BACKGROUND:Hip fractures (HF) are a major cause of morbidity and mortality and account for substantial health and social care costs. We report the incidence and characteristics of older patients (≥60 years) presenting with hip fractures (HFs) in England, Wales and Northern Ireland. METHODS:We conducted a national cohort study of HF events recorded in the National Hip Fracture Database (NHFD) between May 2011 and September 2023. HF incidence was derived using sex and age-banded mid-year population estimates from the Office for National Statistics to calculate at-risk population incidence for the whole cohort and by sex and age strata. RESULTS:735 436 HF events were included (71% female, mean age 82.9 years). Annual NHFD HF numbers increased across the study period from 55 832 to 63 341 (13.5%). However, overall incidence declined from 422.8 to 412.8 per 100 000 population. Divergence was observed between sexes, with falling incidence in females but rising in males. HF patients are presenting with greater systemic disease burden, with the proportion graded American Society of Anaesthesiologists ≥3 increasing in both females (66.4% to 80.4%) and males (73.4% to 84.3%). CONCLUSION:Despite modest declines in overall incidence in women, absolute HF numbers continue to rise. The divergent sex-specific trends and substantial increase in patient comorbidity represent important shifts in HF epidemiology with implications for service capacity, risk stratification and secondary prevention strategies. This mandates urgent realignment of care resources to minimise the impact on patient mortality and economic health burden.

Using data from the HIV pre-exposure prophylaxis (PrEP) Impact trial, an implementation trial of PrEP across sexual health services to inform routine PrEP commissioning in England, we examined sexual health service use and PrEP need during UK COVID-19 social restrictions (March-November 2020) to assess the pandemic’s impact on PrEP delivery in England. This is the first analysis extending trial data beyond February 2020. We collated monthly aggregate data from 157 PrEP Impact Trial clinics in England (October 2017–November 2020), focusing on gay, bisexual, and other men who have sex with men (MSM). For trial participants and non-trial attendees (NTA), we examined trends in service use, STI/HIV test positivity, PrEP need, and prescriptions (30, 60, 90, ≥ 120 tablets). We also assessed changes in the enrolment patterns of key subgroups (aged 16–24, ethnic minority background, and bacterial STI history) over time. COVID-19 restrictions were defined as March–July and September–November 2020. Attendances markedly decreased between February and April 2020 (-34

Abstract Influenza surveillance has typically been carried out using influenza-like illness (ILI) rates and proportions of laboratory tests positive for influenza as metrics to monitor, with sample sizes for the number of tests to carry out based on the precision of the resulting estimate of proportions positive. The transition out of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic period has encouraged the establishment of integrated surveillance of respiratory pathogens, in the context of multiple surveillance objectives, as set out by WHO in its revised integrated surveillance guidance and Mosaic Respiratory Surveillance Framework. These objectives include outbreak detection, situational awareness and intensity evaluation, among others. We illustrate how to design respiratory surveillance in primary care, by considering multiple surveillance objectives for different metrics of different types of respiratory pathogen circulation seasons in England, the USA and Hong Kong. We focus on a proxy of influenza activity as a metric to compare between these countries/regions. Taking advantage of England’s integrated sentinel primary care surveillance system, we propose further metrics to monitor: a proxy of respiratory activity, novelly defined as the product of an acute respiratory infection (ARI) consultation rate and the proportion of tests positive for at least one pathogen ; pathogen-specific ARI-based activity proxies for more detailed monitoring of influenza and SARS-CoV-2; and integrated monitoring of proportions positive for all pathogens tested. We use a simulation approach to determine sample sizes by optimising either the probability of, or time to, detection of different events in monitored metrics, according to the different surveillance objectives. We find that sample sizes to maximise detection probabilities or minimise detection times vary by metric, objective, event and country/region. At a national level, the current sample sizes used are sufficient to detect most events in most weeks for both the USA and Hong Kong, but for England the numbers of swabs taken for ILI consultations may not be sufficient in all weeks, particularly at the start of the season when outbreak detection is important. However, broadening the criteria for swabbing to acute respiratory symptoms does allow for sufficient sample sizes.

