Adjusting expected deaths for mortality displacement during the COVID-19 pandemic: a model based counterfactual approach at the level of individuals.

BACKGROUND: Near-real time surveillance of excess mortality has been an essential tool during the COVID-19 pandemic. It remains critical for monitoring mortality as the pandemic wanes, to detect fluctuations in the death rate associated both with the longer-term impact of the pandemic (e.g. infection, containment measures and reduced service provision by the health and other systems) and the responses that followed (e.g. curtailment of containment measures, vaccination and the response of health and other systems to backlogs). Following the relaxing of social distancing regimes and reduction in the availability of testing, across many countries, it becomes critical to measure the impact of COVID-19 infection. However, prolonged periods of mortality in excess of the expected across entire populations has raised doubts over the validity of using unadjusted historic estimates of mortality to calculate the expected numbers of deaths that form the baseline for computing numbers of excess deaths because many individuals died earlier than they would otherwise have done: i.e. their mortality was displaced earlier in time to occur during the pandemic rather than when historic rates predicted. This is also often termed "harvesting" in the literature. METHODS: We present a novel Cox-regression-based methodology using time-dependent covariates to estimate the profile of the increased risk of death across time in individuals who contracted COVID-19 among a population of hip fracture patients in England (N = 98,365). We use these hazards to simulate a distribution of survival times, in the presence of a COVID-19 positive test, and then calculate survival times based on hazard rates without a positive test and use the difference between the medians of these distributions to estimate the number of days a death has been displaced. This methodology is applied at the individual level, rather than the population level to provide a better understanding of the impact of a positive COVID-19 test on the mortality of groups with different vulnerabilities conferred by sociodemographic and health characteristics. Finally, we apply the mortality displacement estimates to adjust estimates of excess mortality using a "ball and urn" model. RESULTS: Among the exemplar population we present an end-to-end application of our methodology to estimate the extent of mortality displacement. A greater proportion of older, male and frailer individuals were subject to significant displacement while the magnitude of displacement was higher in younger females and in individuals with lower frailty: groups who, in the absence of COVID-19, should have had a substantial life expectancy. CONCLUSION: Our results indicate that calculating the expected number of deaths following the first wave of the pandemic in England based solely on historical trends results in an overestimate, and excess mortality will therefore be underestimated. Our findings, using this exemplar dataset are conditional on having experienced a hip fracture, which is not generalisable to the general population. Fractures that impede mobility in the weeks that follow the accident/surgery considerably shorten life expectancy and are in themselves markers of significant frailty. It is therefore important to apply these novel methods to the general population, among whom we anticipate strong patterns in mortality displacement - both in its length and prevalence - by age, sex, frailty and types of comorbidities. This counterfactual method may also be used to investigate a wider range of disruptive population health events. This has important implications for public health monitoring and the interpretation of public health data in England and globally.

The changing health needs of the UK population.

The demographics of the UK population are changing and so is the need for health care. In this Health Policy, we explore the current health of the population, the changing health needs, and future threats to health. Relative to other high-income countries, the UK is lagging on many health outcomes, such as life expectancy and infant mortality, and there is a growing burden of mental illness. Successes exist, such as the striking improvements in oral health, but inequalities in health persist as well. The growth of the ageing population relative to the working-age population, the rise of multimorbidity, and persistent health inequalities, particularly for preventable illness, are all issues that the National Health Service (NHS) will face in the years to come. Meeting the challenges of the future will require an increased focus on health promotion and disease prevention, involving a more concerted effort to understand and tackle the multiple social, environmental, and economic factors that lie at the heart of health inequalities. The immediate priority of the NHS will be to mitigate the wider and long-term health consequences of the COVID-19 pandemic, but it must also strengthen its resilience to reduce the impact of other threats to health, such as the UK leaving the EU, climate change, and antimicrobial resistance.

Changes in health in the countries of the UK and 150 English Local Authority areas 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016.

