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

Stanton, Michelle and Agier, Agier and Taylor, Benjamin and Diggle, Peter (2014) Towards real-time spatio-temporal prediction of district-level meningitis incidence in sub-Saharan Africa. Journal of the Royal Statistical Society: Series C (Applied Statistics), 177 (3). pp. 661-678. ISSN 0035-9254

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Abstract

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 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.

Item Type:
Journal Article
Journal or Publication Title:
Journal of the Royal Statistical Society: Series C (Applied Statistics)
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1800/1804
Subjects:
ID Code:
68817
Deposited By:
Deposited On:
05 Mar 2014 08:58
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Nov 2020 03:29