Accelerated failure time (AFT) modeling for the development and survival of Russian wheat aphid, Diuraphis noxia (Mordvilko)

Accelerated failure time model (AFT) and Cox's proportional hazards model (PHM) are considered the two most significant models in survival analysis, which has become a de facto standard for biomedical data analysis and modeling. AFT not only plays an extremely significant role in survival analysis but also finds extensive applications in engineering reliability. Survival analysis studies a special type of random variables: time‐to‐event (also known as failure time, lifetime or survival time) random variables. Examples of time‐to‐event random variables include survival times of patients in a clinical trial and failure times of machine components. Since molting and death times of insect individuals are also perfect examples of time‐to‐event random variables, we argue that survival analysis including AFT modeling is ideal for analyzing insect development and survival data, and further for building dynamic models of insect development and survival. Here we demonstrate such an application with data collected by observing stage‐to‐stage development and survival of 1,800 Russian wheat aphids (RWA), Diuraphis noxia , reared in laboratory growth chambers arranged in 25 treatments (each with 72 individuals). The main advantages of survival analysis, including the unified modeling of survival and development as well as handling of information censoring, are also discussed.