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ObjectiveIn September 2020, records of 15,861 SARS-CoV-2 cases failed to upload from the Second Generation Laboratory Surveillance System (SGSS) to the Contact Tracing Advisory Service (CTAS) tool, resulting in a delay in the contact tracing of these cases. This study used CTAS data to determine the impact of this delay on health outcomes: transmission events, hospitalisations, and mortality. Previously, a modelling study had suggested a substantial impact.DesignObservational studySettingEngland.PopulationIndividuals testing positive for SARS-CoV-2 and their reported contacts.Main outcome measuresSecondary attack rates (SARs), hospitalisations, and deaths amongst primary and secondary contacts were calculated, compared to all other concurrent, unaffected cases. SGSS records affected by the event were matched to CTAS records and successive contacts and cases were identified.ResultsThe initiation of contact tracing was delayed by 3 days on average in the primary cases in the delay group (6 days) compared to the control group (3 days). This was associated with lower completion of contact tracing of primary cases in the delay group: 80% (95%CI: 79-81%) in the delay group and 83% (95%CI: 83-84%) in the control group. There was some evidence to suggest an increase in transmission to non-household contacts amongst those affected by the delay. The SAR for non-household contacts was higher amongst secondary contacts in the delay group than the control group (delay group: 7.9%, 95%CI:6.4% to 9.2%; control group: 5.9%, 95%CI: 5.3% to 6.6%). There was no evidence of a difference between the delay and control groups in the odds of hospitalisation (crude odds ratio: 1.1 (95%CI: 0.9 to 1.2) or death (crude odds ratio: 0.7 (0.1 to 4.0)) amongst secondary contacts.ConclusionsThe delay in contact tracing had a limited impact on population health outcomes.Strengths and limitations of the studyShows empirical data on the health impact of an event leading to a delay in contact tracing so can test hypotheses generated by models of the potential impact of a delay in contact tracingEstimates the extent of further transmission and odds of increased mortality or hospitalisation in up to the third generation of cases affected by the eventThe event acts as a natural experiment to describe the possible impact of contact tracing, comparing a group affected by chance by delayed contact tracing to a control group who experienced no delayContact tracing was not completed for all individuals, so the study might not capture all affected contacts or transmissions

Background Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. Methods In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. Findings Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. Interpretation Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. Funding British Heart Foundation Data Science Centre, led by Health Data Research UK.

Background The Cystic Fibrosis (CF) Registry collects clinical data on all patients attending specialist CF centres in the UK. These data have been used to make comparisons between centres on key outcomes such as forced expiratory volume in 1 second (FEV1) using simple rankings, which promote the assumption that those with the highest measures provide ‘better’ care. Objectives To explore whether or not using statistical ‘process control’ charts that move away from league tables and adjusting for case mix (age, where appropriate; sex; CF genotype; pancreatic sufficiency; and socioeconomic status) could identify exceptional CF care services in terms of clinically meaningful outcomes. Then, using insight from patients and clinicians on what structures, processes and policies are necessary for delivering good CF care, to explore whether or not care is associated with observed differences in outcomes. Design Cross-sectional analyses. Setting Specialist CF centres in the UK. Participants Patients aged ≥ 6 years attending specialist CF centres and clinicians at these centres. Main outcome measures FEV1% predicted. Data sources Annual reviews taken from the UK CF Registry (2007–15). Results We studied FEV1 in many different ways and in different periods. In our analyses of both adult and paediatric centres, we observed that some centres showed repeated evidence of ‘special-cause variation’, with mean FEV1 being greater than the mean in some cases and lower than the mean in others. Some of these differences were explained by statistical adjustment for different measures of case mix, such as age, socioeconomic status, genotype and pancreatic sufficiency. After adjustment, there was some remaining evidence of special-cause variation for some centres. Our data at these centres suggest that there may be an association with the use of intravenous antibiotics. Workshops and focus groups with clinicians at paediatric and adult centres identified a number of structures, processes and policies that were felt to be associated with good care. From these, questionnaires for CF centre directors were developed and disseminated. However, the response rate was low, limiting the questionnaires’ use. Focus groups with patients to gain their insights into what is necessary for the delivery of good care identified themes similar to those identified by clinicians, and a patient questionnaire was developed based on these insights. Limitations Our data analyses suggest that differences in intravenous antibiotic usage may be associated with centre-level outcomes; this needs to be explored further in partnership with the centres. Our survey of centre directors yielded a low response, making it difficult to gain useful knowledge to inform further discussions with sites. Conclusions Our findings confirm that the CF Registry can be used to identify differences in clinical outcomes between centres and that case mix might explain some of these differences. As such, adjustment for case mix is essential when trying to understand how and why centres differ from the mean. Future work Future work will involve exploring with clinicians how care is delivered so that we can understand associations between care and outcomes. Patients will also be asked for their perspectives on the care they receive. Funding The National Institute for Health Research Health Services and Delivery Research programme.

