A5065530129- Vaccine Coverage and Hesitancy
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- Employment and Welfare Studies
- Digital Economy and Work Transformation
- Long-Term Effects of COVID-19
- COVID-19 Pandemic Impacts
- Neuroinflammation and Neurodegeneration Mechanisms
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Social Policy and Reform Studies
- COVID-19 epidemiological studies
- Romani and Gypsy Studies
- Human-Automation Interaction and Safety
- Liver Disease Diagnosis and Treatment
- Intracerebral and Subarachnoid Hemorrhage Research
- Statistical Methods in Epidemiology
- Housing, Finance, and Neoliberalism
- Influenza Virus Research Studies
- Energy, Environment, and Transportation Policies
- Reliability and Agreement in Measurement
- Intensive Care Unit Cognitive Disorders
- Frailty in Older Adults
- Electoral Systems and Political Participation
- Taxation and Compliance Studies
- Healthcare Policy and Management
King's College London
2019-2025
University of Edinburgh
2023-2025
Long COVID is a debilitating multisystem condition. The objective of this study was to estimate the prevalence long in adult population Scotland, and identify risk factors associated with its development.
SummaryBackgroundPrioritisation of COVID-19 care led to widespread cancellations elective care, creating a substantial backlog for healthcare systems worldwide. While the pandemic's impacts on hospital waiting lists during early phase pandemic have been described in multiple countries, there is limited research longer-term and recovery efforts.MethodsWe conducted country-wide analysis Scotland's system over an 11-year period (January 1, 2013–December 31, 2023) assess impact backlog, evaluate...
Many of the measures widely-used to estimate workers' exposure automation are subject limitations. Notably, existing do not allow for possibility that could lead positive, as well negative, outcomes workers. Moreover, such underpinned by a theoretical framework conceives non-routine tasks impossible automatean assumption is increasingly being challenged developments in artificial intelligence (AI). I discuss limitations measurement approaches, and argue survey data improve our understanding...
Background: Long COVID is a debilitating multisystem condition. To estimate prevalence and identify risk factors, we analysed routinely collected data from almost the entire adult population of Scotland.Methods: A cohort adults (≥18 years) resident in Scotland between March 1, 2020, October 20, 2022, was created by linking primary care, secondary laboratory testing prescribing. Four outcome measures were used to long COVID: clinical codes, free text care records, on sick notes, novel...
Abstract Background We noted that there remains some confusion in the health-science literature on reporting sample odds ratios as estimated rate case-control studies. Methods recap historical definitively answered question of when (ORs) from a study are consistent estimators for population ratios. use numerical examples to illustrate magnitude disparity between ORs and sufficient conditions them be equal not satisfied. Results stress study, sampling controls those still at risk time outcome...
Vaccination continues to be the key public health measure for preventing severe COVID-19 outcomes. Certain groups may at higher risk of incomplete vaccine schedule, which leave them vulnerable hospitalisation and death. To identify sociodemographic clinical predictors not receiving a scheduled after previously one. We conducted two retrospective cohort studies with ≥3.7 million adults aged ≥18 years in Scotland. Multivariable logistic regression was used estimate adjusted odds ratios (aOR)...
Objectives We undertook a national analysis to characterise and identify risk factors for acute respiratory infections (ARIs) resulting in hospitalisation during the winter period Scotland. Design A population-based retrospective cohort analysis. Setting Participants The study involved 5.4 million residents Main outcome measures Cox proportional hazard models were used estimate adjusted ratios (aHRs) 95% confidence intervals (CIs) association between ARI hospitalisation. Results Between 1...
Objectives Using electronic health records, we derived and internally validated a prediction model to estimate risk factors for long COVID predict individual of developing COVID. Design Population-based, retrospective cohort study. Setting Scotland. Participants Adults (≥18 years) with positive COVID-19 test, registered general medical practice between 1 March 2020 20 October 2022. Main outcome measures Adjusted odds ratios (aORs) 95% confidence intervals (CIs) predictors COVID, patients’...
Abstract Background We compared the quality of ethnicity coding within Public Health Scotland Ethnicity Look-up (PHS-EL) dataset, and other National Service datasets, with 2011 Scottish Census. Methods Measures included level missingness misclassification. examined impact misclassification using Cox proportional hazards to compare risk severe coronavirus disease (COVID-19) (hospitalization & death) by ethnic group. Results Misclassification PHS-EL was higher for all minority groups [12.5...
