title: Analysing spatio-temporal clustering of meningococcal meningitis outbreaks in Niger reveals opportunities for improved disease control.
abstract: BACKGROUND
  Meningococcal meningitis is a major health problem in the "African Meningitis Belt" where recurrent epidemics occur during the hot, dry season. In Niger, a central country belonging to the Meningitis Belt, reported meningitis cases varied between 1,000 and 13,000 from 2003 to 2009, with a case-fatality rate of 5-15%.
  
  
  RESULTS
  In order to gain insight in the epidemiology of meningococcal meningitis in Niger and to improve control strategies, the emergence of the epidemics and their diffusion patterns at a fine spatial scale have been investigated. A statistical analysis of the spatio-temporal distribution of confirmed meningococcal meningitis cases was performed between 2002 and 2009, based on health centre catchment areas (HCCAs) as spatial units. Anselin's local Moran's I test for spatial autocorrelation and Kulldorff's spatial scan statistic were used to identify spatial and spatio-temporal clusters of cases. Spatial clusters were detected every year and most frequently occurred within nine southern districts. Clusters most often encompassed few HCCAs within a district, without expanding to the entire district. Besides, strong intra-district heterogeneity and inter-annual variability in the spatio-temporal epidemic patterns were observed. To further investigate the benefit of using a finer spatial scale for surveillance and disease control, we compared timeliness of epidemic detection at the HCCA level versus district level and showed that a decision based on threshold estimated at the HCCA level may lead to earlier detection of outbreaks.
  
  
  CONCLUSIONS
  Our findings provide an evidence-based approach to improve control of meningitis in sub-Saharan Africa. First, they can assist public health authorities in Niger to better adjust allocation of resources (antibiotics, rapid diagnostic tests and medical staff). Then, this spatio-temporal analysis showed that surveillance at a finer spatial scale (HCCA) would be more efficient for public health response: outbreaks would be detected earlier and reactive vaccination would be better targeted.
authors.affiliation: Unité d'Epidémiologie des Maladies Emergentes, Institut Pasteur, Paris, France. juliette.paireau@gmail.com
authors.forename: Juliette
authors.initials: J
authors.lastname: Paireau
authors.forename: Florian
authors.initials: F
authors.lastname: Girond
authors.forename: Jean-Marc
authors.initials: JM
authors.lastname: Collard
authors.forename: Halima B
authors.initials: HB
authors.lastname: Maïnassara
authors.forename: Jean-François
authors.initials: JF
authors.lastname: Jusot
mesh_terms: D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D003140:Communicable Disease Control / Q000379:methods*; D004196:Disease Outbreaks; D005260:Female; D005843:Geography; D006801:Humans; D008297:Male; D008585:Meningitis, Meningococcal / Q000453:epidemiology*; D009548:Niger / Q000453:epidemiology; D012189:Retrospective Studies; D013997:Time Factors