Understanding the relationship between prevalence of microfilariae and antigenaemia using a model of lymphatic filariasis infection

Distinguishing recrudescence from reinfection in lymphatic filariasis

BACKGROUND

The Global Program to Eliminate Lymphatic Filariasis (GPELF) is the largest public health program based on mass drug administration (MDA). Despite decades of MDA, ongoing transmission in some countries remains a challenge. To optimise interventions, it is critical to differentiate between recrudescence and new infections. Since adult filariae are inaccessible in humans, deriving a method that relies on the offspring microfilariae (mf) is necessary.

METHODS

We developed a genome amplification and kinship analysis-based approach using Brugia malayi samples from gerbils, and applied it to analyse Wuchereria bancrofti mf from humans in Côte d'Ivoire. We examined the pre-treatment genetic diversity in 269 mf collected from 18 participants, and further analysed 1-year post-treatment samples of 74 mf from 4 participants. Hemizygosity of the male X-chromosome allowed for direct inference of haplotypes, facilitating robust maternal parentage inference. To enrich parasite DNA from samples contaminated with host DNA, a whole-exome capture panel was created for W. bancrofti.

FINDINGS

By reconstructing and temporally tracking sibling relationships across pre- and post-treatment samples, we differentiated between new and established maternal families, suggesting reinfection in one participant and recrudescence in three participants. The estimated number of reproductively active adult females ranged between 3 and 11 in the studied participants. Population structure analysis revealed genetically distinct parasites in Côte d'Ivoire compared to samples from other countries. Exome capture identified protein-coding variants with ∼95% genotype concordance rate.

INTERPRETATION

We have generated resources to facilitate the development of molecular genetic tools that can estimate adult worm burdens and monitor parasite populations, thus providing essential information for the successful implementation of GPELF.

FUNDING

This work was financially supported by the Bill and Melinda Gates Foundation (https://www.gatesfoundation.org) under grant OPP1201530 (Co-PIs PUF & Gary J. Weil). B. malayi parasite material was generated with support of the Foundation for Barnes Jewish Hospital (PUF). In addition, the development of computational methods was supported by the National Institutes of Health under grants AI144161 (MM) and AI146353 (MM). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

An Ensemble Framework for Projecting the Impact of Lymphatic Filariasis Interventions Across Sub-Saharan Africa at a Fine Spatial Scale

BACKGROUND

Lymphatic filariasis (LF) is a neglected tropical disease targeted for elimination as a public health problem by 2030. Although mass treatments have led to huge reductions in LF prevalence, some countries or regions may find it difficult to achieve elimination by 2030 owing to various factors, including local differences in transmission. Subnational projections of intervention impact are a useful tool in understanding these dynamics, but correctly characterizing their uncertainty is challenging.

METHODS

We developed a computationally feasible framework for providing subnational projections for LF across 44 sub-Saharan African countries using ensemble models, guided by historical control data, to allow assessment of the role of subnational heterogeneities in global goal achievement. Projected scenarios include ongoing annual treatment from 2018 to 2030, enhanced coverage, and biannual treatment.

RESULTS

Our projections suggest that progress is likely to continue well. However, highly endemic locations currently deploying strategies with the lower World Health Organization recommended coverage (65%) and frequency (annual) are expected to have slow decreases in prevalence. Increasing intervention frequency or coverage can accelerate progress by up to 5 or 6 years, respectively.

CONCLUSIONS

While projections based on baseline data have limitations, our methodological advancements provide assessments of potential bottlenecks for the global goals for LF arising from subnational heterogeneities. In particular, areas with high baseline prevalence may face challenges in achieving the 2030 goals, extending the "tail" of interventions. Enhancing intervention frequency and/or coverage will accelerate progress. Our approach facilitates preimplementation assessments of the impact of local interventions and is applicable to other regions and neglected tropical diseases.

Subnational Projections of Lymphatic Filariasis Elimination Targets in Ethiopia to Support National Level Policy

BACKGROUND

Lymphatic filariasis (LF) is a debilitating, poverty-promoting, neglected tropical disease (NTD) targeted for worldwide elimination as a public health problem (EPHP) by 2030. Evaluating progress towards this target for national programmes is challenging, due to differences in disease transmission and interventions at the subnational level. Mathematical models can help address these challenges by capturing spatial heterogeneities and evaluating progress towards LF elimination and how different interventions could be leveraged to achieve elimination by 2030.

