Atmospheric Dust, Early Cases, and Localized Meningitis Epidemics in the African Meningitis Belt: An Analysis Using High Spatial Resolution Data

BACKGROUND: Bacterial meningitis causes a high burden of disease in. the African meningitis belt, with regular seasonal hyperendemicity and sporadic short, but intense, localized epidemics during the late dry season occurring at a small spatial scale [i.e., below the district level, in individual health centers (HCs)]. In addition, epidemic waves with larger geographic extent occur every 7-10 y. Although atmospheric dust load is thought to be an essential factor for hyperendemicity, its role for localized epidemics remains hypothetic. OBJECTIVES: Our goal was to evaluate the association of localized meningitis epidemics in HC catchment areas with the dust load and the occurrence of cases in the same population early in the dry season. METHODS: We compiled weekly reported cases of suspected bacterial meningitis at the HC resolution for 14 districts of Burkina Faso for the period 2004-2014. Using logistic regression, we evaluated the association of epidemic HC-weeks with atmospheric dust [approximated by the aerosol optical thickness (AOT) satellite product] and with the observation of early meningitis cases during October December. RESULTS: Although AOT was strongly associated with epidemic HC-weeks in crude analyses across all HC-weeks during the meningitis season [odds ratio (OR) = 6.82; 95% CI: 4.90, 9.50], the association was no longer apparent when controlling for calendar week (OR = 0.92; 95% CI: 0.60, 1.50). The number of early meningitis cases reported during October-December was associated with epidemic HC-weeks in the same HC catchment area during January May of the following year (OR for each additional early case = 1.14; 95% CI: 1.06, 1.21). CONCLUSIONS: Spatial variations of atmospheric dust load do not seem to be a factor in the occurrence of localized meningitis epidemics, and the factor triggering them remains to be identified. The pathophysiological mechanism linking early cases to localized epidemics is not understood, but their occurrence and number of early cases could be an indicator for epidemic risk.