The Lancet

Introduction: Respiratory infections are a leading cause of morbidity. Newly available vaccines to prevent respiratory syncytial virus (RSV) disease and encouraging clinical progress on vaccines for human metapneumovirus (hMPV) and parainfluenza (PIV) could reduce the disease burden beyond existing influenza and SARS-CoV-2 immunisation programs. However, evidence on the contribution of these viruses to respiratory disease burden across the lifespan remains limited. Methods: We reviewed studies from 01/2002-11/2025 reporting age-stratified, medically attended cases of influenza, and at least one of RSV, hMPV, or PIV, in high-income countries, excluding periods substantially overlapping with the COVID-19 pandemic. Using only studies that tested for all four viruses, we estimated the age-specific proportion of cases that were non-influenza (total across RSV, hMPV and PIV) compared to influenza using a mixed-effects logistic regression model. Results: Following exclusions and screening, 61 studies were included in the primary analysis comprising >500,000 detections of the four viruses. We found that a substantial proportion of medically attended respiratory illness in infants and young children was due to PIV, hMPV and RSV, rather than influenza, with a non-influenza virus proportion of 90.2% (95% CI 85.9-93.2%) in young infants aged 0-6 months. The converse was true for school-aged children, with a non-influenza virus proportion of 34.8% (95% CI 26.5-44.2%) in children aged 5-18 years. In adults aged 65+ years, non-influenza causes of medically attended disease were common at 60.2% (95% CI 50.0-69.5%). Restricting to studies reporting hospitalised cases (n=19) produced broadly similar age-specific trends in relative virus burden contributions. Discussion: We highlight the significant burden of medically attended illness due to PIV, hMPV and RSV across ages, particularly in infant and preschool-aged children and older adults, supporting the need for effective vaccines targeting this burden.

BackgroundViet Nam has one of the worlds most diverse hepatitis C virus (HCV) epidemics, dominated by genotype 6. Understanding pre-treatment resistance-associated substitutions (RASs) particularly in under-studied genotype 6 is essential to protect cure rates and guide national elimination strategies. We aimed to evaluate the landscape of viral diversity and baseline drug resistance in Vietnam. MethodsWe utilized whole-genome sequencing to analyze HCV isolates from a cohort of 1,649 patients enrolled in six clinical studies in Viet Nam between 2013 and 2023. The study assessed genotype and subtype distribution, associations with demographic and clinical variables, and prevalence of known and putative RASs in NS3, NS5A, and NS5B relevant to DAAs used in Viet Nam. FindingsPhylogenetic analysis revealed that genotype 6 was dominant (50.3%, 829/1,649). We observed distinct geographical and demographic partitioning: genotype 2 was concentrated in the south and associated with older age and HIV co-infection, while genotype 3 was clustered in the north among younger males. Clinically relevant RASs were detected in 37.9% (617/1,630) of patients, with the highest burden in NS5A region. Genotypes 2 and 3 displayed near-universal intrinsic resistance. Among genotype 6 infections, subtype 6a frequently carried L28F mutation (43.3%, 181/418), whereas subtype 6e remained largely susceptible. InterpretationViet Nam is characterized by a complex, genotype 6-predominant HCV epidemic with significant reservoirs of natural resistance. The high-level resistance mutations in genotypes 2 and 3 suggests that "pan-genotypic" regimens may face efficacy gaps, highlighting the need for subtype-level molecular surveillance to guide national treatment policies.

BackgroundBacterial co-infection contributes substantially to influenza-associated morbidity and mortality. Patterns of viral circulation, diagnostic testing and antimicrobial use changed markedly during the COVID-19 pandemic, yet contemporary estimates of bacterial co-infection and antimicrobial use in influenza have not been synthesised. ObjectivesTo estimate the pooled prevalence of microbiologically confirmed bacterial co-infection among hospital-attended patients with laboratory-confirmed influenza. Secondary objectives were to characterise co-infecting bacterial pathogens, quantify antimicrobial prescribing overall and across key subgroups. This study was registered with PROSPERO (CRD420251072782). Data sources and eligibilityWe searched Embase (Ovid), MEDLINE, PubMed, Scopus, and Web of Science to 15th June 2025 for English-language studies including [≥]50 hospital-attended patients with laboratory-confirmed influenza and reporting bacterial co-infection. MethodsPooled prevalence estimates and antimicrobial prescription proportions were calculated using a generalised linear mixed model with logit link. Subgroup analyses included age group, clinical setting, and seasonal vs. pandemic influenza. Risk of bias was assessed using ROBINS-E and certainty of evidence using GRADE. ResultsNinety-three studies from 30 countries, comprising 111,889 patients with influenza, met inclusion criteria; 9,899 had confirmed bacterial co-infection. The pooled prevalence was 17.3% (95%CI 13.6-21.7%; I2=99.2%). Prevalence was higher in ICU compared to non-ICU settings (28.3% vs. 13.6%). The most frequently identified bacterial pathogens were Streptococcus pneumoniae (35.7%) and Staphylococcus aureus (30.3%). Antimicrobial use, reported in 38 studies, was high (pooled prevalence 88.1%, 95%CI 76.0-94.5%; I2=99.9%), and was more common in adults than children (97.8% vs 65.0%), and in ICU compared with non-ICU settings (96% vs 81%). ConclusionsBacterial co-infection was identified in approximately one in six hospital-attended influenza cases, yet antimicrobial prescribing is near-universal. Substantial heterogeneity and diagnostic variability constraint interpretation but underscore persistent challenges in clinical decision-making. These findings support strengthened diagnostic capacity and antimicrobial stewardship to optimise management of suspected influenza-associated bacterial co-infection.