METHODS

Here we used a novel approach to combine historical geo-spatial disease prevalence maps of LF in Ethiopia with 3 contemporary disease transmission models to project trends in infection under different intervention scenarios at subnational level.

RESULTS

Our findings show that local context, particularly the coverage of interventions, is an important determinant for the success of control and elimination programmes. Furthermore, although current strategies seem sufficient to achieve LF elimination by 2030, some areas may benefit from the implementation of alternative strategies, such as using enhanced coverage or increased frequency, to accelerate progress towards the 2030 targets.

CONCLUSIONS

The combination of geospatial disease prevalence maps of LF with transmission models and intervention histories enables the projection of trends in infection at the subnational level under different control scenarios in Ethiopia. This approach, which adapts transmission models to local settings, may be useful to inform the design of optimal interventions at the subnational level in other LF endemic regions.

Reducing the Antigen Prevalence Target Threshold for Stopping and Restarting Mass Drug Administration for Lymphatic Filariasis Elimination: A Model-Based Cost-effectiveness Simulation in Tanzania, India and Haiti

BACKGROUND

The Global Programme to Eliminate Lymphatic Filariasis (GPELF) aims to reduce and maintain infection levels through mass drug administration (MDA), but there is evidence of ongoing transmission after MDA in areas where Culex mosquitoes are the main transmission vector, suggesting that a more stringent criterion is required for MDA decision making in these settings.

METHODS

We use a transmission model to investigate how a lower prevalence threshold (<1% antigenemia [Ag] prevalence compared with <2% Ag prevalence) for MDA decision making would affect the probability of local elimination, health outcomes, the number of MDA rounds, including restarts, and program costs associated with MDA and surveys across different scenarios. To determine the cost-effectiveness of switching to a lower threshold, we simulated 65% and 80% MDA coverage of the total population for different willingness to pay per disability-adjusted life-year averted for India ($446.07), Tanzania ($389.83), and Haiti ($219.84).

RESULTS

Our results suggest that with a lower Ag threshold, there is a small proportion of simulations where extra rounds are required to reach the target, but this also reduces the need to restart MDA later in the program. For 80% coverage, the lower threshold is cost-effective across all baseline prevalences for India, Tanzania, and Haiti. For 65% MDA coverage, the lower threshold is not cost-effective due to additional MDA rounds, although it increases the probability of local elimination. Valuing the benefits of elimination to align with the GPELF goals, we find that a willingness to pay per capita government expenditure of approximately $1000-$4000 for 1% increase in the probability of local elimination would be required to make a lower threshold cost-effective.

CONCLUSIONS

Lower Ag thresholds for stopping MDAs generally mean a higher probability of local elimination, reducing long-term costs and health impacts. However, they may also lead to an increased number of MDA rounds required to reach the lower threshold and, therefore, increased short-term costs. Collectively, our analyses highlight that lower target Ag thresholds have the potential to assist programs in achieving lymphatic filariasis goals.

Distinguishing recrudescence from reinfection in lymphatic filariasis: a genomics-based approach for monitoring worm burden

Background

The Global Program to Eliminate Lymphatic Filariasis is the largest public health program based on mass drug administration (MDA). Despite decades of MDA, ongoing transmission in some countries remains a challenge. To optimize interventions, it is essential to differentiate between recrudescence (poor drug response and persistent infection) and new infections (ongoing transmission). Since adult filariae are inaccessible in humans, an approach that relies on genotyping the offspring microfilariae (mf) is required.

Methods

We utilized Brugia malayi adults and mf obtained from gerbils with a known pedigree to develop and validate our whole-genome amplification and kinship analysis approach. We then sequenced the genomes of Wuchereria bancrofti mf from infected humans from Côte d'Ivoire (CDI), characterized the population genetic diversity, and made inferences about the adult breeders. We developed a whole-exome capture panel for W. bancrofti to enrich parasite nuclear DNA from lower-quality samples contaminated with host DNA.

Results

We established a robust analysis pipeline using B. malayi adult and mf. We estimated the pre-treatment genetic diversity in W. bancrofti from 269 mf collected from 18 individuals, and further analyzed 1-year post-treatment samples of 74 mf from 4 individuals. By reconstructing and temporally tracking sibling relationships across pre- and post-treatment samples, we differentiated between new and established maternal families, suggesting reinfection in one subject and recrudescence in three subjects. Estimated reproductively active adult females ranged between 3 and 9 in the studied subjects. Hemizygosity of the male X-chromosome allowed for direct inference of haplotypes, facilitating robust maternal parentage inference, even when the genetic diversity was low. Population structure analysis revealed genetically distinct parasites among our CDI samples. Sequence composition and variant analysis of whole-exome libraries showed that the hybridization capture approach can effectively enrich parasite nuclear DNA and identify protein-coding variants with ∼95% genotype concordance rate.

