Screening at ports of entry for Ebola Virus Disease in England-a descriptive analysis of screening assessment data, 2014-2015.

BACKGROUND: In response to the outbreak of Ebola Virus Disease (EVD) in West Africa in 2014 and evidence of spread to other countries, pre-entry screening was introduced by PHE at five major ports of entry in the England. METHODS: All passengers that entered the England via the five ports returning from Liberia, Guinea and Sierra Leonne were required to complete a Health Assessment Form and have their temperature taken. The numbers, characteristics and outcomes of these passengers were analysed. RESULTS: Between 14 October 2014 and 13 October 2015, a total of 12 648 passengers from affected countries had been screened. The majority of passengers were assessed as having no direct contact with EVD cases or high-risk events (12 069, 95.4%), although 535 (4.2%) passengers were assessed as requiring public health follow-up. In total, 39 passengers were referred directly to secondary care, although none were diagnosed with EVD. One high-risk passenger was later referred to secondary care and diagnosed with EVD. CONCLUSIONS: Collection of these screening data enabled timely monitoring of the numbers and characteristics of passengers screened for EVD, facilitated resourcing decisions and acted as a mechanism to inform passengers of the necessary public health actions.

Age-specific associations between underlying health conditions and hospitalisation, death and in-hospital death among confirmed COVID-19 cases: a multi-country study based on surveillance data, June to December 2020.

BackgroundUnderlying conditions are risk factors for severe COVID-19 outcomes but evidence is limited about how risks differ with age.AimWe sought to estimate age-specific associations between underlying conditions and hospitalisation, death and in-hospital death among COVID-19 cases.MethodsWe analysed case-based COVID-19 data submitted to The European Surveillance System between 2 June and 13 December 2020 by nine European countries. Eleven underlying conditions among cases with only one condition and the number of underlying conditions among multimorbid cases were used as exposures. Adjusted odds ratios (aOR) were estimated using 39 different age-adjusted and age-interaction multivariable logistic regression models, with marginal means from the latter used to estimate probabilities of severe outcome for each condition-age group combination.ResultsCancer, cardiac disorder, diabetes, immunodeficiency, kidney, liver and lung disease, neurological disorders and obesity were associated with elevated risk (aOR: 1.5-5.6) of hospitalisation and death, after controlling for age, sex, reporting period and country. As age increased, age-specific aOR were lower and predicted probabilities higher. However, for some conditions, predicted probabilities were at least as high in younger individuals with the condition as in older cases without it. In multimorbid patients, the aOR for severe disease increased with number of conditions for all outcomes and in all age groups.ConclusionWhile supporting age-based vaccine roll-out, our findings could inform a more nuanced, age- and condition-specific approach to vaccine prioritisation. This is relevant as countries consider vaccination of younger people, boosters and dosing intervals in response to vaccine escape variants.

Effectiveness of Influenza Vaccination in Preventing Hospitalization Due to Influenza in Children: A Systematic Review and Meta-analysis.

This systematic review assesses the literature for estimates of influenza vaccine effectiveness (IVE) against laboratory-confirmed influenza-associated hospitalization in children. Studies of any design to June 8, 2020, were included if the outcome was hospitalization, participants were 17 years or younger and influenza infection was laboratory-confirmed. A random-effects meta-analysis of 37 studies that used a test-negative design gave a pooled seasonal IVE against hospitalization of 53.3% (47.2-58.8) for any influenza. IVE was higher against influenza A/H1N1pdm09 (68.7%, 56.9-77.2) and lowest against influenza A/H3N2 (35.8%, 23.4-46.3). Estimates by vaccine type ranged from 44.3% (30.1-55.7) for live-attenuated influenza vaccines to 68.9% (53.6-79.2) for inactivated vaccines. IVE estimates were higher in seasons when the circulating influenza strains were antigenically matched to vaccine strains (59.3%, 48.3-68.0). Influenza vaccination gives moderate overall protection against influenza-associated hospitalization in children supporting annual vaccination. IVE varies by influenza subtype and vaccine type.

Investigating regional variation of respiratory infections in a general practice syndromic surveillance system.

