Soil-transmitted helminth (STH) infections in the Wolaita zone in Southern Ethiopia: mid-stage evaluation of the Geshiyaro project and progress towards the interruption of transmission.

BACKGROUND: This paper documents changes in the prevalence and intensity of soil-transmitted helminth (STH) infections in the Geshiyaro project in the Wolaita zone of Southern Ethiopia. METHODS: The Geshiyaro project comprises three intervention arms. Arm 1 is subdivided into the Arm 1 pilot (one district) and Arm 1 (four other districts), both receiving integrated community-wide mass drug administration MDA (cMDA) with intensive water, sanitation, and hygiene (WaSH) interventions. Arm 2 involves 18 districts with cMDA interventions plus the existing government-led One WaSH program, while Arm 3 serves as a control with school-based MDA (sMDA) interventions plus the existing government-led One WaSH program in three districts. The study is designed as a cohort investigation over time, with the establishment of longitudinal sentinel sites where infection levels are assessed annually. A total of 45 longitudinal parasitological surveillance sentinel sites are being used across all three intervention arms to monitor STH prevalence and intensity of infection. From each of the 45 sentinel sites, 150 individuals were randomly selected, stratified by age and gender. The t-test and analysis of variance (ANOVA) were employed to compare infection prevalence and intensity across the three study arms over time. RESULTS: The prevalence of STH decreased significantly from 34.5% (30.6%, 38.5%) in 2019 to 10.6% (8.3%, 13.4%) in 2022/2023 (df = 1, P < 0.0001) in the Arm 1 pilot, from 27.4% (25.2%, 29.7%) in 2020 to 5.5% (4.4%, 6.7%) in 2023 (df = 1, P < 0.0001) in Arm 1, from 23% (21.3%, 24.8%) in 2020 to 4.5% (3.7%, 5.3%) in 2023 (df = 1, P < 0.001) in Arm 2, and from 49.6% (47.4%, 51.7%) in 2021 to 26.1% in 2023 (df = 1, P < 0.0001) in Arm 3. The relative reduction in the prevalence of any STH was the highest in the arms employing cMDA, namely Arm 2, with a decrease of 82.5% (79.3%, 84.2%), followed by Arm 1 with a reduction of 80.1% (75.3%, 84.6%), and then the Arm 1 pilot with a decrease of 69.4% (60.1%. 76.6%). Arm 3 employing sMDA had the lowest decrease, with a reduction of 46.9% (43.6%, 51%). The mean intensity of infection (based on Kato-Katz egg count measures) for Ascaris lumbricoides species, which was the dominant STH species present in the study area, decreased significantly in Arms 1 and 2, but only slightly in Arm 3. The prevalence of hookworm and Trichuris trichiura infections were found to be very low in all arms but also decreased significantly. CONCLUSIONS: The reduction in the prevalence and intensity of STH in Arms 1 and 2 revealed steady progress towards transmission interruption based on cMDA intervention, but additional efforts with MDA coverage and WaSH interventions are needed to achieve a prevalence threshold < 2% based on the quantitative polymerase chain reaction (qPCR) diagnostic method.

How Does Treatment Coverage and Proportion Never Treated Influence the Success of Schistosoma mansoni Elimination as a Public Health Problem by 2030?

BACKGROUND: The 2030 target for schistosomiasis is elimination as a public health problem (EPHP), achieved when the prevalence of heavy-intensity infection among school-aged children (SAC) reduces to <1%. To achieve this, the new World Health Organization guidelines recommend a broader target of population to include pre-SAC and adults. However, the probability of achieving EPHP should be expected to depend on patterns in repeated uptake of mass drug administration by individuals. METHODS: We employed 2 individual-based stochastic models to evaluate the impact of school-based and community-wide treatment and calculated the number of rounds required to achieve EPHP for Schistosoma mansoni by considering various levels of the population never treated (NT). We also considered 2 age-intensity profiles, corresponding to a low and high burden of infection in adults. RESULTS: The number of rounds needed to achieve this target depends on the baseline prevalence and the coverage used. For low- and moderate-transmission areas, EPHP can be achieved within 7 years if NT ≤10% and NT <5%, respectively. In high-transmission areas, community-wide treatment with NT <1% is required to achieve EPHP. CONCLUSIONS: The higher the intensity of transmission, and the lower the treatment coverage, the lower the acceptable value of NT becomes. Using more efficacious treatment regimens would permit NT values to be marginally higher. A balance between target treatment coverage and NT values may be an adequate treatment strategy depending on the epidemiological setting, but striving to increase coverage and/or minimize NT can shorten program duration.