INTRODUCTION:Despite the existing hybrid immunity, a sharp increase in SARS-CoV-2 reinfections was observed worldwide following Omicron variant emergence. We investigated whether the first infecting variant indelibly shapes serological responses against Omicron (BA.1 and BA.2) reinfection. METHODS:Participants with a sequence-confirmed Alpha (n = 23) or Delta (n = 10) first infection before third vaccine dose (V3) that subsequently had a BA.1 or BA.2 reinfection were selected. Sera were tested for anti-SARS-CoV-2 spike (anti-S) and live virus microneutralisation (LV-N) against Ancestral, Alpha, Delta, Omicron BA.1 and BA.2. Antibody responses and waning post-V3 were compared by first infection variant using mixed-effect models, as well as inferred titres days before reinfections. Individual's neutralisation responses were compared 12 weeks post-V3, among those with Alpha and Delta primary infection. RESULTS:After V3, those with Delta first infection had higher LV-N Omicron BA.1 titres (fold difference (FD) = 2.7, p = 0.05) compared to Alpha primary infection. Participants with Delta first infection presented higher LV-N BA.1 (FD = 1.89, p = 0.004) and LV-N BA.2 (FD = 2.06, p = 0.001) titres pre-Omicron reinfections. Individuals' neutralisation responses against Ancestral were higher than any other subsequent variants, regardless of first infection variant. CONCLUSIONS:A previous Delta SARS-CoV-2 infection induced a higher serological response against a subsequent Omicron infection when compared to Alpha first infections.

National foodborne outbreaks of gastrointestinal disease often require rapid case-control investigations to identify the source. Online market panels offer a potential alternative to traditional control recruitment. We compared market panel controls to traditional controls in case-control recruitment during a 2024 UK outbreak of STEC O145. Two case-control studies were conducted for two different control groups (a) Salmonella cases as case-controls and (b) online market panel members. Timeliness, cost, and resources were compared, and a logistic regression compared findings in a control-control analysis. In total, 43 cases of STEC O145, 63 Salmonella case-controls, and 93 panel controls were recruited. Neither control group reached the recruitment target for the younger adult age group. Salmonella case-controls had a ninefold greater staff time to recruit and cost five times more than panel controls (£25.82 vs. £4.99 per control), partially due to interviewer-administered questionnaires compared with self-completion by panel controls. Both analytical approaches identified the same outbreak source, with no significant differences in exposures between the control groups. The cost and resource savings associated with panel controls justify their use as a standard procedure in outbreak investigations. We recommend exploring engagement with age groups that are difficult to recruit and assessing alternative strategies to reach them.

BACKGROUND:Health inequalities in Escherichia coli bacteraemia are increasingly recognised, with disadvantaged and minority groups disproportionately affected. Understanding intersecting inequality factors will clarify the poorly understood drivers of overall and resistant E. coli infections. METHODS:We retrospectively analysed English surveillance data (2018/19-2023/24) of E. coli bacteraemia and resistance. Multivariable logistic regression assessed healthcare- vs community-associated (HA vs CA) and resistant vs susceptible cases. FINDINGS:Between April 2018 and March 2024, 242,604 cases of E. coli bacteraemia were reported. Minority ethnic groups were disproportionately represented among patients aged <75 years, in both HA and CA categories. CA cases in females aged 30-44 were 2.7, 4.2, 4.4 and 4.0 times greater in Asian, Black, Mixed and Other ethnicities vs their White counterparts. Multivariable analysis showed odds of antibiotic resistant E. coli bacteraemia were more than twice that in the Asian (OR 2.45, p<0.0001), and 51.0% greater in the Black (p<0.0001) ethnicities, respectively, compared to their White counterparts. Odds of resistance amongst the Asian ethnic group was twice the national average for 2nd (37.2 vs 18.3%) and 3rd generation cephalosporins (35.2 vs 16.1%) and ciprofloxacin (37.1 vs 17.9%). Residing within a care home more than doubled the odds of resistant infection (OR 2.28, p<0.0001). CONCLUSIONS:Younger individuals of ethnic minorities particularly females experienced a disproportionate burden of infection, with resistance to key antibiotics particularly elevated in the Asian population. Care home residents had significantly higher rates of CA and resistant E. coli bacteraemia. Greater understanding of the source of infection in these groups is essential to inform targeted interventions.

