Spatio-Temporal Factors Associated with Meningococcal Meningitis Annual Incidence at the Health Centre Level in Niger, 2004–2010

International audienceBackgroundEpidemics of meningococcal meningitis (MM) recurrently strike the African Meningitis Belt. This study aimed at investigating factors, still poorly understood, that influence annual incidence of MM serogroup A, the main etiologic agent over 2004–2010, at a fine spatial scale in Niger.Methodology/Principal FindingsTo take into account data dependencies over space and time and control for unobserved confounding factors, we developed an explanatory Bayesian hierarchical model over 2004–2010 at the health centre catchment area (HCCA) level. The multivariate model revealed that both climatic and non-climatic factors were important for explaining spatio-temporal variations in incidence: mean relative humidity during November–June over the study region (posterior mean Incidence Rate Ratio (IRR) = 0.656, 95% Credible Interval (CI) 0.405–0.949) and occurrence of early rains in March in a HCCA (IRR = 0.353, 95% CI 0.239–0.502) were protective factors; a higher risk was associated with the percentage of neighbouring HCCAs having at least one MM A case during the same year (IRR = 2.365, 95% CI 2.078–2.695), the presence of a road crossing the HCCA (IRR = 1.743, 95% CI 1.173–2.474) and the occurrence of cases before 31 December in a HCCA (IRR = 6.801, 95% CI 4.004–10.910). At the study region level, higher annual incidence correlated with greater geographic spread and, to a lesser extent, with higher intensity of localized outbreaks.ConclusionsBased on these findings, we hypothesize that spatio-temporal variability of MM A incidence between years and HCCAs result from variations in the intensity or duration of the dry season climatic effects on disease risk, and is further impacted by factors of spatial contacts, representing facilitated pathogen transmission. Additional unexplained factors may contribute to the observed incidence patterns and should be further investigated

Evaluation of response strategies against epidemics due to Neisseria meningitidis C in Niger

International audienceOBJECTIVE: To inform public health recommendations, we evaluated the effectiveness and efficiency of current and hypothetical surveillance and vaccine response strategies against Neisseria meningitidis C meningitis epidemics in 2015 in Niger.METHODS : We analysed reports of suspected and confirmed cases of meningitis from the region of Dosso during 2014 and 2015. Based on a definition of epidemic signals, the effectiveness and efficiency of surveillance and vaccine response strategies were evaluated by calculating the number of potentially vaccine-preventable cases and number of vaccine doses needed per epidemic signal.RESULTS : A total of 4763 weekly health area reports, collected in 90 health areas with 1282 suspected meningitis cases, were included. At a threshold of 10 per 100 000, the total number of estimated vaccine-preventable cases was 29 with district-level surveillance and vaccine response, 141 with health area-level surveillance and vaccination and 339 with health area-level surveillance and district-level vaccination. While being most effective, the latter strategy required the largest number of vaccine doses (1.8 million), similar to the strategy of surveillance and vaccination at district level (1.3 million), whereas the strategy of surveillance and vaccination at health area level would have required only 0.8 million doses. Thus, efficiency was lowest for district-level surveillance and highest for health area-level surveillance with district-level vaccination.CONCLUSION : In this analysis, we found that effectiveness and efficiency were higher at health area-level surveillance and district-level vaccination than for other strategies. Use of N. meningitidis C vaccines in a preventive strategy thus should be considered, in particular as most reactive vaccine response strategies in our analysis had little impact on disease burden

Response Strategies against Meningitis Epidemics after Elimination of Serogroup A Meningococci, Niger

To inform epidemic response strategies for the African meningitis belt after a meningococcal serogroup A conjugate vaccine was introduced in 2010, we compared the effectiveness and efficiency of meningitis surveillance and vaccine response strategies at district and health area levels using various thresholds of weekly incidence rates. We analyzed reports of suspected cases from 3 regions in Niger during 2002–2012 (154,392 health area weeks), simulating elimination of serogroup A meningitis by excluding health area years with identification of such cases. Effectiveness was highest for health area surveillance and district vaccination (58–366 cases; thresholds 7–20 cases/100,000 doses), whereas efficiency was optimized with health area vaccination (5.6–7.7 cases/100,000 doses). District-level intervention prevented <6 cases (0.2 cases/100,000 doses). Reducing the delay between epidemic signal and vaccine protection by 2 weeks doubled efficiency. Subdistrict surveillance and response might be most appropriate for meningitis epidemic response after elimination of serogroup A meningitis

Serogroup-Specific Characteristics of Localized Meningococcal Meningitis Epidemics in Niger 2002–2012 and 2015: Analysis of Health Center Level Surveillance Data

International audienceTo compare dynamics of localized meningitis epidemics (LE) by meningococcal (Nm) ser-ogroup, we analyzed a surveillance database of suspected and laboratory-confirmed Nm cases from 373 health areas (HA) of three regions in Niger during 2002–2012 and one region concerned by NmC epidemics during 2015. We defined LE as HA weekly incidence rates of !20 suspected cases per 100,000 during !2 weeks and assigned the predominant serogroup based on polymerase chain reaction testing of cerebrospinal fluid. Among the 175 LE, median peak weekly incidence rate in LE due to NmA, W, X and C were 54, 39, 109 and 46 per 100,000, respectively. These differences impacted ability of the epidemic to be detected at the district level. While this analysis is limited by the small number of LE due to NmX (N = 4) and NmW (N = 5), further research should explore whether strategies for prevention and response to meningitis epidemics need to be adapted according to predominant meningococcal serogroups

Results from the Bayesian hierarchical model of meningococcal meningitis (MM) A annual incidence at the health centre catchment area (HCCA) level over the study region, Niger 2004–2010.

<p>Posterior mean parameter estimates and their 95% credible intervals (CIs) for the “null” model (no covariates included) and the multivariate model.</p><p>* CI: Bayesian credible interval.</p>†<p>IRR: Incidence rate ratio.</p>‡<p>Standardized variables.</p

Multivariate model goodness of fit.

<p>(A) Scatter plot of the fitted posterior mean numbers of meningococcal meningitis A cases per year and health centre catchment area and their 95% credible intervals (CIs) (light-blue shaded region) versus the observed numbers. (B) Observed incidence rates (horizontal blue lines) per year over the study region and their corresponding fitted posterior mean annual incidence rates (filled dark-blue circles) and their 95%CIs (vertical dark-blue lines).</p

Spatial distribution of meningococcal meningitis A in Niger from July 2003 to June 2010.

<p>Cumulative incidence rates in each health centre catchment area (cases per 100000 inhabitants).</p

Annual meningitis incidences at health area level in three selected districts, Niger, 2002–2012.

<p>One district was selected for illustration in each of the three regions: A) Konni district in Tahoua region, B) Say district in Tillabery region, and C) Boboye district in Dosso region. Boxplots show median, 25^th and 75^th percentile and range of annual incidences in the health areas of the district. Dotted lines indicate annual incidence of 100 per 100,000, a threshold previously used as a retrospective definition of epidemics at the district level.¹³ The epidemiological year <i>n</i>, from 1^st July of calendar year <i>n-1</i> to 30^th June of calendar year <i>n</i>, is used here.</p