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BackgroundThe detection of meningococcal outbreaks relies on serogrouping and epidemiologic definitions. Advances in molecular epidemiology have improved the ability to distinguish unique Neisseria meningitidis strains, enabling the classification of isolates into clones. Around 98% of meningococcal cases in the United States are believed to be sporadic.MethodsMeningococcal isolates from 9 Active Bacterial Core surveillance sites throughout the United States from 2000 through 2005 were classified according to serogroup, multilocus sequence typing, and outer membrane protein (porA, porB, and fetA) genotyping. Clones were defined as isolates that were indistinguishable according to this characterization. Case data were aggregated to the census tract level and all non-singleton clones were assessed for non-random spatial and temporal clustering using retrospective space-time analyses with a discrete Poisson probability model.ResultsAmong 1,062 geocoded cases with available isolates, 438 unique clones were identified, 78 of which had ≥2 isolates. 702 cases were attributable to non-singleton clones, accounting for 66.0% of all geocoded cases. 32 statistically significant clusters comprised of 107 cases (10.1% of all geocoded cases) were identified. Clusters had the following attributes: included 2 to 11 cases; 1 day to 33 months duration; radius of 0 to 61.7 km; and attack rate of 0.7 to 57.8 cases per 100,000 population. Serogroups represented among the clusters were: B (n = 12 clusters, 45 cases), C (n = 11 clusters, 27 cases), and Y (n = 9 clusters, 35 cases); 20 clusters (62.5%) were caused by serogroups represented in meningococcal vaccines that are commercially available in the United States.ConclusionsAround 10% of meningococcal disease cases in the U.S. could be assigned to a geotemporal cluster. Molecular characterization of isolates, combined with geotemporal analysis, is a useful tool for understanding the spread of virulent meningococcal clones and patterns of transmission in populations.

BackgroundThe detection of meningococcal outbreaks relies on serogrouping and epidemiologic definitions. Advances in molecular epidemiology have improved the ability to distinguish unique Neisseria meningitidis strains, enabling the classification of isolates into clones. Around 98% of meningococcal cases in the United States are believed to be sporadic.MethodsMeningococcal isolates from 9 Active Bacterial Core surveillance sites throughout the United States from 2000 through 2005 were classified according to serogroup, multilocus sequence typing, and outer membrane protein (porA, porB, and fetA) genotyping. Clones were defined as isolates that were indistinguishable according to this characterization. Case data were aggregated to the census tract level and all non-singleton clones were assessed for non-random spatial and temporal clustering using retrospective space-time analyses with a discrete Poisson probability model.ResultsAmong 1,062 geocoded cases with available isolates, 438 unique clones were identified, 78 of which had ≥2 isolates. 702 cases were attributable to non-singleton clones, accounting for 66.0% of all geocoded cases. 32 statistically significant clusters comprised of 107 cases (10.1% of all geocoded cases) were identified. Clusters had the following attributes: included 2 to 11 cases; 1 day to 33 months duration; radius of 0 to 61.7 km; and attack rate of 0.7 to 57.8 cases per 100,000 population. Serogroups represented among the clusters were: B (n = 12 clusters, 45 cases), C (n = 11 clusters, 27 cases), and Y (n = 9 clusters, 35 cases); 20 clusters (62.5%) were caused by serogroups represented in meningococcal vaccines that are commercially available in the United States.ConclusionsAround 10% of meningococcal disease cases in the U.S. could be assigned to a geotemporal cluster. Molecular characterization of isolates, combined with geotemporal analysis, is a useful tool for understanding the spread of virulent meningococcal clones and patterns of transmission in populations.

The screening method, which employs readily available data, is an inexpensive and quick means of estimating vaccine effectiveness (VE). We compared estimates of effectiveness of heptavalent pneumococcal conjugate vaccine (PCV7) against invasive pneumococcal disease (IPD) using the screening and case-control methods. Cases were children aged 19-35 months with pneumococcus isolated from normally sterile sites residing in Active Bacterial Core surveillance areas in the United States. Case-control VE was estimated for 2001-2004 by comparing the odds of vaccination among cases and community controls. Screening-method VE for 2001-2009 was estimated by comparing the proportion of cases vaccinated to National Immunization Survey-derived coverage among the general population. To evaluate the plausibility of screening-method VE findings, we estimated attack rates among vaccinated and unvaccinated persons. We identified 1,154 children with IPD. Annual population PCV7 coverage with ≥1 dose increased from 38% to 97%. Case-control VE for ≥1 dose was estimated as 75% against all-serotype IPD (annual range: 35-83%) and 91% for PCV7-type IPD (annual range: 65-100%). By the screening method, the overall VE was 86% for ≥1 dose (annual range: -240-70%) against all-serotype IPD and 94% (annual range: 62-97%) against PCV7-type IPD. As cases of PCV7-type IPD declined during 2001-2005, estimated attack rates for all-serotype IPD among vaccinated and unvaccinated individuals became less consistent than what would be expected with the estimated effectiveness of PCV7. The screening method yields estimates of VE that are highly dependent on the time period during which it is used and the choice of outcome. The method should be used cautiously to evaluate VE of PCVs.

