In this paper we analyze survival data of populations of sterilized nematodes, Caenorhabditis elegans, exposed to heat shocks of different duration at the beginning of their adult lives. There are clear hormesis effects after short exposure to heat and clear debilitation effects after long exposure. Intermediate durations result in a mixture of these two effects. In this latter case, the survival curves for the control and experimental populations intersect. We show that observed effects may be explained by using a model of discrete heterogeneity. According to this model, each population of worms in the experiment is a mixture of subcohorts of frail, normal, and robust individuals; exposure to heat changes the initial proportion of worms in the subcohorts (heterogeneity distribution); and these changes depend on the duration of exposure. In other words, exposure to heat does not influence mortality rates (survival functions) in the subcohorts but does cause individuals to move from one subcohort to another. In a biological interpretation of this finding we hypothesize that, when coping with stress, the organisms of worms use several lines of defense. Switching these lines on and off in response to stress in individual organisms generates the spectrum of observed survival effects at the population level. We discuss possible molecular biological mechanisms of stress response and directions for further research.

No abstract

BackgroundVectorial capacity and the basic reproductive number (R0) have been instrumental in structuring thinking about vector-borne pathogen transmission and how best to prevent the diseases they cause. One of the more important simplifying assumptions of these models is age-independent vector mortality. A growing body of evidence indicates that insect vectors exhibit age-dependent mortality, which can have strong and varied affects on pathogen transmission dynamics and strategies for disease prevention.Methodology/Principal FindingsBased on survival analysis we derived new equations for vectorial capacity and R0 that are valid for any pattern of age-dependent (or age–independent) vector mortality and explore the behavior of the models across various mortality patterns. The framework we present (1) lays the groundwork for an extension and refinement of the vectorial capacity paradigm by introducing an age-structured extension to the model, (2) encourages further research on the actuarial dynamics of vectors in particular and the relationship of vector mortality to pathogen transmission in general, and (3) provides a detailed quantitative basis for understanding the relative impact of reductions in vector longevity compared to other vector-borne disease prevention strategies.Conclusions/SignificanceAccounting for age-dependent vector mortality in estimates of vectorial capacity and R0 was most important when (1) vector densities are relatively low and the pattern of mortality can determine whether pathogen transmission will persist; i.e., determines whether R0 is above or below 1, (2) vector population growth rate is relatively low and there are complex interactions between birth and death that differ fundamentally from birth-death relationships with age-independent mortality, and (3) the vector exhibits complex patterns of age-dependent mortality and R0∼1. A limiting factor in the construction and evaluation of new age-dependent mortality models is the paucity of data characterizing vector mortality patterns, particularly for free ranging vectors in the field.

No abstract