Modelling malaria elimination on the internet

Mathematical modelling has great potential as a tool to help guide efforts towards malaria elimination [1]. Different combinations of interventions are required for different epidemiological settings. However, there are limited data available to policymakers to inform their decisions on which strategies to employ. Mathematical modelling combines mechanistic understanding with available data from multiple sources to make predictions. It could potentially be used for preliminary evaluation of different strategies for malaria elimination in different epidemiological contexts much more rapidly and at lower cost than is possible through trial and error in the field [1]. Modelling is particularly useful where a field study cannot be done as is the case with large-scale elimination programmes for which it is desirable to get the strategy right first time. There is a risk that the current unprecedented commitment of financial resources by international agencies will not be sustained if attempts at elimination are perceived to be failing.

Although modelling is beginning to be used for this purpose [2], it is often inaccessible to the majority of those planning malaria elimination efforts. Much of the modelling currently undertaken remains in the hands of the specialist research community and is presented as selected results in the scientific literature. Although recent modelling studies have provided useful generally applicable insights, interaction with policymakers at the level of individual nations is rare. This remains a major barrier to realising the potential of mathematical modelling in this area. In addition, awareness must be raised and training provided to policymakers in order for them to access mathematical modelling effectively for their individual circumstances.

One solution to this problem is to make models accessible to all via the internet. Several such models are available for malaria [3‐5] and more are in development. One inherent problem with this method is that to remain user-friendly, websites need to run quickly. It is technically difficult to incorporate a complex model into a website and maintain usability as such models tend to be processor-intensive and thus run slowly. One solution to this is to present a range of pre-prepared modelling results from model runs carried out offline. This has the drawbacks that the range of possible scenarios is limited and the user has less scope for exploring the behaviour of the model, for example with interacting interventions. Another approach has been to offer the model as a downloadable and installable application e.g. the Malaria Tools project (currently limited to a population of up to 1000 people and certain pre-specified scenarios) [3]. This has the advantages that it uses the native processing power of the user's computer and can be run offline. However, not all users want or are able (many workplace security systems do not allow it) to install third party code and to update such a model requires a new version of the software to be installed each time.

An alternative approach is to incorporate the model code into a website where it can be run in situ in the web browser and easily adjusted and expanded by the designer. Several approaches to this are being attempted. By using cloud computing, the model can be quite complex. This is being trialled at malariacontrol.net where the computing power of large numbers of volunteers is accessed over the internet [4]. However, in its current form, the input parameters and model runs are set by the malariacontrol.net team and outside users cannot run the models themselves. Another approach has been to restrict the model to detailed exploration of the potential impact of a single intervention, e.g. intermittent preventive treatment in infants [5].

This paper describes a flexible and user-friendly website with an online mathematical model of malaria elimination that is being developed interactively with end-users. There is a trade-off between user-friendliness and model complexity, and hence the underlying structure of the model is relatively simple [6]. The aim is for this to be an accessible introduction to mathematical modelling for those less familiar with the discipline and ultimately, by further development, a simple tool with which malaria control programmes can explore the potential impact of strategies being considered for deployment. The current model is based on a previously published framework and there is a detailed description elsewhere [6]. This methodology paper focusses particularly on the web platform.

Mathematical modelling has an important contribution to make to planning malaria elimination [10] but has been under-utilized to date. This project provides an accessible and user-friendly platform for presenting mathematical models on the internet that is suitable for use by non-modellers. In the initial phase, a simple model of malaria elimination is presented that is not suitable for detailed planning of real-world strategies. As is the ideal for mathematical modelling, this will be developed as an ongoing iterative process of collaboration with the end users of the modelling results to produce modelling tools that are increasingly useful and relevant. Although it currently hosts a single model, multiple different models will be available on the site designed to answer specific and pressing questions from policymakers. The development team will work in collaboration with users to update and refine the platform to maximize its potential and if necessary to assist non-mathematicians with the interpretation of the model results. It is hoped that an online community can be built and by continuous refinement develop the platform into a usable tool to help plan local strategies for malaria elimination. Readers are encouraged to try the platform for themselves and invited to get involved in what is hoped will be a useful contribution to malaria elimination efforts worldwide.

A free, internet-based, user-friendly and interactive platform for mathematical models of malaria elimination is presented. This platform will be developed and refined in collaboration with users to maximize its potential as an educational and public health policy planning tool. This will assist with preliminary optimisation of local malaria elimination strategies before commitment of valuable resources.