Official Statistics

Quality and methodology information: Heat mortality monitoring reports

Published 3 April 2025

Applies to England

About this report

This report explains the quality and methodology information (QMI) relevant to the ‘Heat mortality monitoring reports’ official statistics published by the UK Health Security Agency (UKHSA).

This QMI report helps users understand the strengths and limitations of these statistics, ensuring UKHSA is compliant with the quality standards stated in the Code of Practice for Statistics. The report explains:

• The strengths and limitations of the data used to produce the statistics
• The methods used to produce the statistics
• The quality of the statistical outputs

About the statistics

Hot weather can cause people to become unwell through dehydration, heat exhaustion and heatstroke, and can increase the risk of heart attack, stroke, lung problems and other diseases. This can lead to increased deaths. During the summer, the UKHSA and the Met Office work together to issue Heat Health Alerts (HHAs) if the weather is hot enough that it has the potential to affect people’s health.

Heat mortality monitoring reports provide information on deaths observed during heat episodes each year to inform public health actions. The statistics show the number of heat-associated deaths and years of life lost (YLL), broken down by age, sex, region, local resilience forum (LRF) area, cause of death and place of death. In addition, the report compares observed mortality with modelled predictions based on the temperature-mortality relationship in previous summers.

The annual heat mortality monitoring reports have been published as official statistics for the first time for heat episodes in 2024, demonstrating that they are produced in line with the standards of trustworthiness, quality and value in the Code of Practice for Statistics. The previous reports for 2016 to 2023 were published by the UK Health Security Agency (UKHSA) and Public Health England.

Geographical coverage: England

Publication frequency: Annual

Changes to this document

3 April 2025: QMI report first published

Contact

Lead analyst: Mo Davies

Contact information: extremeevents@ukhsa.gov.uk

Suitable data sources

Statistics should be based on the most appropriate data to meet intended uses.

This section describes the data used to produce the statistics.

Data sources

Data on deaths is derived from the Office for National Statistics (ONS) death registrations data. Deaths with a mention of COVID-19 on the death certificate are removed. For calculations of observed deaths in summer 2024, provisional weekly registrations data for 2024 onwards is used. Final annual registrations data for 2019 to 2023 is also used in the statistical model for previous years.

Heat episodes are defined as an amber HHA in at least one region or the mean Central England Temperature (CET) being at least 20°C. One day either side is also included; an extra day can also be included if merited by a sudden change in temperature. UKHSA’s logging data from the Weather Health Alerting system is used to identify amber or red HHA periods. Data on the Central England Temperature is obtained from the Met Office Hadley Centre data set.

Daily mean temperature data from the Met Office at regional level is used in the statistical model. This is obtained through the UKHSA Environmental Public Health Surveillance System.

The latest available ONS mid-year population estimates are used to calculate rates per million population. The latest available ONS life tables for England are used in the calculation of years of life lost (YLL). 

Data quality

The data that we use to produce statistics must be fit for purpose. Poor quality data can cause errors and can hinder effective decision making.

We have assessed the quality of the source data against the data quality dimensions in the Government Data Quality Framework.

This assessment covers the quality of the data that was used to produce the statistics, not the quality of the final statistical outputs. The quality summary section below explains the quality of the final statistical outputs.

Strengths and limitations of the deaths data

The strengths of the data include:

• a comprehensive record of deaths occurring in England because the registration of deaths is mandatory,
• review of deaths data carried out by the ONS on a provisional basis throughout the year, as well as on a final basis annually,
• a high level of completion of all required information for analysis because death certificates have required fields and
• using international standards to code underlying causes of death.

A limitation of the data includes death registration delays, particularly for deaths referred to a coroner, meaning some deaths which occurred in 2024 will not be included in the analysis in spring 2025.

Summary

The ONS deaths data is the most appropriate source of data for the statistics.

Accuracy

Accuracy is about the degree to which the data reflects the real world. This can refer to correct names, addresses or represent factual and up-to-date data.

The ONS Mortality statistics in England and Wales QMI report gives information on accuracy and validation checks performed.

Completeness

Completeness describes the degree to which records are present.

For a data set to be complete, all records are included, and the most important data is present in those records. This means that the data set contains all the records that it should and all essential values in a record are populated.

Completeness is not the same as accuracy as a full data set may still have incorrect values.

Death certificates contain several mandatory fields, and so the data used in this report for age, sex, place of death, cause of death and geographical area of death is highly complete. Age and sex  are 100% complete in provisional data. Geographical area and cause of death are over 99% complete, and place of death is over 98% complete.

Uniqueness

Uniqueness describes the degree to which there is no duplication in records. This means that the data contains only one record for each entity it represents, and each value is stored once.