Background: The detection of meningococcal outbreaks relies on serogrouping and epidemiologic definitions. Advances in molecular epidemiology have improved the ability to distinguish unique Neisseria meningitidis strains, enabling the classification of isolates into clones. Around 98% of meningococcal cases in the United States are believed to be sporadic. Methods: Meningococcal isolates from 9 Active Bacterial Core surveillance sites throughout the United States from 2000 through 2005 were classified according to serogroup, multilocus sequence typing, and outer membrane protein (porA, porB, and fetA) genotyping. Clones were defined as isolates that were indistinguishable according to this characterization. Case data were aggregated to the census tract level and all non-singleton clones were assessed for non-random spatial and temporal clustering using retrospective space-time analyses with a discrete Poisson probability model. Results: Among 1,062 geocoded cases with available isolates, 438 unique clones were identified, 78 of which had ≥2 isolates. 702 cases were attributable to non-singleton clones, accounting for 66.0% of all geocoded cases. 32 statistically significant clusters comprised of 107 cases (10.1% of all geocoded cases) were identified. Clusters had the following attributes: included 2 to 11 cases; 1 day to 33 months duration; radius of 0 to 61.7 km; and attack rate of 0.7 to 57.8 cases per 100,000 population. Serogroups represented among the clusters were: B (n = 12 clusters, 45 cases), C (n = 11 clusters, 27 cases), and Y (n = 9 clusters, 35 cases); 20 clusters (62.5%) were caused by serogroups represented in meningococcal vaccines that are commercially available in the United States. Conclusions: Around 10% of meningococcal disease cases in the U.S. could be assigned to a geotemporal cluster. Molecular characterization of isolates, combined with geotemporal analysis, is a useful tool for understanding the spread of virulent meningococcal clones and patterns of transmission in populations. [ABSTRACT FROM AUTHOR]

Background: Neisseria meningitidis serogroup B has been predominant in Brazil, but no broadly effective vaccine is available to prevent endemic meningococcal disease. To understand genetic diversity among serogroup B strains in Brazil, we selected a nationally representative sample of clinical disease isolates from 2004, and a temporally representative sample for the state of São Paulo (1988-2006) for study (n = 372). Methods: We performed multi-locus sequence typing (MLST) and sequence analysis of five outer membrane protein (OMP) genes, including novel vaccine targets fHbp and nadA. Results: In 2004, strain B:4:P1.15,19 clonal complex ST-32/ET-5 (cc32) predominated throughout Brazil; regional variation in MLST sequence type (ST), fetA, and porB was significant but diversity was limited for nadA and fHbp. Between 1988 and 1996, the São Paulo isolates shifted from clonal complex ST-41/44/Lineage 3 (cc41/44) to cc32. OMP variation was associated with but not predicted by cc or ST. Overall, fHbp variant 1/subfamily B was present in 80% of isolates and showed little diversity. The majority of nadA were similar to reference allele 1. Conclusions: A predominant serogroup B lineage has circulated in Brazil for over a decade with significant regional and temporal diversity in ST, fetA, and porB, but not in nadA and fHbp. [ABSTRACT FROM AUTHOR]

Real-time (RT)-PCR increases diagnostic yield for bacterial meningitis and is ideal for incorporation into routine surveillance in a developing country. We validated a multiplex RT-PCR assay for Streptococcus pneumoniae, Neisseria meningitidis, and Haemophilus influenzae in Brazil. Risk factors for being culture-negative, RT-PCR positive were determined. The sensitivity of RT-PCR in cerebrospinal fluid (CSF) was 100% (95% confidence limits, 96.0%-100%) for N. meningitidis, 97.8% (85.5%-99.9%) for S. pneumoniae, and 66.7% (9.4%-99.2%) for H. influenzae. Specificity ranged from 98.9% to 100%. Addition of RT-PCR to routine microbiologic methods increased the yield for detection of S. pneumoniae, N. meningitidis, and H. influenzae cases by 52%, 85%, and 20%, respectively. The main risk factor for being culture negative and RT-PCR positive was presence of antibiotic in CSF (odds ratio 12.2, 95% CI 5.9-25.0). RT-PCR using CSF was highly sensitive and specific and substantially added to measures of meningitis disease burden when incorporated into routine public health surveillance in Brazil. [ABSTRACT FROM AUTHOR]

Real-time PCR (rt-PCR) is a widely used molecular method for detection of Neisseria meningitidis (Nm). Several rt-PCR assays for Nm target the capsule transport gene, ctrA. However, over 16% of meningococcal carriage isolates lack ctrA, rendering this target gene ineffective at identification of this sub-population of meningococcal isolates. The Cu-Zn superoxide dismutase gene, sodC, is found in Nm but not in other Neisseria species. To better identify Nm, regardless of capsule genotype or expression status, a sodC-based TaqMan rt-PCR assay was developed and validated. Standard curves revealed an average lower limit of detection of 73 genomes per reaction at cycle threshold (Ct) value of 35, with 100% average reaction efficiency and an average R² of 0.9925. 99.7% (624/626) of Nm isolates tested were sodC-positive, with a range of average Ct values from 13.0 to 29.5. The mean sodC Ct value of these Nm isolates was 17.6±2.2 (±SD). Of the 626 Nm tested, 178 were nongroupable (NG) ctrA-negative Nm isolates, and 98.9% (176/178) of these were detected by sodC rt-PCR. The assay was 100% specific, with all 244 non-Nm isolates testing negative. Of 157 clinical specimens tested, sodC detected 25/157 Nm or 4 additional specimens compared to ctrA and 24 more than culture. Among 582 carriage specimens, sodC detected Nm in 1 more than ctrA and in 4 more than culture. This sodC rt-PCR assay is a highly sensitive and specific method for detection of Nm, especially in carriage studies where many meningococcal isolates lack capsule genes. [ABSTRACT FROM AUTHOR]