Conclusions

We have generated resources to facilitate development of field-deployable genotyping tools that can estimate worm burdens and monitor parasite populations. These tools are essential for the success of lymphatic filariasis MDA programs. With further expansion of the databases to include geographically diverse samples, we will be able to spatially track parasite movement associated with host/vector migration.

Diagnosis of helminths depends on worm fecundity and the distribution of parasites within hosts

Helminth transmission and morbidity are dependent on the number of mature parasites within a host; however, observing adult worms is impossible for many natural infections. An outstanding challenge is therefore relating routine diagnostics, such as faecal egg counts, to the underlying worm burden. This relationship is complicated by density-dependent fecundity (egg output per worm reduces due to crowding at high burdens) and the skewed distribution of parasites (majority of helminths aggregated in a small fraction of hosts). We address these questions for the carcinogenic liver fluke Opisthorchis viverrini, which infects approximately 10 million people across Southeast Asia, by analysing five epidemiological surveys (n = 641) where adult flukes were recovered. Using a mechanistic model, we show that parasite fecundity varies between populations, with surveys from Thailand and Laos demonstrating distinct patterns of egg output and density-dependence. As the probability of observing faecal eggs increases with the number of mature parasites within a host, we quantify diagnostic sensitivity as a function of the worm burden and find that greater than 50% of cases are misdiagnosed as false negative in communities close to elimination. Finally, we demonstrate that the relationship between observed prevalence from routine diagnostics and true prevalence is nonlinear and strongly influenced by parasite aggregation.

Comparing antigenaemia- and microfilaraemia as criteria for stopping decisions in lymphatic filariasis elimination programmes in Africa

BACKGROUND

Mass drug administration (MDA) is the main strategy towards lymphatic filariasis (LF) elimination. Progress is monitored by assessing microfilaraemia (Mf) or circulating filarial antigenaemia (CFA) prevalence, the latter being more practical for field surveys. The current criterion for stopping MDA requires <2% CFA prevalence in 6- to 7-year olds, but this criterion is not evidence-based. We used mathematical modelling to investigate the validity of different thresholds regarding testing method and age group for African MDA programmes using ivermectin plus albendazole.

METHODOLGY/PRINCIPAL FINDINGS

We verified that our model captures observed patterns in Mf and CFA prevalence during annual MDA, assuming that CFA tests are positive if at least one adult worm is present. We then assessed how well elimination can be predicted from CFA prevalence in 6-7-year-old children or from Mf or CFA prevalence in the 5+ or 15+ population, and determined safe (>95% positive predictive value) thresholds for stopping MDA. The model captured trends in Mf and CFA prevalences reasonably well. Elimination cannot be predicted with sufficient certainty from CFA prevalence in 6-7-year olds. Resurgence may still occur if all children are antigen-negative, irrespective of the number tested. Mf-based criteria also show unfavourable results (PPV <95% or unpractically low threshold). CFA prevalences in the 5+ or 15+ population are the best predictors, and post-MDA threshold values for stopping MDA can be as high as 10% for 15+. These thresholds are robust for various alternative assumptions regarding baseline endemicity, biological parameters and sampling strategies.

CONCLUSIONS/SIGNIFICANCE

For African areas with moderate to high pre-treatment Mf prevalence that have had 6 or more rounds of annual ivermectin/albendazole MDA with adequate coverage, we recommend to adopt a CFA threshold prevalence of 10% in adults (15+) for stopping MDA. This could be combined with Mf testing of CFA positives to ensure absence of a significant Mf reservoir for transmission.

Community-based trial assessing the impact of annual versus semiannual mass drug administration with ivermectin plus albendazole and praziquantel on helminth infections in northwestern Liberia

•

Mass drug administration (MDA) with ivermectin plus albendazole was more effective for clearing bancroftian filariasis than it was for onchocerciasis or hookworm.

•

Semiannual MDA was no more effective than annual MDA for reducing prevalences of W. bancrofti, O. volvulus, or hookworm infections.

•

Decreases in bancroftian filariasis prevalence were achieved despite unavoidable interruptions in our study related to the 2014 West Africa Ebola epidemic and the 2020 SARS-CoV-2 pandemic.