How Does the Proportion of Never Treatment Influence the Success of Mass Drug Administration Programs for the Elimination of Lymphatic Filariasis?

BACKGROUND: Mass drug administration (MDA) is the cornerstone for the elimination of lymphatic filariasis (LF). The proportion of the population that is never treated (NT) is a crucial determinant of whether this goal is achieved within reasonable time frames. METHODS: Using 2 individual-based stochastic LF transmission models, we assess the maximum permissible level of NT for which the 1% microfilaremia (mf) prevalence threshold can be achieved (with 90% probability) within 10 years under different scenarios of annual MDA coverage, drug combination and transmission setting. RESULTS: For Anopheles-transmission settings, we find that treating 80% of the eligible population annually with ivermectin + albendazole (IA) can achieve the 1% mf prevalence threshold within 10 years of annual treatment when baseline mf prevalence is 10%, as long as NT <10%. Higher proportions of NT are acceptable when more efficacious treatment regimens are used. For Culex-transmission settings with a low (5%) baseline mf prevalence and diethylcarbamazine + albendazole (DA) or ivermectin + diethylcarbamazine + albendazole (IDA) treatment, elimination can be reached if treatment coverage among eligibles is 80% or higher. For 10% baseline mf prevalence, the target can be achieved when the annual coverage is 80% and NT ≤15%. Higher infection prevalence or levels of NT would make achieving the target more difficult. CONCLUSIONS: The proportion of people never treated in MDA programmes for LF can strongly influence the achievement of elimination and the impact of NT is greater in high transmission areas. This study provides a starting point for further development of criteria for the evaluation of NT.

Progress in controlling the transmission of schistosome parasites in Southern Ethiopia: the Geshiyaro Project in the Wolaita Zone.

BACKGROUND: This paper describes changes in the prevalence and intensity of schistosome parasite infections in a project integrating mass drug administration (MDA), water, sanitation, and hygiene (WaSH), and behavioral change interventions. METHODS: The Geshiyaro Project comprises three intervention arms. Arm 1 is subdivided into "Arm 1 pilot" (one district) and Arm 1 (four other districts), both receiving integrated community-wide MDA with intensive WaSH interventions. Arm 2 involves 17 districts with community-wide MDA interventions, while Arm 3 serves as a control with school-based MDA interventions in three districts. A total of 150 individuals, stratified by age group, were randomly selected from each of the 45 sentinel sites. Arm sizes were 584 (Arm 1 pilot), 1636 (Arm 1), 2203 (Arm 2), and 2238 (Arm 3). Statistical tests were employed to compare infection prevalence and intensity across the different arms. RESULTS: The prevalence of schistosome parasite infection ranged from 0% to 2.6% and from 1.7% to 25.7% across districts, employing the Kato-Katz (KK) and point-of-care circulating cathodic antigen (POC-CCA) diagnostics, respectively. The mean infection intensity level showed no marked difference between baseline and follow-up surveys when measured by KK, except in Arm 2 (t = 6.89, P < 0.0001). Infection prevalence decreased significantly in Arm 1 (t = 8.62, P < 0.0001), Arm 2 (t = 6.94, P < 0.0001), and Arm 3 (t = 8.83, P < 0.0001), but not in Arm 1 pilot (t = 1.69, P = 0.09) by POC-CCA, when trace was considered positive. The decrease was significant only in Arm 1 (t = 3.28, P = 0.0001) and Arm 2 (t = 7.62, P < 0.0001) when the trace was considered negative in POC-CCA. Arm 2 demonstrated a significant difference in difference (DID) compared to the control group, Arm 3, regardless of whether trace in POC-CCA was considered positive (DID = 3.9%, df = 8780, P = 0.025) or negative (DID = -5.2, df = 8780, P = 0.0004). CONCLUSIONS: The prevalence of schistosomiasis was low when employing the KK diagnostic but moderate in some locations by the POC-CCA diagnostic. The infection level had decreased across all arms of the Geshiyaro study at mid-term of the 7-year project, but further efforts are needed to reduce the rate of parasite transmission based on the POC-CCA diagnostic scores.

