A multi-state spatio-temporal Markov model for categorized incidence of meningitis in sub-Saharan Africa.

Agier, L and Stanton, M and Soga, G and Diggle, PJ (2013) A multi-state spatio-temporal Markov model for categorized incidence of meningitis in sub-Saharan Africa. Epidemiology and Infection, 141 (8). pp. 1764-1771. ISSN 0950-2688

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Abstract

Meningococcal meningitis is a major public health problem in the African Belt. Despite the obvious seasonality of epidemics, the factors driving them are still poorly understood. Here, we provide a first attempt to predict epidemics at the spatio-temporal scale required for in-year response, using a purely empirical approach. District-level weekly incidence rates for Niger (1986–2007) were discretized into latent, alert and epidemic states according to pre-specified epidemiological thresholds. We modelled the probabilities of transition between states, accounting for seasonality and spatio-temporal dependence. One-week-ahead predictions for entering the epidemic state were generated with specificity and negative predictive value >99%, sensitivity and positive predictive value >72%. On the annual scale, we predict the first entry of a district into the epidemic state with sensitivity 65·0%, positive predictive value 49·0%, and an average time gained of 4·6 weeks. These results could inform decisions on preparatory actions.

Item Type:
Journal Article
Journal or Publication Title:
Epidemiology and Infection
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2700/2713
Subjects:
ID Code:
134806
Deposited By:
Deposited On:
22 Jun 2019 09:19
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Jan 2020 12:04