Swiss Medical Weekly

BACKGROUND: We used anthropometric data from electronic health records (EHRs) of Swiss childrens hospitals to evaluate growth references and estimate centile curves. METHODS: We received EHRs extracted from seven Swiss childrens hospitals and analysed two samples: all children with a height, weight, body mass index (BMI), or head circumference recording, and a subsample restricted to children without diseases potentially affecting growth, weighted to represent the general population. We calculated mean z-scores based on the World Health Organization growth references adopted for Switzerland in 2011 (CH-WHO 2011) and current Swiss growth references (Swiss 2026). We estimated sex-specific centile curves in the subsample using generalised additive models for location, scale, and shape. RESULTS: We included 213,868 children with height, 448,002 with weight, 209,244 with BMI, and 67,397 with head circumference recordings. Mean z-scores in the all children sample were (CH-WHO 2011; Swiss 2026): height (0.10; -0.19), weight (0.16; -0.09), BMI (0.04; -0.07), head circumference (-0.28, -0.28); and in the subsample: height (0.34; 0.00), weight (0.27; 0.01), BMI (0.18; 0.05), and head circumference (0.04; 0.01). The 50th height, weight, BMI, and head circumference centiles of girls and boys in the subsample closely followed those of Swiss 2026, with slightly wider 3rd and 97th centiles in infancy and adolescence. CONCLUSION: Height, weight, BMI, and head circumference centiles aligned well with the Swiss 2026 growth references in Switzerland, demonstrating that hospital EHRs could contribute to future growth references.

Purpose: Outcome consequences of critically ill children treated outside of pediatric intensive care units (PICU) are unknown. We assessed case fatality of children receiving complex intensive care treatment (CICT) by treating department in Germany and explored reasons for admission to adult intensive care units (AICU). Methods: Retrospective study using the German nationwide hospital discharge dataset 2016 to 2023. Cases aged [&ge;] 28 days and < 18 years receiving CICT were classified as PICU, AICU, or interdisciplinary by department codes. Odds ratios (OR) for in-hospital case fatality were estimated in generalized linear mixed models with the hospital as random effect, adjusted for age, acute organ dysfunction, and chronic conditions. Excess deaths were estimated and a survey among pediatric and adult intensivists was analyzed qualitatively. Results: Of 143,034 cases, 67.8 % were treated in PICUs, 14.0 % in AICUs, and 18.2 % were interdisciplinary. The crude OR for death in PICUs versus AICUs was 1.14 (95 % CI 1.03 to 1.26), reversing to 0.73 (0.63 to 0.84) after adjustment. For PICU and interdisciplinary cases combined versus AICU, the fully adjusted OR was 0.61 (0.54 to 0.70). Estimated excess deaths across the study period were 100, rising to 191 when interdisciplinary cases counted as pediatric. Capacity constraints, organizational factors, and clinical expertise were the main domains underlying AICU admissions. Conclusions: Children treated outside of PICUs had higher risk-adjusted case fatality, while crude figures pointed in the opposite direction. The findings support treating critically ill children in settings with routine pediatric intensive care experience.

Background Severe acute respiratory infections (SARI) strain healthcare systems. Sentinel surveillance remains central to SARI monitoring, but routinely collected hospital discharge data offer a scalable, population-wide complement. In Finland, national registers now enable register-based surveillance, yet SARI case definitions remain unevaluated. Aim To evaluate whether routinely collected electronic health records can support register-based SARI surveillance and establish a national case definition. Methods We conducted a retrospective register-based study linking inpatient discharge data from the Finnish Care Register for Health Care (Hilmo) and laboratory-confirmed pathogen notifications from the National Infectious Diseases Register (NIDR). Admissions were aggregated into hospitalisation episodes using generic and pathogen-specific respiratory ICD-10 codes and linked to laboratory-confirmed respiratory pathogens within an admission-centred window. We assessed the impact of diagnostic coding position, laboratory linkage windows and alternative case definitions on age distribution, seasonality and epidemic trend detection. Results We included 145,435 respiratory hospitalisation episodes. Laboratory confirmations clustered around admission, and a -7-to-+3-day window was selected; 51,498 (35.4%) had a linked laboratory confirmation. Specific primary-position diagnoses preserved clear seasonality and age distributions consistent with SARI epidemiology, whereas secondary-position diagnoses showed attenuated seasonality. A combined case definition incorporating specific primary diagnoses and laboratory-supported syndromic episodes produced stable epidemic curves while improving sensitivity over laboratory confirmation alone. Conclusion National discharge and laboratory registers can support robust SARI surveillance in Finland when case definitions are carefully designed. A combined register-based definition balances specificity, sensitivity and feasibility, complementing sentinel surveillance and integrated respiratory monitoring. Keywords Severe acute respiratory infection (SARI); surveillance; electronic health records; ICD-10; case definition; Finland

