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Retrospective cohort studies in Cameroon found an association between Onchocerca volvulus microfilarial load in childhood (measured in 1991–1993) and risk of developing epilepsy later in life (measured in 2017). We parameterised and integrated this relationship (across children aged 3–15 years) into the previously published, stochastic transmission model, EPIONCHO-IBM, for Simulium damnosum sensu lato-transmitted onchocerciasis. We simulated 19 years (1998–2017) of annual ivermectin mass drug administration (MDA) reflecting coverage in the study area, and modelled epilepsy prevalence and incidence. Scenario-based simulations of 25 years of (annual and biannual) MDA in hyper- and holoendemic settings, with 65% and 80% therapeutic coverage, were also conducted. EPIONCHO-IBM predicted 7.6% epilepsy prevalence (compared to 8.2% in the Cameroon study) and incidence of 317 cases/100,000 person-years (compared to 350). In hyperendemic areas, 25 years of biannual MDA (80% coverage) eliminated onchocerciasis-associated epilepsy (OAE) and protected untreated under-fives from its development. Strengthening onchocerciasis programmes, implementing alternative strategies, and evaluating treatment for under-fives and school-age children are crucial to prevent OAE in highly-endemic settings. Onchocerciasis is a vector-borne disease endemic to parts of sub-Saharan Africa and associated with substantial morbidity including reports of onchocerciasis-associated epilepsy. Here, the authors use mathematical modelling to assess the impact of community-directed treatment with ivermectin on onchocerciasis-associated epilepsy.

In onchocerciasis endemic areas in Africa, heterogenous biting rates by blackfly vectors on humans are assumed to partially explain age- and sex-dependent infection patterns with Onchocerca volvulus. To underpin these assumptions and further improve predictions made by onchocerciasis transmission models, demographic patterns in antibody responses to salivary antigens of Simulium damnosum s.l. are evaluated as a measure of blackfly exposure. Recently developed IgG and IgM anti-saliva immunoassays for S. damnosum s.l. were applied to blood samples collected from residents in four onchocerciasis endemic villages in Ghana. Demographic patterns in antibody levels according to village, sex and age were explored by fitting generalized linear models. Antibody levels varied between villages but showed consistent patterns with age and sex. Both IgG and IgM responses declined with increasing age. IgG responses were generally lower in males than in females and exhibited a steeper decline in adult males than in adult females. No sex-specific difference was observed in IgM responses. The decline in age-specific antibody patterns suggested development of immunotolerance or desensitization to blackfly saliva antigen in response to persistent exposure. The variation between sexes, and between adults and youngsters may reflect differences in behaviour influencing cumulative exposure. These measures of antibody acquisition and decay could be incorporated into onchocerciasis transmission models towards informing onchocerciasis control, elimination, and surveillance.

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.

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.

