Infectious disease and health systems modelling for local decision making to control neglected tropical diseases

Accelerating Progress Towards the 2030 Neglected Tropical Diseases Targets: How Can Quantitative Modeling Support Programmatic Decisions?

Over the past decade, considerable progress has been made in the control, elimination, and eradication of neglected tropical diseases (NTDs). Despite these advances, most NTD programs have recently experienced important setbacks; for example, NTD interventions were some of the most frequently and severely impacted by service disruptions due to the coronavirus disease 2019 (COVID-19) pandemic. Mathematical modeling can help inform selection of interventions to meet the targets set out in the NTD road map 2021-2030, and such studies should prioritize questions that are relevant for decision-makers, especially those designing, implementing, and evaluating national and subnational programs. In September 2022, the World Health Organization hosted a stakeholder meeting to identify such priority modeling questions across a range of NTDs and to consider how modeling could inform local decision making. Here, we summarize the outputs of the meeting, highlight common themes in the questions being asked, and discuss how quantitative modeling can support programmatic decisions that may accelerate progress towards the 2030 targets.

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.

A mechanistic model of snakebite as a zoonosis: Envenoming incidence is driven by snake ecology, socioeconomics and its impacts on snakes

Snakebite is the only WHO-listed, not infectious neglected tropical disease (NTD), although its eco-epidemiology is similar to that of zoonotic infections: envenoming occurs after a vertebrate host contacts a human. Accordingly, snakebite risk represents the interaction between snake and human factors, but their quantification has been limited by data availability. Models of infectious disease transmission are instrumental for the mitigation of NTDs and zoonoses. Here, we represented snake-human interactions with disease transmission models to approximate geospatial estimates of snakebite incidence in Sri Lanka, a global hotspot. Snakebites and envenomings are described by the product of snake and human abundance, mirroring directly transmitted zoonoses. We found that human-snake contact rates vary according to land cover (surrogate of occupation and socioeconomic status), the impacts of humans and climate on snake abundance, and by snake species. Our findings show that modelling snakebite as zoonosis provides a mechanistic eco-epidemiological basis to understand snakebites, and the possible implications of global environmental and demographic change for the burden of snakebite.

LAMP in Neglected Tropical Diseases: A Focus on Parasites

Neglected Tropical Diseases (NTDs), particularly those caused by parasites, remain a major Public Health problem in tropical and subtropical regions, with 10% of the world population being infected. Their management and control have been traditionally hampered, among other factors, by the difficulty to deploy rapid, specific, and affordable diagnostic tools in low resource settings. This is especially true for complex PCR-based methods. Isothermal nucleic acid amplification techniques, particularly loop-mediated isothermal amplification (LAMP), appeared in the early 21st century as an alternative to PCR, allowing for a much more affordable molecular diagnostic. Here, we present the status of LAMP assays development in parasite-caused NTDs. We address the progress made in different research applications of the technique: xenomonitoring, epidemiological studies, work in animal models and clinical application both for diagnosis and evaluation of treatment success. Finally, we try to shed a light on the improvements needed to achieve a true point-of-care test and the future perspectives in this field.

Tackling zoonoses in a crowded world: Lessons to be learned from the COVID-19 pandemic

The COVID-19 zoonosis is bringing about a number of lessons to humanity. One is that of transforming our links with nature and, particularly, wildlife given the likely COVID-19 origin from illegal wildlife trading. Similar to vector borne diseases (VBD, diseases transmitted by vectors), the COVID-19 pandemic follows related patterns (e.g. no effective or available vaccines, difficult to diagnose, highly localized infection geographical foci, non-human reservoirs) for which we urgently need preventive measures. Towards this aim, governments worldwide must strive to prevent further devastation of natural environments that serve as buffer areas to humans against zoonotic agents (among other health risks), protecting biodiversity and its concomitant causes (e.g. global change), and banning use of wildlife of illegal origin. We herein state that some VBD prevention strategies could also be applied to zoonotic disease prevention, including COVID-19 or any type likely to be related to environmental conditions. The occurrence of future pandemic occurrence will depend on whether governments embrace these aims now.

Assessment of surveillance core and support functions regarding neglected tropical diseases in Kenya

BACKGROUND

Effective surveillance and response systems are vital to achievement of disease control and elimination goals. Kenya adopted the revised guidelines of the integrated disease surveillance and response system in 2012. Previous assessments of surveillance system core and support functions in Africa are limited to notifiable diseases with minimal attention given to neglected tropical diseases amenable to preventive chemotherapy (PC-NTDs). The study aimed to assess surveillance system core and support functions relating to PC-NTDs in Kenya.

