Towards real-time spatio-temporal prediction of district-level meningitis incidence in sub-Saharan Africa

Within an area of sub-Saharan Africa termed ‘the meningitis belt’, meningococcal meningitis epidemics are a major public health concern. The epidemic control strategy currently utilised is reactive, such that a vaccination programme is initiated in a district once a pre-defined weekly incidence threshold is exceeded. In this paper we report progress towards the development of an early warning system based on statistical modelling of district-level weekly incidence data. Four modelling approaches are considered and their forecasting performances are compared using<br/>weekly epidemiological data from Niger for the period 1986-2007. We conclude that the models under consideration are advantageous in different situations. The described three-state Markov model in which observed incidence is categorised according to policy-defined thresholds gives the most reliable short term forecasts, whereas the proposed dynamic linear model, using log-transformed weekly incidence as the response variable, gives more reliable predictions of annual epidemics.<br/>