BackgroundUnited Kingdom Standards for Microbiology Investigations limits the pre-analytical delay of blood cultures to a maximum of four-hours between collection and incubation. Compliance with this delay standard is a measure of the ability of a microbiology service to support the management of sepsis which is a life-threatening complication of infection. A positive blood culture confirms the infection and an early result is critical to the effective management of the condition. Delayed results lead to the prolongation of empiric broad spectrum antimicrobial therapy which is considered a causal factor in the emergence of antimicrobial resistance. This retrospective observational study documents compliance with the standard by microbiology services in England in 2022/23. The impact of laboratory centralisation on the ability of microbiology services to comply with this standard is examined. MethodsFreedom of Information requests were submitted to 116 National Health Service Trusts/administrative units in England requesting retrospective audit data showing compliance with the recommended pre-analytical delay standard. Data relating to service configuration and cost were also requested. ResultsResponses were received from 89 Trusts (76.7%) managing 146 hospitals. Overall, the rate of compliance was low, with only four hospitals (2.7%) showing full compliance and 31.5% showing >80% compliance. ConclusionsPoor rates of compliance with the PAD standard are a concern as prompt attention to blood cultures improves patient outcomes from sepsis and supports antimicrobial stewardship. Laboratory centralisation has resulted in withdrawal of staff and facilities from some hospitals with insufficient investment in others, leading to a demonstrable inability of many hospitals to comply with this standard. Compliance will require investment in microbiology services. The financial implications of the improvements proposed should be evaluated in the context of overall health care and community benefits.

Of the two influenza A virus (IAV) subtypes circulating endemically in humans, A/H3N2 and A/H1N1pdm09, A/H3N2 has historically been the dominant driver of disease burden in older adults. Based on an analysis of publicly available global surveillance data from 2015 to 2025 (>300,000 subtyped, age-stratified infections), we report a substantially increased contribution of A/H1N1pdm09 to influenza morbidity in older adults since approximately 2022. Birth cohort-stratified analyses suggest elevated A/H1N1pdm09 burden among individuals born before 1955-1959, consistent with erosion of pre-existing immunity originally generated by exposure to historical A/H1N1 strains. Pooled estimates across datasets and analytical approaches indicate the increase in A/H1N1pdm09 burden rises with earlier birth year, ranging from 1.22-fold (95% CI 1.08-1.37) for the 1955-1959 birth cohort to 3.10-fold (95% CI 2.58-3.72) for the 1930-1934 cohort. These findings point to a substantial rise in the overall influenza burden among the most vulnerable age groups, with implications for vaccine policy, clinical management, and public health planning.

BackgroundNovel HIV prevention interventions such as long-acting pre-exposure prophylaxis (PrEP) could substantially reduce HIV transmission in Africa. However, efficient implementation in high-prevalence settings where incidence has declined requires an understanding of the contemporary dynamics driving new infections. MethodsWe identified incident HIV cases from a longitudinal, population-based cohort in Uganda. We individually matched cases to HIV-negative controls; traced and enrolled reported sexual partners; and enrolled female sex workers (FSWs) from reported venues. Conditional logistic regression, transmission modeling, and phylogenetics were used to characterize transmission networks. FindingsFrom 2021-2024, 38,899 HIV tests among 22,255 people identified 187 people with incident infections (47.6% male); 164 (88%) were enrolled and matched to 164 HIV-negative controls. Overall, 593 non-sex-worker partners (371 enrolled,62.6%), 146 FSW partners (21 enrolled,14.4%), and 28 venues (208 FSWs enrolled) were reported. Incident infection was most strongly predicted by partnership with a FSW (odds ratio:15.5; 95%CI:3.7-64.8), identified in 43.0% of male cases versus 6.3% of controls. Men with FSW partners had larger sexual networks than men without (median:6 vs 2 partners), and 91.2% of men with FSW partners also had non-sex-worker partners. Transmission modeling attributed 34.4% (95%CI:31.5-36.8%) of all male infections and 80.0% (95%CI:73.2-84.4%) of infections among male clients to sex with FSWs. Oral PrEP use among HIV-negative partners of incident cases was low (8.9% in women; 2.1% in men). InterpretationMen with FSW partners accounted for a substantial share of incident HIV infections and had markedly higher odds of infection than men without such partnerships. Together with the high potential for onward transmission within male client networks, these findings suggest that inclusion of male clients in long-acting HIV prevention strategies could be highly efficient and impactful. FundingNational Institutes of Health, United States; Gates Foundation; National Health and Medical Research Council, Australia

