Imagine trying to figure out how many babies might pass away. This is crucial for planning healthcare services. The number can change based on things like the baby's gender, where they live, or their parents' background. Sometimes, local predictions don't match national ones, which can cause problems when dividing resources.
Scientists came up with a clever solution: grouped time-series forecasting. This method combines local predictions to better match national ones. They tested this approach using infant mortality rates in Australia. Surprisingly, it worked well even for long-term forecasts, up to 20 steps ahead!
This technique could help governments make better healthcare decisions now and in the future. It's like having a crystal ball that can see far into the future and help plan services more effectively.
