I would like to conduct a study to look at the effect COVID-19 pandemic lockdown has on the following:
- number of cases at the hospital emergency department (broken down into the different triages and different complaints/diagnoses
- waiting time to consultation
- returns to hospital emergency department within 24 hours (percentage data)
- subsequent admission to general ward or ICU
The pre-period (i.e. before lockdown) and the post-period (i.e. after implementation of lockdown) are not consecutive. We are looking at the same months both in pre- and post-periods, each having a total of 60 days.
Would it be okay if I use t-test to compare pre- and post-period data? But that would mean aggregating the data into 1 data point pre and 1 data point for post. Would we lose resolution here?
Or should I do an interrupted time series, aggregating by day?
Appreciate any advice!