INTRODUCTION:The combination of patient illness and staff absence driven by seasonal viruses culminates in annual "winter pressures" on UK healthcare systems and has been exacerbated by COVID-19. In winter 2022/23 we introduce multiplex testing aiming to determine the incidence of SARS-CoV-2, influenza and respiratory syncytial virus (RSV) in our cohort of UK healthcare workers (HCWs). METHODS:The pilot study was conducted from 28/11/2022-31/03/2023 within the SIREN prospective cohort study. Participants completed fortnightly questionnaires, capturing symptoms and sick leave, and multiplex PCR testing for SARS-CoV-2, influenza and RSV, regardless of symptoms. PCR-positivity rates by virus were calculated over time, and viruses were compared by symptoms and severity. Self-reported symptoms and associated sick leave were described. Sick leave rates were compared by vaccination status and demographics. RESULTS:5,863 participants were included, 84.6% female, 70.3% ≥ 45-years, 91.4% of White ethnicity and 82.6% in a patient facing role. PCR-positivity peaked in early December for all three viruses (4.6 positives per 100 tests (95%CI 3.5, 5.7) SARS-CoV-2, 3.9 (95%CI 2.2, 5.6) influenza, 1.4 (95%CI 0.4, 2.4) RSV), declining to <0.3/100 tests after January for influenza/RSV, and around 2.5/100 tests for SARS-CoV-2. Over one-third of all infections were asymptomatic, and symptoms were similar for all viruses. 1,368 (23.3%) participants reported taking sick leave, median 4 days (range 1-59). Rates of sick leave were higher in participants with co-morbidities, working in clinical settings, and who had not been vaccinated (COVID-19 booster or seasonal influenza vaccine) versus those who had received neither vaccine (2.04 vs 1.41 sick days/100 days, adjusted Incidence Rate Ratio 1.47 (95%CI 1.38, 1.56). CONCLUSION:This pilot demonstrated the use of multiplex testing allowed better understanding of the impact of seasonal respiratory viruses and respective vaccines on the HCW workforce. This highlights the important information on asymptomatic infection and persisting levels of SARS-CoV-2 infection.

OBJECTIVES:To determine vaccine effectiveness against influenza infection among UK healthcare workers between 1 September 2023 and 31 March 2024. METHODS:We conducted a prospective cohort study, including hospital-based healthcare workers (HCWs) enrolled in the SARS-CoV-2 Immunity & Reinfection Evaluation (SIREN) study. Participants completed fortnightly influenza PCR testing and questionnaires. Influenza vaccination status was identified from national vaccination records and questionnaires. Vaccine effectiveness against PCR-positive influenza was estimated using Cox regression adjusted for age group, sex, chronic disease status, patient-facing role, and region. Case-control and test-negative case-control (TNCC) analyses, using multivariable logistic regression, were also performed. RESULTS:Among 4934 participants, median age was 55 years (IQR 47-60 years) and most were female (78.7%) and white (85.6%). Overall, 3857 (78.2%) received influenza vaccination and 266 (5.4%) tested positive for influenza, of which 227 (85.3%) reported acute respiratory infection symptoms. Adjusted vaccine effectiveness was 39.9% (95% confidence interval 21.8 - 53.8), and similar using case-control (41.2%, 22.5 - 55.2) and TNCC (45.9%, 21.8 - 62.2) approaches. CONCLUSIONS:Influenza vaccine effectiveness was 40%, consistent with estimates for symptomatic patients. Applied to the combined UK healthcare workforce, this potentially translates to prevention of over 50,000 infections. These findings emphasise the importance of seasonal influenza vaccination to reduce healthcare workers infections and thereby protect patients and reduce workforce pressures.