Background Limited evidence suggests that exposure to traffic related air pollution is associated with graft failure among lung transplant recipients. We explored associations between pollution and transplant failure among lung and other solid organ transplant recipients in Great Britain through a retrospective cohort study. Methods All patients who received a lung, heart, liver, or kidney transplant between 2000 and 2008 in Great Britain were included, as recorded in the National Health Service Blood and Transplant (NHSBT) register and followed to March 2015. Using residential addresses at time of transplant we calculated distance to nearest (major) road and modelled annual average exposures to airborne nitrogen oxides and particulate matter of diameter ≤10µm and ≤2.5µm for each transplant recipient. All-cause mortality or graft failure (kidney) during follow up was the main outcome; median follow-up was around 10 years for each organ type. We fitted Cox regression models with adjustment for age, sex, year of transplant and donor age/smoking status. Results 780 lung, 1213 heart, 3650 liver and 11966 graft kidney transplant patients were analysed. We did not find any consistent associations between mortality or graft failure and any of the analysed air pollutants or road metrics. Although, exposure to particulate matter was associated with renal transplant failure in univariable analyses but not after adjustment for confounders. Conclusions Our analysis does not confirm previously reported associations between traffic-related air pollution exposure and the risk of transplant failure.

Key Points Question Is exposure to ambient air pollution in the first trimester associated with thyroid function throughout pregnancy? Findings Among 9931 pregnant women in 4 European cohorts and 1 US cohort, an increase of 5 μg/m3 in exposure to particulate matter with an aerodynamic diameter of 2.5 μm or less was associated with 20% higher odds of hypothyroxinemia. Meaning The findings of this study raise the possibility that exposure to particulate matter might disrupt thyroid function in pregnant women., This cohort study evaluates the short-term association of exposure to air pollution in the first trimester with thyroid function throughout pregnancy among European and US cohorts., Importance Air pollutants interact with estrogen nuclear receptors, but their effect on thyroid signaling is less clear. Thyroid function is of particular importance for pregnant women because of the thyroid’s role in fetal brain development. Objective To determine the short-term association of exposure to air pollution in the first trimester with thyroid function throughout pregnancy. Design, Setting, and Participants In this cohort study, 9931 pregnant women from 4 European cohorts (the Amsterdam Born Children and Their Development Study, the Generation R Study, Infancia y Medio Ambiente, and Rhea) and 1 US cohort (Project Viva) with data on air pollution exposure and thyroid function during pregnancy were included. The recruitment period for the Amsterdam Born Children and Their Development Study was January 2003 to March 2004; for Generation R, April 2002 to January 2006; for Infancia y Medio Ambiente, November 2003 to January 2008; for Rhea, February 2007 to February 2008; and for Project Viva, April 1999 to November 2002. Statistical analyses were conducted from January 2018 to April 2019. Main Outcomes and Measures Residential air pollution concentrations (ie, nitrogen oxide and particulate matter [PM]) during the first trimester of pregnancy were estimated using land-use regression and satellite-derived aerosol optical depth models. Free thyroxine, thyrotropin, and thyroid peroxidase antibody levels were measured across gestation. Hypothyroxinemia was defined as free thyroxine below the fifth percentile of the cohort distribution with normal thyrotropin levels, following the American Thyroid Association guidelines. Results Among 9931 participants, the mean (SD) age was 31.2 (4.8) years, 4853 (48.9%) had more than secondary educational levels, 5616 (56.6%) were nulliparous, 404 (4.2%) had hypothyroxinemia, and 506 (6.7%) tested positive for thyroid peroxidase antibodies. Concentrations of nitrogen dioxide and PM with an aerodynamic diameter of 2.5 μm or less (PM2.5) were lower and had less variation in women in the US cohort than those in European cohorts. No associations of nitrogen oxide with thyroid function were found. Higher exposures to PM2.5 were associated with higher odds of hypothyroxinemia in pregnant women (odds ratio per 5-μg/m3 change, 1.21; 95% CI, 1.00-1.47). Although exposure to PM with an aerodynamic diameter of 10 μm or less was not significantly associated with hypothyroxinemia, the coefficient was similar to that for the association of PM2.5 with hypothyroxinemia (odds ratio per 10-μg/m3 change, 1.18; 95% CI, 0.93-1.48). Absorbances of PM2.5 and PM with aerodynamic diameter from 2.5 to 10 μg and were not associated with hypothyroxinemia. There was substantial heterogeneity among cohorts with respect to thyroid peroxidase antibodies (P for heterogeneity