BACKGROUND: Established surveillance systems can follow trends in community disease and illness over many years. However, within England there are known regional differences in healthcare utilisation, which can affect interpretation of trends. Here, we explore regional differences for a range of respiratory conditions using general practitioner (GP) consultation data. METHODS: Daily data for respiratory conditions were extracted from a national GP surveillance system. Average daily GP consultation rates per 100 000 registered patient population were calculated by each region of England and for each study year (2013-17). Consultation rates and incidence rate ratios were also calculated for each condition by deprivation quintile and by rural, urban, and conurbation groups. RESULTS: Upper and lower respiratory tract infections and asthma were higher in the North and the Midlands than in London and the South, were highest in the most deprived groups and tended to be higher in more urban areas. Influenza-like illness was highest in the least deprived and rural areas. CONCLUSIONS: There are consistent differences in GP consultation rates across the English regions. This work has improved our understanding and interpretation of GP surveillance data at regional level and will guide more accurate public health messages.

Estimated number of deaths directly averted in people 60 years and older as a result of COVID-19 vaccination in the WHO European Region, December 2020 to November 2021.

Since December 2019, over 1.5 million SARS-CoV-2-related fatalities have been recorded in the World Health Organization European Region - 90.2% in people ≥ 60 years. We calculated lives saved in this age group by COVID-19 vaccination in 33 countries from December 2020 to November 2021, using weekly reported deaths and vaccination coverage. We estimated that vaccination averted 469,186 deaths (51% of 911,302 expected deaths; sensitivity range: 129,851-733,744; 23-62%). Impact by country ranged 6-93%, largest when implementation was early.

Assessment of Effectiveness of Seasonal Influenza Vaccination During Pregnancy in Preventing Influenza Infection in Infants in England, 2013-2014 and 2014-2015.

Maternal influenza vaccination is increasingly recognized to protect infants from influenza infection in their first 6 months. We used the screening method to estimate vaccine effectiveness (VE) against laboratory-confirmed influenza in infants in England, using newly available uptake data from the Clinical Practice Research Datalink pregnancy register, matched on week of birth and region and adjusted for ethnicity. We found VE of 66% (95% confidence interval [CI], 18%-84%) in the 2013-2014 season and 50% (95% CI, 11%-72%) in 2014-2015, with similar VE against influenza-related hospitalization. VE against the dominant circulating influenza strain was higher, at 78% (95% CI, 16%-94%) against H1N1 in 2013-2014, and 60% (95% CI, 16%-81%) against H3N2 in 2014-2015.

Forecasting the 2017/2018 seasonal influenza epidemic in England using multiple dynamic transmission models: a case study.

BACKGROUND: Since the 2009 A/H1N1 pandemic, Public Health England have developed a suite of real-time statistical models utilising enhanced pandemic surveillance data to nowcast and forecast a future pandemic. Their ability to track seasonal influenza and predict heightened winter healthcare burden in the light of high activity in Australia in 2017 was untested. METHODS: Four transmission models were used in forecasting the 2017/2018 seasonal influenza epidemic in England: a stratified primary care model using daily, region-specific, counts and virological swab positivity of influenza-like illness consultations in general practice (GP); a strain-specific (SS) model using weekly, national GP ILI and virological data; an intensive care model (ICU) using reports of ICU influenza admissions; and a synthesis model that included all data sources. For the first 12 weeks of 2018, each model was applied to the latest data to provide estimates of epidemic parameters and short-term influenza forecasts. The added value of pre-season population susceptibility data was explored. RESULTS: The combined results provided valuable nowcasts of the state of the epidemic. Short-term predictions of burden on primary and secondary health services were initially highly variable before reaching consensus beyond the observed peaks in activity between weeks 3-4 of 2018. Estimates for R0 were consistent over time for three of the four models until week 12 of 2018, and there was consistency in the estimation of R0 across the SPC and SS models, and in the ICU attack rates estimated by the ICU and the synthesis model. Estimation and predictions varied according to the assumed levels of pre-season immunity. CONCLUSIONS: This exercise successfully applied a range of pandemic models to seasonal influenza. Forecasting early in the season remains challenging but represents a crucially important activity to inform planning. Improved knowledge of pre-existing levels of immunity would be valuable.

Estimating age-stratified influenza-associated invasive pneumococcal disease in England: A time-series model based on population surveillance data.