OBJECTIVES:The Difference-in-Differences Investigation Tool ('DiD IT') is a new tool used to estimate the impact of local threats to public health in England. 'DiD IT' is part of a daily all hazards syndromic surveillance service. We present a validation of the 'DiD IT' tool, using synthetic injects to assess how well it can estimate small, localised increases in the number of people presenting to health care. Furthermore, we assess how control settings within 'DiD IT' affect it's performance. STUDY DESIGN:Validation Study METHODS: 'DiD IT' was validated across ten different syndromic indicators, chosen to cover a range of data volumes and potential public health threats. Injects were added across different times of year and days of week, including public holidays. Also, different size of injects were created, including some with an impact spread to neighbouring locations or spread over several days. The control settings within 'DiD IT' were tested by varying the control location and periods, using, for example a 'washout period' or excluding nearest neighbours. Performance was measured by comparing the estimates for excess counts produced by 'DiD IT' with the actual synthetic injects added. RESULTS:'DiD IT' was able to provide a positive estimate in 99.8 % of trials, with a mean absolute error of 1.50. However, confidence intervals for the central estimate could not be produced in 42.5 % of trials. Furthermore, the 95 % confidence intervals for the central estimates only included the actual inject count within 62.8 % of the intervals. Unsurprising, mean errors were slightly higher when synthetic injects were not concentrated in one location on one day but were spread across neighbouring areas or days. Selecting longer control periods and using more locations as controls tended to lower the errors slightly. Including a washout period or excluding neighbouring locations from the controls did not improve performance. CONCLUSIONS:We have shown that 'DiD IT' is accurate for assessing the impact of local incidents but that further work is needed to improve the how the uncertainty of these estimates are communicated to users.

OBJECTIVES:The HIV pre-exposure prophylaxis (PrEP) Impact Trial demonstrated the feasibility and effectiveness of PrEP in England, providing critical evidence to inform national commissioning. Using trial data, we assess regional variation in delivery and examine how service provision differences impacted outcomes across the PrEP Prevention Care Continuum (PPCC) (ie, those at risk of HIV acquisition, those eligible for PrEP, PrEP uptake and coverage). METHODS:We assessed PPCC outcomes among HIV-negative men who have sex with men (MSM) attending trial sexual health services (SHS) from October 2017 to February 2020. Outcomes were stratified by SHS region (London, Outside London) and MSM throughput, defined as the mean annual number of MSM attendees, to approximate differences in service structure and provision based on attendee composition. HIV incidence per 100 person-years was calculated for SHS in and outside of London, restricted to those with ≥2 visits during the study period. RESULTS:Across 157 trial SHS, 165 270 MSM attended during the study period, of whom 20 349 were enrolled in the trial. HIV incidence was calculated among 102 842 MSM, including 17 770 trial participants. PrEP uptake ranged from 42% to 92%, and coverage from 16% to 31%, varying by MSM throughput strata and consistently higher among London SHS. HIV incidence was significantly lower in trial participants (London: 0.07 (95% CI 0.04 to 0.14); Outside London: 0.22 (0.13 to 0.36)) versus non-trial attendees (London: 0.98 (0.88 to 1.10); Outside London: 0.93 (0.82 to 1.04)). CONCLUSIONS:This analysis supports ongoing enhancements to PrEP delivery across England. Findings highlight the success of varied service models, including those not traditionally focused on MSM populations. High HIV seroconversions among individuals without clear markers of risk for HIV acquisition support the need for broader, less restrictive PrEP access, aligned with recent updates to national guidance. To evaluate the long-term impact of PrEP on HIV and sexually transmitted infection (STI) incidence, consistent, high-quality data reporting to national surveillance remains essential.

Estimating epidemiological parameters is essential for informing an effective public health response during waves of infectious disease transmission. However, many parameters are challenging to estimate from real-world data and rely on human challenge studies or mass community testing. During Winter 2023/2024, a community cohort study of SARS-CoV-2 was conducted across households in England and Scotland. From this survey, questionnaire data and follow-up testing protocols provided valuable data on the duration of positivity and test sensitivity for lateral flow device (LFD) tests. Here, Bayesian statistical modelling methods are developed and applied to estimate the underlying parameters. The duration of LFD positivity is found to increase with increasing age, with a mean of 9.1 days (95% CrI: 8.4 days, 9.9 days) in the 18 to 34 years age group compared to 10.8 days (95% CrI: 10.3 days, 11.3 days) in the 75 years and over age group. Sex is found to have no impact on the duration of positivity. LFD test sensitivity at the time of symptom onset is very high, with an estimated sensitivity of 95% (95% CrI: 92%, 98%) across all age groups. As a function of time since symptom onset, LFD test sensitivity decays fastest in the youngest age group, reaching a minimum sensitivity of 0.26 (95% CrI: 0.16, 0.37) compared to 0.53 (95% CrI: 0.46, 0.6). Such patterns are expected since younger individuals experience less severe symptoms of COVID-19 and are likely to clear the virus faster. Females are found to have a slightly faster rate at which sensitivity decreases, but the same minimum sensitivity as Males. Combining the duration of positivity and test sensitivity distributions, we estimate the probability of returning a positive LFD test. Close to the symptom onset date, this probability is approximately 95%. However, this rapidly drops off, dropping below 5% after 13.8 days (95% CrI: 11.0 days, 17.3 days) for the youngest age group (3 to 17 years) and 17.8 days (95% CrI: 16.6 days, 19.2 days) for the 75 years and over age group. Although the probability of returning a positive LFD test rapidly drops off, it remains very high close to the time of symptom onset, which is when individuals are expected to be the most infectious.