Background: The association between air pollution exposure and emotional and behavioural problems in children is unclear. We aimed to assess prenatal and postnatal exposure to several air pollutants and child's depressive and anxiety symptoms, and aggressive symptoms in children of 7-11 years. Methods: We analysed data of 13182 children from 8 European population-based birth cohorts. Concentrations of nitrogen dioxide (NO2), nitrogen oxides (NOx), particulate matter (PM) with diameters of

Background: Exposure to air pollution during pregnancy may increase several behavior problems, including depression/anxiety or conduct/aggressive problems in children, but findings have been incons...

Background: There is limited evidence that exposure to traffic related air pollution is associated with the development of chronic lung allograft dysfunction and graft failure among lung transplant recipients. Objectives: The aim of the study is to explore associations between traffic related air pollution and transplant failure among lung and other solid organ transplant recipients in Great Britain. Methods: All lung, heart, liver, and kidney transplants between 2000 and 2008 were included. Using residential postcode at time of transplant we calculated distance to nearest road, distance to nearest major road, as well as traffic intensity on nearest major road. In addition, annual average air pollution exposures were modelled for each transplant recipient, including nitrogen dioxide, nitrogen oxides and particulate matter (PM 10 , PM 2.5 and PM-Coarse). Cox regression models were fitted to assess associations between each air pollutant and transplant failure after adjustment for age, sex, transplant year and donor age/smoking status. Results: 780 lung, 1213 heart, 3650 liver and 11966 graft kidney transplant patients were included in the analysis. We did not find any consistent association between first lung, liver and kidney transplant failure and any of the analysed air pollutants. For heart transplants there was a borderline significant increased risk of transplant failure (HR 1.40, 95%CI: 1.01-1.95, p=0.045) for each increase in log NOx, however we found no increased risk in heart transplant failure for any other pollutants or exposure proxies. Conclusion: Our analysis does not confirm associations between traffic related air pollution exposure and the risk of transplant failure as reported by previous studies.

There is limited evidence that exposure to traffic-related air pollution is associated with the development of chronic lung allograft dysfunction and graft failure among lung transplant recipients....

Background In order to increase the levels of physical activity in urban population, it is essential to evaluate how real-life policy interventions affect the population cycling attitudes and behaviour. There is evidence to support that policies of different nature have the potential to influence cycling behaviour, but few studies have done longitudinal and multiple interventions assessments. Methods As part of the PASTA European project (Physical Activity through Sustainable Travel Approaches), a longitudinal survey in 7 European cities provides data for the analysis. The questionnaires in the survey feature socio-demographic, psycho-social and city-specific policy-related questions. For each of the 7 cities, a selection of the highest impact policy measures implemented during the survey (November 2014 – January 2017) has been made. The effect of the policy interventions is studied as a natural experiment, with exposed and non-exposed population based on the distance to the infrastructure. The study includes unique a dose-response function which considers the exposure to multiple interventions, the technical quality of these interventions and an adapted bikeability index associated to each participant in each time stamp. Results Our sample includes 10,557 participants across the seven cities. Results will be shown for the complete dataset. Preliminary results from the initial questionnaire (baseline) are already available. A substantial part of the participants are initially either non-cyclists (24%) or cycling less than once a month (23%), which means that 47% of the sample could potentially start cycling or increase their frequency. Furthermore, 52% of the participants intend to increase their cycling rates in the future. All the cities have selected “top measures” and details are being collected. Measures range from bike to work campaigns, to cycle superhighways or other built environment interventions. For example, we have an estimate of a 36% of the participants in London being exposed to any kind of cycling policies. Once the evaluation model will be applied, results will show which profiles of participants are influenced by which types and dose of policies in their attitudes and decisions around cycling for transport. Conclusions The PASTA project explores the bridges between science and policymaking. This study develops and tests an innovative evaluation model which seeks to account for the impact in cycling behaviour of multiple interventions and for the quality of the build environment and interventions themselves. The relation between cycling policies and cycling behavioural aspects will help to determine the most promising policy avenues to promote cycling.

