Sickness and death are individual- and population level phenomena. At the individual level, they are best understood in terms of their causes. In illness the best prognosis derives from what is known about the cause and about the individual. At the population level, sickness and death can also be understood in terms of incidence. Future rates of sickness and death can be forecast from experience, taking into account the trend and likely variations from it. Population-level statements about sickness and death – morbidity and mortality rates – can be considered statements of comparison. As such, they underlie many judgments about health and health care.

Morbidity and mortality are also structural phenomena, which is to say that, considered for a sizable number of people, they display certain regularities. The most important of these relate to age and appear as curves or schedules when morbidity and mortality data are arranged by age. Age-specific sickness and death rates should not be expected to be identical in any two populations, but their structure – their distribution by age – should be similar. This makes it possible to make estimates for missing data and to compare individual- and population-level experience with sickness and death over time. This essay summarizes the basic method of analysis, which employs a life table, and suggests some ways in which the problem of incomplete information can be overcome with various estimation procedures.