BACKGROUND: Measures of the contribution of influenza to Streptococcus pneumoniae infections, both in the seasonal and pandemic setting, are needed to predict the burden of secondary bacterial infections in future pandemics to inform stockpiling. The magnitude of the interaction between these two pathogens has been difficult to quantify because both infections are mainly clinically diagnosed based on signs and symptoms; a combined viral-bacterial testing is rarely performed in routine clinical practice; and surveillance data suffer from confounding problems common to all ecological studies. We proposed a novel multivariate model for age-stratified disease incidence, incorporating contact patterns and estimating disease transmission within and across groups. METHODS AND FINDINGS: We used surveillance data from England over the years 2009 to 2017. Influenza infections were identified through the virological testing of samples taken from patients diagnosed with influenza-like illness (ILI) within the sentinel scheme run by the Royal College of General Practitioners (RCGP). Invasive pneumococcal disease (IPD) cases were routinely reported to Public Health England (PHE) by all the microbiology laboratories included in the national surveillance system. IPD counts at week t, conditional on the previous time point t-1, were assumed to be negative binomially distributed. Influenza counts were linearly included in the model for the mean IPD counts along with an endemic component describing some seasonal background and an autoregressive component mimicking pneumococcal transmission. Using age-specific counts, Akaike information criterion (AIC)-based model selection suggested that the best fit was obtained when the endemic component was expressed as a function of observed temperature and rainfall. Pneumococcal transmission within the same age group was estimated to explain 33.0% (confidence interval [CI] 24.9%-39.9%) of new cases in the elderly, whereas 50.7% (CI 38.8%-63.2%) of incidence in adults aged 15-44 years was attributed to transmission from another age group. The contribution of influenza on IPD during the 2009 pandemic also appeared to vary greatly across subgroups, being highest in school-age children and adults (18.3%, CI 9.4%-28.2%, and 6.07%, CI 2.83%-9.76%, respectively). Other viral infections, such as respiratory syncytial virus (RSV) and rhinovirus, also seemed to have an impact on IPD: RSV contributed 1.87% (CI 0.89%-3.08%) to pneumococcal infections in the 65+ group, whereas 2.14% (CI 0.87%-3.57%) of cases in the group of 45- to 64-year-olds were attributed to rhinovirus. The validity of this modelling strategy relies on the assumption that viral surveillance adequately represents the true incidence of influenza in the population, whereas the small numbers of IPD cases observed in the younger age groups led to significant uncertainty around some parameter estimates. CONCLUSIONS: Our estimates suggested that a pandemic wave of influenza A/H1N1 with comparable severity to the 2009 pandemic could have a modest impact on school-age children and adults in terms of IPD and a small to negligible impact on infants and the elderly. The seasonal impact of other viruses such as RSV and rhinovirus was instead more important in the older population groups.

Exploiting routinely collected severe case data to monitor and predict influenza outbreaks.

BACKGROUND: Influenza remains a significant burden on health systems. Effective responses rely on the timely understanding of the magnitude and the evolution of an outbreak. For monitoring purposes, data on severe cases of influenza in England are reported weekly to Public Health England. These data are both readily available and have the potential to provide valuable information to estimate and predict the key transmission features of seasonal and pandemic influenza. METHODS: We propose an epidemic model that links the underlying unobserved influenza transmission process to data on severe influenza cases. Within a Bayesian framework, we infer retrospectively the parameters of the epidemic model for each seasonal outbreak from 2012 to 2015, including: the effective reproduction number; the initial susceptibility; the probability of admission to intensive care given infection; and the effect of school closure on transmission. The model is also implemented in real time to assess whether early forecasting of the number of admissions to intensive care is possible. RESULTS: Our model of admissions data allows reconstruction of the underlying transmission dynamics revealing: increased transmission during the season 2013/14 and a noticeable effect of the Christmas school holiday on disease spread during seasons 2012/13 and 2014/15. When information on the initial immunity of the population is available, forecasts of the number of admissions to intensive care can be substantially improved. CONCLUSION: Readily available severe case data can be effectively used to estimate epidemiological characteristics and to predict the evolution of an epidemic, crucially allowing real-time monitoring of the transmission and severity of the outbreak.