The long-term impact of COVID-19 vaccination on post-acute COVID-19 symptoms and associated quality of life (QoL) changes remains incompletely described. This study aimed to explore the impact of the timing of COVID-19 priming and booster doses, on reporting long COVID symptoms and associated QoL changes. Individuals who had PCR testing for SARS-CoV-2 processed in government hospitals in Northern Israel between 15th March 2021 and 15th June 2022 were invited to answer serial online surveys collecting information on SARS-CoV-2 infection, vaccination status and post-acute symptoms every 3-4 months for two years. Participants were categorized into groups based on the number of doses received prior to infection. We compared these groups over time in terms of reporting post-COVID symptom clusters and QoL, using population-average and mixed-effects regression models, respectively. A total of 4809 individuals are enrolled and respond to up to five follow-up surveys. Of these, 1377 (28.61

Public health surveillance stratifies populations into age groups to help identify threats and provide appropriate responses. However, there is considerable variation in the age groupings used for epidemiology both between and within countries. We evaluate the age groups (under 1, 1-4, 5-14, 15-44, 45-64, over 65 years) used for syndromic surveillance in England. Comparing the existing age grouping with alternatives and using syndromic data to suggest new age groupings that maximise the homogeneity within groups and heterogeneity between groups. Data between November 2011 and March 2024 was extracted from four syndromic systems including 79 different syndromic indicators. Correlations between time series for individual ages in years were used to calculate homogeneity of specific age groups and age groupings (collections of age groups that completely span 0 to 90 years). Young adolescents were identified as a specific age group with distinct trends different to younger children or older adolescents. The current age group of 5 to 14 years was found to be more heterogeneous that over age groups, even those with a much wider span. Also, the age group over 65 years was assessed to be too broad and would benefit from being split into those over 90 years and below. Thus, our recommendation is a new age grouping for syndromic surveillance consisting of under 1s, 1 to 4, 5 to 8, 9 to 17, 18 to 33, 34 to 50, 51 to 67, 68 to 89 and over 90 years. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study did not receive any funding ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Only publically available aggregated surveillance data were used for this study. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

A central pillar of the UK’s response to the SARS-CoV-2 pandemic was the provision of up-to-the moment nowcasts and short-term projections to monitor current trends in transmission and associated healthcare burden. Here, we present a detailed deconstruction of one of the ‘real-time’ models that was a key contributor to this response, focussing on the model adaptations required over 3 pandemic years characterized by the imposition of lockdowns, mass vaccination campaigns, and the emergence of new pandemic strains. The Bayesian model integrates an array of surveillance and other data sources including a novel approach to incorporate prevalence estimates from an unprecedented large-scale household survey. We present a full range of estimates of the epidemic history and the changing severity of the infection, quantify the impact of the vaccination programme, and deconstruct contributing factors to the reproduction number. We further investigate the sensitivity of model-derived insights to the availability and timeliness of prevalence data, identifying its importance to the production of robust estimates.

During winter months, there is increased pressure on health care systems in temperature climates due to seasonal increases in respiratory illnesses. Providing real-time short-term forecasts of the demand for health care services helps managers plan their services. During the Winter of 2022-23 we piloted a new forecasting pipeline, using existing surveillance indicators which are sensitive to increases in respiratory syncytial virus (RSV). Indicators including telehealth cough calls and emergency department (ED) bronchiolitis attendances, both in children under 5 years. We utilised machine learning techniques to train and select models that would best forecast the timing and intensity of peaks up to 28 days ahead. Forecast uncertainty was modelled usings a novel generalised additive model for location, scale and shape (gamlss) approach which enabled prediction intervals to vary according to the level of the forecast activity. The winter of 2022-23 was atypical because the demand for healthcare services in children was exceptionally high, due to RSV circulating in the community and increased concerns around invasive group A streptococcal (iGAS) infections. However, our short-term forecasts proved to be adaptive forecasting a new higher peak once the increasing demand due to iGAS started. Thus, we have demonstrated the utility of our approach, adding forecasts to existing surveillance systems.