•

Neglected Tropical Disease elimination programs in areas coendemic for lymphatic filariasis and onchocerciasis should focus on delivering high quality annual MDA with high coverage and compliance and not try to stretch limited resources to deliver semiannual MDA.

•

MDA with praziquantel had little impact on Schistosoma mansoni infection in the heavily infected area.

We assessed the impact of three annual vs five semiannual rounds of mass drug administration (MDA) with ivermectin plus albendazole followed by praziquantel for the control or elimination of lymphatic filariasis (LF), onchocerciasis, soil-transmitted helminth (STH) infections and schistosomiasis in Lofa County, Liberia. The study started in 2012 and was interrupted in 2014 during the Ebola virus outbreak. Repeated cross-sectional surveys were conducted in individuals 5 years and older to measure infection markers. Wuchereria bancrofti antigenemia prevalences decreased from 12.5 to 1.2% (90% reduction) and from 13.6 to 4.2% (69% reduction) one year after three rounds of annual or five rounds of semiannual MDA, respectively. Mixed effects logistic regression models showed decreases in odds of antigenemia positivity were 91 and 74% at that time in the annual and semiannual treatment zones, respectively (p < 0.001). Semiannual MDA was slightly more effective for reducing Onchocerca volvulus microfiladermia prevalence and at follow-up 3 were 74% (from 14.4 to 3.7%) and 83% (from 23.6 to 4.5%) in the annual and semiannual treatment zones, respectively. Both treatment schedules had similar beneficial effects on hookworm prevalence. Thus, annual and semiannual MDA with ivermectin and albendazole had similar beneficial impacts on LF, onchocerciasis, and STH in this setting. In contrast, MDA with praziquantel had little impact on hyperendemic Schistosoma mansoni in the study area. Results from a long-term follow-up survey showed that improvements in infection parameters were sustained by routine annual MDA provided by the Liberian Ministry of Health after our study endpoint.

Sensitivity Analysis of a Transmission Interruption Model for the Soil-Transmitted Helminth Infections in Kenya

As the world rallies toward the endgame of soil-transmitted helminths (STH) elimination by the year 2030, there is a need for efficient and robust mathematical models that would enable STH programme managers to target the scarce resources and interventions, increase treatment coverage among specific sub-groups of the population, and develop reliable surveillance systems that meet sensitivity and specificity requirements for the endgame of STH elimination. However, the considerable complexities often associated with STH-transmission models underpin the need for specifying a large number of parameters and inputs, which are often available with considerable degree of uncertainty. Additionally, the model may behave counter-intuitive especially when there are non-linearities in multiple input-output relationships. In this study, we performed a global sensitivity analysis (GSA), based on a variance decomposition method: extended Fourier Amplitude Sensitivity Test (eFAST), to a recently developed STH-transmission model in Kenya (an STH endemic country) to; (1) robustly compute sensitivity index (SI) for each parameter, (2) rank the parameters in order of their importance (from most to least influential), and (3) quantify the influence of each parameter, singly and cumulatively, on the model output. The sensitivity analysis (SA) results demonstrated that the model outcome (STH worm burden elimination in the human host) was significantly sensitive to some key parameter groupings: combined effect of improved water source and sanitation (ϕ), rounds of treatment offered (τ), efficacy of the drug used during treatment (h), proportion of the adult population treated (g_a: akin to community-wide treatment), mortality rate of the mature worms in the human host (μ), and the strength of the -dependence of worm egg production (γ). For STH control programmes to effectively reach the endgame (STH elimination in the entire community), these key parameter groupings need to be targeted since together they contribute to a strategic public health intervention.

Risk factors associated with failing pre-transmission assessment surveys (pre-TAS) in lymphatic filariasis elimination programs: Results of a multi-country analysis