Background Exposure to environmental tobacco smoke (ETS) negatively affects children`s health, but few studies examined parental smoking behaviour in families of children with respiratory diseases. We studied parental smoking prevalence, characteristics, and changes over one year among families in the Swiss Paediatric Airway Cohort (SPAC). Methods We included children aged 0-17 years referred to paediatric respiratory outpatient clinics in Switzerland from 2017 to 2024. Parents answered a questionnaire at the initial clinic visit and again after one year. We used multivariable logistic regression to explore the characteristics of mothers and fathers who smoked and assessed changes in smoking behavior over one year. Results Among 4,199 children (median age 9 years [IQR 5-12]), 31% were exposed to parental smoking at baseline (paternal smoking: 16%; maternal smoking: 6%; both parents smoking: 9%). Mothers were more likely to smoke if they had a lower education level (OR 2.0, 95%CI 1.6-2.5 for compulsory education vs university education), did not have Swiss nationality (OR 1.3, 1.0-1.6) and lived in a socially disadvantaged neighborhood (OR 1.3, 1.0-1.7). Similar associations were observed for fathers. In addition, fathers were more likely to smoke if they were unemployed (OR 2.0, 1.3-3.2 vs having a full-time job. The strongest predictor of smoking was having a partner who smoked, with ORs above 6 for both mothers and fathers. Parents of 2,338 children completed the one-year follow-up questionnaire. Data from 2226 mothers and 1895 fathers showed that among baseline smokers with follow-up data, 225 (78%) mothers and 382 (81%) of fathers continued smoking, and only 63 (22%) of mothers and 90 (19%) of fathers quit. Among baseline non-smokers, 47 (2%) mothers and 54 (3%) fathers started smoking. Conclusions One-third of children consulting respiratory specialists in Switzerland are exposed to parental smoking. ETS exposure was strongly associated with socio-economic factors. Even after visiting a specialized clinic, most parents continued to smoke. This highlights the urgent need for stronger national smoking policies and targeted support to help these parents quit and stay smoke-free.

Background: Socioeconomic deprivation is associated with childhood morbidity, but nationwide evidence on critical illness and death in a health system with universal insurance coverage is scarce. We assessed the association between area-level deprivation and the population-level incidence of hospital admission, complex intensive care treatment (CICT), and CICT-related mortality in German children, and changes over time. Methods: Population-based analysis of complete German hospital discharge data, 2016 to 2023, covering all cases aged > 28 days to < 18 years. Cases were linked to the German Index of Socioeconomic Deprivation (GISD) via the municipality of residence and grouped into quintiles (Q1 least, Q5 most deprived). Incidence rates were calculated per 100,000 child years. Negative binomial regression adjusted for calendar year, with population as offset, yielded adjusted incidence rate ratios (aIRR) per one-quintile increase in deprivation; sensitivity analyses additionally adjusted for age group. Excess cases were estimated by applying Q1 incidence rates to Q2 to Q5. Results: Of 8,890,103 pediatric cases, 140,509 (1.6 %) received CICT and 3,386 (2.40 %) of these died. Incidence rose with deprivation from Q1 to Q5: admissions 6,191 to 9,255 per 100,000 child years, CICT 97 to 128, mortality 2.54 to 2.96. Each one-quintile increase was associated with higher risk of admission (aIRR 1.10, 95 % CI 1.10-1.11), CICT (1.07, 1.05-1.08), and mortality (1.04, 1.01-1.06); estimates were unchanged after age adjustment. Relative to Q1 rates, Q2 to Q5 accounted for 1,295,896 excess admissions (20.8 %), 11,254 excess CICT cases (12.6 %), and 194 excess deaths (8.7 %). Case fatality among CICT cases was lower in more deprived quintiles (2.35 % in Q5 versus 2.64 % in Q1), as were organ dysfunction and chronic conditions. Disparities in admission and CICT narrowed over time, whereas the mortality gradient persisted. Conclusions: Universal health insurance did not eliminate socioeconomic inequalities in pediatric critical illness. Deprivation increased the population burden of admission, intensive care, and death, but did not worsen outcomes once intensive care had begun, indicating that inequalities arise before pediatric intensive care and that prevention upstream in the care continuum is the primary target.