BACKGROUND:Understanding the effectiveness of SARS-CoV-2 vaccines over time is critical for informing booster strategies, vaccine types, and public health policies, particularly with the continued emergence of novel SARS-CoV-2 variants. METHODS:The Winter Coronavirus (COVID-19) Infection Study (WCIS), conducted from November 2023 to March 2024, involved approximately 150,000 participants aged 3 years and older from England and Scotland. The WCIS tested participants at regular intervals for SARS-CoV-2 using lateral flow tests to estimate prevalence and incidence in near real-time. Survival analysis using Cox proportional hazards regression was conducted, using WCIS data linked to participant vaccination records, to evaluate the association between time since vaccination and the risk of SARS-CoV-2 infection and symptomatic infection. Vaccine effectiveness (VE) was evaluated for the Comirnaty Omicron XBB.1.5 and Comirnaty Omicron BA.5 vaccines for those aged 65 years old and over. The model incorporated time-varying covariates within the counting process framework, stratified baseline hazards by age group, region, and time, and included key covariates such as sex, clinical risk status, ethnicity, and socioeconomic indicators. VE was estimated from hazard ratios, and penalised cubic splines were used to capture the nonlinear effects of time since vaccination. RESULTS:We estimated that the VE for the Comirnaty Omicron XBB.1.5 vaccine peaked at day 14 post-vaccination, reaching 70.63% (95% Confidence Intervals (CI): 43.33%, 84.78%) against infection and 63.62% (95% CI: 22.69%, 82.88%) against symptomatic infection. VE declined rapidly and by approximately weeks 9-12 post vaccination, the VE point estimates were close to zero with considerable uncertainty in the estimates from day 60 onwards. In contrast, the Comirnaty Omicron BA.5 bivalent vaccine showed little evidence of effectiveness within the study period, with VE estimates close to zero and wide confidence intervals crossing zero. CONCLUSIONS:These findings provide important insights into the effectiveness of targeted vaccine strategies in the context of an evolving pandemic. As SARS-CoV-2 continues to mutate, adaptive approaches in vaccine design and public health policy will be key to addressing emerging variants and protecting high-risk groups.

