Schistosoma haematobium Infections and Infestations
Conditions
Interventions
The study is designed as an observational study with the following components:
1. Cross-sectional surveys: Collect single urine samples from students in 15 schools that were also part of the Zanzibar
Sponsors
Swiss Tropical and Public Health Institute
Eligibility
Sex/Gender
All
Inclusion criteria
Inclusion criteria: The study population will consist of children attending 17 schools in Pemba, Tanzania: 1. Attendance of grades 1-7 in one among the 17 schools selected to be part of the study 2. Aged 5-16 years 3. Randomised to participate in the study (if the number of attending children is greater than required) 4. Written informed consent signed by the parents 5. Written assent signed by the participant if aged 12-16 years old
Exclusion criteria
Exclusion criteria: 1. Not attending any of the 17 selected schools 2. Not attending grades 1-7 3. Not aged 5-16 years 4. Not randomised to participate in the study (if the number of attending children is greater than required) 5. No written informed consent signed by the parents submitted 6. No written assent signed by the participant if aged 12-16 years old 7. Clinically significant severe disease
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Frequency of praziquantel resistance associated single nucleotide polymorphisms (SNPs) in S. haematobium miracidia collected in the school surveys in 2024/25 as measured using whole genome sequencing (WGS) methodologies and bioinformatic pipelines/tools. | — |
Secondary
| Measure | Time frame |
|---|---|
| 1. Genome assemblies and TRPMPZQ SNP profiles of S. haematobium miracidia from 17 different schools in Pemba, collected in 2024/25, as measured using WGS methodologies and bioinformatic pipelines/tools 2. Genome assemblies and TRPMPZQ SNP profiles of S. haematobium miracidia from the same 17 schools in Pemba, collected as part of the ZEST study in 2012 and 2017, and archived in SCAN, as measured using WGS methodologies and bioinformatic pipelines/tools 3. Genome assemblies and TRPMPZQ SNP profiles of S. haematobium miracidia collected before and after MDA from two different schools in Pemba in 2024/25, as measured using WGS methodologies and bioinformatic pipelines/tools 4. Spatiotemporal genetic diversity patterns of S. haematobium populations across Pemba in 2012, 2017 and 2024/25, as measured by the fixation index (FST) 5. Associations between genetic variants and PZQ sensitivity measured by ERR in two different schools in Pemba in 2024/25, based on pairwise comparisons of parasite sub-populations in terms of the FST, partitioned by the individual-level egg reduction rates 6. Associations between genetic variants and PZQ sensitivity in terms of Ca2+ influx in HEK293 cells, measured by functional profiling of TRPMPZQ SNPs in two different schools in Pemba in 2024/25 7. Prevalence and intensity of S. haematobium infections in schoolchildren from 17 schools in 2024/25, as measured by urine filtration 8. Prevalence and intensity of S. haematobium infections in schoolchildren from two schools before and after MDA in 2024/25, as measured by urine filtration 9. Individual and population-level S. haematobium ERR of MDA in two different locations in Pemba in 2024/25, based on the population-level arithmetic mean egg counts before and after treatment 10. Model-predicted impact of praziquantel MDA and praziquantel resistance mitigation strategies on trends in S. haematobium infection prevalence and intensity and drug efficacy (ERR) 11. Cost-efficient survey strategies for p | — |
Countries
Tanzania
Contacts
Public ContactStefanie Knopp
Outcome results
None listed