Quantitative evaluation of the strategy to eliminate human African trypanosomiasis in the Democratic Republic of Congo

Modelling timelines to elimination of sleeping sickness in the Democratic Republic of Congo, accounting for possible cryptic human and animal transmission

BACKGROUND

Sleeping sickness (gambiense human African trypanosomiasis, gHAT) is a vector-borne disease targeted for global elimination of transmission (EoT) by 2030. There are, however, unknowns that have the potential to hinder the achievement and measurement of this goal. These include asymptomatic gHAT infections (inclusive of the potential to self-cure or harbour skin-only infections) and whether gHAT infection in animals can contribute to the transmission cycle in humans.

METHODS

Using modelling, we explore how cryptic (undetected) transmission impacts the monitoring of progress towards and the achievement of the EoT goal. We have developed gHAT models that include either asymptomatic or animal transmission, and compare these to a baseline gHAT model without either of these transmission routes, to explore the potential role of cryptic infections on the EoT goal. Each model was independently calibrated to five different health zones in the Democratic Republic of the Congo (DRC) using available historical human case data for 2000-2020 (obtained from the World Health Organization's HAT Atlas). We applied a novel Bayesian sequential updating approach for the asymptomatic model to enable us to combine statistical information about this type of transmission from each health zone.

RESULTS

Our results suggest that, when matched to past case data, we estimated similar numbers of new human infections between model variants, although human infections were slightly higher in the models with cryptic infections. We simulated the continuation of screen-confirm-and-treat interventions, and found that forward projections from the animal and asymptomatic transmission models produced lower probabilities of EoT than the baseline model; however, cryptic infections did not prevent EoT from being achieved eventually under this approach.

CONCLUSIONS

This study is the first to simulate an (as-yet-to-be available) screen-and-treat strategy and found that removing a parasitological confirmation step was predicted to have a more noticeable benefit to transmission reduction under the asymptomatic model compared with the others. Our simulations suggest vector control could greatly impact all transmission routes in all models, although this resource-intensive intervention should be carefully prioritised.

The Hidden Hand of Asymptomatic Infection Hinders Control of Neglected Tropical Diseases: A Modeling Analysis

BACKGROUND

Neglected tropical diseases are responsible for considerable morbidity and mortality in low-income populations. International efforts have reduced their global burden, but transmission is persistent and case-finding-based interventions rarely target asymptomatic individuals.

METHODS

We develop a generic mathematical modeling framework for analyzing the dynamics of visceral leishmaniasis in the Indian sub-continent (VL), gambiense sleeping sickness (gHAT), and Chagas disease and use it to assess the possible contribution of asymptomatics who later develop disease (pre-symptomatics) and those who do not (non-symptomatics) to the maintenance of infection. Plausible interventions, including active screening, vector control, and reduced time to detection, are simulated for the three diseases.

RESULTS

We found that the high asymptomatic contribution to transmission for Chagas and gHAT and the apparently high basic reproductive number of VL may undermine long-term control. However, the ability to treat some asymptomatics for Chagas and gHAT should make them more controllable, albeit over relatively long time periods due to the slow dynamics of these diseases. For VL, the toxicity of available therapeutics means the asymptomatic population cannot currently be treated, but combining treatment of symptomatics and vector control could yield a quick reduction in transmission.

CONCLUSIONS

Despite the uncertainty in natural history, it appears there is already a relatively good toolbox of interventions to eliminate gHAT, and it is likely that Chagas will need improvements to diagnostics and their use to better target pre-symptomatics. The situation for VL is less clear, and model predictions could be improved by additional empirical data. However, interventions may have to improve to successfully eliminate this disease.

Comparison of stochastic and deterministic models for gambiense sleeping sickness at different spatial scales: A health area analysis in the DRC

The intensification of intervention activities against the fatal vector-borne disease gambiense human African trypanosomiasis (gHAT, sleeping sickness) in the last two decades has led to a large decline in the number of annually reported cases. However, while we move closer to achieving the ambitious target of elimination of transmission (EoT) to humans, pockets of infection remain, and it becomes increasingly important to quantitatively assess if different regions are on track for elimination, and where intervention efforts should be focused. We present a previously developed stochastic mathematical model for gHAT in the Democratic Republic of Congo (DRC) and show that this same formulation is able to capture the dynamics of gHAT observed at the health area level (approximately 10,000 people). This analysis was the first time any stochastic gHAT model has been fitted directly to case data and allows us to better quantify the uncertainty in our results. The analysis focuses on utilising a particle filter Markov chain Monte Carlo (MCMC) methodology to fit the model to the data from 16 health areas of Mosango health zone in Kwilu province as a case study. The spatial heterogeneity in cases is reflected in modelling results, where we predict that under the current intervention strategies, the health area of Kinzamba II, which has approximately one third of the health zone's cases, will have the latest expected year for EoT. We find that fitting the analogous deterministic version of the gHAT model using MCMC has substantially faster computation times than fitting the stochastic model using pMCMC, but produces virtually indistinguishable posterior parameterisation. This suggests that expanding health area fitting, to cover more of the DRC, should be done with deterministic fits for efficiency, but with stochastic projections used to capture both the parameter and stochastic variation in case reporting and elimination year estimations.

How correlations between treatment access and surveillance inclusion impact neglected tropical disease monitoring and evaluation-A simulated study

Neglected tropical diseases (NTDs) largely impact marginalised communities living in tropical and subtropical regions. Mass drug administration is the leading intervention method for five NTDs; however, it is known that there is lack of access to treatment for some populations and demographic groups. It is also likely that those individuals without access to treatment are excluded from surveillance. It is important to consider the impacts of this on the overall success, and monitoring and evaluation (M&E) of intervention programmes. We use a detailed individual-based model of the infection dynamics of lymphatic filariasis to investigate the impact of excluded, untreated, and therefore unobserved groups on the true versus observed infection dynamics and subsequent intervention success. We simulate surveillance in four groups-the whole population eligible to receive treatment, the whole eligible population with access to treatment, the TAS focus of six- and seven-year-olds, and finally in >20-year-olds. We show that the surveillance group under observation has a significant impact on perceived dynamics. Exclusion to treatment and surveillance negatively impacts the probability of reaching public health goals, though in populations that do reach these goals there are no signals to indicate excluded groups. Increasingly restricted surveillance groups over-estimate the efficacy of MDA. The presence of non-treated groups cannot be inferred when surveillance is only occurring in the group receiving treatment.

Optimal Interruption of P. vivax Malaria Transmission Using Mass Drug Administration

Plasmodium vivax is the most geographically widespread malaria-causing parasite resulting in significant associated global morbidity and mortality. One of the factors driving this widespread phenomenon is the ability of the parasites to remain dormant in the liver. Known as 'hypnozoites', they reside in the liver following an initial exposure, before activating later to cause further infections, referred to as 'relapses'. As around 79-96% of infections are attributed to relapses from activating hypnozoites, we expect it will be highly impactful to apply treatment to target the hypnozoite reservoir (i.e. the collection of dormant parasites) to eliminate P. vivax. Treatment with radical cure, for example tafenoquine or primaquine, to target the hypnozoite reservoir is a potential tool to control and/or eliminate P. vivax. We have developed a deterministic multiscale mathematical model as a system of integro-differential equations that captures the complex dynamics of P. vivax hypnozoites and the effect of hypnozoite relapse on disease transmission. Here, we use our multiscale model to study the anticipated effect of radical cure treatment administered via a mass drug administration (MDA) program. We implement multiple rounds of MDA with a fixed interval between rounds, starting from different steady-state disease prevalences. We then construct an optimisation model with three different objective functions motivated on a public health basis to obtain the optimal MDA interval. We also incorporate mosquito seasonality in our model to study its effect on the optimal treatment regime. We find that the effect of MDA interventions is temporary and depends on the pre-intervention disease prevalence (and choice of model parameters) as well as the number of MDA rounds under consideration. The optimal interval between MDA rounds also depends on the objective (combinations of expected intervention outcomes). We find radical cure alone may not be enough to lead to P. vivax elimination under our mathematical model (and choice of model parameters) since the prevalence of infection eventually returns to pre-MDA levels.

Does a One Health approach to human African trypanosomiasis control hasten elimination? A stochastic compartmental modeling approach

BACKGROUND

. In response to large strides in the control of human African trypanosomiasis (HAT), in the early 2000s the WHO set targets for elimination of both the gambiense (gHAT) and rhodesiense (rHAT) forms as a public health (EPHP) problem by 2020, and elimination of gHAT transmisson (EOT) by 2030. While global EPHP targets have been met, and EOT appears within reach, current control strategies may fail to achieve gHAT EOT in the presence of animal reservoirs, the role of which is currently uncertain. Furthermore, rHAT is not targeted for EOT due to the known importance of animal reservoirs for this form.

METHODS

. To evaluate the utility of a One Health approach to gHAT and rHAT EOT, we built and parameterized a compartmental stochastic model, using the Institute for Disease Modeling's Compartmental Modeling Software, to six HAT epidemics: the national rHAT epidemics in Uganda and Malawi, the national gHAT epidemics in Uganda and South Sudan, and two separate gHAT epidemics in Democratic Republic of Congo distinguished by dominant vector species. In rHAT foci the reservoir animal sub-model was stratified on four species groups, while in gHAT foci domestic swine were assumed to be the only competent reservoir. The modeled time horizon was 2005-2045, with calibration performed using HAT surveillance data and Optuna. Interventions included insecticide and trypanocide treatment of domestic animal reservoirs at varying coverage levels.