Uptake and impact of vaccinating primary school-age children against influenza: experiences of a live attenuated influenza vaccine programme, England, 2015/16.

The 2015/16 influenza season was the third season of the introduction of an intra-nasally administered live attenuated influenza vaccine (LAIV) for children in England. All children aged 2‒6 years were offered LAIV, and in addition, a series of geographically discrete areas piloted vaccinating school-age children 7‒11 years old. Influenza A(H1N1)pdm09 was the dominant circulating strain during 2015/16 followed by influenza B. We measured influenza vaccine uptake and the overall and indirect effect of vaccinating children of primary school -age, by comparing cumulative disease incidence in targeted and non-targeted age groups in vaccine pilot and non-pilot areas in England. Uptake of 57.9% (range: 43.6-72.0) was achieved in the five pilot areas for children aged 5‒11 years. In pilot areas, cumulative emergency department respiratory attendances, influenza-confirmed hospitalisations and intensive care unit admissions were consistently lower, albeit mostly non-significantly, in targeted and non-targeted age groups compared with non-pilot areas. Effect sizes were less for adults and more severe endpoints. Vaccination of healthy primary school-age children with LAIV at moderately high levels continues to be associated with population-level reductions in influenza-related respiratory illness. Further work to evaluate the population-level impact of the programme is required.

Uptake and effectiveness of influenza vaccine in those aged 65 years and older in the United Kingdom, influenza seasons 2010/11 to 2016/17.

BackgroundIn 2016/17, seasonal influenza vaccine was less effective in those aged 65 years and older in the United Kingdom. We describe the uptake, influenza-associated mortality and adjusted vaccine effectiveness (aVE) in this age group over influenza seasons 2010/11-2016/17. Methods: Vaccine uptake in 2016/17 and five previous seasons were measured using a sentinel general practitioners cohort in England; the test-negative case-control design was used to estimate pooled aVE by subtype and age group against laboratory-confirmed influenza in primary care from 2010-2017. Results: Vaccine uptake was 64% in 65-69-year-olds, 74% in 70-74-year-olds and 80% in those aged 75 and older. Overall aVE was 32.5% (95% CI: 11.6 to 48.5); aVE by sub-type was 60.8% (95% CI: 33.9 to 76.7) and 50.0% (95% CI: 21.6 to 68.1) against influenza A(H1N1)pdm09 and influenza B, respectively, but only 5.6% (95% CI: - 39.2 to 35.9) against A(H3N2). Against all laboratory-confirmed influenza aVE was 45.2% (95% CI: 25.1 to 60.0) in 65-74 year olds; - 26.2% (95% CI: - 149.3 to 36.0) in 75-84 year olds and - 3.2% (95% CI: - 237.8 to 68.5) in those aged 85 years and older. Influenza-attributable mortality was highest in seasons dominated by A(H3N2). Conclusions: Vaccine uptake with non-adjuvanted, normal-dose vaccines remained high, with evidence of effectiveness against influenza A(H1N1)pdm09 and B, though poor against A(H3N2), particularly in those aged 75 years and older. Forthcoming availability of newly licensed vaccines with wider use of antivirals can potentially further improve prevention and control of influenza in this group.

Retrospective Observational Study of Atypical Winter Respiratory Illness Season Using Real-Time Syndromic Surveillance, England, 2014-15.

During winter 2014-15, England experienced severe strains on acute health services. We investigated whether syndromic surveillance could contribute to understanding of the unusually high level of healthcare needs. We compared trends for several respiratory syndromic indicators from that winter to historical baselines. Cumulative and mean incidence rates were compared by winter and age group. All-age influenza-like illness was at expected levels; however, severe asthma and pneumonia levels were above those expected. Across several respiratory indicators, cumulative incidence rates during 2014-15 were similar to those of previous years, but higher for older persons; we saw increased rates of acute respiratory disease, including influenza like illness, severe asthma, and pneumonia, in the 65-74- and >75-year age groups. Age group-specific statistical algorithms may provide insights into the burden on health services and improve early warning in future winters.

Excess all-cause and influenza-attributable mortality in Europe, December 2016 to February 2017.