METHODS

A mixed method cross-sectional survey was adapted involving 192 health facility workers, 50 community-level health workers and 44 sub-national level health personnel. Data was collected using modified World Health Organization generic questionnaires, observation checklists and interview schedules. Descriptive summaries, tests of associations using Pearson's Chi-square or Fisher's exact tests and mixed effects regression models were used to analyse quantitative data. Qualitative data derived from interviews with study participants were coded and analysed thematically.

RESULTS

Surveillance core and support functions in relation to PC-NTDs were assessed in comparison to an indicator performance target of 80%. Optimal performance reported on specimen handling (84%; 100%), reports submission (100%; 100%) and data analysis (84%; 80%) at the sub-county and county levels respectively. Facilities achieved the threshold on reports submission (84%), reporting deadlines (88%) and feedback (80%). However, low performance reported on case definitions availability (60%), case registers (19%), functional laboratories (52%) and data analysis (58%). Having well-equipped laboratories (3.07, 95% CI: 1.36, 6.94), PC-NTDs provision in reporting forms (3.20, 95% CI: 1.44, 7.10) and surveillance training (4.15, 95% CI: 2.30, 7.48) were associated with higher odds of functional surveillance systems. Challenges facing surveillance activities implementation revealed through qualitative data were in relation to surveillance guidelines and reporting tools, data analysis, feedback, supervisory activities, training and resource provision.

CONCLUSION

There was evidence of low-performing surveillance functions regarding PC-NTDs especially at the peripheral surveillance levels. Case detection, registration and confirmation, reporting, data analysis and feedback performed sub-optimally at the facility and community levels. Additionally, support functions including standards and guidelines, supervision, training and resources were particularly weak at the sub-national level. Improved PC-NTDs surveillance performance sub-nationally requires strengthened capacities.

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.

Parasites and wildlife in a changing world: The vector-host- pathogen interaction as a learning case

In the Anthropocene context, changes in climate, land use and biodiversity are considered among the most important anthropogenic factors affecting parasites-host interaction and wildlife zoonotic diseases emergence. Transmission of vector borne pathogens are particularly sensitive to these changes due to the complexity of their cycle, where the transmission of a microparasite depends on the interaction between its vector, usually a macroparasite, and its reservoir host, in many cases represented by a wildlife vertebrate. The scope of this paper focuses on the effect of some major, fast-occurring anthropogenic changes on the vectorial capacity for tick and mosquito borne pathogens. Specifically, we review and present the latest advances regarding two emerging vector-borne viruses in Europe: Tick-borne encephalitis virus (TBEV) and West Nile virus (WNV). In both cases, variation in vector to host ratio is critical in determining the intensity of pathogen transmission and consequently infection hazard for humans. Forecasting vector-borne disease hazard under the global change scenarios is particularly challenging, requiring long term studies based on a multidisciplinary approach in a One-Health framework.

Mapping and modelling the impact of mass drug adminstration on filariasis prevalence in Myanmar

BACKGROUND

Lymphatic filariasis (LF) is endemic in Myanmar and targeted for elimination. To highlight the National Programme to Eliminate Lymphatic Filariasis (NPELF) progress between 2000 and 2014, this paper describes the geographical distribution of LF, the scale-up and impact of mass drug administration (MDA) implementation, and the first evidence of the decline in transmission in five districts.

METHODS

The LF distribution was determined by mapping historical and baseline prevalence data collected by NPELF. Data on the MDA implementation, reported coverage rates and sentinel site surveillance were summarized. A statistical model was developed from the available prevalence data to predict prevalence at township level by year of measurement. Transmission assessment survey (TAS) methods, measuring antigenemia (Ag) prevalence in children, were used to determine whether prevalence was below a level where recrudescence is unlikely to occur.

RESULTS

The highest baseline LF prevalence was found in the Central Valley region. The MDA implementation activities scaled up to cover 45 districts, representing the majority of the endemic population, with drug coverage rates ranging from 60.0% to 98.5%. Challenges related to drug supply and local conflict were reported, and interrupted MDA in some districts. Overall, significant reductions in LF prevalence were found, especially after the first 2 to 3 rounds of MDA, which was supported by the corresponding model. The TAS activities in five districts found only two Ag positive children, resulting in all districts passing the critical threshold.

CONCLUSION

Overall, the Myanmar NPELF has made positive steps forward in the elimination of LF despite several challenges, however, it needs to maintain momentum, drawing on international stakeholder support, to aim towards the national and global goals of elimination.

Probabilistic forecasts of trachoma transmission at the district level: A statistical model comparison

The World Health Organization and its partners are aiming to eliminate trachoma as a public health problem by 2020. In this study, we compare forecasts of TF prevalence in 2011 for 7 different statistical and mechanistic models across 9 de-identified trachoma endemic districts, representing 4 unique trachoma endemic countries. We forecast TF prevalence between 1-6 years ahead in time and compare the 7 different models to the observed 2011 data using a log-likelihood score. An SIS model, including a district-specific random effect for the district-specific transmission coefficient, had the highest log-likelihood score across all 9 districts and was therefore the best performing model. While overall the deterministic transmission model was the least well performing model, although it did comparably well to the other models for 8 of 9 districts. We perform a statistically rigorous comparison of the forecasting ability of a range of mathematical and statistical models across multiple endemic districts between 1 and 6 years ahead of the last collected TF prevalence data point in 2011, assessing results against surveillance data. This study is a step towards making statements about likelihood and time to elimination with regard to the WHO GET2020 goals.

