Forecasting race/ethnicity proportions at city scale

Hello, first time poster here, interested in forecasting.

I am working with a city-sized population (~150k residents, ~30 tracts) in the San Francisco Bay Area, for which I can retrieve ACS population estimates by race/ethnicity (from B01003) for a couple of overlapping intervals (2011-2015, …, 2014-2018).

The proportions are fairly stable, but I’m more interested in the future — specifically, in 2021-2025 — than the past.

As an R user, I could try to adapt some generic forecasting tools, like those in Rob Hyndman's {fable} package, to generate estimates for the near future. But should I be guessing at which tools and approaches to use, or has someone already done a pretty robust job somewhere else that could be adapted or applied? (Note: not asking for R code, just recommendations for an approach.)

Methods that would generate predictive intervals, or at least some metric of uncertainty/confidence, would be ideal. All suggestions would be welcome! I'm hoping to be able to apply the same technique(s) to other city-sized regions in the future, even after Decennial counts become available.

Thank you in advance for your time and attention.

Very best,
David