Since December 2016, excess all-cause mortality was observed in many European countries, especially among people aged ≥ 65 years. We estimated all-cause and influenza-attributable mortality in 19 European countries/regions. Excess mortality was primarily explained by circulation of influenza virus A(H3N2). Cold weather snaps contributed in some countries. The pattern was similar to the last major influenza A(H3N2) season in 2014/15 in Europe, although starting earlier in line with the early influenza season start.

Assessing the use of hospital staff influenza-like absence (ILA) for enhancing hospital preparedness and national surveillance.

BACKGROUND: Early warning and robust estimation of influenza burden are critical to inform hospital preparedness and operational, treatment, and vaccination policies. Methods to enhance influenza-like illness (ILI) surveillance are regularly reviewed. We investigated the use of hospital staff 'influenza-like absences' (hospital staff-ILA), i.e. absence attributed to colds and influenza, to improve capture of influenza dynamics and provide resilience for hospitals. METHODS: Numbers and rates of hospital staff-ILA were compared to regional surveillance data on ILI primary-care presentations (15-64 years) and to counts of laboratory confirmed cases among hospitalised patients from April 2008 to April 2013 inclusive. Analyses were used to determine comparability of the ILI and hospital-ILA and how systems compared in early warning and estimating the burden of disease. RESULTS: Among 20,021 reported hospital-ILA and 4661 community ILI cases, correlations in counts were high and consistency in illness measurements was observed. In time series analyses, both hospital-ILA and ILI showed similar timing of the seasonal component. Hospital-ILA data often commenced and peaked earlier than ILI according to a Bayesian prospective alarm algorithm. Hospital-ILA rates were more comparable to model-based estimates of 'true' influenza burden than ILI. CONCLUSIONS: Hospital-ILA appears to have the potential to be a robust, yet simple syndromic surveillance method that could be used to enhance estimates of disease burden and early warning, and assist with local hospital preparedness.

Uptake and impact of vaccinating school age children against influenza during a season with circulation of drifted influenza A and B strains, England, 2014/15.

The 2014/15 influenza season was the second season of roll-out of a live attenuated influenza vaccine (LAIV) programme for healthy children in England. During this season, besides offering LAIV to all two to four year olds, several areas piloted vaccination of primary (4-11 years) and secondary (11-13 years) age children. Influenza A(H3N2) circulated, with strains genetically and antigenically distinct from the 2014/15 A(H3N2) vaccine strain, followed by a drifted B strain. We assessed the overall and indirect impact of vaccinating school age children, comparing cumulative disease incidence in targeted and non-targeted age groups in vaccine pilot to non-pilot areas. Uptake levels were 56.8% and 49.8% in primary and secondary school pilot areas respectively. In primary school age pilot areas, cumulative primary care influenza-like consultation, emergency department respiratory attendance, respiratory swab positivity, hospitalisation and excess respiratory mortality were consistently lower in targeted and non-targeted age groups, though less for adults and more severe end-points, compared with non-pilot areas. There was no significant reduction for excess all-cause mortality. Little impact was seen in secondary school age pilot only areas compared with non-pilot areas. Vaccination of healthy primary school age children resulted in population-level impact despite circulation of drifted A and B influenza strains.

Enhanced MERS coronavirus surveillance of travelers from the Middle East to England.

During the first year of enhanced MERS coronavirus surveillance in England, 77 persons traveling from the Middle East had acute respiratory illness and were tested for the virus. Infection was confirmed in 2 travelers with acute respiratory distress syndrome and 2 of their contacts. Patients with less severe manifestations tested negative.

Bayesian modeling to unmask and predict influenza A/H1N1pdm dynamics in London.

The tracking and projection of emerging epidemics is hindered by the disconnect between apparent epidemic dynamics, discernible from noisy and incomplete surveillance data, and the underlying, imperfectly observed, system. Behavior changes compound this, altering both true dynamics and reporting patterns, particularly for diseases with nonspecific symptoms, such as influenza. We disentangle these effects to unravel the hidden dynamics of the 2009 influenza A/H1N1pdm pandemic in London, where surveillance suggests an unusual dominant peak in the summer. We embed an age-structured model into a bayesian synthesis of multiple evidence sources to reveal substantial changes in contact patterns and health-seeking behavior throughout the epidemic, uncovering two similar infection waves, despite large differences in the reported levels of disease. We show how this approach, which allows for real-time learning about model parameters as the epidemic progresses, is also able to provide a sequence of nested projections that are capable of accurately reflecting the epidemic evolution.