The significant scale up and success of Transmission Assessment Surveys 'TAS' for endgame surveillance of lymphatic filariasis in Bangladesh: One step closer to the elimination goal of 2020

BACKGROUND

Bangladesh had one of the highest burdens of lymphatic filariasis (LF) at the start of the Global Programme to Eliminate Lymphatic Filariasis (GPELF) with an estimated 70 million people at risk of infection across 34 districts. In total 19 districts required mass drug administration (MDA) to interrupt transmission, and 15 districts were considered low endemic. Since 2001, the National LF Programme has implemented MDA, reduced prevalence, and been able to scale up the WHO standard Transmission Assessment Survey (TAS) across all endemic districts as part of its endgame surveillance strategy. This paper presents TAS results, highlighting the momentous geographical reduction in risk of LF and its contribution to the global elimination target of 2020.

METHODOLOGY/PRINCIPAL FINDINGS

The TAS assessed primary school children for the presence of LF antigenaemia in each district (known as an evaluation unit-EU), using a defined critical cut-off threshold (or 'pass') that indicates interruption of transmission. Since 2011, a total of 59 TAS have been conducted in 26 EUs across the 19 endemic MDA districts (99,148 students tested from 1,801 schools), and 22 TAS in the 15 low endemic non-MDA districts (36,932 students tested from 663 schools). All endemic MDA districts passed TAS, except in Rangpur which required two further rounds of MDA. In total 112 students (male n = 59; female n = 53), predominately from the northern region of the country were found to be antigenaemia positive, indicating a recent or current infection. However, the distribution was geographically sparse, with only two small focal areas showing potential evidence of persistent transmission.

CONCLUSIONS/SIGNIFICANCE

This is the largest scale up of TAS surveillance activities reported in any of the 73 LF endemic countries in the world. Bangladesh is now considered to have very low or no risk of LF infection after 15 years of programmatic activities, and is on track to meet elimination targets. However, it will be essential that the LF Programme continues to develop and maintain a comprehensive surveillance strategy that is integrated into the health infrastructure and ongoing programmes to ensure cost-effectiveness and sustainability.

Fit for purpose: do we have the right tools to sustain NTD elimination?

Priorities for NTD control programmes will shift over the next 10-20 years as the elimination phase reaches the ‘end game’ for some NTDs, and the recognition that the control of other NTDs is much more problematic. The current goal of scaling up programmes based on preventive chemotherapy (PCT) will alter to sustaining NTD prevention, through sensitive surveillance and rapid response to resurgence. A new suite of tools and approaches will be required for both PCT and Intensive Disease Management (IDM) diseases in this timeframe to enable disease endemic countries to:

1. Sensitively and sustainably survey NTD transmission and prevalence in order to identify and respond quickly to resurgence.

2. Set relevant control targets based not only on epidemiological indicators but also entomological and ecological metrics and use decision support technology to help meet those targets.

3. Implement verified and cost-effective tools to prevent transmission throughout the elimination phase.

Liverpool School of Tropical Medicine (LSTM) and partners propose to evaluate and implement existing tools from other disease systems as well as new tools in the pipeline in order to support endemic country ownership in NTD decision-making during the elimination phase and beyond.

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

Quantitative analysis and mathematical models are useful tools in informing strategies to control or eliminate disease. Currently, there is an urgent need to develop these tools to inform policy to achieve the 2020 goals for neglected tropical diseases (NTDs). In this paper we give an overview of a collection of novel model-based analyses which aim to address key questions on the dynamics of transmission and control of nine NTDs: Chagas disease, visceral leishmaniasis, human African trypanosomiasis, leprosy, soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis and trachoma. Several common themes resonate throughout these analyses, including: the importance of epidemiological setting on the success of interventions; targeting groups who are at highest risk of infection or re-infection; and reaching populations who are not accessing interventions and may act as a reservoir for infection,. The results also highlight the challenge of maintaining elimination 'as a public health problem' when true elimination is not reached. The models elucidate the factors that may be contributing most to persistence of disease and discuss the requirements for eventually achieving true elimination, if that is possible. Overall this collection presents new analyses to inform current control initiatives. These papers form a base from which further development of the models and more rigorous validation against a variety of datasets can help to give more detailed advice. At the moment, the models' predictions are being considered as the world prepares for a final push towards control or elimination of neglected tropical diseases by 2020.