RESULTS

. Validation against HAT surveillance data indicates favorable performance overall, with the possible exception of DRC. EOT was not observed in any modeled scenarios for rHAT, however insecticide treatment consistently performed better than trypanocide treatment in terms of rHAT control. EOT was not observed for gHAT at 0% coverage of domestic reservoirs with trypanocides or insecticides, but was observed by 2030 in all test scenarios; again, insecticides demonstrated superior performance to trypanocides.

CONCLUSIONS

EOT likely cannot be achieved for rHAT without control of wildlife reservoirs, however insecticide treatment of domestic animals holds promise for improved control. In the presence of domestic animal reservoirs, gHAT EOT may not be achieved under current control strategies.

A modelling assessment of short- and medium-term risks of programme interruptions for gambiense human African trypanosomiasis in the DRC

Gambiense human African trypanosomiasis (gHAT) is a deadly vector-borne, neglected tropical disease found in West and Central Africa targeted for elimination of transmission (EoT) by 2030. The recent pandemic has illustrated how it can be important to quantify the impact that unplanned disruption to programme activities may have in achieving EoT. We used a previously developed model of gHAT fitted to data from the Democratic Republic of the Congo, the country with the highest global case burden, to explore how interruptions to intervention activities, due to e.g. COVID-19, Ebola or political instability, could impact progress towards EoT and gHAT burden. We simulated transmission and reporting dynamics in 38 regions within Kwilu, Mai Ndombe and Kwango provinces under six interruption scenarios lasting for nine or twenty-one months. Included in the interruption scenarios are the cessation of active screening in all scenarios and a reduction in passive detection rates and a delay or suspension of vector control deployments in some scenarios. Our results indicate that, even under the most extreme 21-month interruption scenario, EoT is not predicted to be delayed by more than one additional year compared to the length of the interruption. If existing vector control deployments continue, we predict no delay in achieving EoT even when both active and passive screening activities are interrupted. If passive screening remains as functional as in 2019, we expect a marginal negative impact on transmission, however this depends on the strength of passive screening in each health zone. We predict a pronounced increase in additional gHAT disease burden (morbidity and mortality) in many health zones if both active and passive screening were interrupted compared to the interruption of active screening alone. The ability to continue existing vector control during medical activity interruption is also predicted to avert a moderate proportion of disease burden.

Challenges of using modelling evidence in the visceral leishmaniasis elimination programme in India

As India comes closer to the elimination of visceral leishmaniasis (VL) as a public health problem, surveillance efforts and elimination targets must be continuously revised and strengthened. Mathematical modelling is a compelling research discipline for informing policy and programme design in its capacity to project incidence across space and time, the likelihood of achieving benchmarks, and the impact of different interventions. To gauge the extent to which modelling informs policy in India, this qualitative analysis explores how and whether policy makers understand, value, and reference recently produced VL modelling research. Sixteen semi-structured interviews were carried out with both users- and producers- of VL modelling research, guided by a knowledge utilisation framework grounded in knowledge translation theory. Participants reported that barriers to knowledge utilisation include 1) scepticism that models accurately reflect transmission dynamics, 2) failure of modellers to apply their analyses to specific programme operations, and 3) lack of accountability in the process of translating knowledge to policy. Political trust and support are needed to translate knowledge into programme activities, and employment of a communication intermediary may be a necessary approach to improve this process.

Modelling to infer the role of animals in gambiense human African trypanosomiasis transmission and elimination in the DRC

Gambiense human African trypanosomiasis (gHAT) has been targeted for elimination of transmission (EoT) to humans by 2030. Whilst this ambitious goal is rapidly approaching, there remain fundamental questions about the presence of non-human animal transmission cycles and their potential role in slowing progress towards, or even preventing, EoT. In this study we focus on the country with the most gHAT disease burden, the Democratic Republic of Congo (DRC), and use mathematical modelling to assess whether animals may contribute to transmission in specific regions, and if so, how their presence could impact the likelihood and timing of EoT. By fitting two model variants-one with, and one without animal transmission-to the human case data from 2000-2016 we estimate model parameters for 158 endemic health zones of the DRC. We evaluate the statistical support for each model variant in each health zone and infer the contribution of animals to overall transmission and how this could impact predicted time to EoT. We conclude that there are 24/158 health zones where there is substantial to decisive statistical support for some animal transmission. However-even in these regions-we estimate that animals would be extremely unlikely to maintain transmission on their own. Animal transmission could hamper progress towards EoT in some settings, with projections under continuing interventions indicating that the number of health zones expected to achieve EoT by 2030 reduces from 68/158 to 61/158 if animal transmission is included in the model. With supplementary vector control (at a modest 60% tsetse reduction) added to medical screening and treatment interventions, the predicted number of health zones meeting the goal increases to 147/158 for the model including animal transmission. This is due to the impact of vector reduction on transmission to and from all hosts.

Identifying regions for enhanced control of gambiense sleeping sickness in the Democratic Republic of Congo

Gambiense human African trypanosomiasis (sleeping sickness, gHAT) is a disease targeted for elimination of transmission by 2030. While annual new cases are at a historical minimum, the likelihood of achieving the target is unknown. We utilised modelling to study the impacts of four strategies using currently available interventions, including active and passive screening and vector control, on disease burden and transmission across 168 endemic health zones in the Democratic Republic of the Congo. Median projected years of elimination of transmission show only 98 health zones are on track despite significant reduction in disease burden under medical-only strategies (64 health zones if > 90% certainty required). Blanket coverage with vector control is impractical, but is predicted to reach the target in all heath zones. Utilising projected disease burden under the uniform medical-only strategy, we provide a priority list of health zones for consideration for supplementary vector control alongside medical interventions.

Cost-effectiveness of sleeping sickness elimination campaigns in five settings of the Democratic Republic of Congo

Gambiense human African trypanosomiasis (gHAT) is marked for elimination of transmission by 2030, but the disease persists in several low-income countries. We couple transmission and health outcomes models to examine the cost-effectiveness of four gHAT elimination strategies in five settings - spanning low- to high-risk - of the Democratic Republic of Congo. Alongside passive screening in fixed health facilities, the strategies include active screening at average or intensified coverage levels, alone or with vector control with a scale-back algorithm when no cases are reported for three consecutive years. In high or moderate-risk settings, costs of gHAT strategies are primarily driven by active screening and, if used, vector control. Due to the cessation of active screening and vector control, most investments (75-80%) are made by 2030 and vector control might be cost-saving while ensuring elimination of transmission. In low-risk settings, costs are driven by passive screening, and minimum-cost strategies consisting of active screening and passive screening lead to elimination of transmission by 2030 with high probability.

How modelling can help steer the course set by the World Health Organization 2021-2030 roadmap on neglected tropical diseases

The World Health Organization recently launched its 2021-2030 roadmap, Ending the Neglect to Attain the Sustainable Development Goals , an updated call to arms to end the suffering caused by neglected tropical diseases. Modelling and quantitative analyses played a significant role in forming these latest goals. In this collection, we discuss the insights, the resulting recommendations and identified challenges of public health modelling for 13 of the target diseases: Chagas disease, dengue, gambiense human African trypanosomiasis (gHAT), lymphatic filariasis (LF), onchocerciasis, rabies, scabies, schistosomiasis, soil-transmitted helminthiases (STH), Taenia solium taeniasis/ cysticercosis, trachoma, visceral leishmaniasis (VL) and yaws. This piece reflects the three cross-cutting themes identified across the collection, regarding the contribution that modelling can make to timelines, programme design, drug development and clinical trials.

Update of transmission modelling and projections of gambiense human African trypanosomiasis in the Mandoul focus, Chad

BACKGROUND

In recent years, a programme of vector control, screening and treatment of gambiense human African trypanosomiasis (gHAT) infections led to a rapid decline in cases in the Mandoul focus of Chad. To represent the biology of transmission between humans and tsetse, we previously developed a mechanistic transmission model, fitted to data between 2000 and 2013 which suggested that transmission was interrupted by 2015. The present study outlines refinements to the model to: (1) Assess whether elimination of transmission has already been achieved despite low-level case reporting; (2) quantify the role of intensified interventions in transmission reduction; and (3) predict the trajectory of gHAT in Mandoul for the next decade under different strategies.

METHOD

Our previous gHAT transmission model for Mandoul was updated using human case data (2000-2019) and a series of model refinements. These include how diagnostic specificity is incorporated into the model and improvements to the fitting method (increased variance in observed case reporting and how underreporting and improvements to passive screening are captured). A side-by-side comparison of fitting to case data was performed between the models.

RESULTS

We estimated that passive detection rates have increased due to improvements in diagnostic availability in fixed health facilities since 2015, by 2.1-fold for stage 1 detection, and 1.5-fold for stage 2. We find that whilst the diagnostic algorithm for active screening is estimated to be highly specific (95% credible interval (CI) 99.9-100%, Specificity = 99.9%), the high screening and low infection levels mean that some recently reported cases with no parasitological confirmation might be false positives. We also find that the focus-wide tsetse reduction estimated through model fitting (95% CI 96.1-99.6%, Reduction = 99.1%) is comparable to the reduction previously measured by the decline in tsetse catches from monitoring traps. In line with previous results, the model suggests that transmission was interrupted in 2015 due to intensified interventions.

