Cox regression for non-repeated events with panel data

I have a question with regard to the research design for a research paper I´m writing on. The data comes in the following form:

Country     Dep.Var     Indep.Var.1    Indep.Var2    Indep.Var.3
1             0             5              2.3         4
1             24            10             2.3         4
1             12            12             2.3         4
2             14            0              3           2.1
2             86            25             3           2.1
2             79            63             3           2.1
3             12            0              1.8         5.3
3             55            8              1.8         5.3
3             45            12             1.8         5.3

This is not the actual data, but the structure is like that. The data comes in panel form and the dependent and 1st independent variable are reported on a daily basis (1st independent variable is reported in a cumulative fashion, which is why the log() will be entered into the analysis). However the two other independent variables, which are the ones of prime interest are indicators only reported in a yearly fashion and thus don´t vary over time for the individual countries in the created dataset. What I am trying to do is to perform a survival analysis or more precisely estimate a cox proportional hazard model/Cox regression, defining the hazard as the dependent variable scoring below a certain threshold for the first time.
As I am dealing with panel data, I thought it would make sense to do this in a fixed effects fashion. However trying to find out if this is possible for this dataset feels like going down a statistical rabbit hole and left me with a lot of confusion.
So this led to a few questions:

1. Is it possible to include fixed effects in this analysis and if yes, time-fixed or country-fixed effects or both?
2. How can unbiased estimates in event history analysis be obtained in this setting? There is some literature on this, but all I found ended up with only comparing units with themselves in the "past" and in past event cycles. As there is only one "event-cycle" and the event can´t occur more than once, what is a promising approach? Also, as the main explanatory variables remain constant over time estimates need to be built on variance between the different countries and cant´t based on variance within the units as there is no variance over time.

I´d appreciate any help and wanted to thank you in advance. I´m also happy with literature recommendations!

Edit: I´ve been asked to provide the event code and the time for each era and wanted to make clear, that this is not the "final" dataset to be entered into R for analysis. This is a question purely theoretical, asking, what can possibly be done and how the issue of panel data can be approached with respect to time invariant effects and what consequences arise from this for later event-history analysis.
The countries will later enter the event-history dataset with the dependent variable >0 and the hazard event will be defined as a declining dependent variable first scoring below a threshold to be defined later on.