BACKGROUND: Previous studies have reported national and regional Global Burden of Disease (GBD) estimates for the UK. Because of substantial variation in health within the UK, action to improve it requires comparable estimates of disease burden and risks at country and local levels. The slowdown in the rate of improvement in life expectancy requires further investigation. We use GBD 2016 data on mortality, causes of death, and disability to analyse the burden of disease in the countries of the UK and within local authorities in England by deprivation quintile. METHODS: We extracted data from the GBD 2016 to estimate years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), and attributable risks from 1990 to 2016 for England, Scotland, Wales, Northern Ireland, the UK, and 150 English Upper-Tier Local Authorities. We estimated the burden of disease by cause of death, condition, year, and sex. We analysed the association between burden of disease and socioeconomic deprivation using the Index of Multiple Deprivation. We present results for all 264 GBD causes of death combined and the leading 20 specific causes, and all 84 GBD risks or risk clusters combined and 17 specific risks or risk clusters. FINDINGS: The leading causes of age-adjusted YLLs in all UK countries in 2016 were ischaemic heart disease, lung cancers, cerebrovascular disease, and chronic obstructive pulmonary disease. Age-standardised rates of YLLs for all causes varied by two times between local areas in England according to levels of socioeconomic deprivation (from 14 274 per 100 000 population [95% uncertainty interval 12 791-15 875] in Blackpool to 6888 [6145-7739] in Wokingham). Some Upper-Tier Local Authorities, particularly those in London, did better than expected for their level of deprivation. Allowing for differences in age structure, more deprived Upper-Tier Local Authorities had higher attributable YLLs for most major risk factors in the GBD. The population attributable fractions for all-cause YLLs for individual major risk factors varied across Upper-Tier Local Authorities. Life expectancy and YLLs have improved more slowly since 2010 in all UK countries compared with 1990-2010. In nine of 150 Upper-Tier Local Authorities, YLLs increased after 2010. For attributable YLLs, the rate of improvement slowed most substantially for cardiovascular disease and breast, colorectal, and lung cancers, and showed little change for Alzheimer's disease and other dementias. Morbidity makes an increasing contribution to overall burden in the UK compared with mortality. The age-standardised UK DALY rate for low back and neck pain (1795 [1258-2356]) was higher than for ischaemic heart disease (1200 [1155-1246]) or lung cancer (660 [642-679]). The leading causes of ill health (measured through YLDs) in the UK in 2016 were low back and neck pain, skin and subcutaneous diseases, migraine, depressive disorders, and sense organ disease. Age-standardised YLD rates varied much less than equivalent YLL rates across the UK, which reflects the relative scarcity of local data on causes of ill health. INTERPRETATION: These estimates at local, regional, and national level will allow policy makers to match resources and priorities to levels of burden and risk factors. Improvement in YLLs and life expectancy slowed notably after 2010, particularly in cardiovascular disease and cancer, and targeted actions are needed if the rate of improvement is to recover. A targeted policy response is also required to address the increasing proportion of burden due to morbidity, such as musculoskeletal problems and depression. Improving the quality and completeness of available data on these causes is an essential component of this response. FUNDING: Bill & Melinda Gates Foundation and Public Health England.

Changes in health in England, with analysis by English regions and areas of deprivation, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

