Survival Curves, Prevalence Rates, and Dark Matters Therein

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Abstract
Survival curves are a visual aid to help us think about interrelationships between chronic morbidity, disability, and mortality. Prevalence rates indicate a population's morbidity and disability status at given times. The curves and rates are both residues of very dynamic processes: Chronic conditions may be alleviated as well as progress; functions may be restored as well as lost. The dynamics can be represented by transition rates between states; transition rates can vary across population groups (heterogeneity). Contemporary data and life table techniques are advancing to measure morbidity-disability-mortality dynamics and summarize them in statistical manner. Topics that remain elusive or overlooked are comorbidity, nonfatal chronic conditions, frailty, generalized symptoms, and difficulty in many activity domains; these are dark matters. Future scenarios of health depend on premises about where prevention of chronic conditions will occur. I present three basic scenarios (one includes the compression of morbidity) and note their implications for transitions between states and for morbidity and disability prevalence rates. Compression of morbidity is an intriguing notion, but to know if it occurs or not over the next century requires a deep foundation of epidemiologic data and analysis, and that is where scientific efforts must be devoted.