Quantitative analyses and modelling to support achievement of the 2020 goals for nine neglected tropical diseases

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

Mass drug administration (MDA) is the cornerstone for the elimination of lymphatic filariasis (LF). The proportion of the population that is never treated (NT) is a crucial determinant of whether this goal is achieved within reasonable time frames.

METHODS

Using 2 individual-based stochastic LF transmission models, we assess the maximum permissible level of NT for which the 1% microfilaremia (mf) prevalence threshold can be achieved (with 90% probability) within 10 years under different scenarios of annual MDA coverage, drug combination and transmission setting.

RESULTS

For Anopheles-transmission settings, we find that treating 80% of the eligible population annually with ivermectin + albendazole (IA) can achieve the 1% mf prevalence threshold within 10 years of annual treatment when baseline mf prevalence is 10%, as long as NT <10%. Higher proportions of NT are acceptable when more efficacious treatment regimens are used. For Culex-transmission settings with a low (5%) baseline mf prevalence and diethylcarbamazine + albendazole (DA) or ivermectin + diethylcarbamazine + albendazole (IDA) treatment, elimination can be reached if treatment coverage among eligibles is 80% or higher. For 10% baseline mf prevalence, the target can be achieved when the annual coverage is 80% and NT ≤15%. Higher infection prevalence or levels of NT would make achieving the target more difficult.

CONCLUSIONS

The proportion of people never treated in MDA programmes for LF can strongly influence the achievement of elimination and the impact of NT is greater in high transmission areas. This study provides a starting point for further development of criteria for the evaluation of NT.

Modelling morbidity for neglected tropical diseases: the long and winding road from cumulative exposure to long-term pathology

Reducing the morbidities caused by neglected tropical diseases (NTDs) is a central aim of ongoing disease control programmes. The broad spectrum of pathogens under the umbrella of NTDs lead to a range of negative health outcomes, from malnutrition and anaemia to organ failure, blindness and carcinogenesis. For some NTDs, the most severe clinical manifestations develop over many years of chronic or repeated infection. For these diseases, the association between infection and risk of long-term pathology is generally complex, and the impact of multiple interacting factors, such as age, co-morbidities and host immune response, is often poorly quantified. Mathematical modelling has been used for many years to gain insights into the complex processes underlying the transmission dynamics of infectious diseases; however, long-term morbidities associated with chronic or cumulative exposure are generally not incorporated into dynamic models for NTDs. Here we consider the complexities and challenges for determining the relationship between cumulative pathogen exposure and morbidity at the individual and population levels, drawing on case studies for trachoma, schistosomiasis and foodborne trematodiasis. We explore potential frameworks for explicitly incorporating long-term morbidity into NTD transmission models, and consider the insights such frameworks may bring in terms of policy-relevant projections for the elimination era. This article is part of the theme issue 'Challenges and opportunities in the fight against neglected tropical diseases: a decade from the London Declaration on NTDs'.

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.

Development of a dose-response model for porcine cysticercosis

Taenia solium is an important cause of acquired epilepsy worldwide and remains endemic in Asia, Africa, and Latin America. Transmission of this parasite is still poorly understood despite the design of infection experiments to improve our knowledge of the disease, with estimates for critical epidemiological parameters, such as the probability of human-to-pig infection after exposure to eggs, still lacking. In this paper, a systematic review was carried out and eight pig infection experiments were analyzed to describe the probability of developing cysts. These experiments included different pathways of inoculation: with ingestion of proglottids, eggs, and beetles that ingested eggs, and direct injection of activated oncospheres into the carotid artery. In these experiments, different infective doses were used, and the numbers of viable and degenerated cysts in the body and brain of each pig were registered. Five alternative dose-response models (exponential, logistic, log-logistic, and exact and approximate beta-Poisson) were assessed for their accuracy in describing the observed probabilities of cyst development as a function of the inoculation dose. Dose-response models were developed separately for the presence of three types of cysts (any, viable only, and cysts in the brain) and considered for each of the four inoculation methods ("Proglottids", "Eggs", "Beetles" and "Carotid"). The exact beta-Poisson model best fit the data for the three types of cysts and all relevant exposure pathways. However, observations for some exposure pathways were too scarce to reliably define a dose-response curve with any model. A wide enough range of doses and sufficient sample sizes was only found for the "Eggs" pathway and a merged "Oral" pathway combining the "Proglottids", "Eggs" and "Beetles" pathways. Estimated parameter values from this model suggest that a low infective dose is sufficient to result in a 50% probability for the development of any cyst or for viable cyst infections. Although this is a preliminary model reliant on a limited dataset, the parameters described in this manuscript should contribute to the design of future experimental infections related to T. solium transmission, as well as the parameterization of simulation models of transmission aimed at informing control.

Overcoming roadblocks in the development of vaccines for leishmaniasis

INTRODUCTION

The leishmaniases represent a group of parasitic diseases caused by infection with one of several species of Leishmania parasites. Disease presentation varies because of differences in parasite and host genetics and may be influenced by additional factors such as host nutritional status or co-infection. Studies in experimental models of Leishmania infection, vaccination of companion animals and human epidemiological data suggest that many forms of leishmaniasis could be prevented by vaccination, but no vaccines are currently available for human use.

AREAS COVERED

We describe some of the existing roadblocks to the development and implementation of an effective leishmaniasis vaccine, based on a review of recent literature found on PubMed, BioRxiv and MedRxiv. In addition to discussing scientific unknowns that hinder vaccine candidate identification and selection, we explore gaps in knowledge regarding the commercial and public health value propositions underpinning vaccine development and provide a route map for future research and advocacy.

EXPERT OPINION

Despite significant progress, leishmaniasis vaccine development remains hindered by significant gaps in understanding that span the vaccine development pipeline. Increased coordination and adoption of a more holistic view to vaccine development will be required to ensure more rapid progress in the years ahead.

Host Controls of Within-Host Disease Dynamics: Insight from an Invertebrate System

AbstractWithin-host processes (representing the entry, establishment, growth, and development of a parasite inside its host) may play a key role in parasite transmission but remain challenging to observe and quantify. We develop a general model for measuring host defenses and within-host disease dynamics. Our stochastic model breaks the infection process down into the stages of parasite exposure, entry, and establishment and provides associated probabilities for a host's ability to resist infections with barriers and clear internal infections. We tested our model on Daphnia dentifera and the parasitic fungus Metschnikowia bicuspidata and found that when faced with identical levels of parasite exposure, Daphnia patent (transmitting) infections depended on the strength of internal clearance. Applying a Gillespie algorithm to the model-estimated probabilities allowed us to visualize within-host dynamics, within which signatures of host defense could be clearly observed. We also found that early within-host stages were the most vulnerable to internal clearance, suggesting that hosts have a limited window during which recovery can occur. Our study demonstrates how pairing longitudinal infection data with a simple model can reveal new insight into within-host dynamics and mechanisms of host defense. Our model and methodological approach may be a powerful tool for exploring these properties in understudied host-parasite interactions.

