This LIDA Seminar will be presented via Zoom
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Meeting ID: 831 6757 9004
Presentation 1: Spatial Analysis of the COVID-19 Pandemic in Bradford Metropolitan District
By: Harry Tata
Abstract: The metropolitan 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 by the COVID-19 Scientific Advisory Group at the Bradford Institute of Health Research to build a detailed local understanding of the pandemic and its repercussions. This talk presents a descriptive analysis of the dynamics of infections within the district, with a focus on characterising the spatial pattern of cases at different stages of the pandemic.
Presentation 2: Exploring the predictors of low birthweight between pre-austerity and austerity periods 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, and compared between the pre-austerity and austerity periods. The rich, longitudinal dataset enables gestational and socio-economic factors associated with low birthweight to be investigated.
This talk utilises data visualisations and statistical analysis to study and identify such associations, along with whether those associations have changed over time. Where factors are identified as predictors of low birthweight, the project aims to develop a predictive model.
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 3: 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 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. The aim of this project is to design and build a cohort building library, analysis scripts, along with written tutorials in order to make data retrieval and analysis from the common data model as easy and as fast as possible.
If you wish to ask the presenters any questions or offer feedback, please email LIDA