If aging is defined as an increase in mortality rate over time, then old flies eventually stop aging - their mortality rate reaches a high level but increases no further after that point. As a phenomenon this is much harder to explain than a continued rise in mortality rate, both from a mechanistic and evolutionary point of view. There was some suggestion that the sparse human data for extremely old individuals showed signs of this late life mortality plateau, but that has since been fairly comprehensively refuted:
The growing number of individuals living beyond age 80 underscores the need for accurate measurement of mortality at advanced ages. Accurate estimates of mortality at advanced ages are essential for improving forecasts of mortality and predicting the population size of the oldest-old age group. At the same time, estimating hazard rates at very old ages is difficult because of the very small fraction of survivors at these ages in most countries. Data for extremely long-lived individuals are scarce and subject to age exaggeration. To minimize statistical noise in estimates of mortality at advanced ages, researches have to pool data for several calendar periods.
Single-year life tables for many countries have very small numbers of survivors to age 100, which makes estimates of mortality at advanced ages unreliable. On the other hand, aggregation of deaths for several calendar periods creates a heterogeneous mixture of cases from different birth cohorts. In addition to the heterogeneity problem, there is the issue of using proper empirical estimates of hazard rate at extreme ages when mortality is high and grows with age very rapidly. This problem is sometimes overlooked by researchers who believe that mortality estimates, which work well at young adult ages (like one-year probability of death) can work equally well at very old ages.
Our earlier published study challenged the common view that the exponential growth of mortality with age (Gompertz law) is followed by a period of deceleration, with slower rates of mortality increase. Taking into account the significance of this finding for actuarial theory and practice, we tested these earlier observations using additional independent datasets and alternative statistical approaches. An alternative approach for studying mortality patterns at advanced ages is based on calculating the age-specific rate of mortality change (life table aging rate, or LAR) after age 80. This approach was applied to age-specific death rates for Canada, France, Sweden and the United States. It was found that for all 24 studied single-year birth cohorts, LAR does not change significantly with age in the age interval 80-100, suggesting no mortality deceleration in this interval. Simulation study of LAR demonstrated that the apparent decline of LAR after age 80 found in earlier studies may be related to biased estimates of mortality rates measured in a wide five-year age interval.
Taking into account that there exists several empirical estimates of hazard rate, a simulation study was conducted to find out which one is the most accurate and unbiased estimate of hazard rate at advanced ages. Computer simulations demonstrated that some estimates of mortality as well as kernel smoothing of hazard rates may produce spurious mortality deceleration at extreme ages.