In studies released today in Clinical Infectious Diseases, Professor Déirdre Hollingsworth from NDM's Big Data Institute and Centre for Global Health Research, along with colleagues from the Neglected Tropical Disease Modelling Consortium and public health experts, including from the World Health Organization (WHO), examine the adaptability of mathematical models of NTDs to local contexts.
Their research aims to better understand which interventions are needed to achieve the 2030 NTD targets, determine the best strategies for keeping NTDs under control after target achievement, and assess the costs associated with different options. This comprehensive approach provides insights into the current and future spread of various NTDs across multiple countries, facilitating improved control and elimination efforts.
Neglected tropical diseases (NTDs) are a group of 21 diseases and disease groups caused by a range of bacteria, fungi, parasites, viruses, and toxins, which together affect over 1 billion people globally – more than 1 in 8 people worldwide. This diverse set of diseases, which includes dengue, leprosy, rabies, leishmaniasis, parasitic worms and many others, is grouped together because they affect disadvantaged communities in tropical and subtropical areas, where they cause major health, economic and social problems, perpetuating cycles of poverty.
Although resources dedicated to NTDs remain limited, the past decade has witnessed substantial progress in their control, elimination and eradication, driven first by the 2012–2020 road map for accelerating work to overcome the global impact of NTDs; followed by the 2021–2030 WHO road map, which sets out disease-specific targets and sets out key actions to achieve a world free of NTDs by 2030.
For example, 50 countries have now successfully eliminated at least one NTD, and the number of people requiring NTD interventions decreased by 600 million between 2010 and 2020. Accurate, context-specific information is crucial for shaping policy decisions at both national and subnational levels for NTD programmes.
How to achieve the 2030 targets
Models can be used to evaluate if programmes are on track and explore how to accelerate progress. For example, models can estimate the likely impact of expanding treatment to new groups or deploying new interventions such as new drugs. One study illustrates how expanding preventative mass drug administration (MDA) campaigns against schistosomiasis from school aged children to other groups (including pre-school aged children, women of reproductive age and adults) can shorten programme duration. Another study forecasts how trachoma and lymphatic filariasis infection numbers are likely to change across sub-Saharan African countries, identifying specific districts that are likely to require better treatment campaigns to meet 2030 targets.
What to do once targets are achieved
The success of some control programmes means that there is a need to plan the next stages, focusing on eliminating the last few hotspots of disease, designing surveillance strategies to ensure the long-term sustainability of NTD programmes and avoid disease resurgence. Models offer insights for designing optimal strategies post-intervention cessation and for monitoring disease elimination. For example, one study looking at lymphatic filariasis in India found that using a single survey of ongoing transmission one year after the last MDA round provides limited information on whether transmission has been stopped, whereas including two additional surveys provides much more accurate information on whether disease will eventually reappear.
Understanding costs
The costs related to continuing treatments, monitoring and surveillance need to be balanced with the benefits of maintaining NTDs under control and avoiding resurgence. Models can help inform decision making, by better incorporating economic parameters. For example, in the case of onchocerciasis, there are ongoing concerns that annual MDA using the current drug Ivermectin may not lead to disease elimination in all endemic areas, which has led to studies on the utility of alternative drugs, particularly Moxidectin. An updated economic assessment of Moxidectin vs Ivermectin suggests that Moxidectin-based strategies could not only accelerate progress towards elimination of onchocerciasis transmission but are also likely to reduce programmatic delivery costs.
Deirdre Hollingsworth, Professor of Infectious Disease Epidemiology, Big Data Institute and Centre for Global Health Research at the University of Oxford and leader of the NTD Modelling Consortium said, “These studies illustrate the value of collaborative research between infectious disease experts, modelers and policymakers in supporting policies on interventions and surveillance strategies and to better understand the dynamic impact of new drugs, vaccines or diagnostics.
We hope that these studies will support progress towards the control and elimination of neglected tropical diseases by proving analyses which support endemic country policymakers in achieving their goals where these diseases continue to be responsible for disability and economic hardship in the most vulnerable communities."