Leap years and time intelligence

I have a model that shows running daily uptime (YTD).  I am attempting to calculate the year-over-year variance (on a daily basis), but the lack of 29-Feb in 2017 is skewing the numbers.  When it jumps from 28-Feb to 01-Mar it is taking away an extra day's worth of data.

TYTDRUDelta = 
TOTALYTD(sum('Date'[UptimeMin]),'Date'[Date]) - 
TOTALYTD(sumx(
            filter(
               relatedtable('IT Outages'), 'IT Outages'[Business Impact]="TRUE"
            ),
            'IT Outages'[Downtime]
        ),
	'Date'[Date]
)

LYRUpDelta =
CALCULATE(
            [TYTDRUDelta],
            SAMEPERIODLASTYEAR('Date'[Date])
)

[UpTimeMin] is just 24*60 (number of minutes in a day).  So the values I am seeing are:

Date            TYTDRUDelta     LYRUpDelta
27-Feb-2017     83042           83520
28-Feb-2017     84482           84960
1-Mar-2017      85922           87840

Notice that the gap in LYRUpDelta between 28-Feb and 1-Mar is 2880 (or 2 * 24 *60) while the gap between 27-Feb and 28-Feb is just 1440 (24 * 60).  There are no records in 'IT Outages' for 28-Feb-2017 or 1-Mar-2017.

I tried PARALLELPERIOD but that ended up putting nothing but blanks in LYRUpDelta.

How do I deal with the leap day in 2016 ?

Thanks,

David