Modeling Optimal Laboratory Testing Strategies for Bacterial Meningitis Surveillance in Africa.

Since 2010, the introduction of an effective serogroup A meningococcal conjugate vaccine has led to the near-elimination of invasive Neisseria meningitidis serogroup A disease in Africa's meningitis belt. However, a significant burden of disease and epidemics due to other bacterial meningitis pathogens remain in the region. High-quality surveillance data with laboratory confirmation is important to monitor circulating bacterial meningitis pathogens and design appropriate interventions, but complete testing of all reported cases is often infeasible. Here, we use case-based surveillance data from 5 countries in the meningitis belt to determine how accurately estimates of the distribution of causative pathogens would represent the true distribution under different laboratory testing strategies. Detailed case-based surveillance data was collected by the MenAfriNet surveillance consortium in up to 3 seasons from participating districts in 5 countries. For each unique country-season pair, we simulated the accuracy of laboratory surveillance by repeatedly drawing subsets of tested cases and calculating the margin of error of the estimated proportion of cases caused by each pathogen (the greatest pathogen-specific absolute error in proportions between the subset and the full set of cases). Across the 12 country-season pairs analyzed, the 95% credible intervals around estimates of the proportion of cases caused by each pathogen had median widths of ±0.13, ±0.07, and ±0.05, respectively, when random samples of 25%, 50%, and 75% of cases were selected for testing. The level of geographic stratification in the sampling process did not meaningfully affect accuracy estimates. These findings can inform testing thresholds for laboratory surveillance programs in the meningitis belt.

Implementation of Case-Based Surveillance and Real-time Polymerase Chain Reaction to Monitor Bacterial Meningitis Pathogens in Chad.

BACKGROUND: Meningococcal serogroup A conjugate vaccine (MACV) was introduced in Chad during 2011-2012. Meningitis surveillance has been conducted nationwide since 2003, with case-based surveillance (CBS) in select districts from 2012. In 2016, the MenAfriNet consortium supported Chad to implement CBS in 4 additional districts and real-time polymerase chain reaction (rt-PCR) at the national reference laboratory (NRL) to improve pathogen detection. We describe analysis of bacterial meningitis cases during 3 periods: pre-MACV (2010-2012), pre-MenAfriNet (2013-2015), and post-MenAfriNet (2016-2018). METHODS: National surveillance targeted meningitis cases caused by Neisseria meningitidis, Haemophilus influenzae, and Streptococcus pneumoniae. Cerebrospinal fluid specimens, inoculated trans-isolate media, and/or isolates from suspected meningitis cases were tested via culture, latex, and/or rt-PCR; confirmed bacterial meningitis was defined by a positive result on any test. We calculated proportion of suspected cases with a specimen received by period, and proportion of specimens with a bacterial meningitis pathogen identified, by period, pathogen, and test. RESULTS: The NRL received specimens for 6.8% (876/12813), 46.4% (316/681), and 79.1% (787/995) of suspected meningitis cases in 2010-2012, 2013-2015, and 2016-2018, respectively, with a bacterial meningitis pathogen detected in 33.6% (294/876), 27.8% (88/316), and 33.2% (261/787) of tested specimens. The number of N. meningitidis serogroup A (NmA) among confirmed bacterial meningitis cases decreased from 254 (86.4%) during 2010-2012 to 2 (2.3%) during 2013-2015, with zero NmA cases detected after 2014. In contrast, proportional and absolute increases were seen between 2010-2012, 2013-2015, and 2016-2018 in cases caused by S. pneumoniae (5.1% [15/294], 65.9% [58/88], and 52.1% [136/261]), NmX (0.7% [2/294], 1.1% [1/88], and 22.2% [58/261]), and Hib (0.3% [1/294], 11.4% [10/88], and 14.9% [39/261]). Of specimens received at the NRL, proportions tested during the 3 periods were 47.7% (418), 53.2% (168), and 9.0% (71) by latex; 81.4% (713), 98.4% (311), and 93.9% (739) by culture; and 0.0% (0), 0.0% (0), and 90.5% (712) by rt-PCR, respectively. During the post-MenAfriNet period (2016-2018), 86.1% (678) of confirmed cases were tested by both culture and rt-PCR, with 12.5% (85) and 32.4% (220) positive by culture and rt-PCR, respectively. CONCLUSIONS: CBS implementation was associated with increased specimen referral. Increased detection of non-NmA cases could reflect changes in incidence or increased sensitivity of case detection with rt-PCR. Continued surveillance with the use of rt-PCR to monitor changing epidemiology could inform the development of effective vaccination strategies.