What Can Modeling Tell Us About Sustainable End Points for Neglected Tropical Diseases?

As programs move closer toward the World Health Organization (WHO) goals of reduction in morbidity, elimination as a public health problem or elimination of transmission, countries will be faced with planning the next stages of surveillance and control in low prevalence settings. Mathematical models of neglected tropical diseases (NTDs) will need to go beyond predicting the effect of different treatment programs on these goals and on to predicting whether the gains can be sustained. One of the most important challenges will be identifying the policy goal and the right constraints on interventions and surveillance over the long term, as a single policy option will not achieve all aims—for example, minimizing morbidity and minimizing costs cannot both be achieved. As NTDs move toward 2030 and beyond, more nuanced intervention choices will be informed by quantitative analyses which are adapted to national context.

CHRONIC WASTING DISEASE MODELING: AN OVERVIEW

Chronic wasting disease (CWD) is an infectious and fatal prion disease occurring in the family Cervidae. To update the research community regarding the status quo of CWD epidemic models, we conducted a meta-analysis on CWD research. We collected data from peer-reviewed articles published since 1980, when CWD was first diagnosed, until December 2018. We explored the analytical methods used historically to understand CWD. We used 14 standardized variables to assess overall analytical approaches of CWD research communities, data used, and the modeling methods used. We found that CWD modeling initiated in the early 2000s and has increased since then. Connectivity of the research community was heavily reliant on a cluster of CWD researchers. Studies focused primarily on regression and compartment-based models, population-level approaches, and host species of game management concern. Similarly, CWD research focused on single populations, species, and locations, neglecting modeling using community ecology and biogeographic approaches. Chronic wasting disease detection relied on classic diagnostic methods with limited sensitivity for most stages of infection. Overall, we found that past modeling efforts generated a solid baseline for understanding CWD in wildlife and increased our knowledge on infectious prion ecology. Future analytical efforts should consider more sensitive diagnostic methods to quantify uncertainty and broader scale studies to elucidate CWD transmission beyond population-level approaches. Considering that infectious prions may not follow biological rules of well-known wildlife pathogens (i.e., viruses, bacteria, fungi), assumptions used when modeling other infectious disease may not apply for CWD. Chronic wasting disease is a new challenge in wildlife epidemiology.

Strengthening data collection for neglected tropical diseases: What data are needed for models to better inform tailored intervention programmes?

Locally tailored interventions for neglected tropical diseases (NTDs) are becoming increasingly important for ensuring that the World Health Organization (WHO) goals for control and elimination are reached. Mathematical models, such as those developed by the NTD Modelling Consortium, are able to offer recommendations on interventions but remain constrained by the data currently available. Data collection for NTDs needs to be strengthened as better data are required to indirectly inform transmission in an area. Addressing specific data needs will improve our modelling recommendations, enabling more accurate tailoring of interventions and assessment of their progress. In this collection, we discuss the data needs for several NTDs, specifically gambiense human African trypanosomiasis, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminths (STH), trachoma, and visceral leishmaniasis. Similarities in the data needs for these NTDs highlight the potential for integration across these diseases and where possible, a wider spectrum of diseases.

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.

When, Who, and How to Sample: Designing Practical Surveillance for 7 Neglected Tropical Diseases as We Approach Elimination

As neglected tropical disease programs look to consolidate the successes of moving towards elimination, we need to understand the dynamics of transmission at low prevalence to inform surveillance strategies for detecting elimination and resurgence. In this special collection, modelling insights are used to highlight drivers of local elimination, evaluate strategies for detecting resurgence, and show the importance of rational spatial sampling schemes for several neglected tropical diseases (specifically schistosomiasis, soil-transmitted helminths, lymphatic filariasis, trachoma, onchocerciasis, visceral leishmaniasis, and gambiense sleeping sickness).

Towards Evidence-based Control of Opisthorchis viverrini

Transmission of the carcinogenic liver fluke Opisthorchis viverrini is ongoing across Southeast Asia. Endemic countries within the region are in different stages of achieving control. However, evidence on which interventions are the most effective for reducing parasite transmission, and the resulting liver cancer, is currently lacking. Quantitative modelling can be used to evaluate different control measures against O. viverrini and assist the design of clinical trials. In this article we evaluate the epidemiological parameters that underpin models of O. viverrini and the data necessary for their estimation, with the aim of developing evidence-based strategies for parasite control at a national or regional level.

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.

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.

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).

Synthesis and Structure-Activity Relationship of Dehydrodieugenol B Neolignans against Trypanosoma cruzi

Trypanosoma cruzi is the etiologic agent of Chagas disease, which affects over seven million people, especially in developing countries. Undesirable side effects are frequently associated with current therapies, which are typically ineffective in the treatment of all stages of the disease. Here, we report the first synthesis of the neolignan dehydrodieugenol B, a natural product recently shown to exhibit activity against T. cruzi. Using this strategy, a series of synthetic analogues were prepared to explore structure-activity relationships. The in vitro antiparasitic activities of these analogues revealed a wide tolerance of modifications and substituent deletions, with maintained or improved bioactivities against the amastigote forms of the parasite (50% inhibitory concentration (IC₅₀) of 4-63 μM) and no mammalian toxicity (50% cytotoxic concentration (CC₅₀) of >200 μM). Five of these analogues meet the Drugs for Neglected Disease Initiative (DNDi) "hit criteria" for Chagas disease. This work has enabled the identification of key structural features of the natural product and sites where scaffold modification is tolerated.

SCORE Operational Research on Moving toward Interruption of Schistosomiasis Transmission

As part of its diverse portfolio, the Schistosomiasis Consortium for Operational Research and Evaluation (SCORE) included two cluster-randomized trials evaluating interventions that could potentially lead to interruption of schistosomiasis transmission (elimination) in areas of Africa with low prevalence and intensity of infection. These studies, conducted in Zanzibar and Côte d’Ivoire, demonstrated that multiyear mass drug administration (MDA) with praziquantel failed to interrupt the transmission of urogenital schistosomiasis, even when provided biannually and/or supplemented by small-scale implementation of additional interventions. Other SCORE activities related to elimination included a feasibility and acceptability assessment of test–treat–track–test–treat (T5) strategies and mathematical modeling. Future evaluations of interventions to eliminate schistosomiasis should recognize the difficulties inherent in conducting randomized controlled trials on elimination and in measuring small changes where baseline prevalence is low. Highly sensitive and specific diagnostic tests for use in very low–prevalence areas for schistosomiasis are not routinely available, which complicates accurate measurement of infection rates and assessment of changes resulting from interventions in these settings. Although not encountered in these two studies, as prevalence and intensity decrease, political and community commitment to population-wide MDA may decrease. Because of this potential problem, SCORE developed and funded the T5 strategy implemented in Egypt, Kenya, and Tanzania. It is likely that focal MDA campaigns, along with more targeted approaches, including a T5 strategy and snail control, will need to be supplemented with the provision of clean water and sanitation and behavior change communications to achieve interruption of schistosome transmission.