CONCLUSIONS

We recommend that additional confirmatory testing is performed in Mandoul to ensure the endgame can be carefully monitored. More specific measurement of cases, would better inform when it is safe to stop active screening and vector control, provided there is a strong passive surveillance system in place.

Spatial analysis of G.f.fuscipes abundance in Uganda using Poisson and Zero-Inflated Poisson regression models

BACKGROUND

Tsetse flies are the major vectors of human trypanosomiasis of the form Trypanosoma brucei rhodesiense and T.b.gambiense. They are widely spread across the sub-Saharan Africa and rendering a lot of challenges to both human and animal health. This stresses effective agricultural production and productivity in Africa. Delimiting the extent and magnitude of tsetse coverage has been a challenge over decades due to limited resources and unsatisfactory technology. In a bid to overcome these limitations, this study attempted to explore modelling skills that can be applied to spatially estimate tsetse abundance in the country using limited tsetse data and a set of remote-sensed environmental variables.

METHODOLOGY

Entomological data for the period 2008-2018 as used in the model were obtained from various sources and systematically assembled using a structured protocol. Data harmonisation for the purposes of responsiveness and matching was carried out. The key tool for tsetse trapping was itemized as pyramidal trap in many instances and biconical trap in others. Based on the spatially explicit assembled data, we ran two regression models; standard Poisson and Zero-Inflated Poisson (ZIP), to explore the associations between tsetse abundance in Uganda and several environmental and climatic covariates. The covariate data were constituted largely by satellite sensor data in form of meteorological and vegetation surrogates in association with elevation and land cover data. We finally used the Zero-Inflated Poisson (ZIP) regression model to predict tsetse abundance due to its superiority over the standard Poisson after model fitting and testing using the Vuong Non-Nested statistic.

RESULTS

A total of 1,187 tsetse sampling points were identified and considered as representative for the country. The model results indicated the significance and level of responsiveness of each covariate in influencing tsetse abundance across the study area. Woodland vegetation, elevation, temperature, rainfall, and dry season normalised difference vegetation index (NDVI) were important in determining tsetse abundance and spatial distribution at varied scales. The resultant prediction map shows scaled tsetse abundance with estimated fitted numbers ranging from 0 to 59 flies per trap per day (FTD). Tsetse abundance was found to be largest at low elevations, in areas of high vegetative activity, in game parks, forests and shrubs during the dry season. There was very limited responsiveness of selected predictors to tsetse abundance during the wet season, matching the known fact that tsetse disperse most significantly during wet season.

CONCLUSIONS

A methodology was advanced to enable compilation of entomological data for 10 years, which supported the generation of tsetse abundance maps for Uganda through modelling. Our findings indicate the spatial distribution of the G. f. fuscipes as; low 0-5 FTD (48%), medium 5.1-35 FTD (18%) and high 35.1-60 FTD (34%) grounded on seasonality. This approach, amidst entomological data shortages due to limited resources and absence of expertise, can be adopted to enable mapping of the vector to provide better decision support towards designing and implementing targeted tsetse and tsetse-transmitted African trypanosomiasis control strategies.

Modelling the impact of fexinidazole use on human African trypanosomiasis (HAT) transmission in the Democratic Republic of the Congo

Gambiense human African trypanosomiasis is a deadly disease that has been declining in incidence since the start of the Century, primarily due to increased screening, diagnosis and treatment of infected people. The main treatment regimen currently in use requires a lumbar puncture as part of the diagnostic process to determine disease stage and hospital admission for drug administration. Fexinidazole is a new oral treatment for stage 1 and non-severe stage 2 human African trypanosomiasis. The World Health Organization has recently incorporated fexinidazole into its treatment guidelines for human African trypanosomiasis. The treatment does not require hospital admission or a lumbar puncture for all patients, which is likely to ease access for patients; however, it does require concomitant food intake, which is likely to reduce adherence. Here, we use a mathematical model calibrated to case and screening data from Mushie territory, in the Democratic Republic of the Congo, to explore the potential negative impact of poor compliance to an oral treatment, and potential gains to be made from increases in the rate at which patients seek treatment. We find that reductions in compliance in treatment of stage 1 cases are projected to result in the largest increase in further transmission of the disease, with failing to cure stage 2 cases also posing a smaller concern. Reductions in compliance may be offset by increases in the rate at which cases are passively detected. Efforts should therefore be made to ensure good adherence for stage 1 patients to treatment with fexinidazole and to improve access to care.

Sleeping sickness is a parasitic disease present in parts of Central and West Africa that is fatal if left untreated. Current case management requires unpleasant procedures such as a lumbar puncture and intravenous drug administration, but has high compliance rates as the treatment is given by hospital staff to patients. In this study, we explore the impact of a new oral treatment on compliance rates for treatment using a mathematical model fitted to data on sleeping sickness cases and screening activities. We also look at the possibility of patients being more likely to seek and access treatment since the new treatment can be used without a lumbar puncture if the patient does not display clinically severe symptoms. We find that reduced compliance, especially from patients suffering from the first less severe stage of the disease, will lead to more sleeping sickness cases and delay elimination, but increases in the number of patients seeking treatment will likely counter effects of reduced compliance.

Modelling gambiense human African trypanosomiasis infection in villages of the Democratic Republic of Congo using Kolmogorov forward equations

Stochastic methods for modelling disease dynamics enable the direct computation of the probability of elimination of transmission. For the low-prevalence disease of human African trypanosomiasis (gHAT), we develop a new mechanistic model for gHAT infection that determines the full probability distribution of the gHAT infection using Kolmogorov forward equations. The methodology allows the analytical investigation of the probabilities of gHAT elimination in the spatially connected villages of different prevalence health zones of the Democratic Republic of Congo, and captures the uncertainty using exact methods. Our method provides a more realistic approach to scaling the probability of elimination of infection between single villages and much larger regions, and provides results comparable to established models without the requirement of detailed infection structure. The novel flexibility allows the interventions in the model to be implemented specific to each village, and this introduces the framework to consider the possible future strategies of test-and-treat or direct treatment of individuals living in villages where cases have been found, using a new drug.

Modelling to explore the potential impact of asymptomatic human infections on transmission and dynamics of African sleeping sickness

Gambiense human African trypanosomiasis (gHAT, sleeping sickness) is one of several neglected tropical diseases (NTDs) where there is evidence of asymptomatic human infection but there is uncertainty of the role it plays in transmission and maintenance. To explore possible consequences of asymptomatic infections, particularly in the context of elimination of transmission—a goal set to be achieved by 2030—we propose a novel dynamic transmission model to account for the asymptomatic population. This extends an established framework, basing infection progression on a number of experimental and observation gHAT studies. Asymptomatic gHAT infections include those in people with blood-dwelling trypanosomes, but no discernible symptoms, or those with parasites only detectable in skin. Given current protocols, asymptomatic infection with blood parasites may be diagnosed and treated, based on observable parasitaemia, in contrast to many other diseases for which treatment (and/or diagnosis) may be based on symptomatic infection. We construct a model in which exposed people can either progress to either asymptomatic skin-only parasite infection, which would not be diagnosed through active screening algorithms, or blood-parasite infection, which is likely to be diagnosed if tested. We add extra parameters to the baseline model including different self-cure, recovery, transmission and detection rates for skin-only or blood infections. Performing sensitivity analysis suggests all the new parameters introduced in the asymptomatic model can impact the infection dynamics substantially. Among them, the proportion of exposures resulting in initial skin or blood infection appears the most influential parameter. For some plausible parameterisations, an initial fall in infection prevalence due to interventions could subsequently stagnate even under continued screening due to the formation of a new, lower endemic equilibrium. Excluding this scenario, our results still highlight the possibility for asymptomatic infection to slow down progress towards elimination of transmission. Location-specific model fitting will be needed to determine if and where this could pose a threat.

Gambiense African sleeping sickness is an infectious disease targeted for elimination of transmission by 2030. Despite this there is still some uncertainty how frequently some infected people who may not have symptoms could “self-cure” without ever having disease and whether some types of infections, such as infections only in the skin, but not the blood, could still contribute to transmission, yet go undiagnosed. To explore how problematic these asymptomatic infections could be in terms of the elimination goal, we use a mathematical model which quantitatively describes changes to infection and transmission over time and includes these different types of infection. We use results of published experimental or field studies as inputs for the model parameters governing asymptomatic infections. We examined the impact of asymptomatic infections when control interventions are put in place. Compared to a baseline model with no asymptomatics, including asymptomatic infection using plausible biological parameters can have a profound impact on transmission and slow progress towards elimination. In some instances it could be possible that even after initial decline in sleeping sickness cases, progress could stagnate without reaching the elimination goal at all, however location-specific modelling will be needed to determine if and where this could pose a threat.

A gene expression panel for estimating age in males and females of the sleeping sickness vector Glossina morsitans

Many vector-borne diseases are controlled by methods that kill the insect vectors responsible for disease transmission. Recording the age structure of vector populations provides information on mortality rates and vectorial capacity, and should form part of the detailed monitoring that occurs in the wake of control programmes, yet tools for obtaining estimates of individual age remain limited. We investigate the potential of using markers of gene expression to predict age in tsetse flies, which are the vectors of deadly and economically damaging African trypanosomiases. We use RNAseq to identify candidate expression markers, and test these markers using qPCR in laboratory-reared Glossina morsitans morsitans of known age. Measuring the expression of six genes was sufficient to obtain a prediction of age with root mean squared error of less than 8 days, while just two genes were sufficient to classify flies into age categories of ≤15 and >15 days old. Further testing of these markers in field-caught samples and in other species will determine the accuracy of these markers in the field.