Introduction: Streptococcus pneumoniae is a leading cause of serious bacterial infections worldwide, including pneumonia, meningitis, and sepsis, especially in young children. The World Health Organization estimates that it is responsible for approximately 5% of global infant deaths [1]. Pneumococcal conjugate vaccines (PCVs) have been developed to protect against the most clinically relevant serotypes and introduced into infant immunization programs across multiple countries. PCV7, targeting seven serotypes, was followed by PCV13, extending protection to thirteen. These vaccines have substantially reduced vaccine-type invasive pneumococcal disease (VT-IPD). Nevertheless, over 80 additional serotypes remain uncovered [2; 3]. In recent years, several settings have reported increases in non-vaccine-type (NVT) IPD, suggesting possible serotype replacement. In England, this phenomenon has been particularly marked, raising concerns about whether the population-level benefits of PCVs might be offset. However, interpreting post-vaccination trends in IPD is challenging. Observed changes in disease incidence may reflect not only biological responses to vaccination but also coincident changes in surveillance systems, healthcare-seeking behaviour, diagnostic practices, or case definitions. Traditional before–after comparisons may misattribute such secular trends to vaccine effects, especially in ecological designs where randomized controls are absent. Objectives: We aim to estimate the causal impact of PCV7 and PCV13 introduction on IPD incidence in England, focusing on both direct reductions in VT-IPD and potential increases in NVT-IPD. A key goal is to disentangle true serotype replacement from surveillance-driven artifacts by constructing a data-driven counterfactual using unaffected pathogens as controls. Methods: We analysed monthly national IPD surveillance data in England from 2000 to 2018, covering the introduction of PCV7 in 2006 and PCV13 in 2010. To estimate the impact of vaccination, we employed a Bayesian structural time series (BSTS) model [4], a causal inference framework designed for population-level interventions without randomized control groups. The model accounts for seasonality, underlying trends, and time-varying confounders. To adjust for secular changes unrelated to PCVs, we used time series of other bacterial infections (H. influenzae, E. coli, S. aureus, P. aeruginosa, and others) as control outcomes. These pathogens share similar diagnostic pathways and reporting mechanisms but are unaffected by pneumococcal vaccination. The model included a spike-and-slab prior for Bayesian variable selection, allowing only those control series with high predictive value in the pre-intervention period to inform post-intervention counterfactuals. This synthetic control design improves robustness over simple before–after approaches and helps isolate vaccine effects from unrelated system-level changes. Results We estimate a 60% overall reduction in IPD incidence following the introduction of PCV7 and PCV13, comparing the pre-vaccine (2000–2006) and post-PCV13 (2011–2018) periods. The greatest reductions occurred among children under five (−73%). Specifically, PCV7-type IPD fell by 92% across age groups, and PCV13-type IPD declined by 42% following its introduction in 2010. These effects were consistent across subpopulations and robust to alternative model specifications. In contrast, NVT-IPD incidence increased by 36.5% after PCV7 and by 31.8% after PCV13 in raw surveillance data. However, when adjusted for confounding trends using control pathogens, the estimated increase in NVT-IPD was attenuated to +16% overall, with wide credible intervals and non-significant effects in most age groups. This suggests that previous unadjusted analyses may have overestimated the magnitude of serotype replacement by not accounting for coincident improvements in detection and reporting. Conclusions Our findings demonstrate that PCVs have had a substantial and sustained public health impact, dramatically reducing IPD caused by vaccine-covered serotypes. While serotype replacement is evident, much of the apparent increase in NVT-IPD can be explained by concurrent changes in surveillance and diagnostic practices rather than biological displacement alone. By leveraging control pathogens and a Bayesian synthetic control approach, we provide more credible causal estimates than conventional time series analyses. These results are important for public health planning and support continued investment in pneumococcal immunization, particularly as higher-valency PCVs are developed. Future evaluations of vaccine impact should incorporate similar causal modelling strategies to avoid misinterpretation of surveillance-based trends.

Background:In 2022, a global mpox outbreak occurred among gay and bisexual men who have sex with men (GBMSM). In England, the outbreak was controlled through reductions in sexual risk behaviour and vaccination of high-risk GBMSM. However, mpox continues to circulate, including an expanding outbreak in Africa. We evaluated the most cost-effective vaccination strategy to minimise future mpox outbreaks among GBMSM in England. Methods:A mathematical model of mpox transmission among GBMSM was developed to estimate the costs per quality-adjusted-life-year (QALY) gained for different vaccination strategies starting in 2024 (10-year time-horizon; 3.5% discount rate; willingness-to-pay threshold £20,000/QALY). Reactive vaccination (only during outbreaks) and/or pre-emptive vaccination (continuous routine) strategies targeting high-risk GBMSM were compared to no vaccination. Baseline projections assumed importation of new mpox cases, and a vaccine effectiveness following 1/2 doses of 78%/89% for 5/10 years at £160/dose. Costs were estimated for case management, vaccination and public health responses during an outbreak. Findings:All vaccination strategies reduced future outbreaks, gained QALYs and reduced costs compared to no vaccination. Continuous pre-emptive vaccination (daily rate 54 doses) with reactive vaccination (daily rate 81 doses) if there is an outbreak was most cost-effective, saving £8.8 million and gaining 108.6 QALYs over 10-years. Vaccination remains cost-effective if the vaccine costs less than £330/dose. Pre-emptive with reactive vaccination remains the preferred strategy across many sensitivity analyses, with just pre-emptive vaccination at a higher rate becoming the preferred strategy in some sensitivity analyses. Just reactive vaccination only becomes the preferred strategy when public health response costs are not included, and in this case the vaccine has to cost less than £110 per dose for vaccination to be cost-effective. Interpretation:Vaccination of high-risk GBMSM is likely to be a cost-saving strategy for preventing future mpox outbreaks. Funding:NIHR and Wellcome Trust.