Application of Schistosomiasis Consortium for Operational Research and Evaluation Study Findings to Refine Predictive Modeling of Schistosoma mansoni and Schistosoma haematobium Control in Sub-Saharan Africa

An essential mission of the Schistosomiasis Consortium for Operational Research and Evaluation (SCORE) was to help inform global health practices related to the control and elimination of schistosomiasis. To provide more accurate, evidence-based projections of the most likely impact of different control interventions, whether implemented alone or in combination, SCORE supported mathematical modeling teams to provide simulations of community-level Schistosoma infection outcomes in the setting of real or hypothetical programs implementing multiyear mass drug administration (MDA) for parasite control. These models were calibrated using SCORE experience with Schistosoma mansoni and Schistosoma haematobium gaining and sustaining control studies, and with data from comparable programs that used community-based or school-based praziquantel MDA in other parts of sub-Saharan Africa. From 2010 to 2019, models were developed and refined, first to project the likely SCORE control outcomes, and later to more accurately reflect impact of MDA across different transmission settings, including the role of snail ecology and the impact of seasonal rainfall on snail abundance. Starting in 2014, SCORE modeling projections were also compared with the models of colleagues in the Neglected Tropical Diseases Modelling Consortium. To explore further possible improvement to program-based control, later simulations examined the cost-effectiveness of combining MDA with environmental snail control, and the utility of early impact assessment to more quickly identify persistent hot spots of transmission. This article provides a nontechnical summary of the 11 SCORE-related modeling projects and provides links to the original open-access articles describing model development and projections relevant to schistosomiasis control policy.

Patterns of individual non-treatment during multiple rounds of mass drug administration for control of soil-transmitted helminths in the TUMIKIA trial, Kenya: a secondary longitudinal analysis

BACKGROUND

Few studies have been done of patterns of treatment during mass drug administration (MDA) to control neglected tropical diseases. We used routinely collected individual-level treatment records that had been collated for the Tuangamize Minyoo Kenya Imarisha Afya (Swahili for Eradicate Worms in Kenya for Better Health [TUMIKIA]) trial, done in coastal Kenya from 2015 to 2017. In this analysis we estimate the extent of and factors associated with the same individuals not being treated over multiple rounds of MDA, which we term systematic non-treatment.

METHODS

We linked the baseline population of the TUMIKIA trial randomly assigned to receive biannual community-wide MDA for soil-transmitted helminthiasis to longitudinal records on receipt of treatment in any of the four treatment rounds of the study. We fitted logistic regression models to estimate the association of non-treatment in a given round with non-treatment in the previous round, controlling for identified predictors of non-treatment. We also used multinomial logistic regression to identify factors associated with part or no treatment versus complete treatment.

FINDINGS

36 327 participants were included in our analysis: 16 236 children aged 2-14 years and 20 091 adults aged 15 years or older. The odds of having no treatment recorded was higher if a participant was not treated during the previous round of MDA (adjusted odds ratio [OR] 3·60, 95% CI 3·08-4·20 for children and 5·58, 5·01-6·21 for adults). For children, school attendance and rural residence reduced the odds of receiving part or no treatment, whereas odds were increased by least poor socioeconomic status and living in an urban or periurban household. Women had higher odds than men of receiving part or no treatment. However, when those with pregnancy or childbirth in the previous 2 weeks were excluded, women became more likely to receive complete treatment. Adults aged 20-25 years were the age group with the highest odds of receiving part (OR 1·41, 95% CI 1·22-1·63) or no treatment (OR 1·81, 95% CI 1·53-2·14).

INTERPRETATION

Non-treatment was associated with specific sociodemographic groups and characteristics and did not occcur at random. This finding has important implications for MDA programme effectiveness, the relevance of which will intensify as disease prevalence decreases and infections become increasingly clustered.

FUNDING

Bill & Melinda Gates Foundation, Joint Global Health Trials Scheme of the Medical Research Council, UK Department for International Development, Wellcome Trust, Children's Investment Fund Foundation, and London Centre for Neglected Tropical Diseases.

Predicting lymphatic filariasis elimination in data-limited settings: A reconstructive computational framework for combining data generation and model discovery

Although there is increasing importance placed on the use of mathematical models for the effective design and management of long-term parasite elimination, it is becoming clear that transmission models are most useful when they reflect the processes pertaining to local infection dynamics as opposed to generalized dynamics. Such localized models must also be developed even when the data required for characterizing local transmission processes are limited or incomplete, as is often the case for neglected tropical diseases, including the disease system studied in this work, viz. lymphatic filariasis (LF). Here, we draw on progress made in the field of computational knowledge discovery to present a reconstructive simulation framework that addresses these challenges by facilitating the discovery of both data and models concurrently in areas where we have insufficient observational data. Using available data from eight sites from Nigeria and elsewhere, we demonstrate that our data-model discovery system is able to estimate local transmission models and missing pre-control infection information using generalized knowledge of filarial transmission dynamics, monitoring survey data, and details of historical interventions. Forecasts of the impacts of interventions carried out in each site made by the models estimated using the reconstructed baseline data matched temporal infection observations and provided useful information regarding when transmission interruption is likely to have occurred. Assessments of elimination and resurgence probabilities based on the models also suggest a protective effect of vector control against the reemergence of LF transmission after stopping drug treatments. The reconstructive computational framework for model and data discovery developed here highlights how coupling models with available data can generate new knowledge about complex, data-limited systems, and support the effective management of disease programs in the face of critical data gaps.

As modelling becomes commonly used in the design and evaluation of parasite elimination programs, the need for well-defined models and datasets describing the nature of transmission processes in local settings is becoming pronounced. For many neglected tropical diseases, however, data for site-specific model identification are typically sparse or incomplete. In this study, we present a new data-model computational discovery system that couples data-assimilation methods based on existing monitoring survey data with model-generated data about baseline conditions to discover the local transmission models required for simulating the impacts of interventions in typical endemic locations for the macroparasitic disease, lymphatic filariasis (LF). Using data from eight study sites in Nigeria and elsewhere, we show that our reconstructive computational framework is able to combine information contained within partially-available site-specific monitoring data with knowledge of parasite transmission dynamics embedded in process-based models to generate the missing data required for inducing reliable locally applicable LF models. We also show that the models so discovered are able to generate the intervention forecasts required for supporting management-relevant decisions in parasite elimination.

Safety and efficacy of co-administered diethylcarbamazine, albendazole and ivermectin during mass drug administration for lymphatic filariasis in Haiti: Results from a two-armed, open-label, cluster-randomized, community study

In Haiti, 22 communes still require mass drug administration (MDA) to eliminate lymphatic filariasis (LF) as a public health problem. Several clinical trials have shown that a single oral dose of ivermectin (IVM), diethylcarbamazine (DEC) and albendazole (ALB) (IDA) is more effective than DEC plus ALB (DA) for clearing Wuchereria bancrofti microfilariae (Mf). We performed a cluster-randomized community study to compare the safety and efficacy of IDA and DA in an LF-endemic area in northern Haiti. Ten localities were randomized to receive either DA or IDA. Participants were monitored for adverse events (AE), parasite antigenemia, and microfilaremia. Antigen-positive participants were retested one year after MDA to assess treatment efficacy. Fewer participants (11.0%, 321/2917) experienced at least one AE after IDA compared to DA (17.3%, 491/2844, P<0.001). Most AEs were mild, and the three most common AEs reported were headaches, dizziness and abdominal pain. Serious AEs developed in three participants who received DA. Baseline prevalence for filarial antigenemia was 8.0% (239/3004) in IDA localities and 11.5% (344/2994) in DA localities (<0.001). Of those with positive antigenemia, 17.6% (42/239) in IDA localities and 20.9% (72/344, P = 0.25) in DA localities were microfilaremic. One year after treatment, 84% percent of persons with positive filarial antigen tests at baseline could be retested. Clearance rates for filarial antigenemia were 20.5% (41/200) after IDA versus 25.4% (74/289) after DA (P = 0.3). However, 94.4% (34/36) of IDA recipients and 75.9% (44/58) of DA recipients with baseline microfilaremia were Mf negative at the time of retest (P = 0.02). Thus, MDA with IDA was at least as well tolerated and significantly more effective for clearing Mf compared to the standard DA regimen in this study. Effective MDA coverage with IDA could accelerate the elimination of LF as a public health problem in the 22 communes that still require MDA in Haiti.

Designing antifilarial drug trials using clinical trial simulators

Lymphatic filariasis and onchocerciasis are neglected tropical diseases (NTDs) targeted for elimination by mass (antifilarial) drug administration. These drugs are predominantly active against the microfilarial progeny of adult worms. New drugs or combinations are needed to improve patient therapy and to enhance the effectiveness of interventions in persistent hotspots of transmission. Several therapies and regimens are currently in (pre-)clinical testing. Clinical trial simulators (CTSs) project patient outcomes to inform the design of clinical trials but have not been widely applied to NTDs, where their resource-saving payoffs could be highly beneficial. We demonstrate the utility of CTSs using our individual-based onchocerciasis transmission model (EPIONCHO-IBM) that projects trial outcomes of a hypothetical macrofilaricidal drug. We identify key design decisions that influence the power of clinical trials, including participant eligibility criteria and post-treatment follow-up times for measuring infection indicators. We discuss how CTSs help to inform target product profiles.

Drugs for filariases are under development and clinical trial simulators could help to inform the design of clinical trials. Here, Walker et al. use an individual-based onchocerciasis transmission model to project trial outcomes of a hypothetical macrofilaricidal drug, resolving key design choices.

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

Schistosomiasis is one of the most important neglected tropical diseases (NTDs) affecting millions of people in 79 different countries. The World Health Organization (WHO) has specified two control goals to be achieved by 2020 and 2025 - morbidity control and elimination as a public health problem (EPHP). Mass drug administration (MDA) is the main method for schistosomiasis control but it has sometimes proved difficult to both secure adequate supplies of the most efficacious drug praziquantel to treat the millions infected either annually or biannually, and to achieve high treatment coverage in targeted communities in regions of endemic infection. The development of alternative control methods remains a priority.

In this paper, using stochastic individual-based models, we analyze whether the addition of a novel vaccine alone or in combination with drug treatment, is a more effective control strategy, in terms of achieving the WHO goals, as well as the time and costs to achieve these goals when compared to MDA alone. The key objective of our analyses is to help facilitate decision making for moving a promising candidate vaccine through the phase I, II and III trials in humans to a final product for use in resource poor settings.

We find that in low to moderate transmission settings, both vaccination and MDA are highly likely to achieve the WHO goals within 15 years and are likely to be cost-effective. In high transmission settings, MDA alone is unable to achieve the goals, whereas vaccination is able to achieve both goals in combination with MDA. In these settings Vaccination is cost-effective, even for short duration vaccines, so long as vaccination costs up to US$7.60 per full course of vaccination. The public health value of the vaccine depends on the duration of vaccine protection, the baseline prevalence prior to vaccination and the WHO goal.

The use of mixture density networks in the emulation of complex epidemiological individual-based models

Complex, highly-computational, individual-based models are abundant in epidemiology. For epidemics such as macro-parasitic diseases, detailed modelling of human behaviour and pathogen life-cycle are required in order to produce accurate results. This can often lead to models that are computationally-expensive to analyse and perform model fitting, and often require many simulation runs in order to build up sufficient statistics. Emulation can provide a more computationally-efficient output of the individual-based model, by approximating it using a statistical model. Previous work has used Gaussian processes (GPs) in order to achieve this, but these can not deal with multi-modal, heavy-tailed, or discrete distributions. Here, we introduce the concept of a mixture density network (MDN) in its application in the emulation of epidemiological models. MDNs incorporate both a mixture model and a neural network to provide a flexible tool for emulating a variety of models and outputs. We develop an MDN emulation methodology and demonstrate its use on a number of simple models incorporating both normal, gamma and beta distribution outputs. We then explore its use on the stochastic SIR model to predict the final size distribution and infection dynamics. MDNs have the potential to faithfully reproduce multiple outputs of an individual-based model and allow for rapid analysis from a range of users. As such, an open-access library of the method has been released alongside this manuscript.

Infectious disease modellers have a growing need to expose their models to a variety of stakeholders in interactive, engaging ways that allow them to explore different scenarios. This approach can come with a considerable computational cost that motivates providing a simpler representation of the complex model. We propose the use of mixture density networks as a solution to this problem. MDNs are highly flexible, deep neural network-based models that can emulate a variety of data, including counts and over-dispersion. We explore their use firstly through emulating a negative binomial distribution, which arises in many places in ecology and parasite epidemiology. Then, we explore the approach using a stochastic SIR model. We also provide an accompanying Python library with code for all examples given in the manuscript. We believe that the use of emulation will provide a method to package an infectious disease model such that it can be disseminated to the widest audience possible.