Estimating the impact of Tiny Targets in reducing the incidence of Gambian sleeping sickness in the North-west Uganda focus

BACKGROUND

Riverine species of tsetse (Glossina) transmit Trypanosoma brucei gambiense, which causes Gambian human African trypanosomiasis (gHAT), a neglected tropical disease. Uganda aims to eliminate gHAT as a public health problem through detection and treatment of human cases and vector control. The latter is being achieved through the deployment of 'Tiny Targets', insecticide-impregnated panels of material which attract and kill tsetse. We analysed the spatial and temporal distribution of cases of gHAT in Uganda during the period 2010-2019 to assess whether Tiny Targets have had an impact on disease incidence.

METHODS

To quantify the deployment of Tiny Targets, we mapped the rivers and their associated watersheds in the intervention area. We then categorised each of these on a scale of 0-3 according to whether Tiny Targets were absent (0), present only in neighbouring watersheds (1), present in the watersheds but not all neighbours (2), or present in the watershed and all neighbours (3). We overlaid all cases that were diagnosed between 2000 and 2020 and assessed whether the probability of finding cases in a watershed changed following the deployment of targets. We also estimated the number of cases averted through tsetse control.

RESULTS

We found that following the deployment of Tiny Targets in a watershed, there were fewer cases of HAT, with a sampled error probability of 0.007. We estimate that during the intervention period 2012-2019 we should have expected 48 cases (95% confidence intervals = 40-57) compared to the 36 cases observed. The results are robust to a range of sensitivity analyses.

CONCLUSIONS

Tiny Targets have reduced the incidence of gHAT by 25% in north-western Uganda.

How modelling can help steer the course set by the World Health Organization 2021-2030 roadmap on neglected tropical diseases

The World Health Organization recently launched its 2021-2030 roadmap, Ending the Neglect to Attain the Sustainable Development Goals , an updated call to arms to end the suffering caused by neglected tropical diseases. Modelling and quantitative analyses played a significant role in forming these latest goals. In this collection, we discuss the insights, the resulting recommendations and identified challenges of public health modelling for 13 of the target diseases: Chagas disease, dengue, gambiense human African trypanosomiasis (gHAT), lymphatic filariasis (LF), onchocerciasis, rabies, scabies, schistosomiasis, soil-transmitted helminthiases (STH), Taenia solium taeniasis/ cysticercosis, trachoma, visceral leishmaniasis (VL) and yaws. This piece reflects the three cross-cutting themes identified across the collection, regarding the contribution that modelling can make to timelines, programme design, drug development and clinical trials.

Modelling to Quantify the Likelihood that Local Elimination of Transmission has Occurred Using Routine Gambiense Human African Trypanosomiasis Surveillance Data

Background

The gambiense human African trypanosomiasis (gHAT) elimination programme in the Democratic Republic of Congo (DRC) routinely collects case data through passive surveillance and active screening, with several regions reporting no cases for several years, despite being endemic in the early 2000s.

Methods

We use mathematical models fitted to longitudinal data to estimate the probability that selected administrative regions have already achieved elimination of transmission (EOT) of gHAT. We examine the impact of active screening coverage on the certainty of model estimates for transmission and therefore the role of screening in the measurement of EOT.

Results

In 3 example health zones of Sud-Ubangi province, we find there is a moderate (>40%) probability that EOT has been achieved by 2018, based on 2000–2016 data. Budjala and Mbaya reported zero cases during 2017–18, and this further increases our respective estimates to 99.9% and 99.6% (model S) and to 87.3% and 92.1% (model W). Bominenge had recent case reporting, however, that if zero cases were found in 2021, it would substantially raise our certainty that EOT has been met there (99.0% for model S and 88.5% for model W); this could be higher with 50% coverage screening that year (99.1% for model S and 94.0% for model W).

Conclusions

We demonstrate how routine surveillance data coupled with mechanistic modeling can estimate the likelihood that EOT has already been achieved. Such quantitative assessment will become increasingly important for measuring local achievement of EOT as 2030 approaches.

Cost-effectiveness modelling to optimise active screening strategy for gambiense human African trypanosomiasis in endemic areas of the Democratic Republic of Congo

BACKGROUND

Gambiense human African trypanosomiasis (gHAT) has been brought under control recently with village-based active screening playing a major role in case reduction. In the approach to elimination, we investigate how to optimise active screening in villages in the Democratic Republic of Congo, such that the expenses of screening programmes can be efficiently allocated whilst continuing to avert morbidity and mortality.

METHODS

We implement a cost-effectiveness analysis using a stochastic gHAT infection model for a range of active screening strategies and, in conjunction with a cost model, we calculate the net monetary benefit (NMB) of each strategy. We focus on the high-endemicity health zone of Kwamouth in the Democratic Republic of Congo.

RESULTS

High-coverage active screening strategies, occurring approximately annually, attain the highest NMB. For realistic screening at 55% coverage, annual screening is cost-effective at very low willingness-to-pay thresholds (20.4 per disability adjusted life year (DALY) averted), only marginally higher than biennial screening (14.6 per DALY averted). We find that, for strategies stopping after 1, 2 or 3 years of zero case reporting, the expected cost-benefits are very similar.

CONCLUSIONS

We highlight the current recommended strategy-annual screening with three years of zero case reporting before stopping active screening-is likely cost-effective, in addition to providing valuable information on whether transmission has been interrupted.

Predicting the impact of COVID-19 interruptions on transmission of gambiense human African trypanosomiasis in two health zones of the Democratic Republic of Congo

Many control programmes against neglected tropical diseases have been interrupted due to the coronavirus disease 2019 (COVID-19) pandemic, including those that rely on active case finding. In this study we focus on gambiense human African trypanosomiasis (gHAT), where active screening was suspended in the Democratic Republic of Congo (DRC) due to the pandemic. We use two independent mathematical models to predict the impact of COVID-19 interruptions on transmission and reporting and achievement of the 2030 elimination of transmission (EOT) goal for gHAT in two moderate-risk regions of the DRC. We consider different interruption scenarios, including reduced passive surveillance in fixed health facilities, and whether this suspension lasts until the end of 2020 or 2021. Our models predict an increase in the number of new infections in the interruption period only if both active screening and passive surveillance were suspended, and with a slowed reduction—but no increase—if passive surveillance remains fully functional. In all scenarios, the EOT may be slightly pushed back if no mitigation, such as increased screening coverage, is put in place. However, we emphasise that the biggest challenge will remain in the higher-prevalence regions where EOT is already predicted to be behind schedule without interruptions unless interventions are bolstered.

Quantifying epidemiological drivers of gambiense human African Trypanosomiasis across the Democratic Republic of Congo

Gambiense human African trypanosomiasis (gHAT) is a virulent disease declining in burden but still endemic in West and Central Africa. Although it is targeted for elimination of transmission by 2030, there remain numerous questions about the drivers of infection and how these vary geographically. In this study we focus on the Democratic Republic of Congo (DRC), which accounted for 84% of the global case burden in 2016, to explore changes in transmission across the country and elucidate factors which may have contributed to the persistence of disease or success of interventions in different regions. We present a Bayesian fitting methodology, applied to 168 endemic health zones (∼100,000 population size), which allows for calibration of a mechanistic gHAT model to case data (from the World Health Organization HAT Atlas) in an adaptive and automated framework. It was found that the model needed to capture improvements in passive detection to match observed trends in the data within former Bandundu and Bas Congo provinces indicating these regions have substantially reduced time to detection. Health zones in these provinces generally had longer burn-in periods during fitting due to additional model parameters. Posterior probability distributions were found for a range of fitted parameters in each health zone; these included the basic reproduction number estimates for pre-1998 (R0) which was inferred to be between 1 and 1.14, in line with previous gHAT estimates, with higher median values typically in health zones with more case reporting in the 2000s. Previously, it was not clear whether a fall in active case finding in the period contributed to the declining case numbers. The modelling here accounts for variable screening and suggests that underlying transmission has also reduced greatly-on average 96% in former Equateur, 93% in former Bas Congo and 89% in former Bandundu-Equateur and Bandundu having had the highest case burdens in 2000. This analysis also sets out a framework to enable future predictions for the country.

Repurposing the orphan drug nitisinone to control the transmission of African trypanosomiasis

Tsetse transmit African trypanosomiasis, which is a disease fatal to both humans and animals. A vaccine to protect against this disease does not exist so transmission control relies on eliminating tsetse populations. Although neurotoxic insecticides are the gold standard for insect control, they negatively impact the environment and reduce populations of insect pollinator species. Here we present a promising, environment-friendly alternative to current insecticides that targets the insect tyrosine metabolism pathway. A bloodmeal contains high levels of tyrosine, which is toxic to haematophagous insects if it is not degraded and eliminated. RNA interference (RNAi) of either the first two enzymes in the tyrosine degradation pathway (tyrosine aminotransferase (TAT) and 4-hydroxyphenylpyruvate dioxygenase (HPPD)) was lethal to tsetse. Furthermore, nitisinone (NTBC), an FDA-approved tyrosine catabolism inhibitor, killed tsetse regardless if the drug was orally or topically applied. However, oral administration of NTBC to bumblebees did not affect their survival. Using a novel mathematical model, we show that NTBC could reduce the transmission of African trypanosomiasis in sub-Saharan Africa, thus accelerating current disease elimination programmes.

