Background: Epidemics of meningococcal meningitis are concentrated in sub-Saharan Africa during the dry season, a period when the region is affected by the Harmattan, a dry and dusty northeasterly trade wind blowing from the Sahara into the Gulf of Guinea.
Objectives: We examined the potential of climate-based statistical forecasting models to predict seasonal incidence of meningitis in Niger at both the national and district levels.
Data and methods: We used time series of meningitis incidence from 1986 through 2006 for 38 districts in Niger. We tested models based on data that would be readily available in an operational framework, such as climate and dust, population, and the incidence of early cases before the onset of the meningitis season in January–May. Incidence was used as a proxy for immunological state, susceptibility, and carriage in the population. We compared a range of negative binomial generalized linear models fitted to the meningitis data.
Results: At the national level, a model using early incidence in December and averaged November–December zonal wind provided the best fit (pseudo-R2 = 0.57), with zonal wind having the greatest impact. A model with surface dust concentration as a predictive variable performed indistinguishably well. At the district level, the best spatiotemporal model included zonal wind, dust concentration, early incidence in December, and population density (pseudo-R2 = 0.41).
Conclusions: We showed that wind and dust information and incidence in the early dry season predict part of the year-to-year variability of the seasonal incidence of meningitis at both national and district levels in Niger. Models of this form could provide an early-season alert that wind, dust, and other conditions are potentially conducive to an epidemic.
1NASA Goddard Institute for Space Studies, New York, New York, USA; 2Department of Applied Physics and Applied Math, Columbia University, New York, New York, USA; 3Lancaster Medical School, Lancaster University, Lancaster, United Kingdom; 4Liverpool School of Tropical Medicine, Liverpool, United Kingdom; 5Department of Epidemiology and Population Health, University of Liverpool, Liverpool, United Kingdom; 6International Research Institute for Climate and Society, Palisades, New York, USA; 7Barcelona Supercomputing Center–Centro Nacional de Supercomputación, Barcelona, Spain; 8Izaña Atmospheric Research Center, Agencia Estatal de Meteorología, Tenerife, Spain; 9Office of Civil Aviation and Meteorology General Direction, Ouagadougou, Burkina Faso; 10Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA
*These authors contributed equally.
Recommended Citation:
Carlos Pérez García-P,o,1,et al. Soil Dust Aerosols and Wind as Predictors of Seasonal Meningitis Incidence in Niger[J]. Environmental Health Perspectives,2014-01-01,Volume 122(Issue 7):679