About the Authors: Matthew R. Behrend * E-mail: behrend04@gmail.com Affiliations Neglected Tropical Diseases, Bill & Melinda Gates Foundation, Seattle, Washington, United States of America, Blue Well 8, Seattle, Washington, United States of America ORCID logo http://orcid.org/0000-0002-5664-0520 María-Gloria Basáñez Affiliation: MRC Centre for Global Infectious Disease Analysis and London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom Jonathan I. D. Hamley Affiliation: MRC Centre for Global Infectious Disease Analysis and London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom Travis C. Porco Affiliation: Francis I. Proctor Foundation for Research in Ophthalmology, Department of Epidemiology and Biostatistics, and Department of Ophthalmology, University of California, San Francisco, United States of America Wilma A. Stolk Affiliation: Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands Martin Walker Affiliations London Centre for Neglected Tropical Disease Research, Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, Hertfordshire, United Kingdom, London Centre for Neglected Tropical Disease Research and Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom Sake J. de Vlas Affiliation: Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ORCID logo http://orcid.org/0000-0002-1830-5668 for the NTD Modelling Consortium Introduction The neglected tropical diseases (NTDs) thrive mainly among the poorest populations of the world. Onchocerciasis (a filarial disease caused by infection with Onchocerca volvulus and transmitted by blackfly, Simulium, vectors) probably provides the best example of impactful modelling, with its long history of using evidence—mostly from the ONCHOSIM and EPIONCHO transmission models [7]—to support decision-making within ongoing multicountry control initiatives (Table 1). Onchocerciasis modelling and policy impact. https://doi.org/10.1371/journal.pntd.0008033.t001 From the start of the NTD Modelling Consortium in 2015, there have been several other examples of impactful modelling, which could be divided over three major scales of operations: (1) developing WHO guidelines (e.g., for triple-drug therapy, with ivermectin, diethylcarbamazine, and albendazole, against lymphatic filariasis [16, 17]); (2) informing funding decisions for new intervention tools (e.g., the development of a schistosomiasis vaccine [18]); and (3) guiding within-country targeting of control (e.g., local vector control for human African trypanosomiasis in the Democratic Republic of the Congo [19, 20] and Chad [21]). Relative word frequencies are represented by size of the font. https://doi.org/10.1371/journal.pntd.0008033.g002 Scoring the guidance statements Authors coded the data set individually (MRB, TCP, WAS, SJdV) and jointly (M-GB, JIDH, MW), producing five independently coded sets of data (S1 Table).

Understanding disease transmission in the workplace is essential for protecting workers. To model disease outbreaks, the small populations in many workplaces require that stochastic effects are considered, which results in higher uncertainty. The aim of this study was to quantify and interpret the uncertainty inherent in such circumstances. We assessed how uncertainty of an outbreak in workplaces depends on i) the infection dynamics in the community, ii) the workforce size, iii) spatial structure in the workplace, iv) heterogeneity in susceptibility of workers, and v) heterogeneity in infectiousness of workers. To address these questions, we developed a multiscale model: A deterministic model to predict community transmission, and a stochastic model to predict workplace transmission. We extended this basic workplace model to allow for spatial structure, and heterogeneity in susceptibility and infectiousness in workers. We found a non-monotonic relationship between the workplace transmission rate and the coefficient of variation (CV), which we use as a measure of uncertainty. Increasing community transmission, workforce size and heterogeneity in susceptibility decreased the CV. Conversely, increasing the level of spatial structure and heterogeneity in infectiousness increased the CV. However, when the model predicts bimodal distributions, for example when community transmission is low and workplace transmission is high, the CV fails to capture this uncertainty. Overall, our work informs modellers and policy makers on how model complexity impacts outbreak uncertainty. In particular: workforce size, community and workplace transmission, spatial structure and individual heterogeneity contribute in a specific and individual manner to the predicted workplace outbreak size distribution.

Density dependence in helminth establishment and heterogeneity in exposure to infection are known to drive resilience to interventions based on mass drug administration (MDA). However, the interaction between these processes is poorly understood. We developed a novel individual-based model for onchocerciasis transmission, EPIONCHO-IBM, which accounts for both processes. We fit the model to pre-intervention epidemiological data and explore parasite dynamics during MDA with ivermectin. Density dependence and heterogeneity in exposure to blackfly (vector) bites were estimated by fitting the model to matched pre-intervention microfilarial prevalence, microfilarial intensity and vector biting rate data from savannah areas of Cameroon and Côte d'Ivoire/Burkina Faso using Latin hypercube sampling. Transmission dynamics during 25 years of annual and biannual ivermectin MDA were investigated. Density dependence in parasite establishment within humans was estimated for different levels of (fixed) exposure heterogeneity to understand how parametric uncertainty may influence treatment dynamics. Stronger overdispersion in exposure to blackfly bites results in the estimation of stronger density-dependent parasite establishment within humans, consequently increasing resilience to MDA. For all levels of exposure heterogeneity tested, the model predicts a departure from the functional forms for density dependence assumed in the deterministic version of the model. This is the first, stochastic model of onchocerciasis, that accounts for and estimates density-dependent parasite establishment in humans alongside exposure heterogeneity. Capturing the interaction between these processes is fundamental to our understanding of resilience to MDA interventions. Given that uncertainty in these processes results in very different treatment dynamics, collecting data on exposure heterogeneity would be essential for improving model predictions during MDA. We discuss possible ways in which such data may be collected as well as the importance of better understanding the effects of immunological responses on establishing parasites prior to and during ivermectin treatment.