Some fields, such as National Insurance number, should be unique. Some data is less likely to be unique, for example geographical data such as town of birth.

Checks are performed by the ONS to identify and remove duplicate death registrations.

Consistency

Consistency describes the degree to which values in a data set do not contradict other values representing the same entity. For example, a mother’s date of birth should be before her child’s.

Data is consistent if it doesn’t contradict data in another data set. For example, the date of birth recorded for the same person in 2 different data sets should be the same.

ONS deaths data reflects information as recorded on death certificates based on information provided by the informant, medical examiner and coroner (if applicable). Data is not required to match with data on other records. The ONS user guide to mortality statistics gives more information on how death certificates are completed.

Timeliness

Timeliness describes the degree to which the data is an accurate reflection of the period that it represents, and that the data and its values are up to date.

Some data, such as date of birth, may stay the same whereas some, such as income, may not.

Data is timely if the time lag between collection and availability is appropriate for the intended use.

Deaths are subject to registration delays, meaning that deaths by date of occurrence are always somewhat incomplete. The ONS have published further information on the impact of registration delays on mortality statistics in England and Wales.

Based on historic patterns in death registration delays, it is expected that when completing analysis in March 2025, approximately 97% of deaths that occurred in summer 2024 have been registered.

Deaths referred to coroners are subject to longer registration delays, meaning there is likely to be a higher proportion of missing deaths among deaths where the underlying cause of death is in the category ‘External causes’.

Validity

Validity describes the degree to which the data is in the range and format expected. For example, date of birth does not exceed the present day and is within a reasonable range.

Valid data is stored in a data set in the appropriate format for that type of data. For example, a date of birth is stored in a date format rather than in plain text.

The ONS mortality statistics in England and Wales QMI report gives information on accuracy and validation checks performed.

Sound methods

Statistical outputs should be produced using appropriate methods and recognised standards.

This section describes how the statistics were produced and quality assured.

Dataset production

Method for calculating observed heat-associated mortality

In the report for 2024, data on deaths was extracted on 17th March 2025 from the ONS deaths data set, including death registrations up to 11th March 2025. Deaths with a mention of COVID-19 on the death certificate were removed.

Heat episodes were identified based on the definition given above. The 28-day baseline period for each heat episode was then identified, comprising the 14 non-episode days before and 14 non-episode days after. The estimate of observed heat-associated mortality for each heat episode was calculated as the difference between average daily deaths during the heat episode and average daily deaths during the baseline period, multiplied by the number of days in the heat episode.

The 95% confidence intervals were calculated based on the standard error obtained from assuming daily deaths came from a Poisson distribution with an adjustment for overdispersion. The overdispersion used was common for all analyses and derived by comparing the within-month variance in daily deaths to the within-month mean daily deaths on non-heat-episode days across the summer.

To calculate an overall figure for the summer, the same method was applied using all heat episode days and all baseline days together.

Methods for breakdowns of observed heat-associated mortality

The number of heat-associated deaths was broken down by region, LRF, age group, sex, place of death and cause of death. This was done by applying the method for observed heat-associated mortality described above to each subset of the data.

Grouping by region and LRF was done based on the Lower Super Output Area (LSOA) of the location of death, aggregated to region and LRF boundaries. Rates per million population were calculated using ONS mid-year population estimates by Local Authority, aggregated to region and LRF boundaries.

Grouping by age was done based on the age at death as recorded on the death certificate. This is based on Grouping B of the Government Analysis Function harmonised standard for age groups, but with an additional breakdown of the ’75 plus’ group into ’75 to 84’ and ’85 plus’. The additional detail for older age groups is used because heat-associated mortality is greatest for older age groups. Greater uncertainty with small numbers of deaths does not allow using smaller groupings below the age of 65. Rates per million population were calculated using ONS mid-year population estimates aggregated to the same groups.

Grouping by sex was done based on sex as recorded on the death certificate. This is the sex as reported by the informant to the registrar, and may differ from legal sex, sex as recorded in health records, or gender identity. Deaths with unknown or other sex recorded were excluded from the breakdown by sex due to small numbers. Rates per million population were calculated using ONS mid-year population estimates by sex.

Grouping by place of death was done based on the coding of communal establishments on death certificates. These were aggregated to the five statistical categories used by the National End of Life Care Intelligence Network: ‘Own residence’, ‘Hospital’, ‘Care home’, ‘Hospice’, and ‘Other places’. Deaths with unknown place were grouped with ‘Other places’. Rates per million population are not applicable to grouping by place of death. Percentages above baseline were calculated as the number of heat-associated deaths as a percentage of baseline deaths in each group.