BackgroundIn England, the burden of respiratory infections varies by ethnicity, contributing to health inequalities, but the role of additional demographic factors remains underexplored. We quantified how differences in social mixing and demographic characteristics between ethnic groups cause inequalities in transmission dynamics. MethodsWe analysed the association between the ethnicity and the number of contacts of 12,484 participants in the 2024-2025 Reconnect social contact survey, using a negative binomial regression model. We simulated respiratory pathogen epidemics using a compartmental model stratified by age, ethnicity, and contact levels, at a national level and in major cities in England. FindingsAfter adjusting for demographic variables, participants of Black and Mixed ethnicities had more contacts than those of White ethnicity (rate ratios (RR): 1.18 [95% Credible Interval (CI): 1.11-1.26], and 1.31 [95% CI: 1.14-1.52]). Participants of Asian ethnicity had fewer contacts (RR: 0.85 [95% CI: 0.79-0.91]). In national-level simulations, individuals of White ethnicity had the lowest attack rates due to demographic differences and mixing patterns. Local demographic structures changed simulated dynamics: attack rates in individuals of Black and Mixed ethnicities were approximately double those of White ethnicity in Birmingham, but less than 60% higher in Liverpool. InterpretationDemographic characteristics and mixing patterns create inequalities in transmission dynamics between ethnicities, while local demographic characteristics and pathogen infectiousness change the expected relative burden. To ensure mitigation strategies are effective and equitable, their evaluation must explicitly account for inequalities arising from local context. FundingMedical Research Council, National Institute for Health and Care Research, Wellcome Trust Research in context Evidence before this studyWe searched PubMed for population-based studies quantifying differences in respiratory infections between ethnic groups, up to 1 April 2026, with no language restrictions. Keywords included: (respiratory pathogens OR influenza OR COVID-19) AND (ethnic* OR race) AND (inequ*) AND (compartmental model OR incidence rate ratio OR hazard ratio). We excluded studies that focused on non-respiratory pathogens (e.g. looking at consequences of COVID-19 on incidence of other pathogens). A population-based cohort study showed that influenza infection risk was higher in South Asian, Black, and Mixed ethnic groups compared to White ethnicity in England. Another population-based cohort study highlighted that during the first wave of COVID-19 in England, the South Asian, Black, and Mixed ethnic groups were more likely to test positive and to be hospitalised than the White ethnic group. Census data in England showed that the distributions of age, household size, household income and employment status differed between ethnic groups, and the recent Reconnect social contact surveys highlighted the impact of each demographic factor on the participants number of contacts. Added value of this studyOur study shows that social contact patterns, mixing, and demographic structure all lead to unequal infection risk between ethnic groups in respiratory pathogen epidemics. Using the largest available social contact survey in England, we show that both the average number of contacts and the proportion of high-contact individuals varied by ethnic group, even after adjusting for participants demographics. These differences, together with mixing patterns and age structure, led to lower expected incidence among individuals of White ethnicity than in all other ethnic groups in simulated outbreaks. The level of inequality between ethnic groups changed when we used different values of pathogen transmissibility. Finally, as ethnic composition and population structure differ between cities in England, our results show differences in expected inequalities at a local level. Implications of all the available evidenceInequalities in infection risk between ethnic groups are context- and pathogen-dependent. They arise from both local population structure and contact patterns. Detailed information on mixing between groups and population structure is needed to accurately measure group-specific infection risk. These findings indicate that public health interventions based only on national-level estimates conceal regional variation in risk and may ultimately increase inequalities. Public health interventions need to be tailored to local contexts to be equitable and effective. Finally, our findings provide a foundation for understanding the progression from infection-risk inequalities to disparities in disease presentation and clinical outcomes.