Estimating the distribution of time to extinction of infectious diseases in mean-field approaches

A key challenge for many infectious diseases is to predict the time to extinction under specific interventions. In general, this question requires the use of stochastic models which recognize the inherent individual-based, chance-driven nature of the dynamics; yet stochastic models are inherently computationally expensive, especially when parameter uncertainty also needs to be incorporated. Deterministic models are often used for prediction as they are more tractable; however, their inability to precisely reach zero infections makes forecasting extinction times problematic. Here, we study the extinction problem in deterministic models with the help of an effective ‘birth–death’ description of infection and recovery processes. We present a practical method to estimate the distribution, and therefore robust means and prediction intervals, of extinction times by calculating their different moments within the birth–death framework. We show that these predictions agree very well with the results of stochastic models by analysing the simplified susceptible–infected–susceptible (SIS) dynamics as well as studying an example of more complex and realistic dynamics accounting for the infection and control of African sleeping sickness (Trypanosoma brucei gambiense).

A pilot study demonstrating the identification of Trypanosoma brucei gambiense and T. b. rhodesiense in vectors using a multiplexed high-resolution melt qPCR

Human African Trypanosomiasis (HAT) is a potentially fatal parasitic infection caused by the trypanosome sub-species Trypanosoma brucei gambiense and T. b. rhodesiense transmitted by tsetse flies. Currently, global HAT case numbers are reaching less than 1 case per 10,000 people in many disease foci. As such, there is a need for simple screening tools and strategies to replace active screening of the human population which can be maintained post-elimination for Gambian HAT and long-term for Rhodesian HAT. Here, we describe the proof of principle application of a novel high-resolution melt assay for the xenomonitoring of Trypanosoma brucei gambiense and T. b. rhodesiense in tsetse. Both novel and previously described primers which target species-specific single copy genes were used as part of a multiplex qPCR. An additional primer set was included in the multiplex to determine if samples had sufficient genomic material for detecting genes present in low copy number. The assay was evaluated on 96 wild-caught tsetse previously identified to be positive for T. brucei s. l. of which two were known to be positive for T. b. rhodesiense. The assay was found to be highly specific with no cross-reactivity with non-target trypanosome species and the assay limit of detection was 104 tryps/mL. The qPCR successfully identified three T. b. rhodesiense positive flies, in agreement with the reference species-specific PCRs. This assay provides an alternative to running multiple PCRs when screening for pathogenic sub-species of T. brucei s. l. and produces results in less than 2 hours, avoiding gel electrophoresis and subjective analysis. This method could provide a component of a simple and efficient method of screening large numbers of tsetse flies in known HAT foci or in areas at risk of recrudescence or threatened by the changing distribution of both forms of HAT.

Development and implementation of a strategy for intensified screening for gambiense human African trypanosomiasis in Kongo Central province, DRC

Background

The Democratic Republic of the Congo (DRC) accounts for the majority of the reported gambiense human African trypanosomiasis (HAT) cases. Kongo Central province in the DRC reports a relatively low, yet steady number of cases, and forms a transboundary focus with Angola and the Republic of Congo. This paper describes an intervention aimed at reducing the case burden in Kongo Central by improving passive case detection, complemented with reactive screening.

Methodology/Principal findings

At the initiation of this programme in August 2015, 620 health facilities were identified and equipped with Rapid Diagnostic Tests (RDTs) for HAT screening. Of these, 603 (97%) reported use of RDTs, and 584 (94%) that continued to use RDTs to the last quarter of 2016 were used in the analysis going forward. Among all health facilities involved, 23 were equipped to confirm HAT by microscopy, and 4 of the latter were equipped to perform molecular testing with loop-mediated isothermal amplification (LAMP). Patients clinically suspected of HAT were tested with an RDT and those with a positive RDT result were referred to the nearest microscopy facility for confirmatory testing. If RDT positive patients were negative by microscopy, they were tested by LAMP, either on fresh blood or blood that was dried on filter paper and transported to a facility performing LAMP. This network of diagnostic facilities reduced the median distance for a patient to travel to a screening facility from 13.7km when the classical card agglutination test for trypanosomiasis (CATT) was used as a screening test in the past, to 3.4km. As a consequence, passive case detection was improved by between 30% and 130% compared to the period before. Furthermore, the proportion of HAT cases detected in early stage disease by passive screening increased from 27% to 64%.

Reactive screening took place in 20 villages where cases were reported by passive screening, and in 45 villages in the neighbourhood of these villages. Reactive screening was responsible for detection of 40% of cases, of which, 90% were in first stage of the disease.

Conclusions

This programme has demonstrated that it is possible to deploy passive screening for HAT at sub-country or country levels in the DRC, and this is made more effective when supplemented with reactive screening. Results and achievements showed an increase in the number of HAT cases detected, the majority of them in early disease, demonstrating that this strategy enables better population coverage and early detection of cases, which is critical in removing the HAT reservoir and interrupting transmission, and could contribute to HAT elimination in regions where it is implemented.

A number of diagnostic tests for HAT have recently been developed, to improve case detection. We report on the use of these technologies in a strategy to increase coverage and early detection of HAT cases in Kongo Central province of DRC.

All 620 health facilities in the focus were equipped with RDTs to test patients presenting with symptoms suggestive of HAT. Among these health facilities, 23 were upgraded to perform confirmatory testing, for a final diagnosis.

This strategy has reduced the distance a patient travels to a facility screening for HAT, from 13.7km to 3.4km. From August 2015 to December 2016, the proportion of HAT cases detected, adjusted annually, increased by between 30% and 130% compared to the previous two years, and 64% of them were in early stage disease, compared to 27% previously. This strategy has enabled better population coverage, and when supplemented with reactive screening, the identification of local outbreaks and early detection of most cases, which is critical in removing the HAT reservoir and interrupting transmission, thus contributing to elimination of the disease.

Impact of tiny targets on Glossina fuscipes quanzensis, the primary vector of human African trypanosomiasis in the Democratic Republic of the Congo

Over the past 20 years there has been a >95% reduction in the number of Gambian Human African trypanosomiasis (g-HAT) cases reported globally, largely as a result of large-scale active screening and treatment programmes. There are however still foci where the disease persists, particularly in parts of the Democratic Republic of the Congo (DRC). Additional control efforts such as tsetse control using Tiny Targets may therefore be required to achieve g-HAT elimination goals. The purpose of this study was to evaluate the impact of Tiny Targets within DRC. In 2015-2017, pre- and post-intervention tsetse abundance data were collected from 1,234 locations across three neighbouring Health Zones (Yasa Bonga, Mosango, Masi Manimba). Remotely sensed dry season data were combined with pre-intervention tsetse presence/absence data from 332 locations within a species distribution modelling framework to produce a habitat suitability map. The impact of Tiny Targets on the tsetse population was then evaluated by fitting a generalised linear mixed model to the relative fly abundance data collected from 889 post-intervention monitoring sites within Yasa Bonga, with habitat suitability, proximity to the intervention and intervention duration as covariates. Immediately following the introduction of the intervention, we observe a dramatic reduction in fly catches by > 85% (pre-intervention: 0.78 flies/trap/day, 95% CI 0.676-0.900; 3 month post-intervention: 0.11 flies/trap/day, 95% CI 0.070-0.153) which is sustained throughout the study period. Declines in catches were negatively associated with proximity to Tiny Targets, and while habitat suitability is positively associated with abundance its influence is reduced in the presence of the intervention. This study adds to the body of evidence demonstrating the impact of Tiny Targets on tsetse across a range of ecological settings, and further characterises the factors which modify its impact. The habitat suitability maps have the potential to guide the expansion of tsetse control activities in this area.

Assessing the effect of insecticide-treated cattle on tsetse abundance and trypanosome transmission at the wildlife-livestock interface in Serengeti, Tanzania

In the absence of national control programmes against Rhodesian human African trypanosomiasis, farmer-led treatment of cattle with pyrethroid-based insecticides may be an effective strategy for foci at the edges of wildlife areas, but there is limited evidence to support this. We combined data on insecticide use by farmers, tsetse abundance and trypanosome prevalence, with mathematical models, to quantify the likely impact of insecticide-treated cattle. Sixteen percent of farmers reported treating cattle with a pyrethroid, and chemical analysis indicated 18% of individual cattle had been treated, in the previous week. Treatment of cattle was estimated to increase daily mortality of tsetse by 5–14%. Trypanosome prevalence in tsetse, predominantly from wildlife areas, was 1.25% for T. brucei s.l. and 0.03% for T. b. rhodesiense. For 750 cattle sampled from 48 herds, 2.3% were PCR positive for T. brucei s.l. and none for T. b. rhodesiense. Using mathematical models, we estimated there was 8–29% increase in mortality of tsetse in farming areas and this increase can explain the relatively low prevalence of T. brucei s.l. in cattle. Farmer-led treatment of cattle with pyrethroids is likely, in part, to be limiting the spill-over of human-infective trypanosomes from wildlife areas.

