Excess pneumonia and influenza death as herald wave of COVID-19 in England and Wales, United Kingdom
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ABSTRACT:
SUBMITTER: Li C
PROVIDER: S-EPMC7501317 | biostudies-literature | 2020 Sep
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo investigate the impact on mortality due to pneumonia or influenza of the change from risk-based to age group-based targeting of the elderly for yearly influenza vaccination in England and Wales.DesignExcess mortality estimated using time series of deaths registered to pneumonia or influenza, accounting for seasonality, trend and artefacts. Non-excess mortality plotted as proxy for long-term trend in mortality.SettingEngland and Wales.ParticipantsPersons aged 65-74 and 75+ years whose deaths were registered to underlying pneumonia or influenza between 1975/1976 and 2004/2005.Outcome measuresMultiplicative effect on average excess pneumonia and influenza deaths each winter in the 4-6 winters since age group-based targeting of vaccination was introduced (in persons aged 75+ years from 1998/1999; in persons aged 65+ years from 2000/2001), estimated using multivariable regression adjusted for temperature, antigenic drift and vaccine mismatch, and stratified by dominant circulating influenza subtype. Trend in baseline weekly pneumonia and influenza death rates.ResultsThere is a suggestion of lower average excess mortality in the six winters after age group-based targeting began compared to before, but the CI for the 65-74 years age group includes no difference. Trend in baseline pneumonia and influenza mortality shows an apparent downward turning point around 2000 for the 65-74 years age group and from the mid-1990s in the 75+ years age group.ConclusionsThere is weakly supportive evidence that the marked increases in vaccine coverage accompanying the switch from risk-based to age group-based targeting of the elderly for yearly influenza vaccination in England and Wales were associated with lower levels of pneumonia and influenza mortality in older people in the first 6 years after age group-based targeting began. The possible impact of these policy changes is observed as weak evidence for lower average excess mortality as well as a turning point in baseline mortality coincident with the changes.
| S-EPMC3733298 | biostudies-literature
Project description:BackgroundChanging population-level exposure to modifiable risk factors is a key driver of changing cancer incidence. Understanding these changes is therefore vital when prioritising risk-reduction policies, in order to have the biggest impact on reducing cancer incidence. UK figures on the number of risk factor-attributable cancers are updated here to reflect changing behaviour as assessed in representative national surveys, and new epidemiological evidence. Figures are also presented by UK constituent country because prevalence of risk factor exposure varies between them.MethodsPopulation attributable fractions (PAFs) were calculated for combinations of risk factor and cancer type with sufficient/convincing evidence of a causal association. Relative risks (RRs) were drawn from meta-analyses of cohort studies where possible. Prevalence of exposure to risk factors was obtained from nationally representative population surveys. Cancer incidence data for 2015 were sourced from national data releases and, where needed, personal communications. PAF calculations were stratified by age, sex and risk factor exposure level and then combined to create summary PAFs by cancer type, sex and country.ResultsNearly four in ten (37.7%) cancer cases in 2015 in the UK were attributable to known risk factors. The proportion was around two percentage points higher in UK males (38.6%) than in UK females (36.8%). Comparing UK countries, the attributable proportion was highest in Scotland (41.5% for persons) and lowest in England (37.3% for persons). Tobacco smoking contributed by far the largest proportion of attributable cancer cases, followed by overweight/obesity, accounting for 15.1% and 6.3%, respectively, of all cases in the UK in 2015. For 10 cancer types, including two of the five most common cancer types in the UK (lung cancer and melanoma skin cancer), more than 70% of UK cancer cases were attributable to known risk factors.ConclusionTobacco and overweight/obesity remain the top contributors of attributable cancer cases. Tobacco smoking has the highest PAF because it greatly increases cancer risk and has a large number of cancer types associated with it. Overweight/obesity has the second-highest PAF because it affects a high proportion of the UK population and is also linked with many cancer types. Public health policy may seek to mitigate the level of harm associated with exposure or reduce exposure levels-both approaches may effectively impact cancer incidence. Differences in PAFs between countries and sexes are primarily due to varying prevalence of exposure to risk factors and varying proportions of specific cancer types. This variation in turn is affected by socio-demographic differences which drive differences in exposure to theoretically avoidable 'lifestyle' factors. PAFs at UK country level have not been available previously and they should be used by policymakers in devolved nations. PAFs are estimates based on the best available data, limitations in those data would generally bias toward underestimation of PAFs. Regular collection of risk factor exposure prevalence data which corresponds with epidemiological evidence is vital for analyses like this and should remain a priority for the UK Government and devolved Administrations.
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Project description:The Covid-19 pandemic has claimed many lives in the UK and globally. The objective of this paper is to study whether the number of deaths not registered as Covid-19-related has increased compared to what would have been expected in the absence of the pandemic. Reasons behind this might include Covid-19 underreporting, avoiding visits to hospitals or GPs, and the effects of the lockdown. I used weekly ONS data on the number of deaths in England and Wales that did not officially involve Covid-19 over the period 2015-2020. Simply observing trends is not sufficient as spikes in deaths may occasionally occur. I thus followed a difference-in-differences econometric approach to study whether there was a relative increase in deaths not registered as Covid-19-related during the pandemic, compared to a control. Results suggest that there were an additional 968 weekly deaths that officially did not involve Covid-19, compared to what would have otherwise been expected. It is possible that some people are dying from Covid-19 without being diagnosed, and/or that there are excess deaths due to other causes as a result of the pandemic. Analysing the cause of death for any excess non-covid-19 deaths will shed light upon the reasons for the increase in such deaths and will help design appropriate policy responses to save lives.