Grouping by cause of death was done using the underlying cause of death in the ONS deaths data set. This is determined by internationally standardised rules, the Multi-causal and Uni-causal Selection Engine [MUSE] 5.8, for assigning an underlying cause of death based on all causes of death recorded. More information is available in the ONS user guide to mortality statistics. Causes were aggregated into the policy-relevant groups in the report using the following International Classification of Diseases, Tenth Revision (ICD-10) codes: C00 to C97 for cancer, F01, F03 and G30 for Dementia and Alzheimer’s, I00 to I99 for all circulatory diseases, J09 to J18 for influenza and pneumonia, J40 to J47 for chronic lower respiratory diseases and S00 to Y98 for external causes. Deaths with any other cause or unknown cause were grouped as ‘All other’. Rates per million population are not applicable to grouping by cause. Percentages above baseline were calculated as the number of heat-associated deaths as a percentage of baseline deaths in each group.

Method for calculating observed heat-associated YLL

YLL is a measure of premature mortality based on average remaining life expectancy at age of death. It is only calculated for those age groups where there are statistically significant heat-associated deaths over the course of the summer. In the report for 2024, these were people aged 75 to 84 and people aged 85 and over only. Average remaining life expectancy for each of these age groups was calculated using the latest available ONS life tables for England, stratified by sex. The YLL was calculated by multiplying the number of deaths by the average remaining life expectancy for each sex-age group cohort, then aggregated by age group.

Method for statistical modelling of heat-associated mortality

Estimates of modelled mortality were obtained from a statistical model based on the observed regional temperature-mortality relationships in recent summers.

Mortality data for deaths occurring 2019 to 2023 was obtained from the ONS (using final annual registrations data for deaths registered 2019 to 2023, and provisional weekly registrations data for deaths registered since the end of 2023), while excluding deaths with a mention of COVID-19. Temperature data was obtained from the Met Office, using a latitude-longitude grid at 0.1 degree resolution to derive daily mean temperature data at regional level for 2019 to 2024.

Temperature and mortality data are joined based on date and region. A quasi-Poisson regression model is fit using the distributed lag non-linear modelling framework, to estimate the relative risk of mortality at each temperature from 2019 to 2023. This model is applied to the actual temperatures in summer 2024 to obtain modelled predictions of heat-associated mortality in each episode.

Quality assurance

The report is produced using R. The production of the figures and the supplementary data tables has been automated, reducing the risk of human error. The code is version-controlled using Git and follows Reproducible Analytical Pipelines principles. Further quality assurance is done after running the code. Interim and final outputs are sense-checked, and figures and tables are compared with those in previous reports by at least 2 members of the production team. 

Confidentiality and disclosure control

Personal and confidential data is collected, processed, and used in accordance with the UKHSA Privacy Notice. All UKHSA staff with access to personal or confidential information must complete mandatory information governance training, which must be refreshed every year. Information is stored on computer systems that are kept up-to-date and regularly tested to make sure they are secure and protected from viruses and hacking. UKHSA staff do not store data on their own laptops or computers. Instead, data is stored centrally on UKHSA servers.

Data presented in the heat mortality monitoring report does not relate to individuals. The figures reported are the difference between the number of deaths during heat episodes and the number of deaths outside of heat episodes. There is no risk of including data which identifies an individual.

Geography

All information in the report is presented for England overall. Some information is also provided at regional level and at LRF area level.

Quality summary

Quality means that statistics fit their intended uses, are based on appropriate data and methods, and are not materially misleading.

Quality requires skilled professional judgement about collecting, preparing, analysing, and publishing statistics and data in ways that meet the needs of people who want to use the statistics.

This section assesses the statistics against the European Statistical System dimensions of quality.

Relevance

Relevance is the degree to which the statistics meet user needs in both coverage and content.

The statistics are relevant for public health professionals and across government. Results are used for national risk assessment such as the National Risk Register for heatwaves, and to develop understanding of the most vulnerable populations in heat episodes. This informs guidance and public health action to protect vulnerable groups.   

Adding more granular geographical breakdowns in the report for 2024 and onwards will improve relevance for local public health teams.  

The report forms part of meeting UKHSA’s commitments under the UK Third National Adaptation Programme. Through reporting on heat-associated deaths and years of life lost, it supports monitoring of Goals 1 and 2 of UKHSA’s Adverse Weather and Health Plan for England. 

Accuracy and reliability

Accuracy is the proximity between an estimate and the unknown true value. Reliability is the closeness of early estimates to subsequent estimated values.

Heat-associated deaths can potentially be underestimated due to registration delays. In the report, for heat episodes in 2024 onwards, we publish a final report only once mortality data is sufficiently complete. In that case, statistics for 2024 were sufficiently complete to be published in April 2025.

There is some uncertainty in the figures as heat-associated deaths cannot be measured directly but only estimated through comparing heat and non-heat episodes. We therefore report 95% confidence intervals around estimates. 

