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 Upper airway disease is common in primary ciliary dyskinesia (PCD), but management evidence is limited. We aimed to describe management practices and identify factors influencing management decisions. Methods Using data from the Ear-Nose-Throat (ENT) Prospective International Cohort of patients with PCD (EPIC-PCD) and an ENT-specialist survey across participating centres, we described management practices recorded at routine follow-up. We assessed clinical factors associated with practices via mixed-effects logistic regression models. In a subgroup of patients, we assessed factors associated with initiation or discontinuation of practices. Results We included 579 patients: median age 15 years, 46% female. Nasal rinsing (54%) and nasal corticosteroids (22%) were most frequently prescribed. Among 466 patients with available data, 47 had grommets (10%) and 42 hearing aids (9%). Nasal corticosteroids and rinsing were more frequently prescribed in patients with polyps (odds ratio [OR] 3.74, 95% confidence interval [CI] 1.80-7.76; OR 3.39, 95% CI 1.37-8.37) or turbinate hypertrophy (OR 1.89, 95% CI 1.03-3.47; OR 2.89, 95% CI 1.55-5.38), and upper airway nebulisation in patients with frequent nasal symptoms (OR 2.86, 95% CI 1.11-7.39). Management practices differed between centres, as seen also by the specialists survey responses. In 177 patients with multiple visits, initiation of nasal rinsing was associated with frequent nasal symptoms (OR 3.18, 95% CI 1.24-8.18) and turbinate hypertrophy (OR 3.21, 95% CI 1.20-8.59). Conclusion Upper airway disease management in PCD varies and is partly guided by symptom burden and clinical findings. This variation across centres highlights the need for care standardisation and PCD-specific management guidelines.

Objectives To assess the feasibility of using clinical data automatically extracted via the Swiss Personalized Health Network (SPHN) to complement or replace manually abstracted clinical data in the Swiss Paediatric Airway Cohort (SPAC). Materials and Methods We studied 1,075 SPAC participants enrolled between 2017-2023 at two Swiss children's hospitals. Clinical data were extracted from electronic health records via SPHN in Resource Description Framework format, transformed into visit-centered datasets, and compared with manually abstracted SPAC clinical data and parent-reported emergency department (ED) visits and hospitalizations from follow-up questionnaires. We assessed feasibility by identifying challenges in acquiring data and evaluated data quantity, completeness, and agreement between datasets. Results We obtained analysis-ready SPHN-derived datasets from two hospitals after 24 months. SPHN-derived data captured more pneumology outpatient visits than manual abstraction (Hospital A: 1,963 vs 1,049; Hospital B: 2,343 vs 1,010) and identified clinical events among children without follow-up questionnaires. Completeness of variables varied across hospitals and encounters, reflecting differences in local clinical documentation practices. SPHN-derived and manually abstracted data showed high agreement for structured clinical variables, including spirometry measurements (concordance correlation coefficient >0.99). Self-reported and SPHN-derived ED visits and hospitalizations showed high absolute agreement but moderate concordance. Discussion and Conclusion Automated extraction of routine clinical data increased the completeness of longitudinal information compared with manual abstraction, suggesting that SPHN-derived data can complement manual data collection in cohort studies. Broader use remains limited by heterogeneous clinical documentation practices and the substantial effort required to harmonize and transform extracted data into analysis-ready research datasets.

Background The outbreak of COVID19 in Greece prompted extensive public health measures, including the first national lockdown and the suspension of in-person schooling. Recognizing the significant role of children in community transmission due to their contacts in schools, school absenteeism data began to be systematically recorded as a potential indicator of outbreak patterns. Objectives This study aims to explore the utility of incorporating school absenteeism data in an early warning surveillance system for respiratory infections, particularly in predicting the onset and spread of diseases such as COVID19 and influenza. Methods We utilized school absenteeism data from primary schools and kindergartens in the Municipality of Larissa for the 2022 2024 school years, alongside health data from the University Hospital of Larissa (UHL). These included incidence rates of respiratory infections, COVID-19, and flu cases, which were cross-referenced with absenteeism patterns. Results The analysis showed that peaks in absenteeism often preceded increases in cases of respiratory infections, COVID19, and flu, suggesting absenteeism as a potential early warning indicator. Notable divergences in patterns were observed during school closures for holidays, which posed challenges in data continuity and surveillance effectiveness. Conclusions School absenteeism data significantly enhances the capability for early detection and monitoring of respiratory disease outbreaks. To improve future surveillance and outbreak prediction, integrating more comprehensive data sources and refining predictive models to accommodate educational calendar variations is recommended.

