Help with forecasting with less-patterned data using UCM

[samp945]

Hello all,

I'm new to forecasting and have been using UCM with good results for certain analyses. However, I'm currently working with a couple of datasets where the training data appears less patterned (i.e., no seasonality). Specifically, I'm trying to create retrospective forecasts for 2020+ using monthly vehicle fatality data from 2015 - 2019. My goal is to assess how much of an impact pandemic conditions had on certain types of mortality unrelated to COVID.

I've attached the dataset I'm using. Any hints or tips on how to create a better model? My current model has very wide confidence intervals.

Here's my code (I've commented out certain statements because the model diagnostics suggested I should based on papers I've read):

%let Cause=Traffic;

proc ucm data=CountsDeathMonthCause;
		where CauseOfDeath="&Cause";
id DeathMonth interval=month;
	model Count;

	irregular;
		*variance=0 NoEst;
	level
		variance=0 NoEst;
	*slope
		variance=0 NoEst;
	*cycle
		variance=0 NoEst=(variance);
	*season
		length=12
		type=trig
		variance=0 NoEst;

	deplag lags=(1);
	
	estimate
		back=48
		plot=panel;
		*outest=pan.EstDeath&Cause;
	forecast
		back=48
		lead=48
		plot=(decomp forecasts)
		outfor=pan.TableDeath&Cause;
	ods output FitStatistics=FitDeath&Cause;
run;

Thanks for reading!