mework for Optimising Control at the Local Level: Coordinated strategies for Neglected Tropical Diseases and Malaria (FOCAL-NTD)

Disease control programmes require knowledge of the geographical distribution of the target disease in order to establish where control interventions are most needed. In instances where the disease risk is approximately constant across a geographical area (i.e. spatially homogeneous), programmes are able to evenly distribute interventions amongst the population. However, disease risk can often be very variable (i.e. spatially heterogeneous), particularly in the case of parasitic diseases in which the relationship between the parasite and the human host is dependent on the surrounding environment. In these instances a 'blanket' intervention approach isn't sufficient to eliminate a disease from an area, as resources are wasted in areas where there is no disease risk, and are not adequately focused to completely remove disease 'hotspots'. The aim of this project is to develop a framework that enables disease control efforts to be targeted more effectively. In addition to considering individual diseases, the framework will encourage coordination between control programmes in areas where multiple diseases are co-endemic, thus accelerating these programmes simultaneously towards their control/elimination goals.
This project will focus on three neglected tropical diseases (NTDs) and coinfections with malaria in order to demonstrate the flexibility of the framework being developed. These NTDs are Human African Trypanosomiasis (HAT, transmitted by tsetse flies) schistosomiasis (transmitted in freshwater by an intermediate host snail) and lymphatic filariasis (LF, transmitted by mosquitoes). Local level risk maps for each of these diseases will be produced using data provided by project collaborators from endemic countries, including Malawi and Uganda. These maps will combine disease/vector/intermediate host information with information on the risk factors of the diseases in question. Geographically referenced risk factors could include those that influence the presence and/or density of the disease's vector/intermediate host, or influence how likely a person is to come into contact with the vector/intermediate host. Using the example of schistosomiasis, this may include factors such as the distance of the village to the nearest freshwater source, factors influencing the intermediate host/parasite ability to survive and breed (e.g. altitude, temperature, vegetation) and information on control activities have been implemented in the area.
Traditional methods of collecting local level disease risk data use survey teams to collect information, with surveys often being expensive, time-consuming and logistically difficult to undertake in rural areas of developing countries. In addition to developing risk maps based on previously collected information, alternative methods for obtaining local level disease-related data will be explored. Two approaches will be considered. Firstly, more efficient spatial sampling methods for determining which sites should be surveyed will be developed. These methods will be 'flexible' in the sense that the selection of sites to sample will be done iteratively, and will be selected strategically in order to reduce the uncertainty in the estimated geographical distribution of disease risk in the study area. The second approach focuses on using community members to collect disease-related information, as opposed to a dedicated survey team. Community members are becoming increasingly involved in disease control activities in developing countries, and this has been shown to improve intervention coverage and acceptability. This project will explore ways in which community members can more directly contribute to disease control activities through the development of mobile phone-based surveillance and reporting tools. Community members in Malawi and Uganda will be trained to report information such as preventive therapy coverage (for schistosomiasis and LF) and vector control (malaria and HAT) respectively.

This project aims to develop a spatial framework for optimising the coordinated control of spatially heterogeneous neglected tropical diseases i.e. Human African Trypanosomiasis (HAT), schistosomiasis and lymphatic filariasis (LF), together with malaria coinfection at the local level. This will involve: identifying factors associated with local level spatial variability in disease risk; developing spatial sampling strategies for monitoring changes in the disease distribution over time; and developing intervention targeting strategies. Further, community-based surveillance tools will be developed as a low-cost method of obtaining local level disease information.
Georeferenced data on disease prevalence, plus high resolution environmental, demographic, socio-economic and intervention data for Malawi and Uganda will be obtained from project collaborators, publicly available data sources and commercial satellite imagery. Using a binomial geostatistical modelling approach, these data will be analysed to quantify the relationship between potential risk factors and disease risk, culminating in the production of risk maps. These maps will be used to targeted disease intervention strategies. Further, a series of 'in silico' experiments will be undertaken to determine the influence of spatial sampling strategies on the resulting estimated risk map. More traditional sampling techniques will be compared with novel 'flexible' sampling strategies in which sampling locations are selected according to their potential to reduce the uncertainty in the estimated risk surface. Lastly, mobile phone-based surveillance tools will be developed and tested by community members in Malawi and Uganda to determine their potential for obtaining local information on intervention activities.
The outcomes of this project have the potential to guide policy makers and disease control programmes to adopt more effective strategies, and thus simultaneously accelerate towards control/elimination.

The outcomes of this project have the potential to impact local, national and international beneficiaries. The potential economic and societal impacts include:
- Improved computer simulation tools and methods for enhancing the effectiveness of public health services,
- Improved disease control strategies that are adaptable to the local setting,
- Greater evidence of the impact of disease control programmes on disease burden,
- An improvement in the socio-economic status of endemic community members due to an alleviation in disease burden.

The proposed work will focus on strategies and tools for HAT, schistosomiasis, malaria and LF control, and will provide a platform upon which the respective international and national policy makers and control programmes can devise locally tailored control strategies. These local strategies, as opposed to the traditional 'top-down' approach in disease control will help to drive disease control efforts closer to an elimination scenario. In the longer term, the methods and tools that will be developed during this study may serve to enhance parasitic disease control efforts in developing countries, and contribute towards alleviating the disease burden of those living in endemic areas.

Impact on policy makers
Whilst policy makers, specifically WHO, have developed guidelines for the control of a number of NTDs targeted for control and elimination e.g. district-level mass drug administration (MDA) for schistosomiasis and LF, these guidelines operate at the national or regional scale, and as yet do not provide any information on how to target interventions at the local scale. The NTD community recognises that more spatially refined strategies are required in order to achieve control and elimination of selected diseases. The outcomes of this research will provide further insight into how these diseases can be more effectively monitored and targeted at the local scale in order to progress closer to an elimination scenario. Tools that engage community members in control activities such as those proposed in this project will complement this local level disease control approach.

Impact on national control programmes
The risk maps produced as a result of this research will enable control programmes to learn more about the disease they are targeting, monitor changes in disease prevalence over time, more effectively target disease interventions, and monitor the progress of these interventions. This information will provide them with an evidence base to present to donors when requesting further financial support.

Impact on endemic communities
By enhancing control programmes' knowledge of the disease they are targeting, and providing an evidence base for the benefits of locally-focused disease control strategies, this project has the potential to contribute towards reducing the disease burden in endemic communities. Further, by enabling community members to engage in disease surveillance and reporting activities via a mobile phone-based tool, they will be able to be more directly involved in improving their own health, and have greater access to information relating to disease control activities. This may subsequently increase their compliance in community-based interventions, and help to guide the development of future control initiatives.