Proactive methodological disclosure of a high resolution precision calibrated estimate of the Gompertz-Makeham Law of Mortality and general utilization hazard rates through lifespan interferometry against annual census data consolidated from the administrative data of all publicly funded healthcare provided in a single geopolitical jurisdiction.
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Incorporate Geographic Identifiers and Geometries #2
Incorporating geographic identifiers requires dealing with three thorny data volume problems:
Finding a postal code for each interval for each person. It is not entirely clear what heuristic to use to choose a postal code in the case of multiple choices, particularly because heuristics based on time sorting will be computationally expensive to do at scale.
Finding the local geography code for each postal code requires a non-trivial look-up against a large reference table. Again running this at scale will be computationally punishing.
Finally mapping the local geography code to a geometry requires only a look-up against a relatively small reference table, but then requires incorporating a geometry field.
The strategy for efficiently tabulating geography:
Find all unique combinations of days and putative postal codes.
Filter against the postal code list to pull only valid postal codes.
To resolve day collisions take the alphabetically highest postal code because of the behavior to enter unknown postal codes as alphabetically lower postal codes, e.g. T0T0T0.
For each persons semi-annual interval find the postal code at the beginning and the end of the period.
Incorporating geographic identifiers requires dealing with three thorny data volume problems: