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. Published by Oxford University Press for the Infectious Diseases Society of America 2019. This work is written by (a) US Government employee(s) and is in the public domain in the US.
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. Published by Oxford University Press for the Infectious Diseases Society of America 2019. This work is written by (a) US Government employee(s) and is in the public domain in the US.
Entities:
Keywords:
Africa; bacterial; meningitis; public health surveillance
Authors: Brenda Anna Kwambana-Adams; Adam L Cohen; Lee Hampton; Aquino Albino Nhantumbo; Robert S Heyderman; Martin Antonio; Andre Bita; Jason Mathiu Mwenda Journal: J Infect Dis Date: 2021-09-01 Impact factor: 5.226
Authors: Jaymin C Patel; Heidi M Soeters; Alpha Oumar Diallo; Brice W Bicaba; Goumbi Kadadé; Assétou Y Dembélé; Mahamat A Acyl; Christelle Nikiema; Clement Lingani; Cynthia Hatcher; Anna M Acosta; Jennifer D Thomas; Fabien Diomande; Stacey Martin; Thomas A Clark; Richard Mihigo; Rana A Hajjeh; Catherine H Zilber; Flavien Aké; Sarah A Mbaeyi; Xin Wang; Jennifer C Moisi; Olivier Ronveaux; Jason M Mwenda; Ryan T Novak Journal: J Infect Dis Date: 2019-10-31 Impact factor: 5.226