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: Mass gathering events (MGEs) are associated with several public health challenges and may cause a strain on healthcare services. Literature findings on the impact of MGEs on emergency departments (EDs) are heterogeneous. Objectives: To examine shifts in ED attendance characteristics during a major sporting tournament, namely the UEFA European Football Championship 2024 held in Germany. Methods: We conducted a retrospective observational study using ED data from the Emergency Department Data Registry. We compared baseline ED attendance characteristics between the tournament and the reference period, defined as two weeks before and two weeks after the tournament, and between Germany game days and non-Germany game days. Hourly attendance patterns were analysed for all Germany games using a reference range. Results: We included data from 41 EDs, totalling 253,493 attendances during the study period. A 1.57% increase in attendance was observed during the tournament compared to the reference period, with baseline characteristics remaining similar. The median daily attendance within all EDs was slightly lower on Germany game days (4066) compared to non-Germany game days (4128). Modest changes were observed in the hourly attendance on Germany game days, most notable during the last Germany game where a decrease in attendance below the reference range extended over three hours. Conclusions: The observed shifts in ED attendance were minimal, suggesting that no major changes of public health relevance occurred in ED attendance during the tournament. We highlight the utility of using ED data for monitoring and for enhancing the understanding of the public health risks and challenges associated with MGEs.

Background: Clinical guidelines recommend objective tests to diagnose asthma in school-age children, but their availability and use in routine practice remain uncertain. We evaluated asthma diagnostic practices in Switzerland, focusing on first-line tests (spirometry, bronchodilator reversibility testing, and fractional exhaled nitric oxide [FeNO]). Methods: Cross-sectional, nationwide online survey of primary care paediatricians (PCPs) and respiratory specialists. We assessed access to and use of diagnostic tests, focusing on first-line tests, and examined reasons for non-use, referral practices, and guideline consultation. We used multivariable logistic regression to identified factors associated with spirometry access among PCPs. Results: Of 1,055 respondents, 625 diagnosed asthma in children, including 419 PCPs. Among PCPs, 50% (95% confidence interval [CI] 45-55) reported no access to spirometry and 95% (95% CI 92-97) no access to FeNO, whereas all paediatric respiratory specialists and almost all adult respiratory specialists had access to both tests. Barriers to first-line testing among PCPs included economic constraints and difficulties interpreting test results. Spirometry access was lower in French- and Italian-speaking regions than in German-speaking regions (adjusted odds ratio [aOR] 0.09, 95% CI 0.05-0.15), but higher among PCPs working full-time (aOR 2.04, 95% CI 1.11-3.82) and those using Swiss asthma guidelines (aOR 1.71, 95% CI 1.01-2.92). PCPs without spirometry access more frequently referred children to specialists for diagnostic confirmation (89% versus 80%; p=0.019). Conclusion: Many PCPs in Switzerland lack access to guideline-recommended tests. Improving access, reimbursement, and training in test interpretation may help reduce the gap between guidelines and clinical practice.

Background/Objectives We evaluated the impact of the COVID-19 adolescent vaccination in England at two different epidemic points: the autumn (August-November) 2021, in the presence of a large Omicron epidemic wave, and the autumn (August-November) 2022, when the subsequent Omicron epidemic was at an endemic stage. Methods Using the Covasim SARS-CoV-2 model for England, under varying vaccine uptake and onset time, we evaluated the impact of a)vaccinating 18+ only versus additional 12+ vaccination from the autumn 2021; and b)the current immunisation strategy at the time versus additional 12+ vaccination from September 2022, projecting the number of new daily SARS-CoV-2 infections, hospitalisations and deaths. Results In presence of the BA.1 Omicron wave in late 2021, the expanded adolescent vaccination averted ~3,000,000 cases across all-ages, ~1,010,000 SARS-CoV-2 infections in the period 2-6 months from vaccine onset in the vaccinated cohort. During the Omicron waves in 2022, additional adolescents vaccination did not significantly reduce the COVID-19 burden in the entire population, nor within the vaccinated cohort. Conclusions Our findings highlight that adolescent vaccination impact depends on the timing/speed of implementation, other present intervention strategies, and the status of the epidemic at the time and it should not be considered as a stand-alone immunisation strategy.