The acute form of sleeping sickness in Africa is caused by the parasite Trypanosoma brucei rhodesiense. It is transmitted by tsetse flies and can be maintained in cycles involving both livestock and wildlife as hosts. Humans are incidentally infected and are particularly at risk of infection near protected areas where there is both wildlife and suitable habitat for tsetse. In these regions, the tsetse vector cannot be eradicated, nor can infection be prevented in wildlife. Here we use field studies of tsetse and livestock in combination with mathematical models of tsetse population change and trypanosome transmission to show that use of pyrethroid-based insecticides on cattle–by farmers at the edge of protected areas–could be contributing to lowering the risk of sleeping sickness in Serengeti District, Tanzania. To our knowledge, our study is the first to report farmer-led tsetse control, co-incident with tsetse decline and relatively low prevalence of T. brucei s.l. in cattle.

Screening Strategies for a Sustainable Endpoint for Gambiense Sleeping Sickness

BACKGROUND

Gambiense human African trypanosomiasis ([gHAT] sleeping sickness) is a vector-borne disease that is typically fatal without treatment. Intensified, mainly medical-based, interventions in endemic areas have reduced the occurrence of gHAT to historically low levels. However, persistent regions, primarily in the Democratic Republic of Congo (DRC), remain a challenge to achieving the World Health Organization's goal of global elimination of transmission (EOT).

METHODS

We used stochastic models of gHAT transmission fitted to DRC case data and explored patterns of regional reporting and extinction. The time to EOT at a health zone scale (~100 000 people) and how an absence of reported cases informs about EOT was quantified.

RESULTS

Regional epidemiology and level of active screening (AS) both influenced the predicted time to EOT. Different AS cessation criteria had similar expected infection dynamics, and recrudescence of infection was unlikely. However, whether EOT has been achieved when AS ends is critically dependent on the stopping criteria. Two or three consecutive years of no detected cases provided greater confidence of EOT compared with a single year (~66%-75% and ~82%-84% probability of EOT, respectively, compared with 31%-51%).

CONCLUSIONS

Multiple years of AS without case detections is a valuable measure to assess the likelihood that the EOT target has been met locally.

NTD Diagnostics for Disease Elimination: A Review

Neglected Tropical Diseases (NTDs) marked out for disease elimination provide a lens through which to explore the changing status of diagnosis in global health. This paper reports on the findings of a scoping review, which set out to explore the main debates around diagnosis for the elimination of NTDs, including the multiple roles diagnostic technologies are being ascribed and the ideal characteristics of tests. It also attempts to summarise the state of diagnosis for three NTDs with elimination goals. The review places special emphasis on point-of-care testing in acknowledgement of the remote and underserved areas where NTDs proliferate. Early NTD campaigns were largely focused on attack phase planning, whereby a similar set of interventions could be transplanted anywhere. Now, with elimination goals in sight, strategies must be tailored to local settings if they are to attain and sustain success. Diagnostic data helps with local adaptation and is increasingly used for programmatic decision-making. The review finds that elimination goals reframe whom diagnosis is for and the myriad roles diagnostics can play. The exigencies of elimination also serve to highlight deficiencies in the current diagnostic arsenal and development pipeline for many NTDs. Moving forward, a guiding framework is needed to drive research and stimulate investment in diagnosis to support NTD goals.

Implications of asymptomatic infection for the natural history of selected parasitic tropical diseases

Progress has been made in the control or elimination of tropical diseases, with a significant reduction of incidence. However, there is a risk of re-emergence if the factors fueling transmission are not dealt with. Although it is essential to understand these underlying factors for each disease, asymptomatic carriers are a common element that may promote resurgence; their impact in terms of proportion in the population and role in transmission needs to be determined. In this paper, we review the current evidence on whether or not to treat asymptomatic carriers given the relevance of their role in the transmission of a specific disease, the efficacy and toxicity of existing drugs, the Public Health interest, and the benefit at an individual level, for example, in Chagas disease, to prevent irreversible organ damage. In the absence of other control tools such as vaccines, there is a need for safer drugs with good risk/benefit profiles in order to change the paradigm so that it addresses the complete infectious process beyond manifest disease to include treatment of non-symptomatic infected persons.

Monitoring the elimination of human African trypanosomiasis at continental and country level: Update to 2018

Background

In 2012 human African trypanosomiasis (HAT), also known as sleeping sickness, was targeted for elimination as a public health problem, set to be achieved by 2020. The World Health Organization (WHO) provides here the 2018 update on the progress made toward that objective. Global indicators are reviewed, in particular the number of reported cases and the areas at risk. Recently developed indicators for the validation of HAT elimination at the national level are also presented.

Methodology/Principal Findings

With 977 cases reported in 2018, down from 2,164 in 2016, the main global indicator of elimination is already well within the 2020 target (i.e. 2,000 cases). Areas at moderate or higher risk (i.e. ≥ 1 case/10,000 people/year) are also steadily shrinking (less than 200,000 km² in the period 2014–2018), thus nearing the 2020 target [i.e. 90% reduction (638,000 km²) from the 2000–2004 baseline (709,000 km²)]. Health facilities providing diagnosis and treatment of gambiense HAT continued to increase (+7% since the previous survey), with a better coverage of at-risk populations. By contrast, rhodesiense HAT health facilities decreased in number (-10.5%) and coverage. At the national level, eight countries meet the requirements to request validation of gambiense HAT elimination as a public health problem (i.e. Benin, Burkina Faso, Cameroon, Côte d’Ivoire, Ghana, Mali, Rwanda, and Togo), while for other endemic countries more efforts are needed in surveillance, control, or both.

Conclusions/Significance

The 2020 goal of HAT elimination as a public health problem is within grasp, and eligible countries are encouraged to request validation of their elimination status. Beyond 2020, the HAT community must gear up for the elimination of gambiense HAT transmission (2030 goal), by preparing for both the expected challenges (e.g. funding, coordination, integration of HAT control into regular health systems, development of more adapted tools, cryptic trypanosome reservoirs, etc.) and the unexpected ones.

Human African trypanosomiasis (HAT), a lethal disease transmitted by tsetse flies, wreaked havoc in Africa at different times in the 20^th century. Over the past twenty years, huge efforts made by a broad coalition of stakeholders curbed the last epidemic and brought the disease to the brink of elimination. In this paper, the latest figures on disease occurrence, geographical distribution and control activities are presented. Strong evidence indicates that the elimination of sleeping sickness ‘as a public health problem’ by 2020 is well within reach. In particular, fewer than one thousand new cases were reported in 2018, and the area where the risk of infection is estimated as moderate, high or very high has shrunk to less than 200,000 km². More than half of this area is in the Democratic Republic of the Congo. The interruption of transmission of the gambiense form, targeted by the World Health Organization (WHO) for 2030, will require renewed efforts to tackle a range of expected and unexpected challenges. The rhodesiense form of the disease represents a small part of the overall HAT burden. For this form, the problem of under detection is on the rise and, because of an important animal reservoir, the elimination of disease transmission is not envisioned at this stage.

Insights from quantitative and mathematical modelling on the proposed 2030 goal for gambiense human African trypanosomiasis (gHAT)

Gambiense human African trypanosomiasis (gHAT) is a parasitic, vector-borne neglected tropical disease that has historically affected populations across West and Central Africa and can result in death if untreated. Following from the success of recent intervention programmes against gHAT, the World Health Organization (WHO) has defined a 2030 goal of global elimination of transmission (EOT). The key proposed indicator to measure achievement of the goal is zero reported cases. Results of previous mathematical modelling and quantitative analyses are brought together to explore both the implications of the proposed indicator and the feasibility of achieving the WHO goal. Whilst the indicator of zero case reporting is clear and measurable, it is an imperfect proxy for EOT and could arise either before or after EOT is achieved. Lagging reporting of infection and imperfect diagnostic specificity could result in case reporting after EOT, whereas the converse could be true due to underreporting, lack of coverage, and cryptic human and animal reservoirs. At the village-scale, the WHO recommendation of continuing active screening until there are three years of zero cases yields a high probability of local EOT, but extrapolating this result to larger spatial scales is complex. Predictive modelling of gHAT has consistently found that EOT by 2030 is unlikely across key endemic regions if current medical-only strategies are not bolstered by improved coverage, reduced time to detection and/or complementary vector control.  Unfortunately, projected costs for strategies expected to meet EOT are high in the short term and strategies that are cost-effective in reducing burden are unlikely to result in EOT by 2030. Future modelling work should aim to provide predictions while taking into account uncertainties in stochastic dynamics and infection reservoirs, as well as assessment of multiple spatial scales, reactive strategies, and measurable proxies of EOT.

Sleeping Sickness at the Crossroads

Human African trypanosomiasis (HAT; sleeping sickness) is a disease with truly historic dimensions [...].

Assessing the impact of aggregating disease stage data in model predictions of human African trypanosomiasis transmission and control activities in Bandundu province (DRC)

Since the turn of the century, the global community has made great progress towards the elimination of gambiense human African trypanosomiasis (HAT). Elimination programs, primarily relying on screening and treatment campaigns, have also created a rich database of HAT epidemiology. Mathematical models calibrated with these data can help to fill remaining gaps in our understanding of HAT transmission dynamics, including key operational research questions such as whether integrating vector control with current intervention strategies is needed to achieve HAT elimination. Here we explore, via an ensemble of models and simulation studies, how including or not disease stage data, or using more updated data sets affect model predictions of future control strategies.

