Description du projet
Surveillance génomique de la fièvre typhoïde
Chaque année, des millions de cas de fièvre typhoïde sont recensés dans le monde. La thérapie antimicrobienne étant la seule option thérapeutique, il convient de contenir l’émergence de la résistance aux médicaments et d’empêcher sa propagation à d’autres pays voisins. À cette fin, le projet TyphiNET, financé par l’UE, utilisera une approche d’épidémiologie génomique pour aider à la surveillance des zones sentinelles et endémiques pour Salmonella typhi. L’objectif est d’obtenir des informations sur la prévalence de souches spécifiques, la résistance aux antimicrobiens et les schémas de transmission régionaux. TyphiNET partagera ces données par le biais d’une plateforme publique en libre accès, améliorant ainsi la prise en charge des maladies et contribuant à la sélection des antimicrobiens.
Objectif
Globally there are ~20 million typhoid fever cases per year, resulting in ~200,000 deaths from infection with the causative agent, Salmonella Typhi. Antimicrobial therapy is the mainstay of typhoid fever control, and genomic epidemiology studies have revealed that drug resistance emerging in one country can rapidly spread to other neighbouring countries and intercontinentally. Genomic and phenotypic surveillance for typhoid and antimicrobial resistance (AMR) is therefore very important for disease control. TyphiNET aims to develop innovative approaches to bring the benefits of typhoid genomic surveillance to LMICs where the disease is endemic through three main goals: (1) to unlock data from travel-associated typhoid cases in high income countries that are adopting genomics for routine Salmonella surveillance (2) to unlock data from project-based genomic surveillance in endemic areas (beginning with five key collaborative projects across Asia and Africa) and (3) develop an open access publicly available platform for synergising, visualising, and disseminating large scale genomic data sourced from sentinel and endemic area surveillance. Research questions will include inferring genomic epidemiology parameters (prevalence of strain types, resistance to specific antimicrobials, and regional transmission patterns) for different countries/regions using data from sentinel surveillance and from endemic area surveillance; comparison of these to demonstrate the utility of sentinel traveller surveillance for predicting endemic area disease patterns; and comparison of disease dynamics between regions. Outcomes will inform management of both endemic disease in LMICs and travel-associated cases elsewhere, including providing region- and country-specific data to inform empirical antimicrobial choice; and will reveal coverage gaps in endemic area surveillance to be targeted in future studies.
Champ scientifique
Programme(s)
Régime de financement
MSCA-IF-EF-ST - Standard EFCoordinateur
WC1E 7HT London
Royaume-Uni