The effects of subcurative praziquantel treatment on life-history traits and trade-offs in drug-resistant Schistosoma mansoni

Natural selection acts on all organisms, including parasites, to maximise reproductive fitness. Drug resistance traits are often associated with life-history costs in the absence of treatment. Schistosomiasis control programmes rely on mass drug administration to reduce human morbidity and mortality. Although hotspots of reduced drug efficacy have been reported, resistance is not widespread. Using Bayesian State-Space Models (SSMs) fitted to data from an in vivo laboratory system, we tested the hypothesis that the spread of resistant Schistosoma may be limited by life-history costs not present in susceptible counterparts. Schistosoma mansoni parasites from a praziquantel–susceptible (S), a praziquantel–resistant (R) or a mixed line of originally resistant and susceptible parasites (RS) were exposed to a range of praziquantel doses. Parasite numbers at each life stage were quantified in their molluscan intermediate and murine definitive hosts across four generations, and SSMs were used to estimate key life-history parameters for each experimental group over time. Model outputs illustrated that parasite adult survival and fecundity in the murine host decreased across all lines, including R, with increasing drug pressure. Trade-offs between adult survival and fecundity were observed in all untreated lines, and these remained strong in S with praziquantel pressure. In contrast, trade-offs between adult survival and fecundity were lost under praziquantel pressure in R. As expected, parasite life-history traits within the molluscan host were complex, but trade-offs were demonstrated between parasite establishment and cercarial output. The observed trade-offs between generations within hosts, which were modified by praziquantel treatment in the R line, could limit the spread of R parasites under praziquantel pressure. Whilst such complex life-history costs may be difficult to detect using standard empirical methods, we demonstrate that SSMs provide robust estimates of life history parameters, aiding our understanding of costs and trade-offs of resistant parasites within this system and beyond

Introduction to special issue: Advancing disease ecology through eDNA monitoring of infectious agents

This special issue focuses on the applications of environmental DNA (eDNA) sequencing for the detection and monitoring of disease‐causing agents, including viruses, bacteria, protozoans, myxozoans, fungi, trematodes, and arthropods. We explore the impact of eDNA technologies, such as metabarcoding and qPCR, in understanding the dynamics of pathogens in various environments as well as their implications for conservation, biosecurity, and veterinary and agricultural health under the “One Health” framework. This issue addresses how molecular sequencing provides innovative solutions to the challenges faced by conventional parasite and pathogen detection methods, enabling a more comprehensive understanding of the spatiotemporal dynamics of disease agents. Finally, we discuss the challenges in eDNA applications, such as primer development and taxonomic resolution, and the opportunities for future research in advancing eDNA methodologies for infectious disease studies. This issue highlights the growing importance of eDNA surveillance in understanding and managing the health of ecosystems and at‐risk species

The problem of scale in the prediction and management of pathogen spillover

Disease emergence events, epidemics and pandemics all underscore the need to predict zoonotic pathogen spillover. Because cross-species transmission is inherently hierarchical, involving processes that occur at varying levels of biological organization, such predictive efforts can be complicated by the many scales and vastness of data potentially required for forecasting. A wide range of approaches are currently used to forecast spillover risk (e.g. macroecology, pathogen discovery, surveillance of human populations, among others), each of which is bound within particular phylogenetic, spatial and temporal scales of prediction. Here, we contextualize these diverse approaches within their forecasting goals and resulting scales of prediction to illustrate critical areas of conceptual and pragmatic overlap. Specifically, we focus on an ecological perspective to envision a research pipeline that connects these different scales of data and predictions from the aims of discovery to intervention. Pathogen discovery and predictions focused at the phylogenetic scale can first provide coarse and pattern-based guidance for which reservoirs, vectors and pathogens are likely to be involved in spillover, thereby narrowing surveillance targets and where such efforts should be conducted. Next, these predictions can be followed with ecologically driven spatio-temporal studies of reservoirs and vectors to quantify spatio-temporal fluctuations in infection and to mechanistically understand how pathogens circulate and are transmitted to humans. This approach can also help identify general regions and periods for which spillover is most likely. We illustrate this point by highlighting several case studies where long-term, ecologically focused studies (e.g. Lyme disease in the northeast USA, Hendra virus in eastern Australia, Plasmodium knowlesi in Southeast Asia) have facilitated predicting spillover in space and time and facilitated the design of possible intervention strategies. Such studies can in turn help narrow human surveillance efforts and help refine and improve future large-scale, phylogenetic predictions. We conclude by discussing how greater integration and exchange between data and predictions generated across these varying scales could ultimately help generate more actionable forecasts and interventions

Impacts of host gender on Schistosoma mansoni risk in rural Uganda-A mixed-methods approach