Data-driven modelling and spatial complexity supports heterogeneity-based integrative management for eliminating Simulium neavei-transmitted river blindness

Concern is emerging regarding the challenges posed by spatial complexity for modelling and managing the area-wide elimination of parasitic infections. While this has led to calls for applying heterogeneity-based approaches for addressing this complexity, questions related to spatial scale, the discovery of locally-relevant models, and its interaction with options for interrupting parasite transmission remain to be resolved. We used a data-driven modelling framework applied to infection data gathered from different monitoring sites to investigate these questions in the context of understanding the transmission dynamics and efforts to eliminate Simulium neavei- transmitted onchocerciasis, a macroparasitic disease that causes river blindness in Western Uganda and other regions of Africa. We demonstrate that our Bayesian-based data-model assimilation technique is able to discover onchocerciasis models that reflect local transmission conditions reliably. Key management variables such as infection breakpoints and required durations of drug interventions for achieving elimination varied spatially due to site-specific parameter constraining; however, this spatial effect was found to operate at the larger focus level, although intriguingly including vector control overcame this variability. These results show that data-driven modelling based on spatial datasets and model-data fusing methodologies will be critical to identifying both the scale-dependent models and heterogeneity-based options required for supporting the successful elimination of S. neavei-borne onchocerciasis.

Discovery and Optimization of a Compound Series Active against Trypanosoma cruzi, the Causative Agent of Chagas Disease

Chagas disease is caused by the protozoan parasite Trypanosoma cruzi. It is endemic in South and Central America and recently has been found in other parts of the world, due to migration of chronically infected patients. The current treatment for Chagas disease is not satisfactory, and there is a need for new treatments. In this work, we describe the optimization of a hit compound resulting from the phenotypic screen of a library of compounds against T. cruzi. The compound series was optimized to the level where it had satisfactory pharmacokinetics to allow an efficacy study in a mouse model of Chagas disease. We were able to demonstrate efficacy in this model, although further work is required to improve the potency and selectivity of this series.

Zoonotic transmission of intestinal helminths in southeast Asia: Implications for control and elimination

Intestinal helminths are extremely widespread and highly prevalent infections of humans, particularly in rural and poor urban areas of low and middle-income countries. These parasites have chronic and often insidious effects on human health and child development including abdominal problems, anaemia, stunting and wasting. Certain animals play a fundamental role in the transmission of many intestinal helminths to humans. However, the contribution of zoonotic transmission to the overall burden of human intestinal helminth infection and the relative importance of different animal reservoirs remains incomplete. Moreover, control programmes and transmission models for intestinal helminths often do not consider the role of zoonotic reservoirs of infection. Such reservoirs will become increasingly important as control is scaled up and there is a move towards interruption and even elimination of parasite transmission. With a focus on southeast Asia, and the Philippines in particular, this review summarises the major zoonotic intestinal helminths, risk factors for infection and highlights knowledge gaps related to their epidemiology and transmission. Various methodologies are discussed, including parasite genomics, mathematical modelling and socio-economic analysis, that could be employed to improve understanding of intestinal helminth spread, reservoir attribution and the burden associated with infection, as well as assess effectiveness of interventions. For sustainable control and ultimately elimination of intestinal helminths, there is a need to move beyond scheduled mass deworming and to consider animal and environmental reservoirs. A One Health approach to control of intestinal helminths is proposed, integrating interventions targeting humans, animals and the environment, including improved access to water, hygiene and sanitation. This will require coordination and collaboration across different sectors to achieve best health outcomes for all.

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.

Policy Recommendations From Transmission Modeling for the Elimination of Visceral Leishmaniasis in the Indian Subcontinent

Background

Visceral leishmaniasis (VL) has been targeted by the World Health Organization (WHO) and 5 countries in the Indian subcontinent for elimination as a public health problem. To achieve this target, the WHO has developed guidelines consisting of 4 phases of different levels of interventions, based on vector control through indoor residual spraying of insecticide (IRS) and active case detection (ACD). Mathematical transmission models of VL are increasingly used for planning and assessing the efficacy of interventions and evaluating the intensity and timescale required to achieve the elimination target.

Methods

This paper draws together the key policy-relevant conclusions from recent transmission modeling of VL, and presents new predictions for VL incidence under the interventions recommended by the WHO using the latest transmission models.

Results

The model predictions suggest that the current WHO guidelines should be sufficient to reach the elimination target in areas that had medium VL endemicities (up to 5 VL cases per 10000 population per year) prior to the start of interventions. However, additional interventions, such as extending the WHO attack phase (intensive IRS and ACD), may be required to bring forward elimination in regions with high precontrol endemicities, depending on the relative infectiousness of different disease stages.

Conclusions

The potential hurdle that asymptomatic and, in particular, post-kala-azar dermal leishmaniasis cases may pose to reaching and sustaining the target needs to be addressed. As VL incidence decreases, the pool of immunologically naive individuals will grow, creating the potential for new outbreaks.

Investigating the Effectiveness of Current and Modified World Health Organization Guidelines for the Control of Soil-Transmitted Helminth Infections

Background

Considerable efforts have been made to better understand the effectiveness of large-scale preventive chemotherapy therapy for the control of morbidity caused by infection with soil-transmitted helminths (STHs): Ascaris lumbricoides, Trichuris trichiura, and the 2 hookworm species, Necator americanus and Ancylostoma duodenale. Current World Health Organization (WHO) guidelines for STH control include mass drug administration (MDA) programs based on prevalence measurements, aiming at reducing morbidity in pre–school-aged children (pre-SAC) and school-aged children (SAC) by lowering the prevalence of moderate- to heavy-intensity infections to <1%.

Methods

We project the likely impact of following the current WHO guidelines and assess whether the WHO morbidity goals will be achieved across a range of transmission settings. We also investigate modifications that could be made to the current WHO treatment guidelines, and project their potential impacts in achieving morbidity and transmission control.

Results

While the standard guidelines are sufficient at low transmission levels, community-wide treatment (ie, involving pre-SAC, SAC, and adults) is essential if WHO morbidity goals are to be met in moderate- to high-transmission settings. Moreover, removing the recommendation of decreasing the treatment frequency at midline (5–6 years after the start of MDA) further improves the likelihood of achieving morbidity control in SAC.

Conclusions

We meld analyses based on 2 mathematical models of parasite transmission and control by MDA for the dominant STH species, to generate a unified treatment approach applicable across all settings, regardless of which STH infection is most common. We recommend clearly defined changes to the current WHO guidelines.

