BACKGROUND: Although vaccines have proved effective to prevent severe COVID-19, their effect on preventing long-term symptoms is not yet fully understood. We aimed to evaluate the overall effect of vaccination to prevent long COVID symptoms and assess comparative effectiveness of the most used vaccines (ChAdOx1 and BNT162b2). METHODS: We conducted a staggered cohort study using primary care records from the UK (Clinical Practice Research Datalink [CPRD] GOLD and AURUM), Catalonia, Spain (Information System for Research in Primary Care [SIDIAP]), and national health insurance claims from Estonia (CORIVA database). All adults who were registered for at least 180 days as of Jan 4, 2021 (the UK), Feb 20, 2021 (Spain), and Jan 28, 2021 (Estonia) comprised the source population. Vaccination status was used as a time-varying exposure, staggered by vaccine rollout period. Vaccinated people were further classified by vaccine brand according to their first dose received. The primary outcome definition of long COVID was defined as having at least one of 25 WHO-listed symptoms between 90 and 365 days after the date of a PCR-positive test or clinical diagnosis of COVID-19, with no history of that symptom 180 days before SARS-Cov-2 infection. Propensity score overlap weighting was applied separately for each cohort to minimise confounding. Sub-distribution hazard ratios (sHRs) were calculated to estimate vaccine effectiveness against long COVID, and empirically calibrated using negative control outcomes. Random effects meta-analyses across staggered cohorts were conducted to pool overall effect estimates. FINDINGS: A total of 1 618 395 (CPRD GOLD), 5 729 800 (CPRD AURUM), 2 744 821 (SIDIAP), and 77 603 (CORIVA) vaccinated people and 1 640 371 (CPRD GOLD), 5 860 564 (CPRD AURUM), 2 588 518 (SIDIAP), and 302 267 (CORIVA) unvaccinated people were included. Compared with unvaccinated people, overall HRs for long COVID symptoms in people vaccinated with a first dose of any COVID-19 vaccine were 0·54 (95% CI 0·44-0·67) in CPRD GOLD, 0·48 (0·34-0·68) in CPRD AURUM, 0·71 (0·55-0·91) in SIDIAP, and 0·59 (0·40-0·87) in CORIVA. A slightly stronger preventative effect was seen for the first dose of BNT162b2 than for ChAdOx1 (sHR 0·85 [0·60-1·20] in CPRD GOLD and 0·84 [0·74-0·94] in CPRD AURUM). INTERPRETATION: Vaccination against COVID-19 consistently reduced the risk of long COVID symptoms, which highlights the importance of vaccination to prevent persistent COVID-19 symptoms, particularly in adults. FUNDING: National Institute for Health and Care Research.

The urban environment during pregnancy may influence child’s respiratory health, but scarce evidence exists on systematic evaluation of multiple urban exposures (e.g., air pollution, natural spaces, noise, built environment) on children’s lung function, wheezing, and asthma development. We aimed to examine the association of the urban environment during pregnancy with lung function, preschool wheezing, and school-age asthma. We included 5624 mother-child pairs participating in a population-based prospective birth cohort. We estimated 30 urban environmental exposures including air pollution, road traffic noise, traffic, green spaces, blue spaces, and built environment during pregnancy. At 10 years of age, lung function was measured by spirometry. Information on preschool wheezing and physician-diagnosed school-age asthma was obtained from multiple questionnaires. We described single-exposure associations with respiratory outcomes using an exposome-wide association study. We also identified patterns of urban exposures with hierarchical clustering on principal components analysis and examined their associations with respiratory outcomes using multivariate regression models. Single-exposure analyses showed associations of higher particulate matter (PM) with lower mid-expiratory flow (FEF25-75%) (e.g., for PM < 2.5 mu m of diameter [PM2.5] z-score = -0.06 [-0.09, -0.03]) and higher forced expiratory volume in 1s (FEV1) and forced vital capacity (FVC) (e.g., for PM2.5 FEV1 0.05 [0.02, 0.08]) after correction for multiple-hypothesis testing. Cluster analysis described three patterns of urban exposures during pregnancy and showed that the cluster characterised by higher levels of air pollution, noise, walkability, street connectivity, and lower levels of natural spaces were associated with lower FEF25-75% (-0.08 [-0.17, 0.00]), and higher odds of preschool wheezing (1.21 [1.03, 1.43]). This study shows that the characteristics of the urban environment during pregnancy are of relevance to the offspring's respiratory health during childhood.

