Forecasting one time series with missing data with help of other time series
Not a fully complete answer, but some inputs.


Your time series are correlated. 
I assume that the measure you want to forecast for a region is an aggregation of units forecasts.


To address the first point, I usually use Vector Autoregressive Model (VAR) that forecast all time-series at once (each one being expressed as a regression using the others)
The second point involves the concept of hierarchical forecasting and reconciliation. You can exploit the fact that the regional forecast should/must equal the unit- forecasts. There can be a process to adjust forecasts to take that into account.

There are both packages for VaR and hierarchical reconciliation in R but as far as I know no direct code to handle both at the same time...

You may find this paper providing some details on the proposed approach:
https://mpra.ub.uni-muenchen.de/76556/1/MPRA_paper_76556.pdf