COVID-19 Health Inequalities Monitoring for England (CHIME) tool
The CHIME tool brings together data relating to the direct impacts of COVID-19, such as on mortality rates and hospital admissions.
By presenting inequality breakdowns, including by age, sex, ethnic group, level of deprivation and region, the tool provides a single point of access in order to:
- show how inequalities have changed during the course of the pandemic and what the current cumulative picture is
- bring together data in one tool to enable users to access and utilise the intelligence more easily
- provide indicators with a consistent methodology across different datasets to facilitate understanding
- support users to identify and address inequalities within their areas and identify priority areas for recovery
The first release of this tool looks at hospital admissions and deaths related to COVID-19, with data split into different demographics to examine the impact of the pandemic on health inequalities.
Within this first release (20/05/2021), the following indicators are presented:
Admissions where COVID-19 was the primary reason for the patient being taken into hospital
- Monthly admission rates
- Cumulative admission rates
- Number of hospital admissions
Deaths involving COVID-19, where it was mentioned anywhere on the death certificate
- Monthly death rates
- Cumulative death rates
- Number of deaths
For each of these indicators, data are split into the following:
- England (persons only indicator)
- Deprivation deciles - England
- Deprivation deciles - England - Under 75s
- Deprivation deciles - Region
- Deprivation deciles - Region - Under 75s
- Ethnic groups - England
- Ethnic groups (detailed Asian) - England
- Ethnic groups (detailed Black) - England
- Ethnic groups - Region (not available for monthly indicators)
The work supplements the 'Disparities in the risk and outcomes of COVID-19' report, published in June 2020.
We are interested in your feedback on the tool. If you have any comments or suggested changes, please contact us.
The COVID-19 Health Inequalities Monitoring for England tool (CHIME) currently includes data on hospital admissions and mortality from COVID-19. It presents the cumulative picture for the pandemic to date and data by month, and includes breakdowns by region, sex, age group, ethnicity and deprivation.
The following indicators are included:
- Cumulative age-standardised hospital admission rate per 100,000 population where COVID-19 was the primary reason for admission between March 2020 and January 2021
- Monthly age-standardised hospital admission rates per 100,000 person-years
- Cumulative age-standardised mortality rates per 100,000 population for deaths involving COVID-19 between March 2020 and March 2021
- Monthly age-standardised hospital admission rates per 100,000 person-years
Trends over time
There were two peaks in monthly mortality and hospital admission rates, in April 2020 and January 2021, during the first and second waves of the pandemic. For England as a whole, the monthly mortality and hospital admission rates at the peak of the second wave were higher than the first wave. Data on hospital admissions for February are not yet available.
Age and sex
Across the course of the pandemic in England, cumulative hospital admission and mortality rates were higher for males than females. In the pandemic period presented to date, the mortality rate in males was 1.6 times higher than the rate for females and the hospital admission rate was 1.5 times higher.
Hospital admission and mortality rates increased with age, with the highest rates in those aged 85 and over. The mortality rate for people in this age group across the pandemic to date was 3.2 times higher than the next oldest group (people aged 75-84) and 10.8 times higher than people aged 65-74. This increase in mortality rates with age was steeper than that seen for hospital admissions.
In England as a whole, the monthly mortality and hospital admission rates at the peak of the second wave were higher than the first wave. For admissions this was true for every region of England, although in Yorkshire and the Humber the month with the highest rate was November 2020. For mortality, the picture varied by region. London and the northern regions had a higher monthly rate at the peak of the first wave than the second, and in the West Midlands the two peaks were similar. All other regions had higher mortality at the peak of the second wave. These are the general patterns and there are some differences by sex.
Across the pandemic period to date, the impact, in terms of hospital admissions and deaths, has been greatest in London and lowest in the South West. London had higher mortality and hospital admission rates than every other region in England at the peak of both the first and second waves. However, during November 2020, an increase in hospital admission and mortality rates in the northern and midlands regions meant they were higher than London at this point. This reflects the difference in timing of the second wave across England.
Across the pandemic period to date, the cumulative mortality and hospital admission rates for the White ethnic group were lower than for all other ethnic groups. The highest rates were in the Black and Asian groups. Among the Black and Asian groups, the Other Black, Bangladeshi and Pakistani groups had the highest rates. The hospital admission rate for the Black and Asian groups was three times higher than the rate for the White group. The mortality rate for the Black and Asian group was two times higher than the White group.
This pattern by ethnicity varied considerably across regions of England. The numbers in each group are small in some regions which makes comparison difficult.
In England as a whole, the Black group had the highest monthly mortality rate at the peak of the first wave, whereas the Asian group had the highest monthly rate at the peak of the second wave. This is also true for hospital admissions although the difference at the peak of the second wave is small. Among the Asian group, the Bangladeshi group had a particularly high admission and mortality rate at the peak of the second wave which was not the case in the first, and may account for this difference between waves.
Inequality between the Black and White groups was greater at the peak of the first wave. At the peak of the first wave the admission rate in the Black group was 3.9 times higher than the White group, but was 3.2 times higher at the peak of the second wave. For mortality the rate in the Black group was 2.9 times higher in the peak of the first wave and 2.1 times in the second.
However, inequality between the Asian and White groups was greater at the peak of the second wave. The admission rate in the Asian group was 2.8 times higher than the White group at the peak of the first wave and increased to 3.3 times higher. The mortality rate was 2.1 times higher at the peak of the first wave and 2.3 times higher in the second.
There was a gradient in hospital admission and mortality rates by level of deprivation: the impact of the pandemic to date increased with each increase in level of deprivation. Across the pandemic to date, the cumulative admission rate for the most deprived in England was 2.8 times the rate for the least deprived and the mortality rate over this period was 2.4 times higher.
This gradient by deprivation is seen across most regions, but there is some variation in the pattern. For example, in the South West the cumulative mortality rate in the most deprived was much higher than all other deprivation groups.
Inequalities by deprivation were slightly lower in the peak of the second wave than the first, however in November 2020, there was an increase in mortality and hospital admission rates in the most deprived decile which meant it was much higher than the other deciles at this time point. This pattern was observed in both males and females and coincided with the increase in the northern and midlands regions of England at this time.
How to use this tool
The tab 'Data' provides visualisations of selected indicators by different breakdowns and their trends over time.
- Select the theme, eg deaths or hospital admissions.
- Select the indicator to display in the 'Indicator' drop down.
- Select the dimension of inequality you would like to display from the ‘Breakdown’ drop down. The dashboard will populate with the selected data.
- Some breakdowns can be further broken down by sex/region by selecting buttons displayed on the chart.
- Navigate between viewing charts, data tables and metadata using the tabs in each theme.
- To see a single variable on a chart, such as a particular ethnic group or deprivation decile, click on the variable name in the legend.
- To access our companion tool on the Wider Impacts of COVID-19 on Health, click on the 'Wider Impacts of COVID-19 - WICH tool' tab and follow the link.
Wider Impacts of COVID-19 on Health (WICH) monitoring tool
The Wider Impacts of COVID-19 on Health (WICH) monitoring tool is designed to allow you to explore the indirect effects of the COVID-19 pandemic on the population's health and wellbeing. WICH presents a range of health and wellbeing metrics in interactive plots that can be broken down to show differences between groups - for example, you can explore grocery purchasing habits by region or social class. WICH is updated monthly and may include the addition of new metrics as they become available.
A range of other PHE analytical tools are available here.