Achieving elimination of lymphatic filariasis (LF) as a public health problem requires a minimum of five effective rounds of mass drug administration (MDA) and demonstrating low prevalence in subsequent assessments. The first assessments recommended by the World Health Organization (WHO) are sentinel and spot-check sites-referred to as pre-transmission assessment surveys (pre-TAS)-in each implementation unit after MDA. If pre-TAS shows that prevalence in each site has been lowered to less than 1% microfilaremia or less than 2% antigenemia, the implementation unit conducts a TAS to determine whether MDA can be stopped. Failure to pass pre-TAS means that further rounds of MDA are required. This study aims to understand factors influencing pre-TAS results using existing programmatic data from 554 implementation units, of which 74 (13%) failed, in 13 countries. Secondary data analysis was completed using existing data from Bangladesh, Benin, Burkina Faso, Cameroon, Ghana, Haiti, Indonesia, Mali, Nepal, Niger, Sierra Leone, Tanzania, and Uganda. Additional covariate data were obtained from spatial raster data sets. Bivariate analysis and multilinear regression were performed to establish potential relationships between variables and the pre-TAS result. Higher baseline prevalence and lower elevation were significant in the regression model. Variables statistically significantly associated with failure (p-value ≤0.05) in the bivariate analyses included baseline prevalence at or above 5% or 10%, use of Filariasis Test Strips (FTS), primary vector of Culex, treatment with diethylcarbamazine-albendazole, higher elevation, higher population density, higher enhanced vegetation index (EVI), higher annual rainfall, and 6 or more rounds of MDA. This paper reports for the first time factors associated with pre-TAS results from a multi-country analysis. This information can help countries more effectively forecast program activities, such as the potential need for more rounds of MDA, and prioritize resources to ensure adequate coverage of all persons in areas at highest risk of failing pre-TAS.

A geostatistical framework for combining spatially referenced disease prevalence data from multiple diagnostics

Multiple diagnostic tests are often used due to limited resources or because they provide complementary information on the epidemiology of a disease under investigation. Existing statistical methods to combine prevalence data from multiple diagnostics ignore the potential overdispersion induced by the spatial correlations in the data. To address this issue, we develop a geostatistical framework that allows for joint modelling of data from multiple diagnostics by considering two main classes of inferential problems: (a) to predict prevalence for a gold-standard diagnostic using low-cost and potentially biased alternative tests; (b) to carry out joint prediction of prevalence from multiple tests. We apply the proposed framework to two case studies: mapping Loa loa prevalence in Central and West Africa, using miscroscopy, and a questionnaire-based test called RAPLOA; mapping Plasmodium falciparum malaria prevalence in the highlands of Western Kenya using polymerase chain reaction and a rapid diagnostic test. We also develop a Monte Carlo procedure based on the variogram in order to identify parsimonious geostatistical models that are compatible with the data. Our study highlights (a) the importance of accounting for diagnostic-specific residual spatial variation and (b) the benefits accrued from joint geostatistical modelling so as to deliver more reliable and precise inferences on disease prevalence.

Mapping the baseline prevalence of lymphatic filariasis across Nigeria

Introduction

The baseline endemicity profile of lymphatic filariasis (LF) is a key benchmark for planning control programmes, monitoring their impact on transmission and assessing the feasibility of achieving elimination. Presented in this work is the modelled serological and parasitological prevalence of LF prior to the scale-up of mass drug administration (MDA) in Nigeria using a machine learning based approach.

Methods

LF prevalence data generated by the Nigeria Lymphatic Filariasis Control Programme during country-wide mapping surveys conducted between 2000 and 2013 were used to build the models. The dataset comprised of 1103 community-level surveys based on the detection of filarial antigenemia using rapid immunochromatographic card tests (ICT) and 184 prevalence surveys testing for the presence of microfilaria (Mf) in blood. Using a suite of climate and environmental continuous gridded variables and compiled site-level prevalence data, a quantile regression forest (QRF) model was fitted for both antigenemia and microfilaraemia LF prevalence. Model predictions were projected across a continuous 5 × 5 km gridded map of Nigeria. The number of individuals potentially infected by LF prior to MDA interventions was subsequently estimated.

Results

Maps presented predict a heterogeneous distribution of LF antigenemia and microfilaraemia in Nigeria. The North-Central, North-West, and South-East regions displayed the highest predicted LF seroprevalence, whereas predicted Mf prevalence was highest in the southern regions. Overall, 8.7 million and 3.3 million infections were predicted for ICT and Mf, respectively.

Conclusions

QRF is a machine learning-based algorithm capable of handling high-dimensional data and fitting complex relationships between response and predictor variables. Our models provide a benchmark through which the progress of ongoing LF control efforts can be monitored.

The roadmap towards elimination of lymphatic filariasis by 2030: insights from quantitative and mathematical modelling

The Global Programme to Eliminate Lymphatic Filariasis was launched in 2000 to eliminate lymphatic filariasis (LF) as a public health problem by 1) interrupting transmission through mass drug administration (MDA) and 2) offering basic care to those suffering from lymphoedema or hydrocele due to the infection. Although impressive progress has been made, the initial target year of 2020 will not be met everywhere. The World Health Organization recently proposed 2030 as the new target year for elimination of lymphatic filariasis (LF) as a public health problem. In this letter, LF modelers of the Neglected Tropical Diseases (NTDs) Modelling Consortium reflect on the proposed targets for 2030 from a quantitative perspective. While elimination as a public health problem seems technically and operationally feasible, it is uncertain whether this will eventually also lead to complete elimination of transmission. The risk of resurgence needs to be mitigated by strong surveillance after stopping interventions and sometimes perhaps additional interventions.