BackgroundIn England, individuals with chronic liver disease (CLD) are among those with the lowest seasonal influenza vaccine uptake despite being at elevated risk of severe influenza. We examined the relationship between CLD severity and aetiology, and influenza vaccine uptake in England. MethodsA retrospective cohort study of adults (18-115 years) using Clinical Practice Research Datalink Aurum primary care data was conducted for five seasons (2019/20-2023/24). Poisson regression was used to estimate rates of uptake by CLD severity (clinical diagnoses categorised as low, moderate, or severe) and aetiology (alcohol-related, viral-related, and diagnoses in the Green Book guidelines). FindingsThere were 182,174-277,470 with CLD per cohort. Among those who were additionally age-eligible for vaccination, uptake was 71{middle dot}1-79{middle dot}7% compared to 30{middle dot}9-40{middle dot}5% in those not additionally age-eligible. Among individuals below age eligibility without other comorbidities, severity was associated with higher uptake (incidence rate ratio [IRR] moderate 1{middle dot}80, 95% CI 1{middle dot}69-1{middle dot}90; severe 1{middle dot}95, 95% CI 1{middle dot}84-2{middle dot}08 in 2023/24); there was no effect in those with at least one additional comorbidity (moderate 1{middle dot}05, 95% CI 0{middle dot}99-1{middle dot}10; severe 1{middle dot}05, 95% CI 1{middle dot}01-1{middle dot}09). Alcohol- and viral-related aetiology were also associated with increased uptake in those not additionally age-eligible. Among individuals meeting age eligibility without additional comorbidities, severity was associated with a reduced uptake (moderate 0{middle dot}81, 95% CI 0{middle dot}73-0{middle dot}90; severe 0{middle dot}79, 95% CI 0{middle dot}74-0{middle dot}85), with attenuation in those with additional comorbidities (moderate 0{middle dot}99, 95% CI 0{middle dot}94-1{middle dot}04; severe 0{middle dot}91, 95% CI 0{middle dot}89-0{middle dot}94). InterpretationCLD severity and aetiology were important determinants of uptake in the absence of additional indications for influenza vaccination. Future research should prioritise understanding facilitators and barriers to vaccine uptake in individuals with CLD, particularly for those at highest risk of severe infection. FundingNIHR Health Protection Research Unit in Vaccines and Immunisation (NIHR200929/NIHR207408). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed up to June 2025 using the terms "chronic liver disease", "cirrhosis", "hepatitis", "influenza vaccination", "seasonal influenza", and "vaccine uptake". Previous research, including national data from England, has shown that people with chronic liver disease tend to have lower seasonal influenza vaccine uptake than individuals with other medical comorbidities which qualify for vaccination such as diabetes, chronic kidney disease or immunosuppression. The reasons for low influenza vaccine uptake in people with chronic liver disease are not well understood, and it is therefore difficult for vaccination providers, principally primary care services in England, to tailor interventions aimed to increase uptake. Qualitative research involving individuals aged less than 65 years living in England with clinical risk comorbidities, most commonly diabetes, found that chronic disease management pathways inconsistently provided information about the importance of influenza vaccination as part of chronic disease management. Individuals with long-term conditions reported low perceived risk of influenza infection and limited awareness of vaccine benefits as important reasons for non-uptake. We hypothesised that the severity and aetiology of chronic liver disease may be important determinants of uptake. Added value of this studyWe conducted a population-based study to examine how chronic liver disease severity and aetiology influence seasonal influenza vaccine uptake in adults in England. Using primary care electronic health record data from five consecutive influenza seasons (2019/20-2023/24), we found that more severe chronic liver disease was associated with a substantial increase in vaccine uptake in those without additional indications for seasonal influenza vaccination (age-based eligibility or other qualifying clinical risk comorbidities). Alcohol- and viral-related aetiology were also associated with increased uptake in those who were not additionally age-eligible for vaccination. In contrast, severity, alcohol- and viral-related underlying aetiology were associated with a modest reduction in uptake for individuals with chronic liver disease who also qualified for vaccination due to age. Implications of all the available evidenceDespite clear clinical vulnerability to infection and a substantially elevated risk of morbidity and mortality following infection, a large proportion of adults with chronic liver disease, particularly those aged under 65 years, remain unvaccinated against seasonal influenza each year. This study suggests that chronic liver disease severity and underlying aetiology are important determinants of uptake in individuals not meeting age-based vaccine eligibility, particularly in those without additional clinical risk comorbidities. This could be because of differing perceptions of influenza risk, or due to varying degrees of interaction with healthcare specialists as part of chronic disease management. In individuals who met age-based vaccination eligibility, the negative effect of severity on influenza vaccine uptake may reflect greater barriers to accessing vaccination services by those with more complex health needs, or competing medical priorities for long-term condition management during consultations. To inform targeted vaccination strategies, future research should aim to understand the specific facilitators and barriers to influenza vaccination experienced by individuals with chronic liver disease. This should include perspectives of individuals with different disease severity, across different age groups, in those with and without additional co-morbidities.

BackgroundVietnams disease burden has shifted from communicable, maternal, neonatal, and nutritional (CMNN) causes to non-communicable diseases (NCDs), but the tempo, drivers, and regional positioning of this transition have not been jointly quantified. We characterised Vietnams epidemiological transition 1990-2023 against ten Southeast-Asian (SEA) peers. MethodsUsing Global Burden of Disease 2023 data, we computed joinpoint-regression AAPC with 95% CI (BIC-penalised, up to three break-points) for age-standardised DALY rates and cause-composition shares. We applied Das Gupta three-factor decomposition to 1990-2023 absolute DALY change (population-size, age-structure, age-specific-rate effects) and benchmarked Vietnams NCD share against an SDI-conditional peer trajectory via leave-one-out quadratic regression. Premature mortality was quantified as WHO 30q70 under both broad NCD and strict SDG 3.4.1 definitions, using Chiang II life-table adjustment identically across all eleven countries. FindingsThe CMNN age-standardised DALY rate fell from 13,295.9 to 4,022.1 per 100,000 (AAPC -4.63%/year; 95% CI -4.80 to -4.46); the NCD rate fell only from 21,688.2 to 19,282.8 (AAPC -0.37; -0.45 to -0.30). NCD share of total DALYs rose from 52.99% to 70.67% (+17.67 pp; AAPC +1.09). Vietnam ranked fourth of eleven SEA countries in 2023 (up from sixth in 1990) and sat 5.3% above the SDI-expected trajectory. Das Gupta decomposition attributed the +10.63 million NCD DALY increase to population growth (+6.26 M) and ageing (+6.08 M); rate change removed only 1.71 M. Premature NCD mortality fell from 25.02% to 21.80% (broad, 12.9% reduction) and from 22.17% to 19.50% (SDG 3.4.1, 12.0%; Vietnam sixth of eleven) - far short of the SDG 3.4 one-third-reduction target. InterpretationVietnam has entered a disability- and ageing-dominated NCD phase. Meeting SDG 3.4 by 2030 requires population-scale primary prevention sized to demographic momentum. FundingThis research received no specific grant from any funding agency.