BACKGROUND: In the Global Burden of Disease Study 2013 (GBD 2013), knowledge about health and its determinants has been integrated into a comparable framework to inform health policy. Outputs of this analysis are relevant to current policy questions in England and elsewhere, particularly on health inequalities. We use GBD 2013 data on mortality and causes of death, and disease and injury incidence and prevalence to analyse the burden of disease and injury in England as a whole, in English regions, and within each English region by deprivation quintile. We also assess disease and injury burden in England attributable to potentially preventable risk factors. England and the English regions are compared with the remaining constituent countries of the UK and with comparable countries in the European Union (EU) and beyond. METHODS: We extracted data from the GBD 2013 to compare mortality, causes of death, years of life lost (YLLs), years lived with a disability (YLDs), and disability-adjusted life-years (DALYs) in England, the UK, and 18 other countries (the first 15 EU members [apart from the UK] and Australia, Canada, Norway, and the USA [EU15+]). We extended elements of the analysis to English regions, and subregional areas defined by deprivation quintile (deprivation areas). We used data split by the nine English regions (corresponding to the European boundaries of the Nomenclature for Territorial Statistics level 1 [NUTS 1] regions), and by quintile groups within each English region according to deprivation, thereby making 45 regional deprivation areas. Deprivation quintiles were defined by area of residence ranked at national level by Index of Multiple Deprivation score, 2010. Burden due to various risk factors is described for England using new GBD methodology to estimate independent and overlapping attributable risk for five tiers of behavioural, metabolic, and environmental risk factors. We present results for 306 causes and 2337 sequelae, and 79 risks or risk clusters. FINDINGS: Between 1990 and 2013, life expectancy from birth in England increased by 5·4 years (95% uncertainty interval 5·0-5·8) from 75·9 years (75·9-76·0) to 81·3 years (80·9-81·7); gains were greater for men than for women. Rates of age-standardised YLLs reduced by 41·1% (38·3-43·6), whereas DALYs were reduced by 23·8% (20·9-27·1), and YLDs by 1·4% (0·1-2·8). For these measures, England ranked better than the UK and the EU15+ means. Between 1990 and 2013, the range in life expectancy among 45 regional deprivation areas remained 8·2 years for men and decreased from 7·2 years in 1990 to 6·9 years in 2013 for women. In 2013, the leading cause of YLLs was ischaemic heart disease, and the leading cause of DALYs was low back and neck pain. Known risk factors accounted for 39·6% (37·7-41·7) of DALYs; leading behavioural risk factors were suboptimal diet (10·8% [9·1-12·7]) and tobacco (10·7% [9·4-12·0]). INTERPRETATION: Health in England is improving although substantial opportunities exist for further reductions in the burden of preventable disease. The gap in mortality rates between men and women has reduced, but marked health inequalities between the least deprived and most deprived areas remain. Declines in mortality have not been matched by similar declines in morbidity, resulting in people living longer with diseases. Health policies must therefore address the causes of ill health as well as those of premature mortality. Systematic action locally and nationally is needed to reduce risk exposures, support healthy behaviours, alleviate the severity of chronic disabling disorders, and mitigate the effects of socioeconomic deprivation. FUNDING: Bill & Melinda Gates Foundation and Public Health England.

Evidence for Health II: Overcoming barriers to using evidence in policy and practice.

Even the highest quality evidence will have little impact unless it is incorporated into decision-making for health. It is therefore critical to overcome the many barriers to using evidence in decision-making, including (1) missing the window of opportunity, (2) knowledge gaps and uncertainty, (3) controversy, irrelevant and conflicting evidence, as well as (4) vested interests and conflicts of interest. While this is certainly not a comprehensive list, it covers a number of main themes discussed in the knowledge translation literature on this topic, and better understanding these barriers can help readers of the evidence to be more savvy knowledge users and help researchers overcome challenges to getting their evidence into practice. Thus, the first step in being able to use research evidence for improving population health is ensuring that the evidence is available at the right time and in the right format and language so that knowledge users can take the evidence into consideration alongside a multitude of other factors that also influence decision-making. The sheer volume of scientific publications makes it difficult to find the evidence that can actually help inform decisions for health. Policymakers, especially in low- and middle-income countries, require context-specific evidence to ensure local relevance. Knowledge synthesis and dissemination of policy-relevant local evidence is important, but it is still not enough. There are times when the interpretation of the evidence leads to various controversies and disagreements, which act as barriers to the uptake of evidence. Research evidence can also be influenced and misused for various aims and agendas. It is therefore important to ensure that any new evidence comes from reliable sources and is interpreted in light of the overall body of scientific literature. It is not enough to simply produce evidence, nor even to synthesize and package evidence into a more user-friendly format. Particularly at the policy level, political savvy is also needed to ensure that vested interests do not undermine decisions that can impact the health of individuals and populations.

Evidence for Health I: Producing evidence for improving health and reducing inequities.