Motivation: With the scaling frequency and intensity of extreme heat events across the globe, it is critical for public institutions to develop early detection systems and continuous monitoring of these events and their impacts. In Brazil, Rio de Janeiro was the first city to publish its heat protocol, with the Rio Heat Dashboard as a central component of this system. Implementation: The dashboard was implemented using R/Shiny and integrates climatic and health data from multiple sources. General features: The application comprises real-time heat exposure monitoring and automatic alert level classification, which is monitored daily by multiple municipal actors and supports activation of actions specified in the heat protocol. It also features a health impact module, which lists each heat event and its impact on mortality, and primary care and emergency visits. Availability: The source for full reproducibility is available through https://github.com/joaohmorais/RioHeatDashboard.

AIM: To evaluate whether selective motor control quantified from spontaneous infant movement recordings provides diagnostic and prognostic information for cerebral palsy (CP) beyond established movement-based assessments. METHOD: This multicenter diagnostic and prognostic accuracy study included 302 infants (151 with CP) with spontaneous movement recordings obtained between 10 and 20 weeks corrected age from cohorts in Australia and the United States. All eligible infants with CP were included, and a comparison sample without CP was randomly selected. Recordings were scored using the Baby Observational Selective Control Appraisal (BabyOSCAR), Motor Optimality Score Revised (MOS-R), and General Movements Assessment (GMA). Outcomes at 2 years or older included CP diagnosis, Gross Motor Function Classification System (GMFCS) level, and motor distribution. RESULTS: BabyOSCAR discriminated CP diagnosis (area under the curve [AUC] 0.98), including children later classified in GMFCS level I. Among infants with CP, BabyOSCAR discriminated GMFCS levels I - II from III - V (AUC 0.89). BabyOSCAR absolute asymmetry also discriminated unilateral CP from all other infants (AUC 0.90). Diagnostic discrimination was also observed for MOS-R (AUC 0.94) and GMA (AUC 0.86). INTERPRETATION: Quantifying selective motor control from brief infant movement recordings may provide complementary early information about CP diagnosis, functional level, and motor distribution.

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 \emph{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.

Primary ciliary dyskinesia (PCD) is a rare, genetic, multiorgan disease requiring lifelong management. Although PCD affects everyday life, little is known about how people with PCD experience social functioning (SF). We conducted a study within the international participatory Living with PCD study to comprehensively explore SF. First, we conducted a focus group and two semi-structured interviews with adults and parents of people with PCD. We analysed qualitative data thematically and used the findings to develop a multilingual online questionnaire on SF. The questionnaire was completed by 277 participants: 225 adults and adolescents with PCD (81%) and 52 parents of children with PCD (19%). Participants reported active social lives and strong close relationships. PCD had a positive impact on family relationships for 39% of adult/adolescent participants and 41% of parents reporting for children. Among adult/adolescent participants, 49% reported positive or no impact on romantic/intimate relationships, while 17% had avoided or ended a relationship because of PCD. PCD affected the ability to meet responsibilities for 54% of participants, free time for 58%, and planning effort for 53%. Participants were more comfortable discussing PCD with family, friends, and partners than in work or educational settings, where only 29% reported receiving support. Financial support, flexible work, or educational policies and better-trained healthcare professionals were the most frequently identified unmet needs. This study suggests that maintaining SF with PCD requires substantial individual and relational work. Improving SF for people with PCD requires systemic responses in healthcare, education, and employment, alongside support from close networks.

