TY - JOUR
T1 - Geotemporal analysis of Neisseria meningitidis clones in the United States
T2 - 2000-2005
AU - Wiringa, Ann E.
AU - Shutt, Kathleen A.
AU - Marsh, Jane W.
AU - Cohn, Amanda C.
AU - Messonnier, Nancy E.
AU - Zansky, Shelley M.
AU - Petit, Susan
AU - Farley, Monica M.
AU - Gershman, Ken
AU - Lynfield, Ruth
AU - Reingold, Arthur
AU - Schaffner, William
AU - Thompson, Jamie
AU - Brown, Shawn T.
AU - Lee, Bruce Y.
AU - Harrison, Lee H.
N1 - Funding Information:
This study was funded in part by the Centers for Disease Control and Prevention. Dr. Harrison has received research support and lecture fees from Sanofi Pasteur; lecture fees from Novartis Vaccines; and has served as a consultant to GlaxoSmithKline, Merck, Novartis Vaccines, Sanofi Pasteur, and Pfizer. Dr. Harrison’s financial ties with industry were terminated before he became a voting member of the Advisory Committee on Immunization Practices in July 2012. Dr. Schaffner is a member of data safety monitoring boards for Merck and has served as a consultant to Dynavax, Pfizer, GSK and Sanofi Pasteur. Dr. Marsh has received research support from Sanofi Pasteur, Merck and ViroPharma Inc. Martin Kulldorff provided technical assistance with the SaTScan software. There are no patents, products in development or marketed products to declare. This does not alter our adherence to all the PLOS ONE policies on sharing data and materials.
Funding Information:
This publication made use of the Neisseria Multi Locus Sequence Typing website ( http://pubmlst.org/neisseria/ ) developed by Keith Jolley and Man-Suen Chan and located at the University of Oxford. The development of this site has been funded by the Wellcome Trust and European Union. We thank Martin Kulldorff for his methodological insight and technical assistance with the SaTScan software. SaTScan™ is a trademark of Martin Kulldorff. The SaTScan™ software was developed under the joint auspices of (i) Martin Kulldorff, (ii) the National Cancer Institute, and (iii) Farzad Mostashari of the New York City Department of Health and Mental Hygiene.
PY - 2013/12/12
Y1 - 2013/12/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84892587475&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84892587475&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0082048
DO - 10.1371/journal.pone.0082048
M3 - Article
C2 - 24349182
AN - SCOPUS:84892587475
VL - 8
JO - PLoS One
JF - PLoS One
SN - 1932-6203
IS - 12
M1 - e82048
ER -