I'd like to look at the effect of lockdown policies(announcements) over time on features of the COVID-19 epidemic. I'm not very familiar with different time-series, so i'd like advice on what type of analysis might be appropriate here. Some information about the data:
- Outcome/Dependent Variable is continuous, but does not change at regular intervals. For example, it may stay constant and then abruptly change on specific dates.
- Each region has implemented multiple government responses in the form of lockdowns. The announcement of these lockdowns does not occur at regular intervals.
- Each instance of a government policy in regards to lockdowns can increase restrictions or decrease restrictions, so we would hypothesize an increase/decrease depending on the policy towards lockdowns.
Here's a picture of what the data might look like in a hypothetical region (in reality, i'd be doing this separately for many regions).
Some questions i'd like to answer:
- What is the average time from a lockdown policy/announcement to a change in the outcome? Perhaps this question lends itself to some kind of survival analysis?
- What is the magnitude of that change, on average?