Background: Mortality and hospital admissions due to Severe Acute Respiratory Infection (SARI) peaked between January and August 2025 in Brazil. Methods: The Brazilian Ministry of Health data on hospital admissions and deaths caused by SARI were compiled by age group (<5, 5-14, 15-49, 50-64, 65+ years) and quarter between January 2023 and June 2025. SARI causes were aggregated into SARS-Cov-2, Influenza, Respiratory Syncytial Virus (RSV), and other viruses (parainfluenza, adenovirus, rhinovirus, bocavirus, metapneumovirus). Multinomial regression was used to impute likely causes of death when these were not laboratory confirmed. Results: In the second quarter of 2025 (2025/2), RSV mortality rate among children <5 years reached 60 per 100,000, which is a 43% increase compared with 2024/2. Mortality rate for the joint impact of parainfluenza, adenovirus, rhinovirus, bocavirus, and metapneumovirus in the same age group doubled from 20 to 40 on the same scale in 2025/2 compared to 2024/2. Over the same period, influenza mortality tripled among the aged, whereas mortality due to other respiratory viruses increased less dramatically, except for SARS-CoV-2, which decreased among the aged from 150 to 25 per 100,000 between 2023/1 and 2025/2. Other age groups remained relatively stable over the period. The variation in hospital admissions largely followed that of mortality. Conclusions: While deaths and hospital admissions caused by SARS-CoV-2 declined rapidly since 2023, mortality rates of other respiratory viruses, mainly influenza and RSV, increased significantly among children <5 years and the aged in 2025/2. Public health policies that facilitate vaccine uptake against these infections should be given high priority.

The COVID-19 pandemic triggered an unprecedented volume of real-time discourse on social media platforms, with Twitter serving as a global forum for public reactions, fears, and evolving narratives. Traditional sentiment analysis approaches treat tweets as independent, static samples, failing to capture the temporal evolution and geographic heterogeneity of public opinion. This paper presents a comprehensive spatio-temporal framework that integrates fine-grained sentiment classification using COVID-Twitter-BERT with dynamic topic modeling via BERTopic to automatically discover and track evolving narratives. Using a corpus of 2.4 million geolocated tweets collected between January 2020 and June 2022, our analysis reveals distinct pandemic phases: early fear-driven narratives about mask shortages (Q1 2020), vaccine optimism followed by polarization (2021), and pandemic fatigue (2022). Regional comparisons show significant differences, with US discourse dominated by freedom-versus-mandate debates while European discussions emphasized collective solidarity. Our framework achieved 76% F1-score in sentiment classification and successfully identified 50 distinct narratives with high coherence scores. This work provides a powerful methodology for real-time epidemiological narrative surveillance and crisis communication monitoring.

Background: Chronic pain affects approximately 20% of children and youth worldwide and is associated with mental and physical health impacts. Canada-specific data on the prevalence of chronic pain in children and youth are limited, highlighting the need for current high-quality population-based estimates Aims: The aim of this study is to provide national estimates of self-reported chronic pain among Canadian children and youth by pain type (headache stomach ache, backache), sex (female, male), age group (5-11, 12-17 years) and province or territory. Methods: Publicly available data were used from the 2019 Canadian Health Survey on Children and Youth (CHSCY), a population-based survey conducted by Statistics Canada using a nationally representative sample of Canadian children and youth Results: Overall, headaches were the most commonly reported pain type (15.4%), followed by stomach aches (12.5%), and backaches (11.1%). Prevalence was consistently higher among females than males and among youth than children, with youth girls reporting the highest prevalence across all pain types. Prevalence also varied geographically, with some of the highest estimates observed in the Atlantic Provinces. Conclusions: Chronic pain affects substantial proportions of Canadian children and youth with disparities observed by pain type, sex, age, and geography. These findings under score pediatric chronic pain as an important public health issue and highlight the need for equity-oriented approaches that address the needs of populations experiencing the greatest burden.

