This LIDA Seminar will be presented via Zoom
Register in advance for this meeting:
This seminar will kick-off with Dr Kate Pickett, who will introduce her work on “Born in Bradford” and the importance of the intern’s analytic contributions to tackling the major societal issues affecting us as we emerge from the pandemic.
Presentation 1: Spatial Analysis of the COVID-19 Pandemic in Bradford Metropolitan District
By: Harry Tata
Abstract: The district of Bradford has been one of the hardest-hit areas of the country throughout the coronavirus pandemic, in terms of community transmission and strain on medical infrastructure. To identify vulnerabilities and advise policy, there is an ongoing effort at the Bradford Institute of Health Research to build a detailed local understanding of the pandemic and its repercussions. At different times, the overall spatial pattern of infections has been ‘ordered’ or ‘disordered’; this talk explores what these overall patterns look like on a smaller scale, and how this relates to the local population.
Presentation 2: Exploring ethnicity as a predictor of low birthweight in the Bradford Better Start area
By: Alex Dalton
Abstract: Low birthweight in Bradford is considerably higher than the rest of the UK, particularly in areas of Bradford suffering from high levels of material deprivation. The Born in Bradford cohort (2007-2011) and their Better Start cohort (2016-2020) allows low birthweight to be studied across a multi-ethnic community over a time period in which austerity measures took effect.
This rich, longitudinal dataset enables maternal and socio-economic factors associated with low birthweight to be investigated. Looking at the prevalence of low birthweight in certain ethnic groups alongside various maternal and socioeconomic variables, this talk will explore whether the association between birthweight and ethnicity had changed over time in a materially deprived, multi-ethnic population. Once these associations have been identified, the data is treated as a single longitudinal dataset to model the trajectory of birthweight over time for specific ethnic groups.
Low birthweight has been linked to poor health outcomes and the nature of its role (whether causal or correlated) is heavily studied and debated. Thus, identifying any meaningful indicators for low birth weight is relevant to this debate and explores the feasibility of reducing the rate of low birth weight.
Presentation 1: Analysing and building cohorts in the OMOP common data model
By: James Lazarus
Abstract: When conducting medical studies one of the most challenging aspects is obtaining the data with issues in privacy; the number of patients required; as well as research results needing to be drawn from many disparate data sources and compared and contrasted. To extract data for analysis purposes traditionally requires strict data use agreements. Thus, a common data model is used to alleviate this need by eliminating this extraction step. However, retrieving these cohorts can be challenging, and can be made easier. This presentation will explain the deployment of the functions made to make this extraction of data easier. As well as an overall outline of the document and the analysis scripts made.
If you wish to ask the presenters any questions or offer feedback, please email LIDA