Mathematical tools to inform sustainable interventions against schistosomiasis in Uganda

Funder: EPSRC (EP/T003618/1)
PI: Joaquin Prada; Glasgow PI: Poppy Lamberton

Summary

Schistosomiasis is a neglected parasitic disease, second only to malaria in its socio-economic and public-health importance. It is estimated that 240 million people are infected worldwide, most of which belong to the poorest populations in many sub-Saharan African countries. Individuals with this disease, the majority children, acquire the infection when they contact infected fresh water through behaviours such as fishing and bathing, and transmit the disease in areas with inadequate sanitation. There is a drug available to treat cases, and the World Health Organization recommends mass treatment of school-age children or whole communities, depending on the disease burden. However, the drug does not prevent reinfection, which occurs rapidly. 

Combining the drug treatment campaigns with improving sanitation infrastructure could hold the key to finally controlling and eventually eliminating this disease in these populations. The question then becomes what is the best intervention, or combination of interventions, that will most rapidly and efficiently reduce disease burden. To tackle this, we will develop a mathematical approach, that integrates the biological infection process (i.e. modelling transmission of infections) with individual behaviour and preference for the different interventions (i.e. using a process of modelling interaction between humans called game theory). Combining these two we can find the most suitable combination of interventions that would be successful in the community and decrease disease. We can then explore the costs associated with the combination of interventions, to leverage the most popular and effective, with the most affordable. Another important aspect is evaluating the interventions, once they are implemented, to measure progress. We need to add the use of different diagnostics to our model, as they might provide different information depending on the setting. 

The combination of all of this work will then enable us to write recommendations for a field trial to test a control program, with an efficient and popular campaign, which we can effectively monitor. The project is highly multidisciplinary and will bring together expertise from mathematics and biology, as well as, statistics, epidemiology and health economics. We will build the models based on our previous work and additional published materials in the literature, using social and economic data locally collected with our partners in Uganda. The project outcomes, specific to local populations in Uganda, could then be expanded to other countries by engaging with other communities and key stakeholders. 

Objectives

Transmission of schistosomiasis is linked to poverty, driven by poor water, sanitation and hygiene (WASH) conditions. The current strategy for control recommended by the World Health Organization (WHO) is mass drug administration (MDA) with praziquantel. However, rapid reinfection can occur after treatment, which makes reducing morbidity, breaking transmission and trying to achieve elimination, very challenging using chemotherapy alone. Our research project focuses on using novel mathematical modelling tools to inform policy-makers on popular and affordable, and therefore feasible and sustainable, WASH interventions to complement MDA campaigns as well as informing monitoring and evaluation methods. 

The project is divided into two work packages: WP1 is focused on the health economics component of the project lead but he PDRA Sergi Alonso while WP2 lead by Eva Janouskova is centred around the transmission modelling and enhancing monitoring and evaluation. There are four key research questions, with associated outcomes, as follows: 

WP1.1 How do people's individual motivations and strategies affect intervention effectiveness?
Outcome: A game-theoretical model and multi-criteria decision analysis to evaluate uptake of different interventions. 

WP2.1 What are the most effective combinations of interventions to control S. mansoni infections when accounting for individual uptake of the different strategies and their impact on transmission.
Outcome: "Best bet" combination of interventions for the control of schistosomiasis. 

WP1.2 Using economic analyses, how do the different interventions rank in their financial costs, health benefits, effectiveness and likely level of uptake?
Outcome: A cost-effectiveness analysis of the most promising interventions: the 'best buys'. 

WP2.2 How does the choice of diagnostic affect the monitoring of the interventions?
Outcome: A monitoring strategy to maximise tracking of the intervention. 

In terms of priority, all four research questions have similar importance, with the two work packages and all research questions complementing each other. WP1.1 and WP2.1 are synergistic, while the first will develop the individual behaviour component, this will be integrated in the latter, as the outcomes for WP2.1 will be informed by individual preference to the different interventions. WP1.2 will build on previous steps focusing on the cost-effectiveness analysis, which is important in policy decision-making, while WP2.2 aims at improving monitoring of the chosen interventions. Together, WP1 & WP2 will provide the evidence necessary to inform the design of a complex intervention trial. 

Our aim is to train the Eva Janouskova and Sergi Alonso in the multidisciplinary field of mathematical modelling for infectious diseases. It will also support multilateral knowledge transfer with our partners in Uganda, as well as with other project partners, helping to reduce the currently maintained high prevalence of schistosomiasis in Uganda and beyond.