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

A modelling analysis of a new multi-stage pathway for classifying achievement of public health milestones for leprosy

Several countries have come close to eliminating leprosy, but leprosy cases continue to be detected at low levels. Due to the long, highly variable delay from infection to detection, the relationship between observed cases and transmission is uncertain. The World Health Organization's new technical guidance provides a path for countries to reach elimination. We use a simple probabilistic model to simulate the stochastic dynamics of detected cases as transmission declines, and evaluate progress through the new public health milestones. In simulations where transmission is halted, 5 years of zero incidence in autochthonous children, combined with 3 years of zero incidence in all ages is a flawed indicator that transmission has halted (54% correctly classified). A further 10 years of only occasional sporadic cases is associated with a high probability of having interrupted transmission (99%). If, however, transmission continues at extremely low levels, it is possible that cases could be misidentified as historic cases from the tail of the incubation period distribution, although misleadingly achieving all three milestones is unlikely (less than 1% probability across a 15-year period of ongoing low-level transmission). These results demonstrate the feasibility and challenges of a phased progression of milestones towards interruption of transmission, allowing assessment of programme status. 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.

Fine-scale-mapping of Schistosoma haematobium infections at the school and community levels and intermediate host snail abundance in the north of Pemba Island: baseline cross-sectional survey findings before the onset of a 3-year intervention study

Background

Schistosomiasis elimination has gained renewed priority in the WHO guidance documents published in 2020 and 2022. The SchistoBreak project, implemented in Pemba, Tanzania between 2020 and 2024, aims to assess new tools and strategies for shifting from elimination as a public health problem towards interruption of transmission. Here we report our baseline findings and discuss implications for future interventions.

Methods

In 2020, human water contact sites (HWCSs) in the study area were geolocated and snail surveys were conducted. A parasitological and questionnaire cross-sectional baseline survey was implemented in 20 communities and their 16 primary schools between November 2020 and February 2021. Urine samples were collected at the school and household levels from individuals aged ≥ 4 years. Schistosoma haematobium infection was detected by urine filtration microscopy. Snail, parasitological and questionnaire-derived data were analyzed descriptively, spatially and with generalized estimated equation models.

Results

The intermediate host snail Bulinus globosus was detected in 19.8% (33/167) of HWCSs. The overall S. haematobium prevalence was 1.2% (26/2196) in school-aged children and 0.8% (31/3893) in community members, with 0.2% (4/2196) and 0.1% (3/3893) heavy-intensity infections, respectively. Children who studied < 1 km away from HWCSs with B. globosus had significantly higher odds for a S. haematobium infection than those attending a school located > 2 km away (odds ratio [OR]: 5.0; 95% confidence interval [CI]: 2.3–11.1). Individuals living in a house located < 1 km away from HWCSs with B. globosus had higher odds than those residing in > 2 km distance (OR: 18.0; 95% CI: 2.9–111.0). Self-reported praziquantel treatment coverage was 83.2% (2015/2423) in schoolchildren in the mass drug administration (MDA) conducted in August 2020. Coverage among adult community members was 59.9% (574/958), but only 34.8% (333/958) took praziquantel correctly.

Conclusions

While the S. haematobium prevalence is very low in Pemba, there are many HWCSs with B. globosus situated close to schools or houses that pose a considerable risk of recrudescence. To maintain and accelerate the progress towards interruption of transmission, targeted and cost-effective interventions that are accepted by the community are needed; for example, snail control plus focal MDA, or test-and-treat in schools and households near infested waterbodies.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05404-6.

The efficacy of sampling strategies for estimating scabies prevalence

Background

Estimating community level scabies prevalence is crucial for targeting interventions to areas of greatest need. The World Health Organisation recommends sampling at the unit of households or schools, but there is presently no standardised approach to scabies prevalence assessment. Consequently, a wide range of sampling sizes and methods have been used. As both prevalence and drivers of transmission vary across populations, there is a need to understand how sampling strategies for estimating scabies prevalence interact with local epidemiology to affect the accuracy of prevalence estimates.

Methods

We used a simulation-based approach to compare the efficacy of different scabies sampling strategies. First, we generated synthetic populations broadly representative of remote Australian Indigenous communities and assigned a scabies status to individuals to achieve a specified prevalence using different assumptions about scabies epidemiology. Second, we calculated an observed prevalence for different sampling methods and sizes.

Results

The distribution of prevalence in subpopulation groups can vary substantially when the underlying scabies assignment method changes. Across all of the scabies assignment methods combined, the simple random sampling method produces the narrowest 95% confidence interval for all sample sizes. The household sampling method introduces higher variance compared to simple random sampling when the assignment of scabies includes a household-specific component. The school sampling method overestimates community prevalence when the assignment of scabies includes an age-specific component.

Discussion

Our results indicate that there are interactions between transmission assumptions and surveillance strategies, emphasizing the need for understanding scabies transmission dynamics. We suggest using the simple random sampling method for estimating scabies prevalence. Our approach can be adapted to various populations and diseases.