During the work of Early Pandemic Evaluation and Enhanced Surveillance COVID-19 (EAVE II) group, we reported on vaccine uptake, safety, effectiveness, waning in specific age groups Scotland (e.g.12-17 years) to enable policymakers make decisions based evidence generated nearly real-time [1].At first, these imperatives appeared methodologically straightforward.However, soon realised that seemingly simplest task theory -i.e.reporting uptake -was challenging practice.
Do beliefs about fairness interact with past experiences of labor market shocks to condition redistributive preferences? In a large-scale survey experiment, we investigate the effect informing individuals that growth in automation could disrupt markets ways are (possibly) viewed as unfair. We then exploit COVID-19-induced shock test for an interaction between treatments and exposure. find exposure increase preferences commitments donate potential prize winnings. Our findings suggest this may...
Several population-level studies have described individual clinical risk factors associated with suboptimal antibody responses following COVID-19 vaccination, but none examined multimorbidity. Others shown that post-vaccination offer reduced protection to subsequent SARS-CoV-2 infection; however, the level of from hospitalisation/death remains unconfirmed. We use national Scottish datasets investigate association between multimorbidity and testing antibody-negative, examining correlation...
I conduct a survey experiment to test how individuals' preferences for redistributive policies respond news of their vulnerability an automation-induced labor market shock. As respondents feel more vulnerable, remain constant or decline. However, introducing rhetoric that causes view inequality as unfair increases several policies. The effects are pronounced among more-educated - group expected increasingly be affected by automation in future. This suggests that, going forward, may become...
<title>Abstract</title> Several population-level studies have described individual clinical risk factors associated with suboptimal antibody responses following COVID-19 vaccination, but none examined multimorbidity. Others shown that post-vaccination offer reduced protection to subsequent SARS-CoV-2 infection; however, the level of from hospitalisation/death remains unconfirmed. We use national Scottish datasets investigate association between multimorbidity and testing antibody-negative,...
I investigate how increasing perceived vulnerability to an automation shock influences redistributive preferences, and exposure rhetoric mediates that response. field a pre-registered survey experiment 2,500 UK residents find as increases, preferences remain constant or decline. However, the addition of causes respondents view automation-induced inequality unfair increases support for policies. The effects are pronounced among more-educated - group expected increasingly be affected by going...
We exploit the labor market disruption caused by COVID-19 pandemic to investigate how experience of a shock interacts with beliefs condition redistributive preferences. field large-scale survey experiment test effect informing shocked and non-shocked individuals that growth in automation could exacerbate inequalities, unfairly penalize certain workers, or benefit elites. Prior exposure appears sensitize respondents information about potential future shock, resulting heightened also find...
Background: Immune responses to COVID-19 vaccines differ between individuals. Identifying characteristics associated with insufficient post-vaccination IgG antibody and describing the association subsequent SARS-CoV-2 infection severe outcomes could inform future vaccination strategies. Methods: We linked population-based seroprevalence surveillance data national cohort from Early Pandemic Evaluation Enhanced Surveillance of (EAVE II), comprising primary care, RT-PCR testing, vaccination,...
Do beliefs about fairness interact with past experiences of labor market shocks to condition redistributive preferences? We field a large-scale survey experiment investigate the effect informing individuals that growth in automation could disrupt markets ways (possibly) viewed as ‘unfair’. then exploit COVID-19-induced shock test for an interaction between treatments and exposure. find exposure increase preferences produce behavioral effects. Our findings suggest this may be motivated by...
The QCovid 2 and 3 algorithms are risk prediction tools developed during the second wave of COVID-19 pandemic that can be used to predict hospitalisation mortality, taking vaccination status into account. In this study, we assess their performance in Scotland. We Early Pandemic Evaluation Enhanced Surveillance national data platform consisting individual-level for population Scotland (5.4 million residents). Primary care were linked reverse-transcription PCR virology testing, mortality data....
I investigate the reliability of using survey data to measure workers’ experiences automation. 4,070 US residents and find that respondents' self-reported exposure automation predicts occupational employment changes at least as reliably widely-used exposure, Routine Task Intensity (RTI). Moreover, improves on RTI by distinguishing between negative positive outcomes from automation, better capturing artificial intelligence. These findings suggest a approach could offer new insights would...