Protecting healthcare professionals is crucial in maintaining a functioning healthcare system. The risk of infection and optimal preventive strategies for healthcare workers during the COVID-19 pandemic remain poorly understood. Here we report the results of a cohort study that included pre- and asymptomatic healthcare workers. A weekly testing regime has been performed in this cohort since the beginning of the COVID-19 pandemic to identify infected healthcare workers. Based on these observations we have developed a mathematical model of SARS-CoV-2 transmission that integrates the sources of infection from inside and outside the hospital. The data were used to study how regular testing and a desynchronisation protocol are effective in preventing transmission of COVID-19 infection at work, and compared both strategies in terms of workforce availability and cost-effectiveness. We showed that case incidence among healthcare workers is higher than would be explained solely by community infection. Furthermore, while testing and desynchronisation protocols are both effective in preventing nosocomial transmission, regular testing maintains work productivity with implementation costs.

The World Health Organization (WHO) has proposed elimination of onchocerciasis transmission (EOT) in a third of endemic countries by 2030. This requires country-wide verification of EOT. Prior to the shift from morbidity control to EOT, interventions in Africa were mostly targeted at moderate- to high-transmission settings, where morbidity was most severe. Consequently, there remain numerous low transmission (hypoendemic) settings which have hitherto not received mass drug administration (MDA) with ivermectin. The WHO has prioritised the delineation of hypoendemic settings to ascertain treatment needs. However, the stability of transmission at such low levels remains poorly understood. We use the stochastic EPIONCHO-IBM transmission model to characterise the stability of transmission dynamics in hypoendemic settings and identify a range of threshold biting rates (TBRs, the annual vector biting rates below which transmission cannot be sustained). We show how TBRs are dependent on population size, inter-individual exposure heterogeneity and simulation time. In contrast with deterministic expectations, there is no fixed TBR; instead, transmission can persist between 70 and 300 bites/person/year. Using survivorship models on data generated from model simulations, we find that multiple vector biting rates can sustain hypoendemic prevalence for several decades. These findings challenge the assumption that hypoendemic foci would naturally fade out following treatment in nearby higher-endemicity regions. Our modelling suggests that, to achieve EOT, treatment should be extended to all areas where endogenous infection is identified, emphasising the need for improved diagnostic tools suitable for detecting low-prevalence infection and for strategies that allow safe treatment of communities where MDA would not be suitable.

The cestode is responsible for a considerable cross-sectoral health and economic burden due to human neurocysticercosis and porcine cysticercosis. The 2012 World Health Organization (WHO) roadmap for neglected tropical diseases called for the development of a validated strategy for control of ; however, such a strategy is not yet available. In 2019, WHO launched a global consultation aimed at refining the post-2020 targets for control of for a new roadmap for neglected tropical diseases. In response, two groups working on taeniasis and cysticercosis mathematical models (cystiSim and EPICYST models), together with a range of other stakeholders organized a workshop to provide technical input to the WHO consultation and develop a research plan to support efforts to achieve the post-2020 targets. The workshop led to the formation of a collaboration, CystiTeam, which aims to tackle the population biology, transmission dynamics, epidemiology and control of through mathematical modelling approaches. In this paper, we outline developments in control and in particular the use of modelling to help achieve post-2020 targets for control of We discuss the steps involved in improving confidence in the predictive capacities of existing mathematical and computational models on transmission, including model comparison, refinement, calibration and validation. Expanding the CystiTeam partnership to other research groups and stakeholders, particularly those operating in different geographical and endemic areas, will enhance the prospects of improving the applicability of transmission models to inform taeniasis and cysticercosis control strategies.