Spatial heterogeneity in mass drug administration from a longitudinal epidemiological study assessing transmission interruption of soil transmitted helminths in the Wolaita zone of southern Ethiopia (Geshiyaro Project).

OBJECTIVES: Deworming programmes of soil-transmitted helminths are generally monitored and evaluated by aggregating drug coverage and infection levels at a district level. However, heterogeneity in drug coverage at finer spatial scales means indicators may remain above thresholds for elimination as a public health problem or of transmission in some areas. This paper aims to highlight the misleading information that aggregating data at larger spatial scales can have for programme decision making. METHODS: Drug coverage data from the Geshiyaro project were compared at two spatial scales with reference to the World Health Organisation's targets. District (woreda) and village (kebele) level were compared. The association between infection levels and drug coverage was analysed by fitting a weighted least-squares function to the mean intensity of infection (eggs per gram of faeces) against drug coverage. RESULTS: The data show clearly that when the evaluation of coverage is aggregated to the district level, information on heterogeneity at a finer spatial scale is lost. Infection intensity decreases significantly (p = 0.0023) with increasing drug coverage. CONCLUSION: Aggregating data at large spatial scales can result in prematurely ceasing deworming, prompting rapid infection bounce-back. There is a strong need to define context-specific spatial scales for monitoring and evaluating intervention programmes.

How important is the spatial movement of people in attempts to eliminate the transmission of human helminth infections by mass drug administration?

Human mobility contributes to the spatial dynamics of many infectious diseases, and understanding these dynamics helps us to determine the most effective ways to intervene and plan surveillance. In this paper, we describe a novel transmission model for the spatial dynamics of hookworm, a parasitic worm which is a common infection across sub-Saharan Africa, East Asia and the Pacific islands. We fit our model, with and without mobility, to data obtained from a sub-county in Kenya, and validate the model's predictions against the decline in prevalence observed over the course of a clustered randomized control trial evaluating methods of administering mass chemotherapy. We find that our model which incorporates human mobility is able to reproduce the observed patterns in decline of prevalence during the TUMIKIA trial, and additionally, that the widespread bounce-back of infection may be possible over many years, depending on the rates of people movement between villages. The results have important implications for the design of mass chemotherapy programmes for the elimination of human helminth transmission. This article is part of the theme issue 'Challenges and opportunities in the fight against neglected tropical diseases: a decade from the London Declaration on NTDs'.

Individual longitudinal compliance to neglected tropical disease mass drug administration programmes, a systematic review.

