  The "meningitis belt" is a region in sub-Saharan Africa where annual
outbreaks of meningitis occur, with large epidemics observed cyclically. While
we know that meningitis is heavily dependent on seasonal trends (in particular,
weather), the exact pathways for contracting the disease are not fully
understood and warrant further investigation. This manuscript examines
meningitis trends in the context of survival analysis, quantifying underlying
seasonal patterns in meningitis rates through the hazard rate for the
population of Navrongo, Ghana. We compare three candidate models: the commonly
used Poisson generalized linear model, the Bayesian multi-resolution hazard
model, and the Poisson generalized additive model. We compare the accuracy and
robustness of the models through the bias, RMSE, and the standard deviation. We
provide a detailed case study of meningitis patterns for data collected in
Navrongo, Ghana.