Are Alternative Strategies Required to Accelerate the Global Elimination of Lymphatic Filariasis? Insights From Mathematical Models

Background

With the 2020 target year for elimination of lymphatic filariasis (LF) approaching, there is an urgent need to assess how long mass drug administration (MDA) programs with annual ivermectin + albendazole (IA) or diethylcarbamazine + albendazole (DA) would still have to be continued, and how elimination can be accelerated. We addressed this using mathematical modeling.

Methods

We used 3 structurally different mathematical models for LF transmission (EPIFIL, LYMFASIM, TRANSFIL) to simulate trends in microfilariae (mf) prevalence for a range of endemic settings, both for the current annual MDA strategy and alternative strategies, assessing the required duration to bring mf prevalence below the critical threshold of 1%.

Results

Three annual MDA rounds with IA or DA and good coverage (≥65%) are sufficient to reach the threshold in settings that are currently at mf prevalence <4%, but the required duration increases with increasing mf prevalence. Switching to biannual MDA or employing triple-drug therapy (ivermectin, diethylcarbamazine, and albendazole [IDA]) could reduce program duration by about one-third. Optimization of coverage reduces the time to elimination and is particularly important for settings with a history of poorly implemented MDA (low coverage, high systematic noncompliance).

Conclusions

Modeling suggests that, in several settings, current annual MDA strategies will be insufficient to achieve the 2020 LF elimination targets, and programs could consider policy adjustment to accelerate, guided by recent monitoring and evaluation data. Biannual treatment and IDA hold promise in reducing program duration, provided that coverage is good, but their efficacy remains to be confirmed by more extensive field studies.

Insights from mathematical modelling and quantitative analysis on the proposed WHO 2030 targets for visceral leishmaniasis on the Indian subcontinent

Visceral leishmaniasis (VL) is a neglected tropical disease (NTD) caused by Leishmania protozoa that are transmitted by female sand flies. On the Indian subcontinent (ISC), VL is targeted by the World Health Organization (WHO) for elimination as a public health problem by 2020, which is defined as <1 VL case (new and relapse) per 10,000 population at district level in Nepal and sub-district level in Bangladesh and India. WHO is currently in the process of formulating 2030 targets, asking whether to maintain the 2020 target or to modify it, while adding a target of zero mortality among detected cases. The NTD Modelling Consortium has developed various mathematical VL transmission models to gain insight into the transmission dynamics of VL, identify the main knowledge gaps, and predict the feasibility of achieving and sustaining the targets by simulating the impact of varying intervention strategies. According to the models, the current target is feasible at the appropriate district/sub-district level in settings with medium VL endemicities (up to 5 reported VL cases per 10,000 population per year) prior to the start of the interventions. However, in settings with higher pre-control endemicities, additional efforts may be required. We also highlight the risk that those with post-kala-azar dermal leishmaniasis (PKDL) may pose to reaching and sustaining the VL targets, and therefore advocate adding control of PKDL cases to the new 2030 targets. Spatial analyses revealed that local hotspots with high VL incidence remain. We warn that the current target provides a perverse incentive to not detect/report cases as the target is approached, posing a risk for truly achieving elimination as a public health problem although this is taken into consideration by the WHO procedures for validation. Ongoing modelling work focuses on the risk of recrudescence when interventions are relaxed after the elimination target has been achieved.

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.

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

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

Evaluating the Evidence for Lymphatic Filariasis Elimination

In the global drive for elimination of lymphatic filariasis (LF), 15 countries have achieved validation of elimination as a public health problem (EPHP). Recent empirical evidence has demonstrated that EPHP does not always lead to elimination of transmission (EOT). Here we show how the probability of elimination explicitly depends on key biological parameters, many of which have been poorly characterized, leading to a poor evidence base for the elimination threshold. As more countries progress towards EPHP it is essential that this process is well-informed, as prematurely halting treatment and surveillance programs could pose a serious threat to global progress. We highlight that refinement of the weak empirical evidence base is vital to understand drivers of elimination and inform long-term policy.

Developing the first national database and map of lymphatic filariasis clinical cases in Bangladesh: Another step closer to the elimination goals

Background

The Bangladesh Lymphatic Filariasis (LF) Elimination Programme has made significant progress in interrupting transmission through mass drug administration (MDA) and has now focussed its efforts on scaling up managing morbidity and preventing disability (MMDP) activities to deliver the minimum package of care to people affected by LF clinical conditions. This paper highlights the Bangladesh LF Programme’s success in conducting a large-scale cross-sectional survey to determine the number of people affected by lymphoedema and hydrocoele, which enabled clinical risk maps to be developed for targeted interventions across the 34 endemic districts (19 high endemic; 15 low endemic).

Methodology/Principal findings

In the 19 high endemic districts, 8,145 community clinic staff were trained to identify and report patients in their catchment area. In the 15 low endemic districts, a team of 10 trained field assistants conducted active case finding with cases reported via a SMS mHealth tool. Disease burden and prevalence maps were developed, with morbidity hotspots identified at sub-district level based on a combination of the highest prevalence rates per 100,000 and case-density rates per square kilometre (km²). The relationship between morbidity and baseline microfilaria (mf) prevalence was also examined. In total 43,678 cases were identified in the 19 high endemic districts; 30,616 limb lymphoedema (70.1%; female 55.3%), 12,824 hydrocoele (29.4%), and 238 breast/female genital swelling (0.5%). Rangpur Division reported the highest cases numbers and prevalence of lymphoedema (26,781 cases, 195 per 100,000) and hydrocoele (11661 cases, 169.6 per 100,000), with lymphoedema predominately affecting females (n = 21,652). Rangpur and Lalmonirhat Districts reported the highest case numbers (n = 11,199), and prevalence (569 per 100,000) respectively, with five overlapping lymphoedema and hydrocoele sub-district hotspots. In the 15 low endemic districts, 732 cases were identified; 661 lymphoedema (90.2%; female 39.6%), 56 hydrocoele (7.8%), and 15 both conditions (2.0%). Spearman’s correlation analysis found morbidity and mf prevalence significantly positively correlated (r = 0.904; p<0.01).

Conclusions/Significance

The Bangladesh LF Programme has developed one of the largest, most comprehensive country databases on LF clinical conditions in the world. It provides an essential database for health workers to identify local morbidity hotspots, deliver the minimum package of care, and address the dossier elimination requirements.