Background. Infectious mononucleosis (IM) with hepatitis is associated with suppression of high-density lipoprotein cholesterol (HDL-C), but the magnitude, specificity, recovery kinetics, and long-term cardiovascular implications of this finding have not been systematically characterised. Methods. Using the TriNetX Global Collaborative Network (<190 million patients, 178 healthcare organisations), we conducted a retrospective real-world evidence study in 1,944 adults with IM and hepatitis. We compared HDL-C distributions at presentation across 14 propensity-score-matched (PSM) comparator cohorts spanning other infectious, metabolic, and immune-mediated conditions. Gaussian mixture modelling characterised the HDL distribution. Longitudinal HDL trajectory was assessed across six post-index time windows, with the number of patients contributing a measurement ranging from 318 (16-30 days) to 2,849 (1-3 years) per window. Long-term major adverse cardiovascular events (MACE) were analysed in PSM cohorts of IM patients with very low HDL ([&le;]20 mg/dL, n = 979 per arm after PSM) versus those without low HDL, over up to 20 years of follow-up, with COVID-19 (n = 83,888 per arm) and pharyngitis (n = 10,618 per arm) as comparators. Results. At presentation, mean HDL in IM hepatitis was 36.7 +/- 22.6 mg/dL (median 33 mg/dL), ~14-17 mg/dL lower compared to pre-illness values. Nearly one quarter (23.9%) had HDL [&le;]20 mg/dL and 43.9% had HDL [&le;]30 mg/dL. HDL suppression was equivalent to CMV hepatitis but substantially greater than pharyngitis and IM without hepatitis, supporting a hepatitis-driven mechanism. Gaussian mixture modelling identified a discrete suppressed subpopulation (mean 16 mg/dL, 41% of patients) absent in non-hepatitis controls. Recovery was rapid in most patients (mean HDL 50.0 mg/dL by 16-30 days) but prolonged among the severely suppressed ([&le;]20 mg/dL), who required 3-6 months to approach baseline. In PSM MACE analyses, IM patients with very low acute HDL had significantly higher long-term event rates for all outcomes (HR 1.92-2.47 versus IM without low HDL), a pattern mirrored in the COVID-19 cohort (HR 2.04-2.70) and, with attenuated effect size, in pharyngitis (HR 1.43-1.69). Conclusions. Very low HDL-C is a prevalent, hepatitis-driven finding in IM affecting approximately one quarter of patients. It identifies a subgroup at elevated long-term cardiovascular risk comparable to that observed after COVID-19. These findings warrant prospective evaluation of cardiovascular follow-up strategies for affected patients.

ObjectivesTo determine whether heterogeneous treatment effects (HTE) explain the inconclusive results of targeted temperature management (TTM) trials after cardiac arrest, using causal machine learning across four datasets. DesignSecondary analysis of one multicenter RCT and three observational ICU cohorts using S-learner and forest-based R-learner models to estimate conditional average treatment effects (CATE). SettingTwenty-six French ICUs (HYPERION), approximately 200 U.S. ICUs (eICU-CRD), Johns Hopkins Hospital (PMAP), and Beth Israel Deaconess Medical Center (MIMIC-IV). PatientsAdults ([&ge;]18 years) with cardiac arrest; 4,507 patients across the four datasets, of whom 1,814 (40.2%) received TTM. InterventionsTTM as administered clinically or per HYPERION protocol. Ascertainment: randomization (HYPERION), treatment documentation (eICU-CRD), sustained hypothermia <36{degrees}C for >12 hours (PMAP), or documented cooling device use [&ge;]12 hours (MIMIC-IV). Measurements and Main ResultsThe primary outcome was hospital mortality; the secondary outcome was favorable neurologic function (Cerebral Performance Category 1-2 at 90 days for HYPERION; last motor Glasgow Coma Scale = 6 for observational cohorts). Three S-learner models (XGBoost, neural network, Bayesian Additive Regression Trees) and one forest-based R-learner (CausalForestDML) estimated CATE. HTE was assessed by likelihood-ratio tests for CATExtreatment interaction, CausalForestDML 95% confidence intervals, Group Average Treatment Effects (GATES) across CATE quintiles, and SHAP feature importance. S-learner discrimination was adequate (AUROC 0.72-0.82). No model showed a significant CATExTTM interaction in any dataset (all p > 0.05). Individual CATE confidence intervals uniformly crossed zero, and GATES showed no monotonic gradient of benefit across quintiles in any dataset. ConclusionsAcross four diverse datasets and multiple causal machine-learning approaches, we found no evidence of heterogeneous treatment effects for TTM after cardiac arrest. The inconclusive findings of TTM trials are unlikely explained by differential effects in identifiable subgroups defined by routinely available clinical features. KEY POINTSQuestion: Do identifiable patient subgroups derive differential benefit from targeted temperature management (TTM) after cardiac arrest? Findings: In a causal machine-learning analysis of 4,507 patients across one randomized trial and three observational ICU cohorts, no model detected significant heterogeneous TTM effects on mortality or neurologic outcome. Meaning: Conflicting TTM trial results are unlikely explained by differential effects in identifiable subgroups, weakening the rationale for personalized TTM strategies based on routinely available clinical features.

BackgroundRibavirin is a guanosine analogue with clinical antiviral activity against a range of RNA viruses including hepatitis C virus (HCV), respiratory syncytial virus and Lassa virus. Several potential mechanisms of action have been proposed, but there is limited data supporting them clinically. MethodsWe studied 196 HCV-infected participants from a trial of short-course directly antiviral therapy (STOPHCV-1) which included a factorial randomisation to ribavirin versus no ribavirin. Deep sequencing of the HCV genome was performed on samples with detectable viremia from three time-points: baseline (n = 191), day 3 of treatment (n = 25) and post-treatment failure (n = 47). ResultsRibavirin exposure significantly increased total mutational load at treatment failure (P = 0.0065) and enriched classical ribavirin-associated transitions, including G[-&gt;]A (P = 0.026) and C[-&gt;]U (P = 0.004), along with other key changes including A[-&gt;]G (P = 0.005), U[-&gt;]C (P = 0.023), C[-&gt;]G (P = 0.010), and U[-&gt;]A (P = 0.026). Ribavirins mutational signature was broad, not dominated by G-related changes. Region-specific analyses demonstrated this increase was broadly distributed across the viral genome, without strong evidence for protection of specific regions. Non-synonymous to synonymous mutation ratios (dN/dS) rose at day 3 (P = 5.5e-5) before declining at failure (P = 8.5e-7), with trends toward higher dN/dS in the ribavirin group at day 3 (P = 0.06). ConclusionsRibavirin acts as a potent in vivo mutagen, driving viral populations toward genome-wide diversity rather than selecting a few highly fit drug-resistant clones. These findings support an error-catastrophe model.