Background The World Health Organization identified Uganda as one of the 10 highly endemic countries for schistosomiasis. Annual mass drug administration (MDA) with praziquantel has led to a decline in intensity of Schistosoma mansoni infections in several areas. However, as hotspots with high (re)infection rates remain, additional research on risk factors and implementing interventions to complement MDA are required to further reduce disease burden in these settings. Through a mixed-methods study we aimed to gain deeper understanding of how gender may impact risk and reinfection in order to inform disease control programmes and ascertain if gender-specific interventions may be beneficial. Methodology/Principal findings In Bugoto, Mayuge District, Eastern Uganda we conducted ethnographic observations (n = 16) and examined epidemiology (n = 55) and parasite population genetics (n = 16) in school-aged children (SAC), alongside a community-wide household survey (n = 130). Water contact was frequent at home, school and in the community and was of domestic, personal care, recreational, religious or commercial nature. Qualitative analysis of type of activity, duration, frequency, level of submersion and water contact sites in children showed only few behavioural differences in water contact between genders. However, survey data revealed that adult women carried out the vast majority of household tasks involving water contact. Reinfection rates (96% overall) and genetic diversity were high in boys (pre-He = 0.66; post-He = 0.67) and girls (pre-He = 0.65; post-He = 0.67), but no differences in reinfection rates (p = 0.62) or genetic diversity by gender before (p = 0.54) or after (p = 0.97) treatment were found. Conclusions/Significance This mixed methods approach showed complementary findings. Frequent water exposure with few differences between boys and girls was mirrored by high reinfection rates and genetic diversity in both genders. Disease control programmes should consider the high reinfection rates among SAC in remaining hotspots of schistosomiasis and the various purposes and settings in which children and adults are exposed to water

Schistosomiasis Control: Leave No Age Group Behind

Despite accelerating progress towards schistosomiasis control in sub-Saharan Africa, several age groups have been eclipsed by current treatment and monitoring strategies that mainly focus on school-aged children. As schistosomiasis poses a threat to people of all ages, unfortunate gaps exist in current treatment coverage and associated monitoring efforts, preventing subsequent health benefits to preschool-aged children as well as certain adolescents and adults. Expanding access to younger ages through the forthcoming pediatric praziquantel formulation and improving treatment coverage in older ages is essential. This should occur alongside formal inclusion of these groups in large-scale monitoring and evaluation activities. Current omission of these age groups from treatment and monitoring exacerbates health inequities and has long-term consequences for sustainable schistosomiasis control

Dynamic and integrative approaches to understanding pathogen spillover

No abstract available

The impact of storage conditions on human stool 16S rRNA microbiome composition and diversity

Background: Multiple factors can influence stool sample integrity upon sample collection. Preservation of faecal samples for microbiome studies is therefore an important step, particularly in tropical regions where resources are limited and high temperatures may significantly influence microbiota profiles. Freezing is the accepted standard to preserve faecal samples however, cold chain methods are often unfeasible in fieldwork scenarios particularly in low and middle-income countries and alternatives are required. This study therefore aimed to address the impact of different preservative methods, time-to-freezing at ambient tropical temperatures, and stool heterogeneity on stool microbiome diversity and composition under real-life physical environments found in resource-limited fieldwork conditions. Methods: Inner and outer stool samples collected from one specimen obtained from three children were stored using different storage preservation methods (raw, ethanol and RNAlater) in a Ugandan field setting. Mixed stool was also stored using these techniques and frozen at different time-to-freezing intervals post-collection from 0–32 h. Metataxonomic profiling was used to profile samples, targeting the V1–V2 regions of 16S rRNA with samples run on a MiSeq platform. Reads were trimmed, combined and aligned to the Greengenes database. Microbial diversity and composition data were generated and analysed using Quantitative Insights Into Microbial Ecology and R software. Results: Child donor was the greatest predictor of microbiome variation between the stool samples, with all samples remaining identifiable to their child of origin despite the stool being stored under a variety of conditions. However, significant differences were observed in composition and diversity between preservation techniques, but intra-preservation technique variation was minimal for all preservation methods, and across the time-to-freezing range (0–32 h) used. Stool heterogeneity yielded no apparent microbiome differences. Conclusions: Stool collected in a fieldwork setting for comparative microbiome analyses should ideally be stored as consistently as possible using the same preservation method throughout

Residence time, water contact, and age-driven Schistosoma mansoni infection in hotspot communities in Uganda