Repeated distribution of preventative chemotherapy (PC) by mass drug administration forms the mainstay of transmission control for five of the 20 recognised neglected tropical diseases (NTDs); soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis and trachoma. The efficiency of such programmes is reliant upon participants swallowing the offered treatment consistently at each round. This is measured by compliance, defined as the proportion of eligible participants swallowing treatment. Individually linked longitudinal compliance data is important for assessing the potential impact of MDA-based control programmes, yet this accurate monitoring is rarely implemented in those for NTDs. Longitudinal compliance data reported by control programmes globally for the five (PC)-NTDs since 2016 is examined, focusing on key associations of compliance with age and gender. PubMed and Web of Science was searched in January 2022 for articles written in English and Spanish, and the subsequent extraction adhered to PRISMA guidelines. Study title screening was aided by Rayyan, a machine learning software package. Studies were considered for inclusion if primary compliance data was recorded for more than one time point, in a population larger than 100 participants. All data analysis was conducted in R. A total of 89 studies were identified containing compliance data, 57 were longitudinal studies, of which 25 reported individually linked data reported by varying methods. The association of increasing age with the degree of systematic treatment was commonly reported. The review is limited by the paucity of data published on this topic. The varying and overlapping terminologies used to describe coverage (receiving treatment) and compliance (swallowing treatment) is reviewed. Consequently, it is recommended that WHO considers clearly defining the terms for coverage, compliance, and longitudinal compliance which are currently contradictory across their NTD treatment guidelines. This review is registered with PROSPERO (number: CRD42022301991).

Predisposition to soil-transmitted helminth reinfection after four rounds of mass drug administration: results from a longitudinal cohort in the Geshiyaro project, a transmission elimination feasibility study in the Wolaita zone of southern Ethiopia.

BACKGROUND: Current WHO strategies for reaching soil-transmitted helminths (STH) elimination as a public health problem excludes treating certain adult populations in endemic areas, creating infection reservoirs that drive 'bounce back' of STH infection to pretreatment levels post-mass drug administration (MDA). Predisposition is a widespread, but poorly understood phenomena among helminth infections where individuals are predisposed to reinfection after repeated treatments. METHODS: This analysis uses Geshiyaro project data, an STH control programme exploring transmission interruption by community-wide MDA and enhanced water, sanitation and hygiene during 2019-2023. Parasitological survey data from longitudinal cohorts are analysed using Kendall's Tau-b rank correlation to assess the evidence for predisposition to light or heavy infection between four consecutive rounds of MDA. RESULTS: Correlation analyses revealed the strongest evidence for predisposition to heavy or light Ascaris lumbricoides infection was between survey 1 and 2 (Tau-b 0.29; p<0.001). Overall patterns were not observed for Trichuris trichiura or hookworm infections, however, some significant and notable correlations were recorded for some stratifications and time points. CONCLUSIONS: Evidence for predisposition in endemic settings in southern Ethiopia with low STH prevalence suggests that more targeted approaches to MDA in those predisposed to infection may be a sensible control strategy if cheap, point of care diagnostics are available.

Informing antimicrobial stewardship with explainable AI.

The accuracy and flexibility of artificial intelligence (AI) systems often comes at the cost of a decreased ability to offer an intuitive explanation of their predictions. This hinders trust and discourage adoption of AI in healthcare, exacerbated by concerns over liabilities and risks to patients' health in case of misdiagnosis. Providing an explanation for a model's prediction is possible due to recent advances in the field of interpretable machine learning. We considered a data set of hospital admissions linked to records of antibiotic prescriptions and susceptibilities of bacterial isolates. An appropriately trained gradient boosted decision tree algorithm, supplemented by a Shapley explanation model, predicts the likely antimicrobial drug resistance, with the odds of resistance informed by characteristics of the patient, admission data, and historical drug treatments and culture test results. Applying this AI-based system, we found that it substantially reduces the risk of mismatched treatment compared with the observed prescriptions. The Shapley values provide an intuitive association between observations/data and outcomes; the associations identified are broadly consistent with expectations based on prior knowledge from health specialists. The results, and the ability to attribute confidence and explanations, support the wider adoption of AI in healthcare.

The observed relationship between the degree of parasite aggregation and the prevalence of infection within human host populations for soil-transmitted helminth and schistosome infections.

BACKGROUND: Soil-transmitted helminths (STH) and schistosome parasites are highly aggregated within the human population. The probability distribution of worms per person is described well by the negative binomial probability distribution with aggregation parameter, k, which varies inversely with parasite clustering. The relationship between k and prevalence in defined populations subject to mass drug administration is not well understood. METHODS AND RESULTS: We use statistical methods to estimate k using two large independent datasets for STH and schistosome infections from India and Niger, respectively, both of which demonstrate increased aggregation of parasites in a few hosts, as the prevalence of infections declines across the dataset. CONCLUSIONS: A greater attention needs to be given in monitoring and evaluation programmes to find and treat the remaining aggregates of parasites.