Background In order to increase the levels of physical activity in urban population, it is essential to know how a behavioural change towards cycling as active mobility can be produced and what factors influence people in their choice to cycle. But few studies have done longitudinal analysis of behavioural changes in cycling in relation to their policy context. Methods As part of the PASTA European project (Physical Activity through Sustainable Travel Approaches), a longitudinal survey in 7 European cities will provide the core data for the analysis. This survey was closed the 13th January 2017, after 2 years of data collection. The PASTA survey features specific questions designed to determine the attitudinal and behavioural profile of the participants. The conceptual framework used for the behavioural change assessment features an adaptation of the Transtheoretical Model of Behaviour Change and further developments, which describes five stages of change: Precontemplation, Contemplation, Preparation, Action and Maintenance. The sub-set of questions to determine the stage of change diagnosis are included in the initial (baseline) and final questionnaires, so that a “before” and “after” analysis can be undertaken. Other relevant psycho-social variables featured in the questionnaires will also be explored. The survey data is being complemented with background information including cycling policy and GIS data. Results Our sample is 10,557 participants across the seven cities (subject to further data cleaning). For this sample, a cross-city analysis of behavioural questions will be explored and compared for the initial (baseline) and final questionnaires. The baseline questionnaire has been already analysed and is showing a share of 23% of the sub-sampled participants (n=7,580) in the Precontemplation stage, 7% in Contemplation, 18% in Preparation, 41% in Action and 11% in Maintenance. In this presentation, results will be shown from the complete dataset (that is including all questionnaires) detailed for each of the seven cities, which is being analysed at the moment. The results of the stage diagnosis will be crossed with several socio-demographic variables, such as income, age, education level and sex. As an example, mean age is 40.08 (13.04) years and 54% of the participants are female. Conclusions Understanding the relative importance of the factors influencing mobility behaviour will help to determine the most promising policy avenues for the change towards cycling. This study puts together a unique mix of theories and methods in order to explore the bridges between behavioural change science and policy making.

Background There is limited evidence that exposure to traffic related air pollution is associated with the development of chronic lung allograft dysfunction and graft failure among lung transplant recipients. The aim of the study is to explore associations between traffic related air pollution and transplant failure among lung and other solid organ transplant recipients in Great Britain. Methods All lung, heart, liver, and kidney transplants between 2000 and 2008 were included. The last follow up date was 2 nd March 2015. Using residential postcode at time of transplant, we calculated distance to nearest road and distance to nearest major road. In addition, annual average air pollution exposures were modelled for each transplant recipient, including nitrogen dioxide, nitrogen oxides and particulate matter (PM 10 , PM 2.5 ). Cox regression models were fitted to assess associations between each air pollutant and transplant failure after adjustment for age, sex, transplant year and donor age/smoking status. Results 780 lung, 1213 heart, 3650 liver and 11966 graft kidney transplant patients were included in the analysis. The estimated median follow up time (years) was 9.1, 10.0, 9.1 and 8.8 for lung, heart, liver and kidney respectively. We did not find any consistent association between first lung, liver and kidney transplant failure and any of the analysed air pollutants. Conclusions Our analysis does not confirm associations between traffic related air pollution exposure and the risk of transplant failure as reported by previous studies.