Timeliness and punctuality

Timeliness refers to the time gap between publication and the reference period. Punctuality refers to the gap between planned and actual publication dates.

The heat mortality report is published in the spring, approximately 6 months after the end of the reference period, 1 June to 30 September of the previous year). This is timely as it is before the beginning of the new HHA season and allows time for the results of the report to inform preparedness and planning for the next summer.

The annual reports are official statistics and are pre-announced at least 28 days in advance. Provisional publication dates for the year ahead are pre-announced online in December and can be found on the UKHSA release calendar.

Accessibility and clarity

Accessibility is the ease with which users can access the data, also reflecting the format in which the data are available and the availability of supporting information. Clarity refers to the quality and sufficiency of the metadata, illustrations and accompanying advice.

Tables and visualisations in the report meet accessibility standards.

Coherence and comparability

Coherence is the degree to which data that are derived from different sources or methods, but refer to the same topic, are similar. Comparability is the degree to which data can be compared over time and domain.

The report has largely followed the same structure since the first 2016 report (published 2018) in providing an assessment of heat-associated mortality. Terminology has, however, changed to avoid confusion with other mortality statistics produced across government. Heat-associated mortality was referred to as “excess mortality” until the 2022 report (published 2023) and since the 2023 report (published 2024) has now been changed to “heat-associated mortality” to avoid confusion with the ONS’s definition of “excess mortality”.    

Definitions and methods for the calculation of observed mortality are consistent in the 2020 report onwards.

A different method was used in the 2016 to 2019 reports where deaths during heat episodes were compared to deaths on the same dates in the previous 5 years instead of the 14 days before and 14 days after the heat episode. This method changed for the 2020 report due to the COVID-19 pandemic’s impact on mortality.

New elements have been introduced to the report over time. Comparison with modelled mortality was introduced in the 2022 report onwards. Small changes were made to the modelling method in the 2023 report. Firstly, for 2023 the temperature-mortality relationship was modelled at regional level and aggregated to England level. Secondly, for the 2023 report the model was fit using the previous five years excluding the current year while the model used the latest five years including the current year for the 2022 report.  

The calculation of YLL and a breakdown of deaths by sex were introduced from the 2023 report onwards. Breakdowns by cause of death, place of death and LRF area were introduced for the 2024 report onwards.

For the 2024 report, the data source for the observed mortality changed from General Registry Office deaths to ONS mortality data. This should not have a significant effect on comparability.

In 2023, the ONS produced a one-off experimental statistics on climate-related mortality 1988 to 2022. The ONS report uses a statistical model to estimate mortality over that period assuming consistent relationship between temperature and mortality across each year. Conversely, the UKHSA report uses the mortality data in a given summer to directly estimate observed heat-associated mortality each year and compares this with predictions by a statistical model to assess changes over time.

Uses and users

Users of statistics and data should be at the centre of statistical production, and statistics should meet user needs.

This section explains how the statistics are used, and how we understand user needs.

Appropriate use of the statistics     

These statistics can be used to:

• monitor national annual trends in heat episode days, heat-associated deaths and heat-associated years of life lost,
• compare heat-associated deaths between different areas, population groups, settings and causes,
• identify heat episodes which had more or fewer heat-associated deaths than predicted by statistical modelling and
• monitor progress against the goals of the UKHSA Adverse Weather and Health Plan to reduce mortality and premature mortality related to adverse weather.

Known users

Public health and emergency planning professionals, at national, regional and local levels.

UK Government bodies involved in monitoring of climate change adaptation.

User engagement

We are running a user survey to gather feedback on this publication.

The heat mortality monitoring reports were included in the joint consultation on health and social care statistical outputs which ran from December 2023 to March 2024. We responded to all feedback received and the joint consultation outcome was published in 2024.

We also informally collect and review user feedback. Our user engagement activities include: 

• stakeholder webinars such as annual summer preparedness and winter preparedness,
• reviews of queries received by the Extreme Events and Health Protection team from stakeholders and
• stakeholder workshops on climate-health metrics development run by the UKHSA Centre for Climate and Health Security.

Related statistics

UKHSA has published past annual heat mortality monitoring reports and continues to report on weekly all-cause mortality surveillance.Other assessments of mortality include the number of weekly deaths registered in England and Wales which is published weekly by the ONS.

The Office for Health Improvement and Disparities also produces the Excess mortality within England report, which provides estimates of expected deaths by month of registration for population subgroups and by cause of death.
The different methods used in the UK for mortality assessment, and their varied purposes, are discussed in more detail in Measuring excess mortality: a guide to the main reports.

In 2023, the ONS also published experimental statistics on climate-related mortality in England and Wales, 1988 to 2022.