Model-based design and analysis of life table experiments for insect vectors

Life tables help identify physiological differences in distinct development stages and detect potential vulnerabilities for conservation and control. However, cataloguing mortality, development, and fecundity by following each individual could be challenging in insects due to interweaving generations and development stages. Here, we propose to use age- and stage- structured population dynamics modelling to help derive life table characteristics from the observed dynamics of reared populations. We examine a hypothetical case, a simulated population with known life parameters, and two experimental cases, observations of the population dynamics of the mosquito vector Culex quinquefasciatus and Culex pipiens, to demonstrate that model-based inference can correctly identify life parameters from longitudinal observations. The analysis reveals not only the differential physiological behaviour of distinct development stages, but also identifies the degree to which each parameter can be inferred from the data. The methods introduced constitute a model-based approach to identifying life table characteristics from incomplete longitudinal data, and help to improve the design of life table experiments. The approach is readily applicable to the development of climate- and environment-driven population dynamics models for important vectors of disease.