Respiratory diseases cause considerable morbidity in autumn and winter and are a priority in public health monitoring. In Germany, they are subject to a number of surveillance systems, including both pathogen-specific and syndromic indicators. In this paper we present a collaborative multi-target and multi-model real-time forecasting system rolled out during the 2024/25 season, and discuss differences to earlier efforts carried out during the COVID-19 pandemic. A total of nine models were run to generate forecasts of general practitioner consultations for acute respiratory infections (ARI), hospitalizations for severe acute respiratory infections (SARI) and confirmed cases of seasonal influenza and RSV. As all indicators were subject to retrospective revisions, forecasting models were combined with a nowcasting step. Whenever multiple models were available for the same indicator, we combined them into an ensemble. Nowcasts showed convincing performance, even though for some models Christmas break effects led to an upward bias in early January. Forecasts were overall well-calibrated and most models outperformed simple benchmark models. These improvements were generally more substantial for age-stratified than pooled targets, and concentrated at lead times of two to three weeks. Anticipating the peak timing and magnitude proved to be challenging, with many models predicting too flat curves with a too early turnaround (e.g. already in late January rather than mid-February for SARI). The combined ensemble forecast was among the best-performing approaches, but unlike in previous related projects did not consistently outperform individual models. We conclude by discussing learnings on the organization of collaborative forecasting projects in post-COVID-19 times and the potential of AI-supported modelling.

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. The recent approval of long-acting monoclonal antibodies (la-mAbs) and a maternal vaccine (MV) in the EU enables universal RSV prevention in infants. Modelling studies are widely used to quantify the population-level impact of alternative immunisation strategies. However, existing assessments of new RSV immunisation products focus on national or sub-national settings. Methods. We developed an age-stratified, stochastic compartmental model of RSV transmission for 28 EU/EEA countries. It combines literature-based parameters on RSV natural history and product efficacy with country-specific demographic and contact patterns. After model calibration against age- and country-specific RSV hospitalisation rates, we designed scenarios for both la-mAbs and MV at four coverage levels, with and without catch-up immunisation for infants under six months at season onset. We then evaluated each scenario against a no-immunisation baseline. Results. At 95% coverage, the cross-country median reduction in RSV hospitalisations over one season in infants under 12 months is 29.9% for la-mAbs (country median range: 27.7-33.9%) and 22.4% for MV (20.0-25.6%), scaling linearly with coverage. Out of all averted hospitalisations, 78.3% (90% CI: [67.3, 92.7]%) are concentrated in infants aged 0-2 months for la-mAbs and 72.7% (90\% CI: [61.4, 88.6]%) for MV. A catch-up campaign nearly doubles the overall reduction in RSV hospitalisations. Conclusions. Despite country-specific heterogeneities, impact of la-mAbs and MV is comparable across settings and herd-immunity effects are largely negligible. This supports harmonised European guidelines on coverage targets. Seasonal catch-up campaigns emerge as an effective lever to maximise the impact of immunisation programmes.

Abstract Importance Acute otitis media is the most common infection in children and a major reason for antibiotic prescriptions, up to one third of which may be unnecessary. Sector of care may influence AOM management through differences in access to care, specialist involvement, parental expectations and financial foundation. Objective The objective is to examine differences in antibiotic prescribing practices between healthcare sectors. Design This is a nationwide register-based study comparing data from different healthcare sectors. Setting Finnish primary and secondary healthcare, covering both public- and private-sector visits. Prescriptions and sociodemographic information were linked from nationwide registers. Participants We included children under 18 years old who received a diagnosis of acute otitis media, defined by ICD-10 codes H65-H67, between January 1, 2017 and December 31, 2022. Exposures The exposure is the sector of care (public sector vs. private sector). Main Outcomes and Measures Primary outcomes were antibiotic prescribing, guideline adherence of the prescribed antibiotics, and rates of management failure. Secondary outcomes included antibiotic selection and guideline-adherent eligibility for tympanostomy tube placement. Associations were estimated using adjusted odds ratios (aORs) with 95% confidence intervals (CIs). Results The study included 295 064 children with 596 634 acute otitis media index visits, of which 77.6% resulted in an antibiotic prescription. Private-sector visits were associated with higher odds of antibiotic being prescribed (adjusted odds ratio [aOR]: 1.45; 95% CI: 1.41-1.49). Overall, 87.3% of antibiotic prescriptions were guideline adherent, but private-sector care was associated with lower odds of guideline-adherent prescribing (aOR: 0.64; 95% CI: 0.60-0.69). Compared with amoxicillin, the private sector showed higher odds of prescribing amoxicillin-clavulanic acid (32.8% vs. 8.3%; aOR: 3.00; 95% CI: 2.91-3.10). Management failure occurred in 7.0% of episodes and was more common in the private sector (aOR:1.52; 95% CI: 1.48-1.56). Only 48.7% of all tympanostomy tube insertions met the eligibility criteria. Conclusions and Relevance In this study overall adherence to guideline-recommended antibiotic treatment for AOM was high in Finland. Nevertheless, observed clinically meaningful sectoral differences in antibiotic selection, treatment failure, and tympanostomy eligibility adherence indicate a need for targeted antimicrobial stewardship and quality-improvement efforts, especially in the private sector.