Commentary on the use of the reproduction number R during the COVID-19 pandemic.

Since the beginning of the COVID-19 pandemic, the reproduction number [Formula: see text] has become a popular epidemiological metric used to communicate the state of the epidemic. At its most basic, [Formula: see text] is defined as the average number of secondary infections caused by one primary infected individual. [Formula: see text] seems convenient, because the epidemic is expanding if [Formula: see text] and contracting if [Formula: see text]. The magnitude of [Formula: see text] indicates by how much transmission needs to be reduced to control the epidemic. Using [Formula: see text] in a naïve way can cause new problems. The reasons for this are threefold: (1) There is not just one definition of [Formula: see text] but many, and the precise definition of [Formula: see text] affects both its estimated value and how it should be interpreted. (2) Even with a particular clearly defined [Formula: see text], there may be different statistical methods used to estimate its value, and the choice of method will affect the estimate. (3) The availability and type of data used to estimate [Formula: see text] vary, and it is not always clear what data should be included in the estimation. In this review, we discuss when [Formula: see text] is useful, when it may be of use but needs to be interpreted with care, and when it may be an inappropriate indicator of the progress of the epidemic. We also argue that careful definition of [Formula: see text], and the data and methods used to estimate it, can make [Formula: see text] a more useful metric for future management of the epidemic.

Spatial scales in human movement between reservoirs of infection.

The life cycle of parasitic organisms that are the cause of much morbidity in humans often depend on reservoirs of infection for transmission into their hosts. Understanding the daily, monthly and yearly movement patterns of individuals between reservoirs is therefore of great importance to implementers of control policies seeking to eliminate various parasitic diseases as a public health problem. This is due to the fact that the underlying spatial extent of the reservoir of infection, which drives transmission, can be strongly affected by inputs from external sources, i.e., individuals who are not spatially attributed to the region defined by the reservoir itself can still migrate and contribute to it. In order to study the importance of these effects, we build and examine a novel theoretical model of human movement between spatially-distributed focal points for infection clustered into regions defined as 'reservoirs of infection'. Using our model, we vary the spatial scale of human moment defined around focal points and explicitly calculate how varying this definition can influence the temporal stability of the effective transmission dynamics - an effect which should strongly influence how control measures, e.g., mass drug administration (MDA), define evaluation units (EUs). Considering the helminth parasites as our main example, by varying the spatial scale of human movement, we demonstrate that a critical scale exists around infectious focal points at which the migration rate into their associated reservoir can be neglected for practical purposes. This scale varies by species and geographic region, but is generalisable as a concept to infectious reservoirs of varying spatial extents and shapes. Our model is designed to be applicable to a very general pattern of infectious disease transmission modified by the migration of infected individuals between clustered communities. In particular, it may be readily used to study the spatial structure of hosts for macroparasites with temporally stationary distributions of infectious focal point locations over the timescales of interest, which is viable for the soil-transmitted helminths and schistosomes. Additional developments will be necessary to consider diseases with moving reservoirs, such as vector-born filarial worm diseases.

Probability distributions of helminth parasite burdens within the human host population following repeated rounds of mass drug administration and their impact on the transmission breakpoint.