The Global Programme to Eliminate Lymphatic Filariasis (GPELF) requires lymphatic filariasis (LF) endemic countries, such as Bangladesh, to estimate the number of lymphoedema and hydrocoele cases in order to deliver the minimum package of care required to control morbidity and reduce patient suffering. This paper highlights the Bangladesh LF Elimination Programme’s progress in training more than 8000 community health workers to identify more than 44,000 cases across 34 endemic districts where approximately 70 million people are at risk. The morbidity data collected enabled the creation of a national database and a series of risk maps of lymphoedema and hydrocoele to be developed, which highlighted the significant burden in northern Rangpur Division, especially of lymphoedema among female patients. The Bangladesh LF Elimination Programme’s efforts to identify LF cases across all endemic districts represents one of the most comprehensive national databases on LF clinical cases in the world. It provides an informative database for health workers to use in the delivery of the minimum package of care and a template for other countries to adopt and develop national strategies to manage morbidity and prevent disability as recommended by GPELF.

Strategies for tackling Taenia solium taeniosis/cysticercosis: A systematic review and comparison of transmission models, including an assessment of the wider Taeniidae family transmission models

Background

The cestode Taenia solium causes the neglected (zoonotic) tropical disease cysticercosis, a leading cause of preventable epilepsy in endemic low and middle-income countries. Transmission models can inform current scaling-up of control efforts by helping to identify, validate and optimise control and elimination strategies as proposed by the World Health Organization (WHO).

Methodology/Principal findings

A systematic literature search was conducted using the PRISMA approach to identify and compare existing T. solium transmission models, and related Taeniidae infection transmission models. In total, 28 modelling papers were identified, of which four modelled T. solium exclusively. Different modelling approaches for T. solium included deterministic, Reed-Frost, individual-based, decision-tree, and conceptual frameworks. Simulated interventions across models agreed on the importance of coverage for impactful effectiveness to be achieved.

Other Taeniidae infection transmission models comprised force-of-infection (FoI), population-based (mainly Echinococcus granulosus) and individual-based (mainly E. multilocularis) modelling approaches. Spatial structure has also been incorporated (E. multilocularis and Taenia ovis) in recognition of spatial aggregation of parasite eggs in the environment and movement of wild animal host populations.

Conclusions/Significance

Gaps identified from examining the wider Taeniidae family models highlighted the potential role of FoI modelling to inform model parameterisation, as well as the need for spatial modelling and suitable structuring of interventions as key areas for future T. solium model development. We conclude that working with field partners to address data gaps and conducting cross-model validation with baseline and longitudinal data will be critical to building consensus-led and epidemiological setting-appropriate intervention strategies to help fulfil the WHO targets.

Taenia solium infection in humans (taeniosis and neurocysticercosis) and pigs (cysticercosis) presents a significant global public health and economic challenge. The World Health Organization has called for validated strategies and wider consensus on which strategies are suitable for different epidemiological settings to support successful T. solium control and elimination efforts. Transmission models can be used to inform these strategies. Therefore, a modelling review was undertaken to assess the current state and gaps relating to T. solium epidemiological modelling. The literature surrounding models for other Taeniidae family infections was also considered, identifying approaches to aid further development of existing T. solium models. A variety of different modelling approaches have been used for T. solium including differences in structural and parametric assumptions associated with T. solium transmission biology. Despite these differences, all models agreed on the importance of coverage on intervention effectiveness. Other Taeniidae family models highlighted the need for incorporating spatial structure when necessary to capture aggregation of transmission stages in the environment and movement of animal hosts.

Insecticide-impregnated dog collars reduce infantile clinical visceral leishmaniasis under operational conditions in NW Iran: A community-wide cluster randomised trial

OBJECTIVE

To assess the effectiveness of community-wide deployment of insecticide-impregnated collars for dogs- the reservoir of Leishmania infantum-to reduce infantile clinical visceral leishmaniasis (VL).

METHODS

A pair matched-cluster randomised controlled trial involving 40 collared and 40 uncollared control villages (161 [95% C.L.s: 136, 187] children per cluster), was designed to detect a 55% reduction in 48 month confirmed VL case incidence. The intervention study was designed by the authors, but implemented by the Leishmaniasis Control Program in NW Iran, from 2002 to 2006.

RESULTS

The collars provided 50% (95% C.I. 17·8%-70·0%) protection against infantile VL incidence (0·95/1000/yr compared to 1·75/1000/yr). Reductions in incidence were observed across 76% (22/29) of collared villages compared to pair-matched control villages, with 31 fewer cases by the end of the trial period. In 11 paired villages, no further cases were recorded post-intervention, whereas in 7 collared villages there were 9 new clinical cases relative to controls. Over the trial period, 6,835 collars were fitted at the beginning of the 4 month sand fly season, of which 6.9% (95% C.I. 6.25%, 7.56%) were lost but rapidly replaced. Collar coverage (percent dogs collared) per village varied between 66% and 100%, with a mean annual coverage of 87% (95% C.I. 84·2, 89·0%). The variation in post-intervention clinical VL incidence was not associated with collar coverage, dog population size, implementation logistics, dog owner compliance, or other demographic variables tested. Larger reductions and greater persistence in incident case numbers (indicative of transmission) were observed in villages with higher pre-existing VL case incidence.

CONCLUSION

Community-wide deployment of collars can provide a significant level of protection against infantile clinical VL, achieved in this study by the local VL Control Program, demonstrating attributes desirable of a sustainable public health program. The effectiveness is not dissimilar to the community-level protection provided against human and canine infection with L. infantum.

Age trends in asymptomatic and symptomatic Leishmania donovani infection in the Indian subcontinent: A review and analysis of data from diagnostic and epidemiological studies

BACKGROUND

Age patterns in asymptomatic and symptomatic infection with Leishmania donovani, the causative agent of visceral leishmaniasis (VL) in the Indian subcontinent (ISC), are currently poorly understood. Age-stratified serology and infection incidence have been used to assess transmission levels of other diseases, which suggests that they may also be of use for monitoring and targeting control programmes to achieve elimination of VL and should be included in VL transmission dynamic models. We therefore analysed available age-stratified data on both disease incidence and prevalence of immune markers with the aim of collating the currently available data, estimating rates of infection, and informing modelling and future data collection.

METHODOLOGY/PRINCIPAL FINDINGS

A systematic literature search yielded 13 infection prevalence and 7 VL incidence studies meeting the inclusion criteria. Statistical tests were performed to identify trends by age, and according to diagnostic cut-off. Simple reversible catalytic models with age-independent and age-dependent infection rates were fitted to the prevalence data to estimate infection and reversion rates, and to test different hypotheses about the origin of variation in these rates. Most of the studies showed an increase in infection prevalence with age: from ≲10% seroprevalence (<20% Leishmanin skin test (LST) positivity) for 0-10-year-olds to >10% seroprevalence (>20% LST-positivity) for 30-40-year-olds, but overall prevalence varied considerably between studies. VL incidence was lower amongst 0-5-year-olds than older age groups in most studies; most showing a peak in incidence between ages 5 and 20. The age-independent catalytic model provided the best overall fit to the infection prevalence data, but the estimated rates for the less parsimonious age-dependent model were much closer to estimates from longitudinal studies, suggesting that infection rates may increase with age.

