Methodology

QuietCost utilizes a Discrete-Time Markov State Transition Model layered with Monte Carlo simulations to project long-term fiscal outcomes.

Markov Model States

The population simulates transitions between six defined states monthly:

  • Stable Housing: Individuals sustainably housed.
  • Emergency Shelter: Temporary emergency housing utilization.
  • Street Homelessness: Unsheltered chronic homelessness.
  • Jail / Justice System: Periods of incarceration preventing housing.
  • Acute Healthcare: Emergency department or prolonged inpatient care.
  • Deceased: An absorbing state calculating survival hazard functions.

Responsible AI Limitations

Hard Bypass Conditions

The simulator will disable itself if any of the following conditions are met to prevent misinformed policy decisions:

  • Data is older than 18 months.
  • Missing data exceeds 25% of any critical column.
  • Baseline population size falls below 100 individuals.
  • An external shock flag (e.g., pandemic, disaster) has been toggled overriding standard transitions.