The existence of multiple stable equilibria in models of parasitic helminth transmission was a ground-breaking discovery over 30 years ago. An implication of this discovery, that there is a level of infection below which transmission cannot self-sustain called the transmission breakpoint, has in part motivated the push towards the elimination of many human diseases caused by the multiple species of helminth worldwide. In the absence of vaccines, the predominant method in this push towards elimination is to repeatedly administer endemic populations with anthelmintic drugs, over several treatment rounds, in what has become to be known as mass drug administration (MDA). MDA will inevitably alter the distribution of parasite burdens among hosts from the baseline distribution, and significantly, the location of the transmission breakpoint is known to be dependent on the level of aggregation of this distribution-for a given mean worm burden, more highly aggregated distributions where fewer individuals harbour most of the burden, will have a lower transmission breakpoint. In this paper, we employ a probabilistic analysis of the changes to the distribution of burdens in a population undergoing MDA, and simple approximations, to determine how key aspects of the programmes (including compliance, drug efficacy and treatment coverage) affect the location of the transmission breakpoint. We find that individual compliance to treatment, which determines the number of times an individual participates in mass drug administration programmes, is key to the location of the breakpoint, indicating the vital importance to ensure that people are not routinely missed in these programmes.

SCHISTOX: An individual based model for the epidemiology and control of schistosomiasis.

A stochastic individual based model, SCHISTOX, has been developed for the study of schistosome transmission dynamics and the impact of control by mass drug administration. More novel aspects that can be investigated include individual level adherence and access to treatment, multiple communities, human sex population dynamics, and implementation of a potential vaccine. Many of the model parameters have been estimated within previous studies and have been shown to vary between communities, such as the age-specific contact rates governing the age profiles of infection. However, uncertainty remains as there are wide ranges for certain parameter values and a few remain relatively unknown. We analyse the model dynamics by parameterizing it with published parameter values. We also discuss the development of SCHISTOX in the form of a publicly available open-source GitHub repository. The next key development stage involves validating the model by calibrating to epidemiological data.

Defining a prevalence level to describe the elimination of Lymphatic Filariasis (LF) transmission and designing monitoring & evaluating (M&E) programmes post the cessation of mass drug administration (MDA).

The global decline in prevalence of lymphatic filariasis has been one of the major successes of the WHO's NTD programme. The recommended strategy of intensive, community-wide mass drug administration, aims to break localised transmission by either reducing the prevalence of microfilaria positive infections to below 1%, or antigen positive infections to below 2%. After the threshold is reached, and mass drug administration is stopped, geographically defined evaluation units must pass Transmission Assessment Surveys to demonstrate that transmission has been interrupted. In this study, we use an empirically parameterised stochastic transmission model to investigate the appropriateness of 1% microfilaria-positive prevalence as a stopping threshold, and statistically evaluate how well various monitoring prevalence-thresholds predict elimination or disease resurgence in the future by calculating their predictive value. Our results support the 1% filaremia prevalence target as appropriate stopping criteria. However, because at low prevalence-levels random events dominate the transmission dynamics, we find single prevalence measurements have poor predictive power for predicting resurgence, which suggests alternative criteria for restarting MDA may be beneficial.

Towards personalized guidelines: using machine-learning algorithms to guide antimicrobial selection.

BACKGROUND: Electronic decision support systems could reduce the use of inappropriate or ineffective empirical antibiotics. We assessed the accuracy of an open-source machine-learning algorithm trained in predicting antibiotic resistance for three Gram-negative bacterial species isolated from patients' blood and urine within 48 h of hospital admission. METHODS: This retrospective, observational study used routine clinical information collected between January 2010 and October 2016 in Birmingham, UK. Patients from whose blood or urine cultures Escherichia coli, Klebsiella pneumoniae or Pseudomonas aeruginosa was isolated were identified. Their demographic, microbiology and prescribing data were used to train an open-source machine-learning algorithm-XGBoost-in predicting resistance to co-amoxiclav and piperacillin/tazobactam. Multivariate analysis was performed to identify predictors of resistance and create a point-scoring tool. The performance of both methods was compared with that of the original prescribers. RESULTS: There were 15 695 admissions. The AUC of the receiver operating characteristic curve for the point-scoring tools ranged from 0.61 to 0.67, and performed no better than medical staff in the selection of appropriate antibiotics. The machine-learning system performed statistically but marginally better (AUC 0.70) and could have reduced the use of unnecessary broad-spectrum antibiotics by as much as 40% among those given co-amoxiclav, piperacillin/tazobactam or carbapenems. A validation study is required. CONCLUSIONS: Machine-learning algorithms have the potential to help clinicians predict antimicrobial resistance in patients found to have a Gram-negative infection of blood or urine. Prospective studies are required to assess performance in an unselected patient cohort, understand the acceptability of such systems to clinicians and patients, and assess the impact on patient outcome.

