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.

Preprint (NOT YET PEER REVIEWED) at: Link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

Project folder structure
- Code
- Codelists
- Data
- Doc
- Graphfiles

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

spiros / COVID-Collateral