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COVID-Collateral

Study investigating the indirect effects of COVID-19.

While a reduction in hospital activity during the COVID-19 pandemic has been well documented, there has been only limited small scale research on impacts on primary care. We explored the effects of the COVID-19 pandemic and its control on general practice consultations for adverse acute physical and mental health outcomes in England to inform public health planning and policy.

Full paper at: Link

Shiny app at: Link

Authors

Kathryn E Mansfield, PhD*, Rohini Mathur, PhD*, John Tazare, MSc*, Alasdair D Henderson, PhD*, Amy Mulick, MSc*, Helena Carreira, PhD, Anthony A Matthews, PhD, Patrick Bidulka, MSc, Alicia Gayle, MSc, Harriet Forbes, PhD, Sarah Cook, PhD, Angel YS Wong, PhD, Helen Strongman, PhD, Kevin Wing, PhD, Charlotte Warren-Gash, PhD, Sharon L Cadogan, PhD, Liam Smeeth, PhD, Joseph Hayes, PhD, Jennifer K Quint, PhD, Martin McKee, PhD, Sinéad M Langan, PhD

* First authors

Table of contents

Project folder structure

Code
  • Run all R code from COVID-Collateral.Rproj
  • data_prep takes raw CPRD data and aggregates into weekly number of outcomes and weekly denominators by strata. Note - data are held on separate secure server.
  • its Interrupted time series analysis code for Figure 3 and Table 3 and sensitivity analysis for diabetes consultations
  • Plot_code Functions to plot weekly percentage of consultations by outcome (Figures 1 and 2, S2-S4)
  • Shiny_app All code and data for the accompanying Shiny app
Codelists
  • Storage for finalised codelists used in the study for all conditions
Data
  • Summary analysis datasets for all conditions. Note data censored if weekly outcomes < 5.
Doc
  • Storage for any relevant documentation
  • Getting Started
  • Approved Independent Scientific Advisory Committee (ISAC) application (Word document)
Graphfiles
  • Outputs from analysis code

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Study investigating the indirect effects of COVID-19

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