The impact of vector migration on the effectiveness of strategies to control gambiense human African trypanosomiasis

Background

Several modeling studies have been undertaken to assess the feasibility of the WHO goal of eliminating gambiense human African trypanosomiasis (g-HAT) by 2030. However, these studies have generally overlooked the effect of vector migration on disease transmission and control. Here, we evaluated the impact of vector migration on the feasibility of interrupting transmission in different g-HAT foci.

Methods

We developed a g-HAT transmission model of a single tsetse population cluster that accounts for migration of tsetse fly into this population. We used a model calibration approach to constrain g-HAT incidence to ranges expected for high, moderate and low transmission settings, respectively. We used the model to evaluate the effectiveness of current intervention measures, including medical intervention through enhanced screening and treatment, and vector control, for interrupting g-HAT transmission in disease foci under each transmission setting.

Results

We showed that, in low transmission settings, under enhanced medical intervention alone, at least 70% treatment coverage is needed to interrupt g-HAT transmission within 10 years. In moderate transmission settings, a combination of medical intervention and a vector control measure with a daily tsetse mortality greater than 0.03 is required to achieve interruption of disease transmission within 10 years. In high transmission settings, interruption of disease transmission within 10 years requires a combination of at least 70% medical intervention coverage and at least 0.05 tsetse daily mortality rate from vector control. However, the probability of achieving elimination in high transmission settings decreases with an increased tsetse migration rate.

Conclusion

Our results suggest that the WHO 2030 goal of G-HAT elimination is, at least in theory, achievable. But the presence of tsetse migration may reduce the probability of interrupting g-HAT transmission in moderate and high transmission foci. Therefore, optimal vector control programs should incorporate monitoring and controlling of vector density in buffer areas around foci of g-HAT control efforts.

Gambian human African trypanosomiasis (g-HAT), also known as sleeping sickness, is a vector-borne parasitic disease transmitted by tsetse flies. If untreated, g-HAT infection will usually result in death. Recently, the World Health Organization (WHO) has targeted g-HAT for elimination through achieving interruption of transmission by 2030. To help inform elimination efforts, mathematical models have been used to evaluate the feasibility of the WHO goals in different g-HAT transmission foci. However, these mathematical models have generally ignored the role that tsetse migration may have in the spread and reemergence of g-HAT. Using a mathematical model, we evaluate the impact of tsetse migration on the effectiveness of current intervention measures for achieving interruption of g-HAT transmission in different transmission foci. We consider different interventions such as enhanced screening and treatment and vector control. We show that vector control has a great potential for reducing transmission. Still, the presence and intensity of tsetse migration can undermine its effectiveness for interrupting disease transmission, especially in high transmission foci. Our results indicate the need of accounting for tsetse surveillance and migration data in designing vector control efforts for g-HAT elimination.

Assessing Strategies Against Gambiense Sleeping Sickness Through Mathematical Modeling

Background

Control of gambiense sleeping sickness relies predominantly on passive and active screening of people, followed by treatment.

Methods

Mathematical modeling explores the potential of 3 complementary interventions in high- and low-transmission settings.

Results

Intervention strategies that included vector control are predicted to halt transmission most quickly. Targeted active screening, with better and more focused coverage, and enhanced passive surveillance, with improved access to diagnosis and treatment, are both estimated to avert many new infections but, when used alone, are unlikely to halt transmission before 2030 in high-risk settings.

Conclusions

There was general model consensus in the ranking of the 3 complementary interventions studied, although with discrepancies between the quantitative predictions due to differing epidemiological assumptions within the models. While these predictions provide generic insights into improving control, the most effective strategy in any situation depends on the specific epidemiology in the region and the associated costs.

Village-scale persistence and elimination of gambiense human African trypanosomiasis

Gambiense human African trypanosomiasis (gHAT) is one of several neglected tropical diseases that is targeted for elimination by the World Health Organization. Recent years have seen a substantial decline in the number of globally reported cases, largely driven by an intensive process of screening and treatment. However, this infection is highly focal, continuing to persist at low prevalence even in small populations. Regional elimination, and ultimately global eradication, rests on understanding the dynamics and persistence of this infection at the local population scale. Here we develop a stochastic model of gHAT dynamics, which is underpinned by screening and reporting data from one of the highest gHAT incidence regions, Kwilu Province, in the Democratic Republic of Congo. We use this model to explore the persistence of gHAT in villages of different population sizes and subject to different patterns of screening. Our models demonstrate that infection is expected to persist for long periods even in relatively small isolated populations. We further use the model to assess the risk of recrudescence following local elimination and consider how failing to detect cases during active screening events informs the probability of elimination. These quantitative results provide insights for public health policy in the region, particularly highlighting the difficulties in achieving and measuring the 2030 elimination goal.

Backward Bifurcation and Optimal Control Analysis of a Trypanosoma brucei rhodesiense Model

In this paper, a mathematical model for the transmission dynamics of Trypanosoma brucei rhodesiense that incorporates three species—namely, human, animal and vector—is formulated and analyzed. Two controls representing awareness campaigns and insecticide use are investigated in order to minimize the number of infected hosts in the population and the cost of implementation. Qualitative analysis of the model showed that it exhibited backward bifurcation generated by awareness campaigns. From the optimal control analysis we observed that optimal awareness and insecticide use could lead to effective control of the disease even when they were implemented at low intensities. In addition, it was noted that insecticide control had a greater impact on minimizing the spread of the disease compared to awareness campaigns.

Insights from quantitative and mathematical modelling on the proposed 2030 goal for gambiense human African trypanosomiasis (gHAT)

Gambiense human African trypanosomiasis (gHAT) is a parasitic, vector-borne neglected tropical disease that has historically affected populations across West and Central Africa and can result in death if untreated. Following from the success of recent intervention programmes against gHAT, the World Health Organization (WHO) has defined a 2030 goal of global elimination of transmission (EOT). The key proposed indicator to measure achievement of the goal is to have zero reported cases. Results of previous mathematical modelling and quantitative analyses are brought together to explore both the implications of the proposed indicator and the feasibility of achieving the WHO goal. Whilst the indicator of zero case reporting is clear and measurable, it is an imperfect proxy for EOT and could arise either before or after EOT is achieved. Lagging reporting of infection and imperfect diagnostic specificity could result in case reporting after EOT, whereas the converse could be true due to underreporting, lack of coverage, and cryptic human and animal reservoirs. At the village-scale, the WHO recommendation of continuing active screening until there are three years of zero cases yields a high probability of local EOT, but extrapolating this result to larger spatial scales is complex. Predictive modelling of gHAT has consistently found that EOT by 2030 is unlikely across key endemic regions if current medical-only strategies are not bolstered by improved coverage, reduced time to detection and/or complementary vector control.  Unfortunately, projected costs for strategies expected to meet EOT are high in the short term and strategies that are cost-effective in reducing burden are unlikely to result in EOT by 2030. Future modelling work should aim to provide predictions while taking into account uncertainties in stochastic dynamics and infection reservoirs, as well as assessment of multiple spatial scales, reactive strategies, and measurable proxies of EOT.

Tsetse peritrophic matrix influences for trypanosome transmission

Tsetse flies are important vectors of parasitic African trypanosomes, agents of human and animal trypanosomiasis. Easily administrable and effective tools for disease control in the mammalian host are still lacking but reduction of the tsetse vector populations can reduce disease. An alternative approach is to reduce the transmission of trypanosomes in the tsetse vector. The gut peritrophic matrix (PM) has emerged as an important regulator of parasite transmission success in tsetse. Tsetse has a Type II PM that is constitutively produced by cells in the cardia organ. Tsetse PM lines the entire gut and functions as an immunological barrier to prevent the gut epithelia from responding to commensal environmental microbes present in the gut lumen. Tsetse PM also functions as a physical barrier to trypanosome infections that enter into the gut lumen in an infective blood meal. For persistence in the gut, African trypanosomes have developed an adaptive manipulative process to transiently reduce PM efficacy. The process is mediated by mammalian trypanosome surface coat proteins, Variant Surface Glycoproteins (VSGs) which are shed in the gut lumen and taken up by cardia cells. The mechanism of PM reduction involves a tsetse microRNA (miR-275) which acts thru the Wnt signaling pathway. The PM efficacy is once again reduced later in the infection process to enable the gut established parasites to reenter into the gut lumen to colonize the salivary glands, an essential process for transmission. The ability to modulate PM integrity can lead to innovative approaches to reduce disease transmission.

Gambian human African trypanosomiasis in North West Uganda. Are we on course for the 2020 target?

In 1994, combined active and passive screening reported 1469 cases from the historic Gambian Human African Trypanosomiasis (gHAT) foci of West Nile, Uganda. Since 2011 systematic active screening has stopped and there has been reliance on passive screening. During 2014, passive screening alone detected just nine cases. In the same year a tsetse control intervention was expanded to cover the main gHAT foci in West Nile to curtail transmission of gHAT contributing to the elimination of gHAT as a public health problem in the area. It is known that sole reliance on passive screening is slow to detect cases and can underestimate the actual true number. We therefore undertook an active screening programme designed to test the efficacy of these interventions against gHAT transmission and clarify disease status. Screening was conducted in 28 randomly selected villages throughout the study area, aiming to sample all residents. Whole blood from 10,963 participants was analysed using CATT and 97 CATT suspects (0.9%) were evaluated with microscopy and trypanolysis. No confirmed cases were found providing evidence that the gHAT prevention programmes in West Nile have been effective. Results confirm gHAT prevalence in the study area of West Nile is below the elimination threshold (1 new case / 10,000 population), making elimination on course across this study area if status is maintained. The findings of this study can be used to guide future HAT and tsetse management in other gHAT foci, where reduced caseloads necessitate a shift from active to passive screening.