School reopening during an Ebola outbreak is often framed as a binary question of whether schools are safe. For Ebola, however, the immediate operational question is where an infected school-age child may reach the school system before recognition and isolation, and whether local systems can detect and respond rapidly. We developed an exploratory, scenario-based health-zone framework for the September 2026 rentree during the ongoing Bundibugyo virus disease outbreak in eastern Democratic Republic of the Congo. The primary estimand was scenario-based expected introduction pressure, expressed on an expected-count scale, for infected school-age children reaching school in each health zone during a one-week window. The framework combined recent reported transmission, estimated school-age exposure and attendance, a surveillance/interception probability, and directed mobility-based importation. Case-fatality patterns were analysed separately and did not determine introduction pressure. A 10,000-draw probabilistic sensitivity analysis examined uncertainty in the school-age case share, attendance, pre-isolation school-entry probability and mobility scaling. Geographic components were retrospectively evaluated at eight non-overlapping weekly origins from 1 June to 20 July 2026, using subsequent reported seven-day health-zone activity and first reported cases in previously unaffected zones as outcomes. Seven-day local epidemic pressure discriminated health zones with subsequent reported activity with pooled ROC-AUC 0.848; the 14-day local measure increased this to 0.885. Adding directed mobility increased ROC-AUC to 0.952. In the base scenario, the six-province combined scenario-based expected introduction pressure was 10.97; the probabilistic sensitivity median was 11.17, with a 2.5-97.5% sensitivity range of 5.56-20.97. Bunia, Rwampara and Nizi had the highest base introduction pressures, followed by Katwa and Nia Nia. Among 24 previously unaffected health zones that subsequently reported a first confirmed case, 13 (54.2%) were in the top 10 and 18 (75.0%) in the top 20 mobility-ranked zones; random selection would have been expected to capture approximately 2.05 and 4.10 events, respectively. In a separate six-origin exploratory nested-specification sensitivity, surveillance/access modifiers did not improve geographic discrimination over local epidemic pressure alone, whereas mobility did. The dominant structural uncertainty remained the probability that an infected child reaches school before being identified. The framework supports targeted geographic prioritisation and minimum school-health readiness, but its probabilities are model-implied scenario probabilities rather than calibrated forecasts or evidence for a single national open/close decision.

Background: Autism spectrum disorder (ASD) is a lifelong neurodevelopmental condition for which timely diagnosis is critical to early intervention, family support, and equitable access to care. However, substantial disparities in access to ASD diagnostic services persist across socioeconomic, geographic, clinical, and health-system contexts. This systematic review and meta-analysis synthesized evidence on determinants of access across the ASD diagnostic pathway, from recognition and referral to diagnostic completion and timely diagnosis. Methods: We systematically searched MEDLINE/PubMed, Embase, Scopus, Web of Science, Global Health, and grey-literature sources for studies published between January 2004 and December 2024. Eligible studies examined determinants of ASD diagnostic completion, diagnostic pathways, diagnostic timeliness, or barriers and facilitators to diagnostic access. Two reviewers independently extracted data and assessed methodological quality using the Mixed Methods Appraisal Tool (MMAT). Quantitatively comparable estimates were synthesized using random-effects models with restricted maximum likelihood estimation. Heterogeneity was assessed using Cochran's Q, I2, tau2, and 95% prediction intervals. Pre-specified subgroup analyses, meta-regression, sensitivity analyses, funnel-plot assessments, and Bayesian random-effects analyses were undertaken. Results: The search identified 4,899 records; after removal of 537 records without associated data, 4,362 records underwent title/abstract screening. 3,800 records were excluded, 562 reports were sought for retrieval, and 450 full-text reports were assessed after 112 could not be retrieved. Ultimately, 22 unique studies met the inclusion criteria. Nine unique studies contributed 23 quantitative effect estimates, while the remaining studies contributed to the narrative synthesis. The evidence covered socioeconomic, geographic, family, communication, screening, child developmental, provider, and health-system determinants. The overall random-effects meta-analysis yielded a pooled diagnostic access outcome of 74.1% (95% CI 65.8-81.1%), with substantial heterogeneity (Qe=209.95, p<0.001; I2=88.4%, 95% CI 79.1-94.4%; tau2=0.691) and a wide 95% prediction interval of 32.8-94.4%. Bayesian analysis produced a highly concordant pooled estimate of 73.3% (95% CrI 65.3-80.2%), with I2=87.5% and tau=0.833, and satisfactory MCMC convergence (R-hat=1.000). By outcome domain, pooled successful outcomes were highest for diagnostic pathways (89.3%, 95% CI 70.1-96.7%), followed by timely diagnosis (76.3%, 95% CI 62.9-86.0%), and lowest for diagnostic completion (67.1%, 95% CI 61.8-72.0%) (Qm=5.98, p=0.050). Timely diagnosis demonstrated particularly high heterogeneity (I2=91.2%), whereas diagnostic completion showed moderate heterogeneity (I2=40.6%). Across determinant domains, frequentist pooled estimates were 79.5% for child developmental/neurobehavioral factors, 74.2% for family/socioeconomic/perceptual factors, 68.0% for intervention/care-navigation factors, and 63.6% for provider/clinical recognition factors. Bayesian estimates were 76.7% (BF=53.76), 72.9% (BF=226.32), 64.3% (BF=25.60), and 53.7% (BF=0.684), respectively. Meta-regression indicated that determinant category (Qm=13.48, p=0.004) and effect measure (Qm=7.81, p=0.020) significantly explained between-study variation, whereas age group (p=0.203) and geographic region (p=0.453) did not. Family/socioeconomic factors had significantly larger effect sizes (B=2.703, 95% CI 0.661-4.744; p=0.009), as did child developmental/neurobehavioral factors (B=1.516, 95% CI 0.047-2.985; p=0.043). Potential small-study effects were detected by two of three asymmetry tests, although the Rosenthal fail-safe N was 1,723. Trim-and-fill identified seven potentially missing estimates, with an adjusted pooled effect of 68.4% (95% CI 27.7-109.1%). Importantly, exclusion of two influential outlying estimates produced a pooled outcome of 77.1% (95% CI 71.6-81.9%), indicating that the principal finding was robust. Conclusions: Approximately three-quarters of observed ASD diagnostic outcomes represented successful access, but the substantial heterogeneity indicates that diagnostic access is highly context-dependent. Families were more likely to successfully navigate diagnostic pathways than to complete diagnostic assessment, while timely diagnosis showed the greatest variability across settings. Family and socioeconomic circumstances and child developmental characteristics emerged as particularly important determinants, whereas provider-related effects were more heterogeneous and uncertain. Improving equitable ASD diagnosis requires interventions spanning the entire diagnostic pathway, including developmental surveillance, screening, referral coordination, family navigation, provider capacity, specialist availability, and mechanisms to ensure completion of diagnostic assessment. Greater longitudinal and implementation research is particularly needed in low- and middle-income countries, where diagnostic infrastructure and specialist capacity remain limited.