BackgroundInfluenza A(H1N1)pdm09 and A(H3N2) viruses predominated during the 2024-25 U.S. influenza season. We estimated influenza vaccine effectiveness (VE) in the United States against mild-to-moderate outpatient influenza illness by influenza type and subtype in the 2024-25 season. MethodsWe enrolled outpatients aged [&ge;]8 months with acute respiratory illness symptoms including cough in 7 states. Upper respiratory specimens were tested for influenza type/subtype by reverse-transcriptase polymerase chain reaction (RT-PCR). Influenza VE was estimated with a test-negative design comparing odds of testing positive for influenza among vaccinated versus unvaccinated participants controlling for age, study site, underlying health status, and month of illness onset. We also estimated VE of current season vaccination among adults stratified by prior season vaccination status. ResultsAmong 6,793 enrolled patients, 2,016 (30%) tested positive for influenza including 961 A(H3N2), 770 A(H1N1)pdm09, and 183 B/Victoria. Overall vaccine effectiveness against any influenza illness was 33% (95% Confidence Interval [CI]: 24 to 41): 27% (95% CI: 14 to 39) against influenza A(H3N2), 37% (95% CI: 24 to 48) against A(H1N1)pdm09, and 40% (95% CI: 12 to 59) against B/Victoria. VE did not differ based on whether or not participants had received influenza vaccine the previous season. ConclusionsInfluenza vaccination during the 2024-25 season protected against circulating influenza viruses, reducing the risk of outpatient medically attended influenza overall by approximately one-third among people who were vaccinated. Key PointsInfluenza vaccine reduced the risk of outpatient acute respiratory illness due to laboratory-confirmed influenza during the 2024-25 season by a third.

Background: The U.S. 2024-2025 influenza season was characterized by sustained elevated activity from November 2024 to April 2025, with circulation of both influenza A(H1N1)pdm09 and A(H3N2), the latter of which included some antigenically drifted viruses. Methods: From October 1, 2024, to April 30, 2025, a multistate respiratory virus surveillance network enrolled adults hospitalized with acute respiratory illness in 26 U.S. medical centers. Influenza vaccine effectiveness (VE) against influenza-associated hospitalization and severe in-hospital outcomes was estimated using a test-negative study. The odds of influenza vaccination among influenza-positive case patients and influenza-negative control patients were compared using multivariable logistic regression; VE was calculated as (1-adjusted odds ratio for vaccination) x 100, expressed as a percent. Results: The 2024-2025 seasonal influenza vaccine was effective against influenza-associated hospitalization (VE: 40% [95% confidence interval (CI): 32%-47%]), consistent across age group and influenza A subtypes. Influenza vaccination also reduced the overall risk of all severe in-hospital outcomes evaluated, including standard oxygen therapy (VE: 41% [95% CI: 31%-50%]), non-invasive advanced respiratory support (VE: 38% [95% CI: 19%-52%]), invasive organ support (VE: 58% [95% CI: 44%-69%]), ICU admission (VE: 58% [95% CI: 47%-67%]), and death (VE: 52% [95% CI: 18%-71%]) with effectiveness varying by influenza A subtype and age. Conclusions: Influenza vaccination reduced the risk of influenza-related hospitalization and severe in-hospital outcomes in adults during the severe 2024-2025 influenza season compared to those not vaccinated.

Background Post-acute sequelae are well described following COVID-19 but may also occur after other respiratory infections and Aedes-borne infections. Evidence remains fragmented due to heterogeneity in study design, populations, and exposure, outcome, and follow-up definitions. Methods We synthesized and compared post-acute sequelae across influenza, RSV-ARI, dengue fever, chikungunya, Zika, and yellow fever. We searched five databases from inception to 25-08-2025 for articles quantifying risk, incidence, or rates of post-acute sequelae following these diseases. Eligible non-randomized observational studies assessed post-acute neurological, psychiatric, gastrointestinal, cardiovascular, respiratory, renal, musculoskeletal, autoimmune, or endocrine outcomes after confirmed infection. Risk of bias was assessed using ROBINS-E. Random-effects meta-analyses with restricted maximum likelihood estimation were conducted when comparable effect estimates were available (PROSPERO #CRD420251124994). Findings 51 studies were included, predominantly from high-income regions. Most were retrospective cohorts using ICD-coded diagnoses; prospective studies used laboratory-confirmed infections. Data sources, comparator groups, exposure definitions, outcome ascertainment, and follow-up periods varied substantially. Meta-analyses were feasible for RSV, influenza, and dengue fever. All RSV-ARI studies were pediatric and assessed infections during infancy, which were associated with higher pooled odds of physician-diagnosed asthma (OR:2.93 [95%CI: 2.12-4.06]). Influenza studies used COVID-19-positive comparators; pooled estimates showed lower risk for neurological (HR:0.82 [0.76-0.89]) and composite outcomes (RR:0.88 [0.82-0.95]), with other organ systems non-significant. Dengue fever studies spanned all ages and showed increased risks of anxiety (HR:1.34 [1.01-1.78]), dementia (HR:1.61 [1.10-2.35]), autoimmune (RR:1.39 [1.17-1.67]), cardiovascular (HR:1.51 [1.27-1.80]), psychiatric (HR:1.17 [1.07-1.28]), and any sequelae (HR:1.19 [1.13-1.25]) versus those without prior infection. Interpretations Post-acute sequelae contribute to overall disease burden following RSV-ARI and dengue fever. The evidence remains limited by heterogeneity in study design, exposure and outcome definitions, comparator selection, and follow-up duration. Greater standardization in study design and reporting is needed to improve comparability and strengthen causal inference.