The number of gHAT cases across West Nile, Uganda has declined in the last 20 years. This decline is due to the impact of programmes of active and passive case detection and treatment which have recently been combined with tsetse control operations (post 2011). We carried out an active survey of gHAT to evaluate the prevalence in areas where vector control has been introduced. Our results confirm that the overall prevalence of gHAT is below 1 case per 10,000 people at risk in the historical foci and shows that results from passive screening are providing an accurate picture of gHAT prevalence in the area.

Mathematical Modelling of Human African Trypanosomiasis Using Control Measures

Human African trypanosomiasis (HAT), commonly known as sleeping sickness, is a neglected tropical vector-borne disease caused by trypanosome protozoa. It is transmitted by bites of infected tsetse fly. In this paper, we first present the vector-host model which describes the general transmission dynamics of HAT. In the tsetse fly population, the HAT is modelled by three compartments, while in the human population, the HAT is modelled by four compartments. The next-generation matrix approach is used to derive the basic reproduction number, R 0, and it is also proved that if R 0 ≤ 1, the disease-free equilibrium is globally asymptotically stable, which means the disease dies out. The disease persists in the population if the value of R 0 > 1. Furthermore, the optimal control model is determined by using the Pontryagin's maximum principle, with control measures such as education, treatment, and insecticides used to optimize the objective function. The model simulations confirm that the use of the three control measures is very efficient and effective to eliminate HAT in Africa.

Cost-effectiveness of using a rapid diagnostic test to screen for human African trypanosomiasis in the Democratic Republic of the Congo

New rapid diagnostic tests (RDTs) for screening human African trypanosomiasis (HAT) have been introduced as alternatives to the card agglutination test for trypanosomiasis (CATT). One brand of RDT, the SD BIOLINE HAT RDT has been shown to have lower specificity but higher sensitivity than CATT, so to make a rational choice between screening strategies, a cost-effectiveness analysis is a key element. In this paper we estimate the relative cost-effectiveness of CATT and the RDT when implemented in the Democratic Republic of the Congo (DRC). Data on the epidemiological parameters and costs were collected as part of a larger study. These data were used to model three different diagnostic algorithms in mobile teams and fixed health facilities, and the relative cost-effectiveness was measured as the average cost per case diagnosed. In both fixed facilities and mobile teams, screening of participants using the SD BIOLINE HAT RDT followed by parasitological confirmation had a lower cost-effectiveness ratio than in algorithms using CATT. Algorithms using the RDT were cheaper by 112.54 (33.2%) and 88.54 (32.92%) US dollars per case diagnosed in mobile teams and fixed health facilities respectively, when compared with algorithms using CATT. Sensitivity analysis demonstrated that these conclusions were robust to a number of assumptions, and that the results can be scaled to smaller or larger facilities, and a range of prevalences. The RDT was the most cost-effective screening test in all realistic scenarios and detected more cases than CATT. Thus, on this basis, the SD BIOLINE HAT RDT could be considered as the most cost-effective option for use in routine screening for HAT in the DRC.

Data-driven models to predict the elimination of sleeping sickness in former Equateur province of DRC

Approaching disease elimination, it is crucial to be able to assess progress towards key objectives using quantitative tools. For Gambian human African trypanosomiasis (HAT), the ultimate goal is to stop transmission by 2030, while intermediary targets include elimination as a public health problem - defined as <1 new case per 10,000 inhabitants in 90% of foci, and <2000 reported cases by 2020. Using two independent mathematical models, this study assessed the achievability of these goals in the former Equateur province of the Democratic Republic of Congo, which historically had endemic levels of disease. The two deterministic models used different assumptions on disease progression, risk of infection and non-participation in screening, reflecting biological uncertainty. To validate the models a censor-fit-uncensor procedure was used to fit to health-zone level data from 2000 to 2012; initially the last six years were censored, then three and the final step utilised all data. The different model projections were used to evaluate the expected transmission and reporting for each health zone within each province under six intervention strategies using currently available tools. In 2012 there were 197 reported HAT cases in former Equateur reduced from 6828 in 2000, however this reflects lower active testing for HAT (1.3% of the population compared to 7.2%). Modelling results indicate that there are likely to be <300 reported cases in former Equateur in 2020 if screening continues at the mean level for 2000-2012 (6.2%), and <120 cases if vector control is introduced. Some health zones may fail to achieve <1 new case per 10,000 by 2020 without vector control, although most appear on track for this target using medical interventions alone. The full elimination goal will be harder to reach; between 39 and 54% of health zones analysed may have to improve their current medical-only strategy to stop transmission completely by 2030.

The development of high resolution maps of tsetse abundance to guide interventions against human African trypanosomiasis in northern Uganda

BACKGROUND

Vector control is emerging as an important component of global efforts to control Gambian sleeping sickness (human African trypanosomiasis, HAT). The deployment of insecticide-treated targets ("Tiny Targets") to attract and kill riverine tsetse, the vectors of Trypanosoma brucei gambiense, has been shown to be particularly cost-effective. As this method of vector control continues to be implemented across larger areas, knowledge of the abundance of tsetse to guide the deployment of "Tiny Targets" will be of increasing value. In this paper, we use a geostatistical modelling framework to produce maps of estimated tsetse abundance under two scenarios: (i) when accurate data on the local river network are available; and (ii) when river information is sparse.

METHODS

Tsetse abundance data were obtained from a pre-intervention survey conducted in northern Uganda in 2010. River network data obtained from either digitised maps or derived from 30 m resolution digital elevation model (DEM) data as a proxy for ground truth data. Other environmental variables were derived from publicly-available resolution remotely sensed data (e.g. Landsat, 30 m resolution). Zero-inflated negative binomial geostatistical models were fitted to the abundance data using an integrated nested Laplace approximation approach, and maps of estimated tsetse abundance were produced.

RESULTS

Restricting the analysis to traps located within 100 m of any river, positive associations were identified between the length of river and the minimum soil/vegetation moisture content of the surrounding area and daily fly catches, whereas negative associations were identified with elevation and distance to the river. The resulting models could accurately distinguish between traps with high and low fly catches (e.g. < 5 or > 5 flies/day), with a ROC-AUC (receiver-operating characteristic - area under the curve) greater than 0.9. Whilst the precise course of the river was not well approximated using the DEM data, the models fitted using DEM-derived river data performed similarly to those that incorporated the more accurate local river information.

CONCLUSIONS

These models can now be used to assist in the design, implementation and monitoring of tsetse control operations in northern Uganda and further can be used as a framework by which to undertake similar studies in other areas where Glossina fuscipes fuscipes spreads Gambian sleeping sickness.

The impact of passive case detection on the transmission dynamics of gambiense Human African Trypanosomiasis

Gambiense Human African Trypanosomiasis (HAT), or sleeping sickness, is a vector-borne disease affecting largely rural populations in Western and Central Africa. The main method for detecting and treating cases of gambiense HAT are active screening through mobile teams and passive detection through self-referral of patients to dedicated treatment centres or hospitals. Strategies based on active case finding and treatment have drastically reduced the global incidence of the disease over recent decades. However, little is known about the coverage and transmission impact of passive case detection. We used a mathematical model to analyse data from the period between active screening sessions in hundreds of villages that were monitored as part of three HAT control projects run by Médecins Sans Frontières in Southern Sudan and Uganda in the late 1990s and early 2000s. We found heterogeneity in incidence across villages, with a small minority of villages found to have much higher transmission rates and burdens than the majority. We further found that only a minority of prevalent cases in the first, haemo-lymphatic stage of the disease were detected passively (maximum likelihood estimate <30% in all three settings), whereas around 50% of patients in the second, meningo-encephalitic were detected. We estimated that passive case detection reduced transmission in affected areas by between 30 and 50%, suggesting that there is great potential value in improving rates of passive case detection. As gambiense HAT is driven towards elimination, it will be important to establish good systems of passive screening, and estimates such as the ones here will be of value in assessing the expected impact of moving from a primarily active to a more passive screening regime.

Gambiense Human African Trypanosomiasis, or sleeping sickness, is transmitted by the tsetse fly and affects rural populations in Western and Central Africa. It is a deadly disease if untreated, and it is therefore important to find people in the early stages of disease so that appropriate care and medication can be provided. Because of this, much emphasis is put on mobile teams going from village to village and actively finding as many potential patients as possible. This does not reach all infected people, though, and some are only detected passively, that is they report themselves to a health provider, often in advanced stages of disease. It is not clear what proportion of cases of sleeping sickness are detected in this way, or how much onwards transmission is prevented. Here we used a mathematical model to analyse data from a sleeping sickness control programme in Uganda and South Sudan, in order to identify which proportion of people infected with the disease are identified through passive case detection. We found that only a minority of patients are identified in this way in the early stages of disease, but around half are identified if they are in the later stages. We further found that passive screening reduced transmission in affected areas by between 30 and 50%. This suggests that there is great potential value in improving the rates of passive case detection, and we recommend that more emphasis is put on tackling potential barriers that prevent people being detected.