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

Using Passive Surveillance to Maintain Elimination as a Public Health Problem for Neglected Tropical Diseases: A Model-Based Exploration

BACKGROUND

Great progress is being made toward the goal of elimination as a public health problem for neglected tropical diseases such as leprosy, human African trypanosomiasis, Buruli ulcer, and visceral leishmaniasis, which relies on intensified disease management and case finding. However, strategies for maintaining this goal are still under discussion. Passive surveillance is a core pillar of a long-term, sustainable surveillance program.

METHODS

We use a generic model of disease transmission with slow epidemic growth rates and cases detected through severe symptoms and passive detection to evaluate under what circumstances passive detection alone can keep transmission under control.

RESULTS

Reducing the period of infectiousness due to decreasing time to treatment has a small effect on reducing transmission. Therefore, to prevent resurgence, passive surveillance needs to be very efficient. For some diseases, the treatment time and level of passive detection needed to prevent resurgence is unlikely to be obtainable.

CONCLUSIONS

The success of a passive surveillance program crucially depends on what proportion of cases are detected, how much of their infectious period is reduced, and the underlying reproduction number of the disease. Modeling suggests that relying on passive detection alone is unlikely to be enough to maintain elimination goals.

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

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

Forecasting models for leprosy cases: a scoping review protocol

INTRODUCTION

Leprosy is a neglected tropical disease caused by Mycobacterium leprae that mainly affects the skin, the peripheral nerves, the mucosa of the upper respiratory tract and the eyes. Mathematical models and statistical methodologies could play an important role in decision-making and help maintain the gains in elimination programmes. Various models for predicting leprosy cases have been reported in the literature, but they have different settings and distinct approaches to predicting the cases. This study describes the protocol for a scoping review to identify and synthesise information from studies using models to forecast leprosy cases.

METHODS AND ANALYSIS

A scoping review methodology will be applied following the Joanna Briggs Institute methodology for scoping reviews and will be reported according to Preferred Reporting Items for Systematic Reviews and Meta-analysis Extension for Scoping Reviews. We will perform a systematic search from when each database started until April 2022 and we will include the following electronic databases: MEDLINE via PubMed, Embase, Cochrane Library and Latin American and Caribbean Health Science Literature Database. Data will be extracted and recorded on a calibrated predefined data form and will be presented in a tabular form accompanied by a descriptive summary. The Prediction Model Study Risk of Bias Assessment Tool (PROBAST) will be used.

ETHICS AND DISSEMINATION

No ethical approval is required for this study. This scoping review will identify and map the methodological and other characteristics of modelling studies predicting leprosy cases. We hope that the review will contribute to scientific knowledge in this area and act as a basis for researchers designing and conducting leprosy models. This information can also be used to enhance national surveillance systems and to target specific policies. The protocol and consequent publications of this scoping review will be disseminated through peer-reviewed publications and policy briefs.

SYSTEMATIC REVIEW REGISTRATION

This scoping review was registered in the Open Science Framework (https://doi.org/10.17605/OSF.IO/W9375).

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.