Summary: Neisseria meningitidis \((Nm)\) is a major cause of bacterial meningitidis outbreaks in Africa and the Middle East. The availability of yearly reported meningitis cases in the African meningitis belt offers the opportunity to analyze the transmission dynamics and the impact of control strategies. In this paper, we propose a method for the estimation of state variables that are not accessible to measurements and an unknown parameter in a \(Nm\) model. We suppose that the yearly number of \(Nm\) induced mortality and the total population are known inputs, which can be obtained from data, and the yearly number of new \(Nm\) cases is the model output. We also suppose that the \(Nm\) transmission rate is an unknown parameter. We first show how the recruitment rate into the population can be estimated using real data of the total population and \(Nm\) induced mortality. Then, we use an auxiliary system called observer whose solutions converge exponentially to those of the original model. This observer does not use the unknown infection transmission rate but only uses the known inputs and the model output. This allows us to estimate unmeasured state variables such as the number of carriers that play an important role in the transmission of the infection and the total number of infected individuals within a human community. Finally, we also provide a simple method to estimate the unknown \(Nm\) transmission rate. In order to validate the estimation results, numerical simulations are conducted using real data of Niger.{
©2016 American Institute of Physics}