Background/ObjectivesThe trajectory of influenza hospitalization burden from pre-pandemic baseline through post-pandemic recovery remains poorly characterized at the national level. This study characterized phase-stratified burden and seasonal structure, quantified racial and ethnic disparities, and assessed whether post-pandemic seasons represent anomalous departures from pre-pandemic expectations. MethodsSixteen seasons of FluSurv-NET surveillance data (2009-2010 through 2024-2025; 509 observation weeks) were analyzed across pre-pandemic, disruption, and recovery phases using OLS regression with effect-size estimation, bootstrapped age-adjusted rate ratios, seasonal-trend decomposition (STL), Prophet time-series forecasting, and Isolation Forest anomaly detection. ResultsMean peak weekly hospitalization rate nearly doubled from pre-pandemic to recovery (5.1 to 11.1 per 100,000), cumulative seasonal burden increased from 46.3 to 87.0 per 100,000, and median peak timing advanced from MMWR week 9 to week 50. STL decomposition revealed a marked shift from weak pre-pandemic seasonality (Fs = 0.14) to substantially stronger annual regularity (Fs = 0.98) across three recovery seasons, with threefold amplitude increase. Non-Hispanic Black persons had rate ratios of 1.72, 2.16, and 1.99 relative to White persons across phases; American Indian and Alaska Native persons showed the highest disruption-phase ratio (2.24, 95% CI 1.90-3.53), based on two contributing seasons. A flat-growth Prophet model detected first exceedance in February 2020, outperforming a linear-growth specification on held-out validation. Isolation Forest identified 2017-2018, 2023-2024, and 2024-2025 as robust anomalies across all contamination thresholds. ConclusionsPost-pandemic influenza recovery is characterized by intensified and restructured seasonality, persistent racial and ethnic disparities, and anomalous burden exceeding pre-pandemic projections, identified independently by time-series forecasting and unsupervised anomaly detection.

Objectives To quantify the frequency of baseline control-group use in published long COVID prevalence studies and assess their key methodological features. Design Cross-sectional meta-epidemiological evaluation of published post-acute COVID-19 prevalence studies, supplemented by a corresponding-author survey. Setting Published studies identified through a systematic review by Hou et al. (2025) and supplementary data obtained through direct email contact with corresponding authors. Participants A total of 440 published long COVID prevalence studies. Main Outcome measures Presence and type of comparator group, reliance on solely self-reported outcomes, acknowledgment of lack of a control group among uncontrolled studies, and availability of additional comparator data through author survey. Results Among 440 studies, 372 (84.5%) reported no control group on their publication. Healthy or uninfected comparators were reported in 55 studies (12.5%) and other comparator types in 14 (3.2%); 1 study included both categories. Solely self-reported outcomes were used in 279 studies (63.4%). Among 372 uncontrolled studies, 244 (65.6%) did not explicitly acknowledge the absence of a baseline comparator as a limitation anywhere in text. Corresponding authors of 140 studies (31.8%) responded to the survey; among them, 126 (90.0%) reported no additional comparative data, while 14 (10.0%) mentioned some available comparative datasets (19 additional datasets). Almost all of that information (10/14, 17/19) had been already published in other articles not captured by the Hou et al. systematic review. Conclusions Most published long COVID prevalence studies lacked comparator groups and relied exclusively on self-reported outcomes without acknowledging this limitation. Direct author contact identified little additional comparator information. Much of the long COVID prevalence literature may therefore be poorly suited to estimating burden attributable specifically to SARS-CoV-2, underscoring the need for appropriately matched comparators and more objective outcome assessment. Registration The protocol was prospectively registered on the Open Science Framework (https://osf.io/f4hra).