Background Childhood respiratory mortality in China has fallen by over 90% in three decades alongside sustained national warming, yet national long-run evidence on temperature and child respiratory mortality is lacking. Methods We linked Global Burden of Disease (GBD) 2021 mortality estimates for China - lower respiratory infections (LRI), ages 0-19, and asthma, ages 0-24, 1990-2021 - with C-LSAT 0.5 deg gridded temperature data (1990-2019), aggregated nationally and to five climate zones. Four annual indicators (mean temperature, diurnal temperature range, seasonal amplitude, interannual variability) entered regressions of log mortality rates with Newey-West standard errors. A bootstrapped (500 resamples) quadratic model probed the minimum mortality temperature (MMT), with PM2.5-adjusted analyses and future-exposure, permutation, and detrended falsification tests. Results LRI deaths fell by 96.3% (330,194 in 1990 to 12,098 in 2021; 95% uncertainty interval 9,669-14,891) and asthma deaths by 94.9% (3,287 to 167), while mean temperature rose 0.364 deg C per decade and diurnal temperature range narrowed 0.092 deg C per decade. Baseline coefficients were large (mean temperature -1.696, SE 0.174; diurnal temperature range +2.408, SE 0.336; seasonal amplitude -0.162, SE 0.082; interannual variability +2.924, SE 1.514, per 1 deg C in log rate), but the future-exposure test failed and detrending nullified every coefficient: the associations are trend-level, and short-cycle causal effects are not identifiable. Nor was the national MMT identifiable - observed temperature support spans only 6.66-8.13 deg C, and the nominal turning point of 35.84 deg C is an extrapolation artifact (quadratic term p = 0.963). Within the observed range, warming and declining mortality moved in the same direction. Conclusions The 96% decline in childhood respiratory mortality cannot be attributed to warming. China sits on the low-temperature side of the optimum, and the marginal direction of future warming requires stronger designs to establish. The falsification framework offers a discipline for climate-health inference in China.

