The uncertainty intervals is used when the dataset is incomplete, the observed data could come from many different complete data sets, and the different complete datasets would lead to different estimates and inference

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https://www.diva-portal.org/smash/get/diva2:1043969/FULLTEXT01.pdf

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offered by the following article:

Measurement of uncertainty and confidence intervals near natural limits.

Royal College of Chemistry, 2008.

Dear,

Public-health reports sometimes leave out confidence intervals when data are presented for an entire population. A rationale cited for this practice is that population statistics are measurements rather than estimates; hence there is no need to consider random error because the statistics show exactly what occurred.

We argue that this reason does not justify leaving out interval estimates. Targeting intervention in areas with high disease rates can be justified only on the assumption that the excess would continue in those areas; in that case, at the very least, we need to allow for random fluctuations over time.

Thus, we recommend that interval estimates be reported even when the entire population is observed.