12 research outputs found
Evaluation du système de surveillance épidémiologique de la méningite bactérienne dans la région des Savanes au Togo, 2016 – 2019: Evaluation of the epidemiological surveillance system for bacterial meningitis in the Savanes region of Togo, 2016 – 2019
Introduction: La surveillance cas par cas de la Méningite Bactérienne Aiguë (MBA) a démarré depuis 2014 dans la ré-gion des Savanes mais le niveau de sa performance est méconnu. L’objectif de cette étude était d’évaluer ce système de surveillance de 2016 à 2019. Méthodes: Il s’est agi d’une étude transversale qui a inclus tous les cas de MBA notifiés dans la région des Savanes entre la semaine 1 (S1) 2016 et S19 2019, 34 Formations Sanitaires (FS) périphériques, sept hôpitaux de districts (HD) et l’hôpital régional (CHR). Les données ont été collectées par interview, observation et examen de registres. Les directives éditées dans le guide « CDC-Atlanta 2001 », ont été utilisées pour dé-crire l’organisation, le fonctionnement et les attributs : utilité, simplicité, acceptabilité, flexibilité, représen-tativité, réactivité, qualité des données et Valeur Prédictive Positive (VPP). Résultats: Le système opérait avec trois mécanismes de transmission des données suivant le circuit : FS-Direction préfectorale-Direction régionale-Niveau central. Trois épidémies causées par Nm W en 2016 et 2017 et Nm C en 2019 ont été détectées. Le délai moyen de vaccination réactive était de cinq semaines. La promp-titude des rapports hebdomadaires, initialement à 100%, a régressé à moins de 60% après introduction de « Argus » et « District Health Information System, deuxième version (DHIS-2) ». Les prestataires avaient prélevé le LCR et rempli la fiche d’investigation dans 92,2% (141/153), IC 95% (86,7% - 95,9%) des cas. Dans la base de données, respectivement 24,6% (252/1024), IC 95% (22,2% - 27,3%) et 20,7% (212/1024), IC 95% (18,3% - 23,3%] des données manquaient pour les variables « Résultat final » et « Classification finale ». Les cas provenaient de tous les districts et représentaient toutes les tranches d’âge. La Valeur Pré-dictive Positive globale a varié de 42,1% (122/290), IC 95% (36,3% - 48,0%) en 2016 à 64,0% (48/75), IC 95% (52,1% - 74,8%) en 2019. Conclusion: Le système de surveillance de la MBA dans la région des Savanes était utile, acceptable et représentatif malgré certaines données manquantes. Il était complexe, non flexible et peu prompt pour la riposte vacci-nale. Il faudrait un mécanisme unique de transmission des données, pouvoir confirmer les cas dans les HD et auditer les données.
Introduction: Case-by-case surveillance of Acute Bacterial Meningitis (ABM) started since 2014 in the Savannah region but the level of its performance is unknown. The objective of this study was to evaluate this surveillance system from 2016 to 2019. Methods: This was a cross-sectional study that included all cases of (ABM) notified in the Savanes region between week 1 (W1) 2016 and week19 2019, 34 peri-urban Health Formations (SFs), seven district hospitals (DHs) and the regional hospital (RHC). Data were collected by interview, observation and review of records. The guidelines published in the CDC-Atlanta 2001 guide were used to describe the organisation, functioning and attributes: utility, simplicity, acceptability, flexibility, representativeness, responsiveness, data quality and Positive Predictive Value (PPV). Results: The system operated with three data transmission mechanisms following the circuit: FS-Prefectural Directorate-Regional Directorate-Central level. Three epidemics caused by Nm W in 2016 and 2017 and Nm C in 2019 were detected. The average time for reactive vaccination was five weeks. The promptness of weekly reporting, initially 100%, decreased to less than 60% after the introduction of Argus and District Health Information System, version 2 (DHIS-2). Providers had collected CSF and completed the investigation form in 92.2% (141/153), 95% CI (86.7% - 95.9%) of cases. In the database, 24.6% (252/1024), 95% CI (22.2% - 27.3%) and 20.7% (212/1024), 95% CI (18.3% - 23.3%) of the data were missing for the variables "Final outcome" and "Final classification" respectively. The cases came from all districts and represented all age groups. The overall Positive Predictive Value ranged from 42.1% (122/290), 95% CI (36.3% - 48.0%) in 2016 to 64.0% (48/75), 95% CI (52.1% - 74.8%) in 2019. Conclusion: The surveillance system for MVA in the Savanes region was useful, acceptable and representative despite some missing data. It was complex, inflexible and not very prompt for the vaccine response. A single data transmission mechanism is needed, as well as the ability to confirm cases in HDs and audit data
Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage
Antimicrobial resistance (AMR) is a serious threat to global public health, but obtaining representative data on AMR for healthy human populations is difficult. Here, we use meta-genomic analysis of untreated sewage to characterize the bacterial resistome from 79 sites in 60 countries. We find systematic differences in abundance and diversity of AMR genes between Europe/North-America/Oceania and Africa/Asia/South-America. Antimicrobial use data and bacterial taxonomy only explains a minor part of the AMR variation that we observe. We find no evidence for cross-selection between antimicrobial classes, or for effect of air travel between sites. However, AMR gene abundance strongly correlates with socio-economic, health and environmental factors, which we use to predict AMR gene abundances in all countries in the world. Our findings suggest that global AMR gene diversity and abundance vary by region, and that improving sanitation and health could potentially limit the global burden of AMR. We propose metagenomic analysis of sewage as an ethically acceptable and economically feasible approach for continuous global surveillance and prediction of AMR.Peer reviewe
Setting a baseline for global urban virome surveillance in sewage