Improving Case-Based Meningitis Surveillance in 5 Countries in the Meningitis Belt of Sub-Saharan Africa, 2015-2017.

BACKGROUND: The MenAfriNet consortium was established in 2014 to support implementation of case-based meningitis surveillance in 5 countries in the meningitis belt of sub-Saharan Africa: Burkina Faso, Chad, Mali, Niger, and Togo. Assessing surveillance performance is critical for interpretation of the collected data and implementation of future surveillance-strengthening initiatives. METHODS: Detailed epidemiologic and laboratory data were collected on suspected meningitis cases through case-based meningitis surveillance in participating districts in 5 countries. Performance of case-based surveillance was evaluated through sensitivity of case ascertainment in case-based versus aggregate meningitis surveillance and an analysis of surveillance indicators. RESULTS: From 2015 to 2017, 18 262 suspected meningitis cases were identified through case-based surveillance and 16 262 were identified through aggregate surveillance, for a case ascertainment sensitivity of 112.3%. Among suspected cases, 16 885 (92.5%) had a cerebrospinal fluid (CSF) specimen collected, 13 625 (80.7%) of which were received at a national reference laboratory. Among these, 13 439 (98.6%) underwent confirmatory testing, and, of those tested, 4371 (32.5%) were confirmed for a bacterial pathogen. CONCLUSIONS: Overall strong performance for case ascertainment, CSF collection, and laboratory confirmation provide evidence for the quality of MenAfriNet case-based surveillance in evaluating epidemiologic trends and informing future vaccination strategies.

Phylogenetic relationships and regional spread of meningococcal strains in the meningitis belt, 2011-2016.

BACKGROUND: Historically, the major cause of meningococcal epidemics in the meningitis belt of sub-Saharan Africa has been Neisseria meningitidis serogroup A (NmA), but the incidence has been substantially reduced since the introduction of a serogroup A conjugate vaccine starting in 2010. We performed whole-genome sequencing on isolates collected post-2010 to assess their phylogenetic relationships and inter-country transmission. METHODS: A total of 716 invasive meningococcal isolates collected between 2011 and 2016 from 11 meningitis belt countries were whole-genome sequenced for molecular characterization by the three WHO Collaborating Centers for Meningitis. FINDINGS: We identified three previously-reported clonal complexes (CC): CC11 (n = 434), CC181 (n = 62) and CC5 (n = 90) primarily associated with NmW, NmX, and NmA, respectively, and an emerging CC10217 (n = 126) associated with NmC. CC11 expanded throughout the meningitis belt independent of the 2000 Hajj outbreak strain, with isolates from Central African countries forming a distinct sub-lineage within this expansion. Two major sub-lineages were identified for CC181 isolates, one mainly expanding in West African countries and the other found in Chad. CC10217 isolates from the large outbreaks in Nigeria and Niger were more closely related than those from the few cases in Mali and Burkina Faso. INTERPRETATIONS: Whole-genome based phylogenies revealed geographically distinct strain circulation as well as inter-country transmission events. Our results stress the importance of continued meningococcal molecular surveillance in the region, as well as the development of an affordable vaccine targeting these strains. FUND: Meningitis Research Foundation; CDC's Office of Advanced Molecular Detection; GAVI, the Vaccine Alliance.