Malaria Elimination

Richard J Maude1,2*, Sompob Saralamba1, Adrian Lewis3, Dean Sherwood1, Nicholas J White1,2, Nicholas PJ Day1,2, Arjen M Dondorp1,2, Lisa J White1,2

  1. Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
  2. Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, Churchill Hospital, University of Oxford, Oxford, UK
  3. iSynch-D, 11/3, Soi Sirisuk, Kwang Sasennok, Khet Huaykwang, Bangkok, Thailand

Contact: Richard Maude

Project Outline


Malaria kills over 1 million people every year. Previous attempts to control malaria have failed and for the past 40 years global eradication was thought to be impossible. However, there are now new, more effective, tools available such as insecticide treated bednets and more powerful antimalarial drugs. There is also unprecedented commitment from international bodies such as the WHO and the Roll Back Malaria Partnership. As a result, global malaria eradication is very much back on the international agenda. The difficulty is knowing which intervention strategies to use and how best to combine them to achieve maximum impact in a variety of different settings. Mathematical modelling has great potential as a tool to help guide and inform these decisions by predicting the impact of various strategies before funds are committed. Although many models of malaria exist, very little modelling of malaria elimination has thus far been attempted.


A user-friendly web-based mathematical model is being developed to examine the elimination potential of all the current major malaria control interventions, alone and in combination, in a variety of settings. The first version of this model can now be accessed via the link at the bottom of this page. It is a deterministic population dynamic model and is coded in Microsoft Silverlight. The model structure is based on a previously published framework which can be accessed here. Users can enter their own data and run the model themselves over the internet. This model will be refined and developed in collaboration with users with the ultimate aim of developing it into a tool to help plan local elimination strategies. Users can make suggestions and help develop refinements and additions via the online forum or by email. We will share the model code on request so specialists, programmers and other modellers can review it and see how it is constructed. Our team will work in collaboration with these users to continuously update and refine the model to maximise its potential and to assist non-mathematicians with the interpretation of the model results.


We have produced a free, internet-based, user-friendly and interactive mathematical model of malaria elimination as a tool for policy makers. We will develop and refine this model in collaboration with users to maximise its potential as an educational and public health policy planning tool. This will enable optimisation of local malaria elimination strategies before commitment of valuable resources.

More details of this project are available here: Maude RJ, Saralamba S, Lewis A, Sherwood D, White NJ, Day NP, Dondorp AM, White LJ. Modelling malaria elimination on the internet. Malar J 2011;10:191.


The Malaria Elimination website is made up of:

  1. General descriptive content relating to the project – this is subject to the same terms of use as for MORU generally;
  2. A mathematical model, which is fully described here and is made available under the terms of the Creative Commons Attribution Non-commercial License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited; and
  3. The modelling code, which is in Berkeley Madonna format. This is available on request via a forum so that specialists, programmers and other modellers can download it, see how it is constructed and make suggestions for its development. The modelling code is not generally available during this prototype phase, other than on request through the forum.

Users should carefully note the following:

Given the above considerations, MORU can accept no responsibility for the consequences of reliance on the model and its outputs – including any loss arising. Specifically, none of MORU, Mahidol University, the University of Oxford or the Wellcome Trust make any representation or warranty of any kind or accept any liability concerning the content of or information on the website, and any reliance you place on such content or information is therefore strictly at your own risk.

Note that the terms of use for this sub-site differ in some respects from the general terms of use for the MORU site.

Use this link to access the model

Use this link for the user guide