The rapid development of megacities, and their growing connectedness across the world is becoming a distinct driver for emerging disease outbreaks. Early detection of unusual disease emergence and spread should therefore include such cities as part of risk-based surveillance. A catch-all metagenomic sequencing approach of urban sewage could potentially provide an unbiased insight into the dynamics of viral pathogens circulating in a community irrespective of access to care, a potential which already has been proven for the surveillance of poliovirus. Here, we present a detailed characterization of sewage viromes from a snapshot of 81 high density urban areas across the globe, including in-depth assessment of potential biases, as a proof of concept for catch-all viral pathogen surveillance. We show the ability to detect a wide range of viruses and geographical and seasonal differences for specific viral groups. Our findings offer a cross-sectional baseline for further research in viral surveillance from urban sewage samples and place previous studies in a global perspective
MenAfriNet: A Network Supporting Case-Based Meningitis Surveillance and Vaccine Evaluation in the Meningitis Belt of Africa
Bacterial Meningitis Epidemiology in Five Countries in the Meningitis Belt of Sub-Saharan Africa, 2015–2017
Setting a baseline for global urban virome surveillance in sewage
The rapid development of megacities, and their growing connectedness across the world is becoming a distinct driver for emerging disease outbreaks. Early detection of unusual disease emergence and spread should therefore include such cities as part of risk-based surveillance. A catch-all metagenomic sequencing approach of urban sewage could potentially provide an unbiased insight into the dynamics of viral pathogens circulating in a community irrespective of access to care, a potential which already has been proven for the surveillance of poliovirus. Here, we present a detailed characterization of sewage viromes from a snapshot of 81 high density urban areas across the globe, including in-depth assessment of potential biases, as a proof of concept for catch-all viral pathogen surveillance. We show the ability to detect a wide range of viruses and geographical and seasonal differences for specific viral groups. Our findings offer a cross-sectional baseline for further research in viral surveillance from urban sewage samples and place previous studies in a global perspective
Setting a baseline for global urban virome surveillance in sewage
The rapid development of megacities, and their growing connectedness across the world is becoming a distinct driver for emerging disease outbreaks. Early detection of unusual disease emergence and spread should therefore include such cities as part of risk-based surveillance. A catch-all metagenomic sequencing approach of urban sewage could potentially provide an unbiased insight into the dynamics of viral pathogens circulating in a community irrespective of access to care, a potential which already has been proven for the surveillance of poliovirus. Here, we present a detailed characterization of sewage viromes from a snapshot of 81 high density urban areas across the globe, including in-depth assessment of potential biases, as a proof of concept for catch-all viral pathogen surveillance. We show the ability to detect a wide range of viruses and geographical and seasonal differences for specific viral groups. Our findings offer a cross-sectional baseline for further research in viral surveillance from urban sewage samples and place previous studies in a global perspective
Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage
Antimicrobial resistance (AMR) is a serious threat to global public health, but obtaining representative data on AMR for healthy human populations is difficult. Here, we use metagenomic analysis of untreated sewage to characterize the bacterial resistome from 79 sites in 60 countries. We find systematic differences in abundance and diversity of AMR genes between Europe/North-America/Oceania and Africa/Asia/South-America. Antimicrobial use data and bacterial taxonomy only explains a minor part of the AMR variation that we observe. We find no evidence for cross-selection between antimicrobial classes, or for effect of air travel between sites. However, AMR gene abundance strongly correlates with socio-economic, health and environmental factors, which we use to predict AMR gene abundances in all countries in the world. Our findings suggest that global AMR gene diversity and abundance vary by region, and that improving sanitation and health could potentially limit the global burden of AMR. We propose metagenomic analysis of sewage as an ethically acceptable and economically feasible approach for continuous global surveillance and prediction of AMR
Setting a baseline for global urban virome surveillance in sewage
The rapid development of megacities, and their growing connectedness across the world is becoming a distinct driver for emerging disease outbreaks. Early detection of unusual disease emergence and spread should therefore include such cities as part of risk-based surveillance. A catch-all metagenomic sequencing approach of urban sewage could potentially provide an unbiased insight into the dynamics of viral pathogens circulating in a community irrespective of access to care, a potential which already has been proven for the surveillance of poliovirus. Here, we present a detailed characterization of sewage viromes from a snapshot of 81 high density urban areas across the globe, including in-depth assessment of potential biases, as a proof of concept for catch-all viral pathogen surveillance. We show the ability to detect a wide range of viruses and geographical and seasonal differences for specific viral groups. Our findings offer a cross-sectional baseline for further research in viral surveillance from urban sewage samples and place previous studies in a global perspective