Informing the pandemic response: the role of the WHO's COVID-19 Weekly Epidemiological Update.

On 31 December 2019, the Municipal Health Commission of Wuhan, China, reported a cluster of atypical pneumonia cases. On 5 January 2020, the WHO publicly released a Disease Outbreak News (DON) report, providing information about the pneumonia cases, implemented response interventions, and WHO's risk assessment and advice on public health and social measures. Following 9 additional DON reports and 209 daily situation reports, on 17 August 2020, WHO published the first edition of the COVID-19 Weekly Epidemiological Update (WEU). On 1 September 2023, the 158th edition of the WEU was published on WHO's website, marking its final issue. Since then, the WEU has been replaced by comprehensive global epidemiological updates on COVID-19 released every 4 weeks. During the span of its publication, the webpage that hosts the WEU and the COVID-19 Operational Updates was accessed annually over 1.4 million times on average, with visits originating from more than 100 countries. This article provides an in-depth analysis of the WEU process, from data collection to publication, focusing on the scope, technical details, main features, underlying methods, impact and limitations. We also discuss WHO's experience in disseminating epidemiological information on the COVID-19 pandemic at the global level and provide recommendations for enhancing collaboration and information sharing to support future health emergency responses.

Evolutionary dynamics of local pandemic H1N1/2009 influenza virus lineages revealed by whole-genome analysis.

Virus gene sequencing and phylogenetics can be used to study the epidemiological dynamics of rapidly evolving viruses. With complete genome data, it becomes possible to identify and trace individual transmission chains of viruses such as influenza virus during the course of an epidemic. Here we sequenced 153 pandemic influenza H1N1/09 virus genomes from United Kingdom isolates from the first (127 isolates) and second (26 isolates) waves of the 2009 pandemic and used their sequences, dates of isolation, and geographical locations to infer the genetic epidemiology of the epidemic in the United Kingdom. We demonstrate that the epidemic in the United Kingdom was composed of many cocirculating lineages, among which at least 13 were exclusively or predominantly United Kingdom clusters. The estimated divergence times of two of the clusters predate the detection of pandemic H1N1/09 virus in the United Kingdom, suggesting that the pandemic H1N1/09 virus was already circulating in the United Kingdom before the first clinical case. Crucially, three clusters contain isolates from the second wave of infections in the United Kingdom, two of which represent chains of transmission that appear to have persisted within the United Kingdom between the first and second waves. This demonstrates that whole-genome analysis can track in fine detail the behavior of individual influenza virus lineages during the course of a single epidemic or pandemic.

An intercountry comparison of the impact of the paediatric live attenuated influenza vaccine (LAIV) programme across the UK and the Republic of Ireland (ROI), 2010 to 2017.

Background: The universal paediatric live attenuated influenza vaccine (LAIV) programme commenced in the United Kingdom (UK) in 2013/2014. Since 2014/2015, all pre-school and primary school children in Scotland and Northern Ireland have been offered the vaccine. England and Wales incrementally introduced the programme with additional school age cohorts being vaccinated each season. The Republic of Ireland (ROI) had no universal paediatric programme before 2017. We evaluated the potential population impact of vaccinating primary school-aged children across the five countries up to the 2016/2017 influenza season. Methods: We compared rates of primary care influenza-like illness (ILI) consultations, confirmed influenza intensive care unit (ICU) admissions, and all-cause excess mortality using standardised methods. To further quantify the impact, a scoring system was developed where each weekly rate/z-score was scored and summed across each influenza season according to the weekly respective threshold experienced in each country. Results: Results highlight ILI consultation rates in the four seasons' post-programme, breached baseline thresholds once or not at all in Scotland and Northern Ireland; in three out of the four seasons in England and Wales; and in all four seasons in ROI. No differences were observed in the seasons' post-programme introduction between countries in rates of ICU and excess mortality, although reductions in influenza-related mortality were seen. The scoring system also reflected similar results overall. Conclusions: Findings of this study suggest that LAIV vaccination of primary school age children is associated with population-level benefits, particularly in reducing infection incidence in primary care.