CONCLUSIONS/SIGNIFICANCE

Age patterns in asymptomatic infection prevalence and VL incidence in the ISC vary considerably with geographical location and time period. The increase in infection prevalence with age and peaked age-VL-incidence distribution may be due to lower exposure to infectious sandfly bites in young children, but also suggest that acquired immunity to the parasite increases with age. However, poor standardisation of serological tests makes it difficult to compare data from different studies and draw firm conclusions about drivers of variation in observed age patterns.

Visceral leishmaniasis: Spatiotemporal heterogeneity and drivers underlying the hotspots in Muzaffarpur, Bihar, India

BACKGROUND

Despite the overall decrease in visceral leishmaniasis (VL) incidence on the Indian subcontinent, there remain spatiotemporal clusters or 'hotspots' of new cases. The characteristics of these hotspots, underlying transmission dynamics, and their importance for shaping control strategies are not yet fully understood and are investigated in this study for a VL endemic area of ~100,000 inhabitants in Bihar, India between 2007-2015.

METHODOLOGY/PRINCIPAL FINDINGS

VL incidence (cases/10,000/year) dropped from 12.3 in 2007 to 0.9 in 2015, which is just below the World Health Organizations' threshold for elimination as a public health problem. Clustering of VL was assessed between subvillages (hamlets), using multiple geospatial and (spatio)temporal autocorrelation and hotspot analyses. One to three hotspots were identified each year, often persisting for 1-5 successive years with a modal radius of ~500m. The relative risk of having VL was 5-86 times higher for inhabitants of hotspots, compared to those living outside hotspots. Hotspots harbour significantly more households from the two lowest asset quintiles (as proxy for socio-economic status). Overall, children and young adelescents (5-14 years) have the highest risk for VL, but within hotspots and at the start of outbreaks, older age groups (35+ years) show a comparable high risk.

CONCLUSIONS/SIGNIFICANCE

This study demonstrates significant spatiotemporal heterogeneity in VL incidence at subdistrict level. The association between poverty and hotspots confirms that VL is a disease of 'the poorest of the poor' and age patterns suggest a potential role of waning immunity as underlying driver of hotspots. The recommended insecticide spraying radius of 500m around detected VL cases corresponds to the modal hotspot radius found in this study. Additional data on immunity and asymptomatic infection, and the development of spatiotemporally explicit transmission models that simulate hotspot dynamics and predict the impact of interventions at the smaller geographical scale will be crucial tools in sustaining elimination.

A comparison of two mathematical models of the impact of mass drug administration on the transmission and control of schistosomiasis

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This paper compares two mathematical models describing the transmission dynamics of schistosome infection and the impact of mass drug administration.

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The models differ structurally in a number of ways, including the dynamics of the intermediate snail host and the treatment of adult worms within the human host.

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The models are validated against data taken from a mass-drug administration trial in Mozambique.

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The differences between the model predictions and the data are discussed in the context of the structural differences between the models.

The predictions of two mathematical models describing the transmission dynamics of schistosome infection and the impact of mass drug administration are compared. The models differ in their description of the dynamics of the parasites within the host population and in their representation of the stages of the parasite lifecycle outside of the host. Key parameters are estimated from data collected in northern Mozambique from 2011 to 2015. This type of data set is valuable for model validation as treatment prior to the study was minimal. Predictions from both models are compared with each other and with epidemiological observations. Both models have difficulty matching both the intensity and prevalence of disease in the datasets and are only partially successful at predicting the impact of treatment. The models also differ from each other in their predictions, both quantitatively and qualitatively, of the long-term impact of 10 years’ school-based mass drug administration. We trace the dynamical differences back to basic assumptions about worm aggregation, force of infection and the dynamics of the parasite in the snail population in the two models and suggest data which could discriminate between them. We also discuss limitations with the datasets used and ways in which data collection could be improved.

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.

Comparison and validation of two mathematical models for the impact of mass drug administration on Ascaris lumbricoides and hookworm infection

The predictions of two mathematical models of the transmission dynamics of Ascaris lumbricoides and hookworm infection and the impact of mass drug administration (MDA) are compared, using data from India. One model has an age structured partial differential equation (PDE) deterministic framework for the distribution of parasite numbers per host and sexual mating. The second model is an individual-based stochastic model. Baseline data acquired prior to treatment are used to estimate key transmission parameters, and forward projections are made, given the known MDA population coverage. Predictions are compared with observed post-treatment epidemiological patterns. The two models could equally well predict the short-term impact of deworming on A. lumbricoides and hookworm infection levels, despite being fitted to different subsets and/or summary statistics of the data. As such, the outcomes give confidence in their use as aids to policy formulation for the use of PCT to control A. lumbricoides and hookworm infection. The models further largely agree in a qualitative sense on the added benefit of semi-annual vs. annual deworming and targeting of the entire population vs. only children, as well as the potential for interruption of transmission. Further, this study also illustrates that long-term predictions are sensitive to modelling assumptions about which age groups contribute most to transmission, which depends on human demography and age-patterns in exposure and contribution to the environmental reservoir of infection, the latter being notoriously difficult to empirically quantify.

Comparison and validation of two computational models of Chagas disease: A thirty year perspective from Venezuela

BACKGROUND

Mathematical models can help aid public health responses to Chagas disease. Models are typically developed to fulfill a particular need, and comparing outputs from different models addressing the same question can help identify the strengths and weaknesses of the models in answering particular questions, such as those for achieving the 2020 goals for Chagas disease.

METHODS

Using two separately developed models (PHICOR/CIDMA model and Princeton model), we simulated dynamics for domestic transmission of Trypanosoma cruzi (T. cruzi). We compared how well the models targeted the last 9 years and last 19 years of the 1968-1998 historical seroprevalence data from Venezuela.

RESULTS

Both models were able to generate the T. cruzi seroprevalence for the next time period within reason to the historical data. The PHICOR/CIDMA model estimates of the total population seroprevalence more closely followed the trends seen in the historic data, while the Princeton model estimates of the age-specific seroprevalence more closely followed historic trends when simulating over 9 years. Additionally, results from both models overestimated T. cruzi seroprevalence among younger age groups, while underestimating the seroprevalence of T. cruzi in older age groups.

CONCLUSION

The PHICOR/CIDMA and Princeton models differ in level of detail and included features, yet both were able to generate the historical changes in T. cruzi seroprevalence in Venezuela over 9 and 19-year time periods. Our model comparison has demonstrated that different model structures can be useful in evaluating disease transmission dynamics and intervention strategies.