ABSTRACT Background: Corticosteroids reduce mortality in severe COVID-19 requiring oxygen or invasive mechanical ventilation, yet emerging data suggest that SARS-CoV-2-associated acute lung injury is biologically heterogeneous and that treatment response may vary across molecularly defined disease states. Lung-derived molecular endotypes of severe COVID-19-associated acute lung injury have been described, but direct molecular profiling is not routinely available at the bedside. We evaluated whether a clinical predictor of previously defined lung molecular endotype identifies heterogeneity in corticosteroid treatment effect among mechanically ventilated patients with COVID-19. Methods: We utilized a single-center cohort of 5,000 patients with COVID-19 treated at the University of North Carolina Hospital between January 1, 2020, and December 31, 2022, to emulate a target trial assessing the effect of corticosteroid receipt on mortality, length of stay, and incident organ support. Confounding was addressed through inverse probability of treatment weighting (IPTW). Outcomes for severely ill patients requiring mechanical ventilation were compared to the RECOVERY trial results, with subsequent moderation analysis and stratified analysis by clinically predicted lung molecular endotype and vaccination status. The primary outcome was 28-day mortality. Secondary Outcomes were time to discharge alive and progression to additional organ support. Results: This emulated target trial showed a directionally favorable but non-statistically significant association between corticosteroid treatment and reduced 28-day mortality in patients requiring mechanical ventilation for SARS-CoV-2 infection. A clinical predictor of lung molecular endotype moderated the effect of corticosteroids on 28-day mortality (p-value for interaction 0.038) and identified distinct predicted endotype-specific treatment effect. Corticosteroid treatment was associated with lower 28-day mortality in the predicted Hyper-Inflammatory endotype (OR 0.62, 95% CI 0.39, 0.99) but not in the predicted Metabolic Dysregulation endotype (OR 1.15, 95% CI 0.82, 1.61). We did not detect significant effect modification by vaccination status (p-value for interaction 0.65), although inference was limited by the small, vaccinated subgroup (28-mortality OR 0.78, 95% CI 0.37, 1.65 in vaccinated vs 0.94, 95% CI 0.70, 1.26 in unvaccinated). Conclusions: In this target trial emulation of mechanically ventilated patients with severe COVID-19, corticosteroid treatment showed a directionally favorable but non-statistically significant association with reduced 28-day mortality in the overall cohort. However, a clinical predictor of lung molecular endotype identified significant heterogeneity in treatment effect, with benefit concentrated in the predicted Hyper-Inflammatory endotype and no apparent benefit in the predicted Metabolic Dysregulation endotype. These findings support prospective validation of clinically deployable endotype-guided corticosteroid treatment strategies in acute lung injury and ARDS.

Background: Wearing facemasks and practising social distancing slow the spread of respiratory pathogens. However, in the event of a new pandemic emerging, the willingness of populations to voluntarily adopt these behaviours is unclear. Methods: A discrete choice experiment was conducted among 2,006 UK-based adults. Participants were presented with hypothetical scenarios describing the emergence of a respiratory virus pandemic and were asked to choose when they would wear facemasks and practise social distancing. A mixed multinomial logit model was used to jointly estimate how disease severity and prevalence, uncertainty in these quantities, and individual-level characteristics influence behavioural choices. Findings: Participants were averse to facemasks and social distancing in the absence of pandemic risk. For each ten-unit increase in severity (10 additional hospitalisations/1,000 infections), the odds of always wearing a facemask outside the home increased by 15.9% (95%CI: 14.3%, 17.5%), relative to rarely/never, and the odds of avoiding all people as much as possible increased by 16.4% (14.6%, 18.2%), relative to not avoiding anyone. Greater disease prevalence, uncertainty in disease severity or disease prevalence, a university education, prior COVID-19 vaccination and non-white ethnicity were also associated with choosing to always wear facemasks and avoid all people as much as possible. The probability of participants choosing to rarely/never wear facemasks varied from 13.4% (11.9%, 14.9%) in the lowest-risk scenario to 1.4% (1.2%, 1.7%) in the highest-risk scenario. Interpretation: Perceived risks of disease and associated uncertainty drive intention of UK adults to adapt their behaviour in a future pandemic.

BackgroundThe 2024-25 influenza season was the most severe in the United States (US) since 2017-18, with co-circulation of both influenza A virus subtypes (H1N1 and H3N2). Influenza vaccine effectiveness (VE) has varied by season, setting, and patient characteristics. MethodsUsing electronic healthcare encounter data from eight US states, we evaluated influenza vaccine effectiveness (VE) against influenza-associated hospitalizations and emergency department or urgent care (ED/UC) encounters from October 2024-April 2025 among children aged 6 months-17 years and adults aged [&ge;]18 years. Using a test-negative, case-control design, we compared the odds of influenza vaccination between acute respiratory illness (ARI) encounters with a positive (cases) versus negative (controls) test for influenza by molecular assay, adjusting for confounders. ResultsAnalyses included 108,618 encounters (5,764 hospitalizations and 102,854 ED/UC encounters) among children and 309,483 encounters (76,072 hospitalizations and 233,411 ED/UC encounters) among adults. Among children across care settings, 17.0% (6,097/35,765) of cases versus 29.4% (21,449/72,853) of controls were vaccinated. Among adults, 28.2% (21,832/77,477) of cases versus 44.2% (102,560/232,006) of controls were vaccinated. VE was 51% (95% confidence interval [95% CI]: 41-60%) against influenza-associated hospitalizations and 54% (95% CI: 52-55%) against influenza-associated ED/UC encounters among children. VE was 43% (95% CI: 41-46%) against influenza-associated hospitalizations and 49% (95% CI: 47-50%) against influenza-associated ED/UC encounters among adults. ConclusionsInfluenza vaccination provided protection against influenza-associated hospitalizations and ED/UC encounters among children and adults in the US during the severe 2024-25 influenza season. These findings support influenza vaccination as an important tool to reduce influenza-associated disease. Brief SummaryDuring the 2024-25 influenza season, influenza vaccination provided protection against influenza-associated hospitalizations (43-51%) and emergency department or urgent care encounters (49-54%) among children and adults in the United States.