Policy implications of the potential use of a novel vaccine to prevent infection with Schistosoma mansoni with or without mass drug administration.

Schistosomiasis is one of the most important neglected tropical diseases (NTDs) affecting millions of people in 79 different countries. The World Health Organization (WHO) has specified two control goals to be achieved by 2020 and 2025 - morbidity control and elimination as a public health problem (EPHP). Mass drug administration (MDA) is the main method for schistosomiasis control but it has sometimes proved difficult to both secure adequate supplies of the most efficacious drug praziquantel to treat the millions infected either annually or biannually, and to achieve high treatment coverage in targeted communities in regions of endemic infection. The development of alternative control methods remains a priority. In this paper, using stochastic individual-based models, we analyze whether the addition of a novel vaccine alone or in combination with drug treatment, is a more effective control strategy, in terms of achieving the WHO goals, as well as the time and costs to achieve these goals when compared to MDA alone. The key objective of our analyses is to help facilitate decision making for moving a promising candidate vaccine through the phase I, II and III trials in humans to a final product for use in resource poor settings. We find that in low to moderate transmission settings, both vaccination and MDA are highly likely to achieve the WHO goals within 15 years and are likely to be cost-effective. In high transmission settings, MDA alone is unable to achieve the goals, whereas vaccination is able to achieve both goals in combination with MDA. In these settings Vaccination is cost-effective, even for short duration vaccines, so long as vaccination costs up to US$7.60 per full course of vaccination. The public health value of the vaccine depends on the duration of vaccine protection, the baseline prevalence prior to vaccination and the WHO goal.

Vaccination or mass drug administration against schistosomiasis: a hypothetical cost-effectiveness modelling comparison.

BACKGROUND: Schistosomiasis is a neglected tropical disease, targeted by the World Health Organization for reduction in morbidity by 2020. It is caused by parasitic flukes that spread through contamination of local water sources. Traditional control focuses on mass drug administration, which kills the majority of adult worms, targeted at school-aged children. However, these drugs do not confer long-term protection and there are concerns over the emergence of drug resistance. The development of a vaccine against schistosomiasis opens the potential for control methods that could generate long-lasting population-level immunity if they are cost-effective. METHODS: Using an individual-based transmission model, matched to epidemiological data, we compared the cost-effectiveness of a range of vaccination programmes against mass drug administration, across three transmission settings. Health benefit was measured by calculating the heavy-intensity infection years averted by each intervention, while vaccine costs were assessed against robust estimates for the costs of mass drug administration obtained from data. We also calculated a critical vaccination cost, a cost beyond which vaccination might not be economically favorable, by benchmarking the cost-effectiveness of potential vaccines against the cost-effectiveness of mass drug administration, and examined the effect of different vaccine protection durations. RESULTS: We found that sufficiently low-priced vaccines can be more cost-effective than traditional drugs in high prevalence settings, and can lead to a greater reduction in morbidity over shorter time-scales. MDA or vaccination programmes that target the whole community generate the most health benefits, but are generally less cost-effective than those targeting children, due to lower prevalence of schistosomiasis in adults. CONCLUSIONS: The ultimate cost-effectiveness of vaccination will be highly dependent on multiple vaccine characteristics, such as the efficacy, cost, safety and duration of protection, as well as the subset of population targeted for vaccination. However, our results indicate that if a vaccine could be developed with reasonable characteristics and for a sufficiently low cost, then vaccination programmes can be a highly cost-effective method of controlling schistosomiasis in high-transmission areas. The population-level immunity generated by vaccination will also inevitably improve the chances of interrupting transmission of the disease, which is the long-term epidemiological goal.