Scabies is a parasitic infestation that is commonly observed in disadvantaged populations. A wide range of sampling sizes and methods have been used to estimate scabies prevalence. With differing key drivers of transmission and varying prevalence across populations, it can be challenging to determine an effective sampling strategy. In this study, we propose a simulation approach to compare the efficacy of different sampling methods and sizes. First, we generate synthetic populations and then assign a scabies status to individuals to achieve a specified prevalence using different assumptions about scabies epidemiology. Second, we calculate an observed prevalence for different sampling methods and sizes. Our results indicate that there are interactions between transmission assumptions and surveillance strategies. We suggest using the simple random sampling method for estimating prevalence as it produces the narrowest 95% confidence interval for all sampling sizes. We propose guidelines for determining a sample size to achieve a desired level of precision in 95 out 100 samples, given estimates of the population size and a priori estimates of true prevalence. Our approach can be adapted to various populations, informing an appropriate sampling strategy for estimating scabies prevalence with confidence.

Towards soil-transmitted helminths transmission interruption: The impact of diagnostic tools on infection prediction in a low intensity setting in Southern Mozambique

World Health Organization goals against soil-transmitted helminthiases (STH) are pointing towards seeking their elimination as a public health problem: reducing to less than 2% the proportion of moderate and heavy infections. Some regions are reaching WHO goals, but transmission could rebound if strategies are discontinued without an epidemiological evaluation. For that, sensitive diagnostic methods to detect low intensity infections and localization of ongoing transmission are crucial. In this work, we estimated and compared the STH infection as obtained by different diagnostic methods in a low intensity setting. We conducted a cross-sectional study enrolling 792 participants from a district in Mozambique. Two stool samples from two consecutive days were collected from each participant. Samples were analysed by Telemann, Kato-Katz and qPCR for STH detection. We evaluated diagnostic sensitivity using a composite reference standard. By geostatistical methods, we estimated neighbourhood prevalence of at least one STH infection for each diagnostic method. We used environmental, demographical and socioeconomical indicators to account for any existing spatial heterogeneity in infection. qPCR was the most sensitive technique compared to composite reference standard: 92% (CI: 83%- 97%) for A. lumbricoides, 95% (CI: 88%- 98%) for T. trichiura and 95% (CI: 91%- 97%) for hookworm. qPCR also estimated the highest neighbourhood prevalences for at least one STH infection in a low intensity setting. While 10% of the neighbourhoods showed a prevalence above 20% when estimating with single Kato-Katz from one stool and Telemann from one stool, 86% of the neighbourhoods had a prevalence above 20% when estimating with qPCR. In low intensity settings, STH estimated prevalence of infection may be underestimated if based on Kato-Katz. qPCR diagnosis outperformed the microscopy methods. Thus, implementation of qPCR based predictive maps at STH control and elimination programmes would disclose hidden transmission and facilitate targeted interventions for transmission interruption.

Novel tools and strategies for breaking schistosomiasis transmission: study protocol for an intervention study

Background

Global elimination of schistosomiasis as a public health problem is set as target in the new World Health Organization’s Neglected Tropical Diseases Roadmap for 2030. Due to a long history of interventions, the Zanzibar islands of Tanzania have reached this goal since 2017. However, challenges occur on the last mile towards interruption of transmission. Our study will investigate new tools and strategies for breaking schistosomiasis transmission.

Methods

The study is designed as an intervention study, documented through repeated cross-sectional surveys (2020–2024). The primary endpoint will be the sensitivity of a surveillance-response approach to detect and react to outbreaks of urogenital schistosomiasis over three years of implementation. The surveys and multi-disciplinary interventions will be implemented in 20 communities in the north of Pemba island. In low-prevalence areas, surveillance-response will consist of active, passive and reactive case detection, treatment of positive individuals, and focal snail control. In hotspot areas, mass drug administration, snail control and behaviour change interventions will be implemented. Parasitological cross-sectional surveys in 20 communities and their main primary schools will serve to adapt the intervention approach annually and to monitor the performance of the surveillance-response approach and impact of interventions. Schistosoma haematobium infections will be diagnosed using reagent strips and urine filtration microscopy, and by exploring novel point-of-care diagnostic tests.

Discussion

Our study will shed light on the field applicability and performance of novel adaptive intervention strategies, and standard and new diagnostic tools for schistosomiasis elimination. The evidence and experiences generated by micro-mapping of S. haematobium infections at community level, micro-targeting of new adaptive intervention approaches, and application of novel diagnostic tools can guide future strategic plans for schistosomiasis elimination in Zanzibar and inform other countries aiming for interruption of transmission.

Trial registration ISRCTN, ISCRCTN91431493. Registered 11 February 2020, https://www.isrctn.com/ISRCTN91431493

Sustainable Surveillance of Neglected Tropical Diseases for the Post-Elimination Era

The World Health Organization’s (WHO’s) 2030 road map for neglected tropical diseases (NTDs) emphasizes the importance of strengthened, institutionalized “post-elimination” surveillance. The required shift from disease-siloed, campaign-based programming to routine, integrated surveillance and response activities presents epidemiological, logistical, and financial challenges, yet practical guidance on implementation is lacking. Nationally representative survey programs, such as demographic and health surveys (DHS), may offer a platform for the integration of NTD surveillance within national health systems and health information systems. Here, we describe characteristics of DHS and other surveys conducted within the WHO Africa region in terms of frequency, target populations, and sample types and discuss applicability for post-validation and post-elimination surveillance. Maximizing utility depends not only on the availability of improved diagnostics but also on better understanding of the spatial and temporal dynamics of transmission at low prevalence. To this end, we outline priorities for obtaining additional data to better characterize optimal post-elimination surveillance platforms.

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.

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.