Combining different diagnostic studies of lymphatic filariasis for risk mapping in Papua New Guinea: a predictive model from microfilaraemia and antigenaemia prevalence surveys

Background

The Global Programme to Eliminate Lymphatic Filariasis has encouraged countries to follow a set of guidelines to help them assess the need for mass drug administration and evaluate its progress. Papua New Guinea (PNG) is one of the highest priority countries in the Western Pacific for lymphatic filariasis and the site of extensive research on lymphatic filariasis and surveys of its prevalence. However, different diagnostic tests have been used and thresholds for each test are unclear.

Methods

We reviewed the prevalence of lymphatic filariasis reported in 295 surveys conducted in PNG between 1990 and 2014, of which 65 used more than one test. Results from different diagnostics were standardised using a set of criteria that included a model to predict antigen prevalence from microfilariae prevalence. We mapped the point location of each of these surveys and categorised their standardised prevalence estimates.

Results

Several predictive models were produced and investigated, including the effect of any mass drug administration and number of rounds prior to the surveys. One model was chosen based on goodness of fit parameters and used to predict antigen prevalence for surveys that tested only for microfilariae. Standardised prevalence values show that 72% of all surveys reported a prevalence above 0.05. High prevalence was situated on the coastal north, south and island regions, while the central highland area of Papua New Guinea shows low levels of prevalence.

Conclusions

Our study is the first to provide an explicit predictive relationship between the prevalence values based on empirical results from antigen and microfilaria tests, taking into account the occurrence of mass drug administration. This is a crucial step to combine studies to develop risk maps of lymphatic filariasis for programme planning and evaluation, as shown in the case of Papua New Guinea.

Electronic supplementary material

The online version of this article (10.1186/s41182-018-0123-8) contains supplementary material, which is available to authorized users.

Substantiating freedom from parasitic infection by combining transmission model predictions with disease surveys

Stopping interventions is a critical decision for parasite elimination programmes. Quantifying the probability that elimination has occurred due to interventions can be facilitated by combining infection status information from parasitological surveys with extinction thresholds predicted by parasite transmission models. Here we demonstrate how the integrated use of these two pieces of information derived from infection monitoring data can be used to develop an analytic framework for guiding the making of defensible decisions to stop interventions. We present a computational tool to perform these probability calculations and demonstrate its practical utility for supporting intervention cessation decisions by applying the framework to infection data from programmes aiming to eliminate onchocerciasis and lymphatic filariasis in Uganda and Nigeria, respectively. We highlight a possible method for validating the results in the field, and discuss further refinements and extensions required to deploy this predictive tool for guiding decision making by programme managers.

The decision when to stop an intervention is a critical component of parasite elimination programmes, but reliance on surveillance data alone can be inaccurate. Here, Michael et al. combine parasite transmission model predictions with disease survey data to more reliably determine when interventions can be stopped.

Understanding the relationship between egg- and antigen-based diagnostics of Schistosoma mansoni infection pre- and post-treatment in Uganda

BACKGROUND

Schistosomiasis is a major socio-economic and public health problem in many sub-Saharan African countries. After large mass drug administration (MDA) campaigns, prevalence of infection rapidly returns to pre-treatment levels. The traditional egg-based diagnostic for schistosome infections, Kato-Katz, is being substituted in many settings by circulating antigen recognition-based diagnostics, usually the point-of-care circulating cathodic antigen test (CCA). The relationship between these diagnostics is poorly understood, particularly after treatment in both drug-efficacy studies and routine monitoring.

RESULTS

We created a model of schistosome infections to better understand and quantify the relationship between these two egg- and adult worm antigen-based diagnostics. We focused particularly on the interpretation of "trace" results after CCA testing. Our analyses suggest that CCA is generally a better predictor of prevalence, particularly after treatment, and that trace CCA results are typically associated with truly infected individuals.

CONCLUSIONS

Even though prevalence rises to pre-treatment levels only six months after MDAs, our model suggests that the average intensity of infection is much lower, and is probably in part due to a small burden of surviving juveniles from when the treatment occurred. This work helps to better understand CCA diagnostics and the interpretation of post-treatment prevalence estimations.