Background: Real-time outbreak analyses are often requested before surveillance systems have stabilised or epidemics have generated enough information for the desired inference. Existing approaches address surveillance quality, forecasting, estimands and identifiability separately, but do not provide a common rule for deciding which analytical product is supportable at a particular data vintage. We developed an estimand-first framework for analytical readiness. Methods: The framework distinguishes surveillance maturity (S), epidemic-process informativeness (E) and estimand-specific analytical readiness, defined as whether the available data vintage, observation process, method and decision-matched validation support a specified inference for a specified decision. We stress-tested four implications using longitudinal data from the 2018-2020 Ebola response in eastern Democratic Republic of the Congo (DRC), archived geographic forecasts, independent forecasting data from Western Area, Sierra Leone, and a targeted mortality-identifiability experiment. Results: During a documented DRC surveillance disruption and recovery, seven-day persistence forecasts had all-health-zone absolute errors of 1, 3, 18 and 4 cases across pre-shock, acute-shock, early-recovery and recovery origins; the largest error occurred during early recovery. Four-week reported-case trend multipliers changed from 0.67 and 0.73 to 1.12 and 1.29, while the final fit was strongly overdispersed (Pearson dispersion 7.65), demonstrating asynchronous readiness across estimands. Archived geographic forecasts improved a Top-3 allocation decision over cumulative burden at only one origin despite consistently lower Brier scores for one specification. In Western Area, persistence forecast mean absolute error increased from 39.1 cases at one week to 82.3 at four weeks, and a history-to-horizon ratio did not define a universal threshold. An observed reported case-fatality ratio of 0.40 was compatible with constructed latent fatality values from 0.10 to 0.80; increasing the reported denominator narrowed sampling uncertainty without reducing structural uncertainty. Conclusions: Analytical readiness is task- and vintage-specific rather than a property of a dataset. More data, model convergence or narrow intervals cannot substitute for estimand definition, observation-process awareness, decision-matched validation and explicit identification analysis. Keywords: outbreak analytics; surveillance maturity; analytical readiness; estimand; identifiability; forecasting; Ebola; reporting process; decision-matched validation

Background Respiratory infections remain the leading infectious cause of death among children and adolescents, yet the share of these deaths that could be averted with currently feasible care is not routinely quantified. Existing amenable-mortality frameworks rely on cause lists and population-level mortality benchmarks and do not exploit information on how many episodes occur. We propose an episode-fatality-ratio (EFR) frontier approach and apply it to lower respiratory infections (LRI), whooping cough (pertussis) and upper respiratory infections (URI) in 204 countries, 1990-2023. Methods For each cause, country and year we computed EFR = deaths/incident episodes using Global Burden of Disease (GBD) 2023 estimates for ages 0-19 years. The frontier was defined as the 10th-percentile country EFR within each GBD super-region, cause and year; avoidable deaths = max(0, deaths - episodes x frontier EFR). Primary estimates are deterministic; 95% uncertainty intervals (UIs) come from 2,000 Monte Carlo draws. Sensitivity analyses varied the frontier percentile, applied an aspirational global frontier, constructed pertussis counterfactuals, and recomputed all estimates within the single under-5 age band. Results In 2023, 333,803 childhood deaths from lower respiratory infections (95% UI 289,123-417,460; 46.9% of LRI deaths) were avoidable. Summing the three causes deterministically gives 391,034 avoidable deaths (46.5% of 840,444); the combined figure is a deterministic sum, and a UI is available for the LRI component only. The pertussis (43,958; 39.0%) and URI (13,273; 81.0%) estimates are secondary: their deterministic point values fall below their own Monte Carlo intervals and the underlying death estimates carry very wide uncertainty (global pertussis UI 12,545-321,874). Avoidable deaths fell from 1,050,468 (44.9%) in 1990, but between 2019 and 2023 the avoidable share for LRI+URI barely moved (48.7% to 47.7%) while absolute avoidable deaths fell 14.5%, a pattern consistent with stalled convergence to the frontier. Sub-Saharan Africa plus South Asia held 73.1% of avoidable deaths in 2023 versus 41.8% in 1990; ten countries accounted for 59.1%. Conclusion Nearly half of childhood respiratory-infection deaths remain avoidable relative to within-region best practice, and the residual burden is increasingly concentrated in low-income settings. In the pertussis counterfactual, most countries kept pace with their regional frontier, so further gains require advancing the frontier itself through quality-of-care improvements.