In an ideal world, researchers and decision-makers would be involved from the outset in co-producing evidence, with local health needs assessments informing the research agenda and research evidence informing the actions taken to improve health. The first step in improving the health of individuals and populations is therefore gaining a better understanding of what the main health problems are, and of these, which are the most urgent priorities by using both quantitative data to develop a health portrait and qualitative data to better understand why the local population thinks that addressing certain health challenges should be prioritized in their context. Understanding the causes of these health problems often involves analytical research, such as case-control and cohort studies, or qualitative studies to better understand how more complex exposures lead to specific health problems (e.g. by interviewing local teenagers discovering that watching teachers smoke in the school yard, peer pressure, and media influence smoking initiation among youth). Such research helps to develop a logic model to better map out the proximal and distal causes of poor health and to determine potential pathways for intervening and impacting health outcomes. Rarely is there a single 'cure' or stand-alone intervention, but rather, a continuum of strategies are needed from diagnosis and treatment of patients already affected, to disease prevention, health promotion and addressing the upstream social determinants of health. Research for developing and testing more upstream interventions must often go beyond randomized controlled trials, which are expensive, less amenable to more complex interventions, and can be associated with certain ethical challenges. Indeed, a much neglected area of the research cycle is implementation and evaluation research, which often involves quasi-experimental research study designs as well as qualitative research, to better understand how to derive the greatest benefit from existing interventions and ways of maximizing health improvements in specific local contexts. There is therefore a need to alter current incentive structures within the research enterprise to place greater emphasis on implementation and evaluation research conducted in collaboration with knowledge users who are in a position to use the findings in practice to improve health.

Evidence for Health III: Making evidence-informed decisions that integrate values and context.

Making evidence-informed decisions with the aim of improving the health of individuals or populations can be facilitated by using a systematic approach. While a number of algorithms already exist, and while there is no single 'right' way of summarizing or ordering the various elements that should be involved in making such health-related decisions, an algorithm is presented here that lays out many of the key issues that should be considered, and which adds a special emphasis on balancing the values of individual patients and entire populations, as well as the importance of incorporating contextual considerations. Indeed many different types of evidence and value judgements are needed during the decision-making process to answer a wide range of questions, including (1) What is the priority health problem? (2) What causes this health problem? (3) What are the different strategies or interventions that can be used to address this health problem? (4) Which of these options, as compared to the status quo, has an added benefit that outweighs the harms? (5) Which options would be acceptable to the individuals or populations involved? (6) What are the costs and opportunity costs? (7) Would these options be feasible and sustainable in this specific context? (8) What are the ethical, legal and social implications of choosing one option over another? (9) What do different stakeholders stand to gain or lose from each option? and (10) Taking into account the multiple perspectives and considerations involved, which option is most likely to improve health while minimizing harms? This third and final article in the 'Evidence for Health' series will go through each of the steps in the algorithm in greater detail to promote more evidence-informed decisions that aim to improve health and reduce inequities.

UK health performance: findings of the Global Burden of Disease Study 2010.