Background: Within the VEBIS-EHR project, monthly vaccine effectiveness (VE) of COVID-19 vaccines is routinely estimated across EU/EEA countries. While VE quantifies direct protection, it does not capture the overall population benefit of vaccination campaigns in terms of severe outcomes prevented. Aim: To estimate the impact of the 2023 and 2024 autumn COVID-19 vaccination campaigns in adults aged [&ge;]65 years. Methods: We conducted a retrospective cohort study using electronic health records data from Belgium, Denmark, Italy, Navarre (Spain), Portugal, Norway and Sweden. Weekly numbers of averted COVID-19-related hospitalisations and deaths during the 12 months following each campaign were estimated using observed COVID-19-related events, vaccine coverage (VC) and interpolated weekly VE. Results: Across participating countries/regions, among adults aged [&ge;]65 years, the 2023 autumn vaccination campaign averted approximately 6,200 hospitalisations (prevented fraction [PF] 10%) compared with 2,200 (PF 12%) in 2024. Among those aged [&ge;]80 years, the number of averted COVID-19-related deaths was 811 (PF 13%) for the 2023 campaign and 156 (PF 12%) for the 2024 campaign. Impact varied across countries, reflecting differences in VC, vaccination timing and outcome occurrence. Conclusion: The 2023 and 2024 autumn vaccination campaigns resulted in substantially different numbers of averted COVID-19-related hospitalisations and deaths among older adults, with fewer events averted in 2024. These findings highlight that the impact of vaccination programmes depends not only on VC and VE but also on alignment between vaccination timing and periods of increased viral circulation.

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.

Objective: The COVID-19 pandemic markedly altered social activity patterns, healthcare utilization, and the epidemiology of infectious diseases. However, its long-term impact on emergency otolaryngologic conditions remains incompletely understood. This study investigated long-term trends in emergency otolaryngologic conditions before, during, and after the COVID-19 pandemic using comprehensive data from a large urban emergency clinic in Osaka, Japan. Methods: All new otolaryngologic outpatients who visited the Chuo Emergency Medical Clinic (CEMC) in Osaka City between 2019 and 2024were retrospectively analyzed. Annual trends in absolute numbers and relative proportions of emergency otolaryngologic conditions were examined by anatomical region and disease category, using 2019 as the pre-pandemic baseline. Results: A total of 99,324 new otolaryngologic outpatients were analyzed. Overall emergency visits declined sharply to approximately half of baseline in 2020, followed by a gradual but incomplete recovery toward pre-pandemic levels by 2024. Most anatomical categories declined to 45-61% of baseline in 2020 and exhibited gradual yet incomplete recovery through 2023; in stark contrast, laryngeal conditions diverged sharply, surging beyond pre-pandemic levels after 2022. Acute infectious otorhinolaryngologic diseases fell to 23-50% of baseline in 2020 and showed variable recovery (69-103%) by 2024. Notably, laryngitis exceeded the baseline, reaching 132% in 2023, whereas epiglottic edema exhibited only a transient increase approaching the baseline in 2021. Non-infectious emergency conditions generally showed only a marginal decrease in 2020 and remained relatively stable throughout the study period, except for sudden sensorineural hearing loss (SSNHL), which dropped sharply to 39% of the baseline in 2020 and remained persistently reduced through 2024. Traumatic emergencies declined variably to 53-81% of the baseline in 2020, followed by an incomplete recovery, reaching only 55-69% by 2024. Conclusion: Emergency otolaryngologic conditions demonstrated heterogeneous recovery trajectories following the COVID-19 pandemic. While most infectious and traumatic conditions gradually but incompletely normalized, laryngeal conditions showed a distinct post-pandemic surge, and SSNHL remained persistently suppressed. These findings reveal heterogeneous, condition-specific recovery trajectories that reflect both genuine shifts in community pathogen burden, true traumatic incidence, and persistent alterations in healthcare-seeking behaviors, insights essential for resource allocation during future public health emergencies.