Schistosomiasis is the second most important parasitic infection after malaria in terms of its socioeconomic impact and is endemic in 78 countries. It affects more than 240 million people worldwide, with 90% of cases occurring in sub-Saharan Africa. In Uganda, Schistosomamansoni is the most common species, with more than seven million people infected and 17 million living at risk despite mass drug administration (MDA) of praziquantel initiated more than 16 years ago. There has been a shift in the WHO schistosomiasis goals from controlling morbidity to elimination as a public health problem. Understanding the drivers of infection in persistent transmission hotspots despite ongoing control interventions is paramount. We conducted a cross-sectional epidemiological study of 381 individuals in Bugoto community, Mayuge district, Eastern Uganda, along with a structured survey to ascertain drivers of S. mansoni infection. Bugoto has had community-wide MDA since 2004. We detected a S. mansoni prevalence of 52% across the whole community and a prevalence of 71% in school-age children. This qualifies Bugoto as a highly endemic community according to WHO guidelines. Using a multivariate logistic regression, we found that S. mansoni infection was best explained by age group, longer residence times, and any daily contact with lake water. Schistosomamansoni infection remains a large burden across this community. This study identifies opportunities for interventions that reduce lake water contact, expand treatment eligibility to all at risk, and improve MDA coverage for long-term residents in these settings to control schistosomiasis in persistent transmission hotspots

Environmental variation across multiple spatial scales and temporal lags influences Hendra virus spillover

1. Pathogens can spill over and infect new host species by overcoming a series of ecological and biological barriers. Hendra virus (HeV) circulates in Australian flying foxes and provides a data-rich study system for identifying environmental drivers underlying spillover events. The frequency of spillover events to horses has varied interannually since the virus was first discovered in 1994. These observations suggest that HeV spillover events are driven, in part, by environmental factors, including loss of flying fox habitat and climate variability. 2. We explicitly examine the impact of environmental variation on the risk of HeV spillover at three spatial scales relevant to this system. We use a dataset of 60 spillover events and boosted regression tree methods to identify environmental features (including concurrent and lagged temperature, rainfall, vegetation indices, land cover, and climate indices) at three spatial scales (1-km, 20-km, 100-km radii) associated with horse contacts and reservoir species ecology. 3. We find that temperature, local (1-km radius) human population density, and landscape (100-km radius) forest cover and pasture are the most influential environmental features associated with HeV spillover risk. By including multiple spatial scales and temporal lags in environmental features, we can more accurately quantify risk across space and time than with models that use a single scale. For example, high quality vegetation at the local scale and within a foraging radius (20-km) in the concurrent month and previous years, combined with poorer quality vegetation at the landscape scale in the concurrent month increase risk of HeV spillover. These and other environmental associations likely influence the dynamic foraging behaviour of reservoir flying foxes and drive contacts that facilitate spillover into horse populations. 4. Synthesis and application: Current management of HeV spillover focuses on local-scale interventions – primarily through vaccination and detection of infected horses. Our study finds that HeV spillover risk is also driven by environmental changes over much larger scales and demonstrates management practices would benefit from incorporating landscape interventions alongside local interventions

Translating from egg- to antigen-based indicators for Schistosoma mansoni elimination targets: A Bayesian latent class analysis study

This Document is Protected by copyright and was first published by Frontiers. All rights reserved. it is reproduced with permission.Schistosomiasis is a parasitic disease affecting over 240-million people. World Health Organization (WHO) targets for Schistosoma mansoni elimination are based on Kato-Katz egg counts, without translation to the widely used, urine-based, point-of-care circulating cathodic antigen diagnostic (POC-CCA). We aimed to standardize POC-CCA score interpretation and translate them to Kato-Katz-based standards, broadening diagnostic utility in progress towards elimination. A Bayesian latent-class model was fit to data from 210 school-aged-children over four timepoints pre- to six-months-post-treatment. We used 1) Kato-Katz and established POC-CCA scoring (Negative, Trace, +, ++ and +++), and 2) Kato-Katz and G-Scores (a new, alternative POC-CCA scoring (G1 to G10)). We established the functional relationship between Kato-Katz counts and POC-CCA scores, and the score-associated probability of true infection. This was combined with measures of sensitivity, specificity, and the area under the curve to determine the optimal POC-CCA scoring system and positivity threshold. A simulation parametrized with model estimates established antigen-based elimination targets. True infection was associated with POC-CCA scores of ≥ + or ≥G3. POC-CCA scores cannot predict Kato-Katz counts because low infection intensities saturate the POC-CCA cassettes. Post-treatment POC-CCA sensitivity/specificity fluctuations indicate a changing relationship between egg excretion and antigen levels (living worms). Elimination targets can be identified by the POC-CCA score distribution in a population. A population with ≤2% ++/+++, or ≤0.5% G7 and above, indicates achieving current WHO Kato-Katz-based elimination targets. Population-level POC-CCA scores can be used to access WHO elimination targets prior to treatment. Caution should be exercised on an individual level and following treatment, as POC-CCAs lack resolution to discern between WHO Kato-Katz-based moderate- and high-intensity-infection categories, with limited use in certain settings and evaluations