females. These characteristics are retrieved from the 2011 Census and so may not accurately reflect people’s socio-economic conditions in 2020, especially among young people, whose circumstances are likely to have changed. However, the risk of dying from COVID-19 is very low among children and young adults. For older adults, who are less likely to experience social mobility, the measurement error may be less of a concern.

First, we adjust for geographical factors. The probability to be infected by COVID-19 is likely to vary by region of residence, with London being the most severely affected region in terms of COVID-19 related hospital admissions. BAME are also more likely to live in London and in urban areas generally compared with the White population. Therefore, we adjust for region of residence and whether the individual lives in a rural or urban area, using the Rural Urban Classification1.

Second, we adjust for level of deprivation of the area by adding the Index of Multiple Deprivation (IMD) 2010 decile of the postcode of the residence in our model. The IMD is an overall measure of deprivation based on factors such as:

  • income
  • employment
  • health
  • education
  • crime
  • living environment
  • access to housing within an area

A previous ONS publication showed that people living in more deprived areas are twice as likely to die from COVID-19 than those living in less deprived areas. As BAME are also more likely to live in more deprived areathan those of White ethnicity, it is important to account for area deprivation.

Third, we adjust for the household composition (living alone, family with no children, family with children, other) and country of birth (UK born, non-UK born). Household composition varies by ethnicity. For instance, only 17.0% of the Asian population live in a one-person household, compared with 30.9% among those of White ethnicity. Living in a household with larger numbers of people is likely to increase the risk of being infected by COVID-19. Since this likelihood varies by ethnicity, it is a possible mediator for the relationship between ethnicity and the risk of dying from COVID-19.

Fourth, we adjust for socio-economic characteristics retrieved from the 2011 Census, which are a proxy of the socio-economic status (SES) of the individuals. We include in our model the level of highest qualification (Degree, A-level or equivalent, GCSE or equivalent, no qualification), the National Statistics Socio-economic Classification (NS-SEC) of the household head, and household tenure (owned, privately or socially rented, or other). These measures of SES vary across ethnic groups. For instance, 10.0% of people with White ethnicity were in higher managerial and professional occupations, compared with 15.4% of people from the Indian ethnic group and 6.9% from the Black ethnic group.

Measures of SES are associated with health outcomes and mortality2, and so are likely to be associated with the risk of dying from COVID-19. SES could have an impact on the risk of infection and also on the risk of dying if infected. In further work, we plan to derive an indicator of whether anyone in the household works in a high-risk occupation, such as in health care or in the transport sector.

Finally, we adjust for some measures of health from the 2011 Census. We include in the model self-reported health (very good, good, fair, poor, very poor) and a variable indicating if the individual has an activity limiting health problem or disability. Existing evidence suggests that physical health, in particular obesity, has a strong effect on the risk of dying from COVID-19. Health status varies across ethnic groups. For instance, the proportion of individuals being overweight differs markedly across ethnic groups. 62.9% of the White British population is overweight or obese, compared with 72.8% of the Black ethnic group.

In Coronavirus-related deaths by ethnic group, England and Wales: 2 March 2020 to 10 April 2020 (Figure 4) we reported the odds ratios for the age-adjusted model and the fully adjusted model. In Figure 2 in this section we show how the odds ratios of dying from COVID-19 relative to the White population vary depending on the set of household and individual characteristics we adjust for. We report the corresponding model metrics in Table 1.

We find that adjusting for region of residence and the rural and urban classification improves the model fit and reduces substantially the odds ratios for all ethnic groups. Ethnic minority groups are also more likely to live in London and in an urban area compared with the White population. The probability to be infected by COVID-19 is likely to vary by region of residence and to be higher in more densely populated urban areas.

Adjusting for the IMD decile of the Lower layer Super Output Area (LSOA) of residence further reduces the odds ratios for all groups, albeit to a small extent. Adjusting for household composition and wider socio-economic status improves the model slightly but has little effect on the odds ratios for most groups. Adjusting for health as measured in the 2011 Census improves the model fit and also reduces the odds ratios for several groups, in particular the Bangladeshi and Pakistani ethnic group.

Figure 2: Risk of COVID-19 death by ethnic group, different specifications

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.png .xlsx

Men Women
Specification Area under the curve Deviance Pseudo R Squared Area under the curve Deviance Pseudo R Squared
Age 0.91 114764.44 0.16 0.91 81626.29 0.15
+ Region, urban/rural 0.92 113141.54 0.18 0.91 80599.39 0.16
+ IMD decile 0.92 112985.94 0.18 0.92 80414.48 0.16
+ Household composition 0.92 112867.37 0.18 0.92 80313.36 0.16
+ Socio-economic Status 0.92 112498.20 0.18 0.92 79944.46 0.17
+ Health 0.93 111577.83 0.19 0.93 78932.52 0.18
Download this table

.xlsx .csv

Notes for Logistic regression method:

  1. The Rural-Urban Classification categorises geographical areas on the basis of physical settlement and related characteristics into four urban and six rural classes.
  2. For more information see Glymour MM, Avendano M and Kawachi I (2014). Socioeconomic Status and Health, in: Berkman L, Kawachi I and Glymour M (Editors), Social Epidemiology (2nd edition., pages 17 to 62), Oxford University Press.

Full PDF Report Here: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/methodologies/coronavirusrelateddeathsbyethnicgroupenglandandwalesmethodology/pdf

#AceHealthDesk report …………..Published: May.11: 2020:

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#Brazil : ” High Demand on Power Supplies `During Low Rainfall ‘could `Spell Trouble’ during `World Cup’ in June”

#AceWorldNews says Several Brazilian states reported power outages Tuesday, as high demand coupled with worries over energy supplies during a time of low rainfall led national grid operator ONS to warn of “disruption” in the north, south-east and south of the country.
Media reports suggest around three million people across 11 states, including Rio de Janeiro, have seen supplies cut, according to AFP. ONS reported the cut lasted about 40 minutes before a gradual return to normal levels. High temperatures in the south contributed to a record-high day of demand on Monday.
Low rainfall, though, has “nothing to do with the demands of the system,” mines and energy ministry executive secretary Marcio Zimmermann insisted.
The power outage concerns some in Brazil given the nation is set to host World Cup action in June.

#afp, #brazil, #media, #ons, #rainfall, #rio-de-janeiro, #world-cup