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.

Urban centres across the world remain structurally unprepared for epidemic events, lacking the real-time intelligence infrastructure needed to anticipate outbreaks, model population-level spread, and evaluate competing health interventions before crises escalate. This chapter presents EpiCity, an open-source, AI enabled epidemic-aware smart city health intelligence framework designed to embed probabilistic outbreak forecasting directly into the urban planning and administrative decision cycle. EpiCity integrates four technical contributions within a unified deployable dashboard: a hybrid ensemble probabilistic forecasting engine driven by more than 500 Monte Carlo simulations; an agent based urban population digital twin that models SEIRD-compartment epidemic dynamics across 200 heterogeneous agents over a 60-day simulation horizon; an intervention policy scenario comparison module for quantitative evaluation of non-pharmaceutical and pharmaceutical control strategies; and a Retrieval-Augmented Generation (RAG) explainable AI chatbot that translates model outputs into plain-language guidance for city officials without specialist epidemiological training. Real-world validation against Johns Hopkins CSSE COVID-19 surveillance data for the United States (June-July 2020) yielded a Pearson correlation of 0.88 between framework forecasts and observed case trajectories, with ensemble prediction intervals achieving 90% empirical coverage, confirming the calibration reliability of the uncertainty quantification pipeline. A representative simulation scenario demonstrated a 99% reduction in simulated peak case load relative to an unmitigated baseline, with an estimated 56 lives saved in the comparison period. Aligned with SDG 3 (Good Health and Well-being), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action), EpiCity offers urban planners, public health officers, and city administrators a scientifically grounded yet practically accessible tool for evidence-based epidemic preparedness and resilient city governance. The code is available at https://github.com/Harmi-kotak22/Artificial_Life_Simulator.

The evolving epidemiology of COVID-19, driven by successive SARS-CoV-2 variants of concern (VOCs), has prompted ongoing evaluation of their impact on disease severity in children. In low- and middle-income countries (LMICs), children experience a higher burden of severe respiratory illness and pneumonia-related mortality due to factors such as malnutrition, incomplete immunisation, HIV exposure or infection, tuberculosis, and disparities in access to healthcare services. Hospital-based paediatric studies from LMICs are therefore needed to understand how the epidemiology and severity of COVID-19 have changed across pandemic waves. This study examined 354 hospitalised children with SARS-CoV-2 infection during the ancestral, pre-Omicron (Beta and Delta), and Omicron waves at Tygerberg Hospital in Cape Town, South Africa. We analysed data collected over an extended period, from March 2020 to June 2022. Statistical analyses were used to describe clinical characteristics across variant periods, and multivariable logistic regression models were applied to evaluate associations between potential risk factors and disease severity. Paediatric COVID-19 severity varied across VOC periods, with the highest burden observed during the pre-Omicron (Beta and Delta) waves. In multivariable analyses, younger age and circulating variants were associated with disease severity; CRP levels emerged as a marker associated with more severe illness, and corticosteroid treatment, while also associated with disease severity, reflects clinical response to more severe cases. These findings contribute to a better understanding of the epidemiology and clinical impact of COVID-19 in children and highlight the importance of context-specific surveillance and treatment strategies in resource-limited settings.

Zika virus (ZIKV) emerged in Brazil in 2015, causing an unprecedented epidemic of Congenital Zika Syndrome (CZS). A decade later, longitudinal analyses evaluating temporal trends and subnational heterogeneity in CZS burden remain limited. Using publicly available data from SINAN/DATASUS and the RESP-Microcephaly registry (SVS/Ministry of Health, updated July 2024), we conducted a descriptive ecological analysis of ZIKV infection and CZS in Brazil from 2015 to 2023. Of 331,309 notified Zika cases (2015-2023), 213,350 occurred in 2016, followed by an 91.75% decline in 2017 and sustained low-level endemic circulation thereafter. Among 3,751 confirmed microcephaly cases, 1,828 were confirmed with ZIKV etiology. The Northeast region accounted for 75.4% of confirmed cases despite representing approximately 27% of the national population. State-level analyses revealed distinct epidemiological patterns, including persistent microcephaly notifications of non-Zika etiology in Minas Gerais and continued detection of ZIKV-attributed CZS in Amazonas and Goias through 2023. These findings highlight pronounced geographic disparities in congenital Zika burden, reflect significant heterogeneity in diagnostic capacity, and underscore the need for sustained surveillance and systematic etiological investigation of congenital abnormalities in the post-epidemic era.