Background Cycling in urban environments is seen as an activity providing many environmental, social and health benefits. There is potential for significant mode shifts towards cycling in many cities, and a better understanding of enabling factors and barriers could help guide more targeted cycle-promoting policies. Eastern-European cities such as Warsaw in particular tend to have low cycling rates and to be under-studied with regards to active travel behaviour. Methods We investigated travel mode choices and perceptions of cycling through surveys administered to two groups of adult population in Warsaw between December 2012 and January 2013. One was a paper and pencil survey of a representative random sample of citizens (“random” sample), while the other was an online survey of respondents who had cycled at least once in the past 6 months (“cyclists” sample). In both surveys, respondents were classified according to their behaviour in the past 6 months as either non-cyclists (did not cycle, for random sample only) utilitarian cyclists (cycled for transport) and recreational cyclists (cycled for recreation). Socio-demographics, travel habits and perceptions of cycling were compared across the categories using the χ2 test or fisher exact test, means using one-way ANOVA and medians using the Kruskal Wallis test. Results The “cyclist” sample (N=505) consisted of 41% recreational cyclists, and 59% utilitarian cyclist (of which 84% were also recreational). Utilitarian cyclists cycled on average 35 minutes per week more than recreational cyclists. They were more likely to perceive more benefits such as rapidity and sense of freedom, while recreational cyclists were more concerned about weather conditions. In the random sample (N=563), there were 46% non-cyclist, 37% recreational, and 15% utilitarian (of which 97% were also recreational) cyclists. The results show that, in general, cyclists tended to perceive less fear of being injured, saw cycling as being cheaper and faster than other modes, believed they had the time and resources needed for bicycle maintenance, felt a sense of freedom and observed to be faster when using bike. In addition, cyclists perceived the lack of cycle lane as less of a barrier to cycling than non-cyclists. Conclusions Cycling is more typically a recreational rather than a utilitarian activity in Warsaw. People who cycle at least occasionally tend to perceive more benefits and fewer barriers to cycling than non-cyclists, and cycling for travel enhances further these beliefs. Improving infrastructure but also making benefits of cycling more salient may increase cycling rates in Warsaw.

Objectives The UK CF Registry annual reports include comparisons between centres on key outcomes such as FEV1 using rankings. While illustrating the distribution between centres, they promote the assumption that those with the highest measures provide “better” care. We hypothesised a more scientific approach based on statistical “process control” using funnel plots and adjustment for case-mix may help to identify exceptional CF care services in terms of clinically meaningful outcomes. Methods We extracted data from annual reviews (2007–2012) on the CF Registry. Our outcomes included FEV1 (% predicted) at 15 years and change in FEV1 between 18 and 21 years. Funnel plots were generated with confidence limits at 2 and 3 standard deviations (SD). Centres with mean values outside these limits are said to display “special cause variation” -variability outside what one would expect. Outcomes were then adjusted for case mix (including gender, genotype, pancreatic sufficiency and socio-economic deprivation) and analysed using funnel plots. Results 31 paediatric centres provided FEV1 data on 15 year olds between 2007 and 2012. Funnel plots of unadjusted FEV1 (% predicted) showed few centres with evidence of special cause variation (2SD limits). Initial case-mix adjustment reduced the number of centres outside these limits to 3. We also identified 28 adult centres providing sufficient data to calculate change in FEV1 (% predicted) between 18–21 years. While there was some evidence of special cause variation (at 2SD limits) in prior to case-mix adjustment, after adjustment none were outside the 2SD limits. None of the centres were outside the 3SD limits in either analysis. Conclusion In conclusion the work to-date illustrates that funnel plots can be used to explore potential differences in FEV1 between specialist centres. Case-mix adjustment models should develop into a useful tool for making centre comparisons which can continue to be used by stakeholders. This is early work, however, and we need to bear in mind that by examining outcomes in small populations risk missing true differences due to low statistical power. Further work is required to assess whether any observed differences are due to chance or are related to the care patients receive.

Objectives The UK CF Registry annual reports include comparisons between centres on key outcomes such as FEV 1 using rankings. While illustrating the distribution between centres, they promote the assumption that those with the highest measures provide "better" care. We hypothesised a more scientific approach based on statistical "process control" and adjustment for case-mix may identify exceptional CF care services in terms of clinically meaningful outcomes. Methods We extracted FEV 1 and BMI on patients aged 12–21 from annual review data (2007–2012). Funnel plots were generated with confidence limits at 2 and 3 standard deviations (SD). Centres with mean values outside these limits are said to display "special cause variation" – variability outside what one would expect. Outcomes were then adjusted for case mix (including gender, genotype, pancreatic sufficiency and socio-economic deprivation) and analysed using funnel plots. Results Using a primary outcome of FEV 1 at age 15, data for 1066 patients from 31 paediatric centres were available. Funnel plots of unadjusted data showed 8 centres with evidence of special cause variation (at 2SD limits). Initial adjustment for case-mix reduced the number of centres outside these limits to 3. None of the centres were outside the 3SD limits in either analysis. Similar patterns were found for BMI percentile in this age group. Conclusion In conclusion the work to-date illustrates that funnel plots can be used to identify differences in FEV 1 and BMI between specialist paediatric centres. Case-mix adjustment models should develop into a useful tool for making centre comparisons which can continue to be used by stakeholders.

Environment International 131, 104927 (2019)