Potential drivers for schistosomiasis persistence: Population genetic analyses from a cluster-randomized urogenital schistosomiasis elimination trial across the Zanzibar islands

Abstract

The World Health Organization’s revised NTD Roadmap and the newly launched Guidelines target elimination of schistosomiasis as a public health problem in all endemic areas by 2030. Key to meeting this goal is elucidating how selective pressures imposed by interventions shape parasite populations. Our aim was to identify any differential impact of a unique cluster-randomized tri-armed elimination intervention (biannual mass drug administration (MDA) applied alone or in association with either mollusciciding (snail control) or behavioural change interventions) across two Zanzibarian islands (Pemba and Unguja) on the population genetic composition of Schistosoma haematobium over space and time. Fifteen microsatellite loci were used to analyse individual miracidia collected from infected individuals across islands and intervention arms at the start (2012 baseline: 1,522 miracidia from 176 children; 303 from 43 adults; age-range 6–75, mean 12.7 years) and at year 5 (2016: 1,486 miracidia from 146 children; 214 from 25 adults; age-range 9–46, mean 12.4 years). Measures of genetic diversity included allelic richness (Ar), Expected (He) and Observed heterozygosity (Ho), inbreeding coefficient ( F _ST), parentage analysis, estimated worm burden, worm fecundity, and genetic sub-structuring. There was little evidence of differential selective pressures on population genetic diversity, inbreeding or estimated worm burdens by treatment arm, with only the MDA+snail control arm within Unguja showing trends towards reduced diversity and altered inbreeding over time. The greatest differences overall, both in terms of parasite fecundity and genetic sub-structuring, were observed between the islands, consistent with Pemba’s persistently higher mean infection intensities compared to neighbouring Unguja, and within islands in terms of infection hotspots (across three definitions). These findings highlight the important contribution of population genetic analyses to elucidate extensive genetic diversity and biological drivers, including potential gene-environmental factors, that may override short term selective pressures imposed by differential disease control strategies.

Trial Registration: ClinicalTrials.gov ISRCTN48837681.

Author summary

Schistosomiasis is a parasitic disease caused by infection with blood flukes, which leads to acute and chronic pathology in millions of infected individuals, particularly those within the poorest tropical and subtropical regions. In 2012, the World Health Organization (WHO) set the ambitious goals to achieve Elimination of Schistosomiasis as a Public Health Problem (i.e., EPHP, prevalence of heavy infection intensity less than 1% in all sentinel sites) and complete Interruption of Transmission (i.e., IoT reduction of incidence of infection to zero) in selected African regions by 2025. More recently, the revised WHO Neglected Tropical Diseases (NTD)-Roadmap and Schistosomiasis Control and Elimination Guidelines aim to achieve EPHP in all regions by 2030. Here we analysed population genetic data associated with a recent 5-year cluster-randomized trial across Zanzibar (Pemba and Unguja islands) aimed to assess the impact of contrasting interventions to achieve urogenital schistosomiasis elimination. Whilst, consistent with the main trial study, no significant differential impact of interventions on parasite prevalence or intensity was detected, our data suggested that the greatest impact on genetic diversity was within the mass drug administration plus concurrent mollusciding arm. Moreover, analyses revealed significant differences in both the genetic sub-structuring and notably the fecundity of parasites between Pemba and Unguja islands, and within island in relation to some (but not all) persistent hotspots, potentially indicative of genetic and biological factors driving persistence. These findings highlight the important contribution of population genetic analyses to reveal high levels of genetic diversity, biological drivers and potential gene-environmental interactions, in determining infection dynamics and persistence, all of which may serve to limit the impact of differential disease control activities.