Abstract
We estimate and interpret two forms of age- and season-specific malaria infection and recovery rates. Our analysis is based on a time series of two-wave panel surveys from the first longitudinal field study that allows for direct estimation of these quantities—a WHO malaria survey in Garki, Kano State, Nigeria. We present a strategy for deciding whether two-state, two-wave panel data could have been generated by continuous-time Markov chains or certain mixtures of such chains. The central idea, applicable to longitudinal surveys generally, is to test estimated conditional probabilities for membership in the set of conditional probabilities that can be generated by specific classes of models (e.g. inhomogeneous Markov chains). Our method assumes a priori only that the observations arise by sampling some continuous-time stochastic process.
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