Identifying drivers of schistosomiasis treatment failure and recommendations for treatment strategies (DRIVERS)
Year of award: 2025
Grantholders
Prof Poppy Lamberton
University of Glasgow, United Kingdom
Prof Poppy Lamberton
University of Glasgow, United Kingdom
Prof Poppy Lamberton
University of Glasgow, United Kingdom
Dr Jessica Clark
University of Glasgow, United Kingdom
Prof Poppy Lamberton
University of Glasgow, United Kingdom
Prof Matthew Berriman
University of Glasgow, United Kingdom
Prof James Cotton
University of Glasgow, United Kingdom
Dr Joaquin Prada
University of Surrey, United Kingdom
Dr Justin Nono Komguep
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Dr Jean Coulibaly
Centre Suisse De Recherches Scientifiques - Cote D'ivoire, Cote d'Ivoire
Dr Rachel Pullan
London School of Hygiene & Tropical Medicine, United Kingdom
Dr Sekeleghe Kayuni
Malawi Liverpool Wellcome Programme, Malawi
Dr Janelisa Musaya
Malawi Liverpool Wellcome Trust Clinical Research Programme, Malawi
Dr Paul Johnson
University of Glasgow, United Kingdom
Dr Fiona Allan
London School of Hygiene & Tropical Medicine, United Kingdom
Dr Fiona Fleming
Default Community Account
Project summary
Over 150 million people have the debilitating disease schistosomiasis. Despite >20 years of praziquantel mass drug administration (MDA) and the WHO 2030 goal of elimination as a public-health problem, transmission remains high in many places and treatment success varies greatly. Understanding drivers of treatment failures is needed to inform more effective control. In low and high endemicity, Schistosoma haematobium and Schistosoma mansoni settings in Côte d’Ivoire and Malawi, we will address key knowledge gaps through three main interlinking aims:
1: Estimate true worm burdens, clearance, reinfection, and proportions of worms shedding eggs, pre- and post-praziquantel.
2: Quantify drivers of treatment failures characterised as:
- 2a: Poor worm-burden reduction in individuals post-treatment;
- 2b: Rapid individual reinfection post-treatment; 2c: Persistent community transmission despite repeated treatments.
3: Develop informed, context-specific models and tools, to identify intervention strategies that tackle treatment failures to more effectively reduce schistosomiasis burden.
Combining detailed longitudinal epidemiology, immunology, pharmacokinetics, parasite genetics, host behaviour, malacology, environmental and MDA coverage data, within geospatial, causal inference, state-space and transmission modelling frameworks, we will provide accurate estimates of worm-burden dynamics, characterise causal factors of treatment failures, and identify and assess the impact of improved intervention strategies in field-validated, individual-based transmission models.