The article discusses how to estimate confidence intervals for parameters in a model that predicts Covid-19 case growth and fatality rates. The model has two parts: one with known values and one with unknown smooth functions. The researchers used a weighted least square method and a smoothing technique called truncated spline to estimate these parts. They then calculated confidence intervals for the parameters using specific mathematical methods. The results can help understand how variables like age, gender, and isolation affect Covid-19 outcomes.