BACKGROUND: The UK has had universal free health care and public health programmes for more than six decades. Several policy initiatives and structural reforms of the health system have been undertaken. Health expenditure has increased substantially since 1990, albeit from relatively low levels compared with other countries. We used data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010) to examine the patterns of health loss in the UK, the leading preventable risks that explain some of these patterns, and how UK outcomes compare with a set of comparable countries in the European Union and elsewhere in 1990 and 2010. METHODS: We used results of GBD 2010 for 1990 and 2010 for the UK and 18 other comparator nations (the original 15 members of the European Union, Australia, Canada, Norway, and the USA; henceforth EU15+). We present analyses of trends and relative performance for mortality, causes of death, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE). We present results for 259 diseases and injuries and for 67 risk factors or clusters of risk factors relevant to the UK. We assessed the UK's rank for age-standardised YLLs and DALYs for their leading causes compared with EU15+ in 1990 and 2010. We estimated 95% uncertainty intervals (UIs) for all measures. FINDINGS: For both mortality and disability, overall health has improved substantially in absolute terms in the UK from 1990 to 2010. Life expectancy in the UK increased by 4·2 years (95% UI 4·2-4·3) from 1990 to 2010. However, the UK performed significantly worse than the EU15+ for age-standardised death rates, age-standardised YLL rates, and life expectancy in 1990, and its relative position had worsened by 2010. Although in most age groups, there have been reductions in age-specific mortality, for men aged 30-34 years, mortality rates have hardly changed (reduction of 3·7%, 95% UI 2·7-4·9). In terms of premature mortality, worsening ranks are most notable for men and women aged 20-54 years. For all age groups, the contributions of Alzheimer's disease (increase of 137%, 16-277), cirrhosis (65%, ?15 to 107), and drug use disorders (577%, 71-942) to premature mortality rose from 1990 to 2010. In 2010, compared with EU15+, the UK had significantly lower rates of age-standardised YLLs for road injury, diabetes, liver cancer, and chronic kidney disease, but significantly greater rates for ischaemic heart disease, chronic obstructive pulmonary disease, lower respiratory infections, breast cancer, other cardiovascular and circulatory disorders, oesophageal cancer, preterm birth complications, congenital anomalies, and aortic aneurysm. Because YLDs per person by age and sex have not changed substantially from 1990 to 2010 but age-specific mortality has been falling, the importance of chronic disability is rising. The major causes of YLDs in 2010 were mental and behavioural disorders (including substance abuse; 21·5% [95 UI 17·2-26·3] of YLDs), and musculoskeletal disorders (30·5% [25·5-35·7]). The leading risk factor in the UK was tobacco (11·8% [10·5-13·3] of DALYs), followed by increased blood pressure (9·0 % [7·5-10·5]), and high body-mass index (8·6% [7·4-9·8]). Diet and physical inactivity accounted for 14·3% (95% UI 12·8-15·9) of UK DALYs in 2010. INTERPRETATION: The performance of the UK in terms of premature mortality is persistently and significantly below the mean of EU15+ and requires additional concerted action. Further progress in premature mortality from several major causes, such as cardiovascular diseases and cancers, will probably require improved public health, prevention, early intervention, and treatment activities. The growing burden of disability, particularly from mental disorders, substance use, musculoskeletal disorders, and falls deserves an integrated and strategic response. FUNDING: Bill & Melinda Gates Foundation.

Improving the representativeness of UK's national COVID-19 Infection Survey through spatio-temporal regression and post-stratification.

Population-representative estimates of SARS-CoV-2 infection prevalence and antibody levels in specific geographic areas at different time points are needed to optimise policy responses. However, even population-wide surveys are potentially impacted by biases arising from differences in participation rates across key groups. Here, we used spatio-temporal regression and post-stratification models to UK's national COVID-19 Infection Survey (CIS) to obtain representative estimates of PCR positivity (6,496,052 tests) and antibody prevalence (1,941,333 tests) for different regions, ages and ethnicities (7-December-2020 to 4-May-2022). Not accounting for vaccination status through post-stratification led to small underestimation of PCR positivity, but more substantial overestimations of antibody levels in the population (up to 21 percentage points), particularly in groups with low vaccine uptake in the general population. There was marked variation in the relative contribution of different areas and age-groups to each wave. Future analyses of infectious disease surveys should take into account major drivers of outcomes of interest that may also influence participation, with vaccination being an important factor to consider.

Protection against SARS-CoV-2 Omicron BA.4/5 variant following booster vaccination or breakthrough infection in the UK.

Following primary SARS-CoV-2 vaccination, whether boosters or breakthrough infections provide greater protection against SARS-CoV-2 infection is incompletely understood. Here we investigated SARS-CoV-2 antibody correlates of protection against new Omicron BA.4/5 (re-)infections and anti-spike IgG antibody trajectories after a third/booster vaccination or breakthrough infection following second vaccination in 154,149 adults ≥18 y from the United Kingdom general population. Higher antibody levels were associated with increased protection against Omicron BA.4/5 infection and breakthrough infections were associated with higher levels of protection at any given antibody level than boosters. Breakthrough infections generated similar antibody levels to boosters, and the subsequent antibody declines were slightly slower than after boosters. Together our findings show breakthrough infection provides longer-lasting protection against further infections than booster vaccinations. Our findings, considered alongside the risks of severe infection and long-term consequences of infection, have important implications for vaccine policy.