Anticipating which health zone will report the next confirmed case is operationally distinct from forecasting national case counts and matters for prepositioning response capacity; most spatial spread models rely on mobile-phone mobility data unavailable in the Democratic Republic of the Congo (DRC). We modelled the discrete-time hazard of a first reported confirmed case across 106 health zones in four provinces affected by the 2026 Bundibugyo virus disease outbreak (47 affected, 59 at risk, 26 July 2026), comparing four connectivity specifications,none, road-distance, a gravity score, and an incidence-weighted force-of-infection (FOI) term, fitted within an identical Bayesian hierarchical hazard architecture. Evaluation used a rolling-origin design, cluster bootstrap resampling, leave-one-origin-out and non-overlapping-origin checks, and a kernel-parameter sensitivity grid, with top-10 hit rate the pre-specified primary metric, matched to the operational question of which few zones warrant attention; AUC-PR, top-5 hit rate, and median rank percentile were secondary. FOI had the highest top-10 hit rate (42.6%), approaching conventional significance against road-distance and no-connectivity comparators. On AUC-PR, a model with no connectivity term performed as well as or better than any connectivity specification (0.437 vs. 0.409 for FOI), a discrepancy we report rather than omit. Rankings were stable across the sensitivity grid (Spearman; 0.90-0.99) and across robustness checks. An incidence-weighted connectivity term modestly and specifically improves identification of the highest-risk zones, concentrated in top-k ranking rather than uniform across metrics. The evaluation is pseudo-prospective, since historical data-vintage snapshots could not rule out retrospective revision, pending verification via a pre-registered top-20 ranking. Keywords: Bundibugyo virus disease; Ebola; spatial epidemiology; hazard model; Bayesian statistics; Democratic Republic of the Congo; disease surveillance

Seasonal Influenza and COVID-19 vaccination programmes are critical for reducing morbidity and mortality in older adults, yet uptake remains uneven across populations. We aimed to profile vaccination attitudes and examine predictors of COVID-19/influenza vaccination uptake among a UK participatory surveillance system - FluSurvey. We analysed FluSurvey data from participants aged [&ge;]65 years who were eligible for both vaccines in the 2023-2024 and 2024-2025 Autumn - Winter seasonal campaigns. Descriptive analyses examined self-reported attitudes to influenza vaccination. Logistic regression examined factors (age, sex, socioeconomic status, education, employment, transport, smoking and chronic conditions) associated with influenza and COVID-19 vaccination uptake in each season, adjusting for confounders. Belonging to a risk group and reducing risk of influenza were frequently reported motivations for influenza vaccination, while building natural immunity and concerns around safety and adverse effects were frequently reported barriers. Individuals vaccinated against COVID-19 were more likely to receive an influenza vaccination (aOR2023-2024=13.90 [9.28-21.17]; aOR2024-2025=8.54 [5.82-12.60]), and vice-versa (aOR2023-2024=13.91 [9.30-21.19]; aOR2024-2025=8.52 [5.81-12.58]). Lower educational attainment was associated with lower odds of COVID-19 vaccination (aOR2023-2024=0.59 [0.45-0.78], aOR2024-2025: 0.56 [0.39-0.79]). Other results were weaker or demonstrated variation by season. Our findings highlight recent attitudes and barriers to influenza and COVID-19 vaccination among the FluSurvey cohort, which may inform approaches to improve vaccination coverage in the population.

Urban air pollution remains a significant public health concern, contributing to premature deaths and adverse health outcomes. However, there is little causal research evaluating the effectiveness of policies designed to improve air quality. This study assesses the impact of all three stages of London's Ultra Low Emission Zone (ULEZ) on air pollution, via PM2.5 levels, and respiratory health, via prescription records for bronchodilator and respiratory corticosteroid medications. Analyses are at general practice level, using a generalised synthetic control method to estimate causal impacts. Stage 1 was associated with a statistically significant but negligible 0.77% reduction in PM2.5 levels, with no corresponding change in prescribing. Stage 2 produced a paradoxical 2.69% increase in PM2.5, alongside a 4.44% decrease in inhaled corticosteroid quantity but a 12.51% increase in average daily quantity (ADQ) usage, suggesting a worsening of disease severity among existing patients. Stage 3 yielded a 2.69% PM2.5 reduction and a modest 2.18% decrease in bronchodilator ADQ usage. Spillover effects beyond the ULEZ boundary were statistically significant, but negligible. We find overall that the ULEZ had minimal effects on both air quality and respiratory prescribing across all three stages. These findings provide new insights into the effectiveness of ULEZ policies in reducing air pollution and its associated health impacts, suggesting the zone's effects are considerably smaller than previously reported, and that integration with broader policy measures may be necessary to achieve meaningful public health gains.