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Project description:During the winter of 2001-02, influenza AH1N2 viruses were detected for the first time in humans in the U.K. The H1N2 viruses co-circulated with H3N2 viruses and a very small number of H1N1 viruses and were isolated in the community and hospitalized patients, predominantly from children <15 years of age. Characterization of H1N2 viruses indicated that they were antigenically and genetically homogeneous, deriving the hemagglutinin (HA) gene from recently circulating A/New Caledonia/20/99-like H1N1 viruses, whereas the other seven genes originated from recently circulating H3N2 viruses. Retrospective reverse transcription-polymerase chain reaction analysis of influenza A H1 viruses isolated in the U.K. during the previous winter identified a single H1N2 virus, isolated in March 2001, indicating that H1N2 viruses did not widely circulate in the U.K. before September 2001. The reassortment event is estimated to have occurred between 1999 and early 2001, and the emergence of H1N2 viruses in humans reinforces the need for frequent surveillance of circulating viruses.
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Project description:Vaccines against viral infections have been proposed to reduce prescribing of antibiotics and thereby help control resistant bacterial infections. However, by combining published data sources, we predict that pediatric live attenuated influenza vaccination in England and Wales will not substantially reduce antibiotic consumption or adverse health outcomes associated with antibiotic resistance.
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Project description: Not available
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Project description:Influenza is rarely laboratory-confirmed and the outpatient influenza burden is rarely studied due to a lack of suitable data. We used the Clinical Practice Research Datalink (CPRD) and surveillance data from Public Health England in a linear regression model to assess the number of persons consulting UK general practitioners (GP episodes) for respiratory illness, otitis media and antibiotic prescriptions attributable to influenza during 14 seasons, 1995-2009. In CPRD we ascertained influenza vaccination status in each season and risk status (conditions associated with severe influenza outcomes). Seasonal mean estimates of influenza-attributable GP episodes in the UK were 857 996 for respiratory disease including 68 777 for otitis media, with wide inter-seasonal variability. In an average season, 2·4%/0·5% of children aged <5 years and 1·3%/0·1% of seniors aged ?75 years had a GP episode for respiratory illness attributed to influenza A/B. Two-thirds of influenza-attributable GP episodes were estimated to result in prescription of antibiotics. These estimates are substantially greater than those derived from clinically reported influenza-like illness in surveillance programmes. Because health service costs of influenza are largely borne in general practice, these are important findings for cost-benefit assessment of influenza vaccination programmes.
| S-EPMC4714299 | biostudies-literature
Project description:School closure is often considered as an influenza control measure, but its effects on transmission are poorly understood. We used 2 approaches to estimate how school holidays affect the contact parameter (the per capita rate of contact sufficient for infection transmission) for influenza using primary care data from England and Wales (1967-2000). Firstly, we fitted an age-structured susceptible-infectious-recovered model to each year's data to estimate the proportional change in the contact parameter during school holidays as compared with termtime. Secondly, we calculated the percentage difference in the contact parameter between holidays and termtime from weekly values of the contact parameter, estimated directly from simple mass-action models. Estimates were combined using random-effects meta-analysis, where appropriate. From fitting to the data, the difference in the contact parameter among children aged 5-14 years during holidays as compared with termtime ranged from a 36% reduction to a 17% increase; estimates were too heterogeneous for meta-analysis. Based on the simple mass-action model, the contact parameter was 17% (95% confidence interval: 10, 25) lower during holidays than during termtime. Results were robust to the assumed proportions of infections that were reported and individuals who were susceptible when the influenza season started. We conclude that school closure may reduce transmission during influenza outbreaks.
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Project description:Risk factors for increased risk of death from COVID-19 have been identified, but less is known on characteristics that make communities resilient or vulnerable to the mortality impacts of the pandemic. We applied a two-stage Bayesian spatial model to quantify inequalities in excess mortality in people aged 40 years and older at the community level during the first wave of the pandemic in England, March-May 2020 compared with 2015-2019. Here we show that communities with an increased risk of excess mortality had a high density of care homes, and/or high proportion of residents on income support, living in overcrowded homes and/or with a non-white ethnicity. We found no association between population density or air pollution and excess mortality. Effective and timely public health and healthcare measures that target the communities at greatest risk are urgently needed to avoid further widening of inequalities in mortality patterns as the pandemic progresses.
| S-EPMC8213785 | biostudies-literature
Project description:Excess mortality due to seasonal influenza is thought to be substantial. However, influenza may often not be recognized as cause of death. Imputation methods are therefore required to assess the public health impact of influenza. The purpose of this study was to obtain estimates of monthly excess mortality due to influenza that are based on an epidemiologically meaningful model.U.S. monthly all-cause mortality, 1995 through 2005, was hierarchically modeled as Poisson variable with a mean that linearly depends both on seasonal covariates and on influenza-certified mortality. It also allowed for overdispersion to account for extra variation that is not captured by the Poisson error. The coefficient associated with influenza-certified mortality was interpreted as ratio of total influenza mortality to influenza-certified mortality. Separate models were fitted for four age categories (< 18, 18-49, 50-64, 65+). Bayesian parameter estimation was performed using Markov Chain Monte Carlo methods. For the eleven year study period, a total of 260,814 (95% CI: 201,011-290,556) deaths was attributed to influenza, corresponding to an annual average of 23,710, or 0.91% of all deaths.Annual estimates for influenza mortality were highly variable from year to year, but they were systematically lower than previously published estimates. The excellent fit of our model with the data suggest validity of our estimates.
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