Lifespan Estimator: Population
About the Model
The Population Lifespan Estimator determines the impact of improved health behaviors on estimated life expectancy and on causes of death for the US population.
What's "beneath the hood?"
At the core is a Monte Carlo microsimulation model that represents the 19 conditions representing the top causes of mortality in the USA and the top 28 risk factors of clinical and statistical significance associated with their onset.
The model works by creating virtual individuals. Each month, an individual can develop new risk factors and/or new conditions, have existing risk factors or conditions resolve (e.g. through treatment), or die. We simulate birth cohorts of patients with characteristics resembling the population of the United States. We then compare current health with the user’s selected health behavior improvements. Each improvement represents an idealized scenario in which the risk factor is eliminated or adherence to therapy was perfect.
Using the Model
The numbered steps below correspond to the steps in the left frame on the model page.
- 1. Select the ways in which you’d like to improve health in your population.
- 2. Select whether to run the simulation as a birth cohort or apply the health improvements to the current population.
- a. Choosing birth cohort will run a simulation of individuals, all entering the model at the same age, who have the selected behavior changes applied over their entire lifespan.
- b. Choosing Current US population will apply the selected behavior changes to the simulated population at each person’s current age. Thus, the behavior change will take place “now” at each individual’s current age, rather than over their entire lifespan.
- 3. Choose whether you want to run men, women, or both genders.
- 4. The model will compare causes of death with and without the selected behavioral changes. Choose how far into the future to view the causes of mortality. Choices are presented as years into the future if you chose “Current US population” in Step 2, or as an age if you chose to run as a birth cohort.
Understanding the results
When you run the model, two elements appear in the results panel.
- 1) Life expectancy estimate. Estimated life expectancy is displayed with and without the selected behavioral changes.
- 2) Mortality forecast. Mortality predictor grids are displayed for the current health risk profile (left) and for the chosen health improvements (right).
The mortality predictor grids represent the probability of being alive and of dying of various mortality-causing conditions at the time period selected in the side panel in Step 4. They are displayed as outcomes per 1,000 persons.
The color green represents the probability of being alive, and the colors red through yellow indicate the probability dying of various conditions. Holding the mouse over the grids pops up a key for that color that corresponds to the legend below the grids. The top five causes of mortality are indicated by shades of red and orange. For a breakdown of causes beyond the top five, hover your cursor over the word, “Breakdown.”
Tailoring for your project
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Publications
In progressAn alternative approach to estimating life-years lost based on simulating an optimally healthy population.
Stevens ER, Zhou Q, Taksler GB, Nucifora KA, Braithwaite RS