Background: A growing body of evidence has reported positive associations between long-term exposure to air pollution and poor COVID-19 outcomes. Inconsistent findings have been reported for short-term air pollution, mostly from ecological study designs. Using individual-level data, we studied the association between short-term variation in air pollutants [nitrogen dioxide (NO2), particulate matter with a diameter of <2.5 m (PM2.5) and a diameter of <10 m (PM10) and ozone (O-3)] and hospital admission among individuals diagnosed with COVID-19. Methods: The COVAIR-CAT (Air pollution in relation to COVID-19 morbidity and mortality: a large population-based cohort study in Catalonia, Spain) cohort is a large population-based cohort in Catalonia, Spain including 240 902 individuals diagnosed with COVID-19 in the primary care system from 1 March until 31 December 2020. Our outcome was hospitalization within 30 days of COVID-19 diagnosis. We used individual residential address to assign daily air-pollution exposure, estimated using machine-learning methods for spatiotemporal prediction. For each pandemic wave, we fitted Cox proportional-hazards models accounting for non-linear-distributed lagged exposure over the previous 7 days. Results: Results differed considerably by pandemic wave. During the second wave, an interquartile-range increase in cumulative weekly exposure to air pollution (lag0_7) was associated with a 12% increase (95% CI: 4% to 20%) in COVID-19 hospitalizations for NO2, 8% (95% CI: 1% to 16%) for PM2.5 and 9% (95% CI: 3% to 15%) for PM10. We observed consistent positive associations for same-day (lag0) exposure, whereas lag-specific associations beyond lag0 were generally not statistically significant. Conclusions: Our study suggests positive associations between NO2, PM2.5 and PM10 and hospitalization risk among individuals diagnosed with COVID-19 during the second wave. Cumulative hazard ratios were largely driven by exposure on the same day as hospitalization.

Background There is a lack of knowledge on how patients with asthma or chronic obstructive pulmonary disease (COPD) are globally treated in the real world, especially with regard to the initial pharmacological treatment of newly diagnosed patients and the different treatment trajectories. This knowledge is important to monitor and improve clinical practice.Methods This retrospective cohort study aims to characterise treatments using data from four claims (drug dispensing) and four electronic health record (EHR; drug prescriptions) databases across six countries and three continents, encompassing 1.3 million patients with asthma or COPD. We analysed treatment trajectories at drug class level from first diagnosis and visualised these in sunburst plots.Results In four countries (USA, UK, Spain and the Netherlands), most adults with asthma initiate treatment with short-acting ss2 agonists monotherapy (20.8%-47.4% of first-line treatments). For COPD, the most frequent first-line treatment varies by country. The largest percentages of untreated patients (for asthma and COPD) were found in claims databases (14.5%-33.2% for asthma and 27.0%-52.2% for COPD) from the USA as compared with EHR databases (6.9%-15.2% for asthma and 4.4%-17.5% for COPD) from European countries. The treatment trajectories showed step-up as well as step-down in treatments.Conclusion Real-world data from claims and EHRs indicate that first-line treatments of asthma and COPD vary widely across countries. We found evidence of a stepwise approach in the pharmacological treatment of asthma and COPD, suggesting that treatments may be tailored to patients’ needs.

Background Around 10% of people infected by SARS-COV-2 report symptoms that persist longer than 3 months. Little has been reported about sex differences in symptoms and clustering over time of non-hospitalised patients in primary care settings.
Methods This is a descriptive study of a cohort of mainly non-hospitalized patients with a persistence of symptoms longer than 3 months from the clinical onset in co-creation with the Long Covid Catalan affected group using an online survey. Recruitment was from March 2020 to June 2021. Exclusion criteria were being admitted to an ICU, < 18 years of age and not living in Catalonia. We focused on 117 symptoms gathered in 18 groups and performed cluster analysis over the first 21 days of infection, at 22-60 days, and >= 3 months.
Results We analysed responses of 905 participants (80.3% women). Median time between symptom onset and the questionnaire response date was 8.7 months. General symptoms (as fatigue) were the most prevalent with no differences by sex, age, or wave although its frequency decreased over time (from 91.8 to 78.3%). Dermatological (52.1% in women, 28.5% in men), olfactory (34.9% women, 20.9% men) and neurocognitive symptoms (70.1% women, 55.8% men) showed the greatest differences by sex. Cluster analysis showed five clusters with a predominance of Taste & smell (24.9%) and Multisystemic clusters (26.5%) at baseline and _Multisystemic (34.59%) and Heterogeneous (24.0%) at >= 3 months. The Multisystemic cluster was more prevalent in men. The Menstrual cluster was the most stable over time, while most transitions occurred from the Heterogeneous cluster to the Multisystemic cluster and from Taste & smell to Heterogeneous.
Conclusions General symptoms were the most prevalent in both sexes at three-time cut-off points. Major sex differences were observed in dermatological, olfactory and neurocognitive symptoms. The increase of the Heterogeneous cluster might suggest an adaptation to symptoms or a non-specific evolution of the condition which can hinder its detection at medical appointments. A carefully symptom collection and patients’ participation in research may generate useful knowledge about Long Covid presentation in primary care settings.