Publication: Modelling malaria elimination on the internet
Issued Date
2011-07-26
Resource Type
ISSN
14752875
Other identifier(s)
2-s2.0-79960562930
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Mahidol University
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SCOPUS
Bibliographic Citation
Malaria Journal. Vol.10, (2011)
Suggested Citation
Richard J. Maude, Sompob Saralamba, Adrian Lewis, Dean Sherwood, Nicholas J. White, Nicholas Pj Day, Arjen M. Dondorp, Lisa J. White Modelling malaria elimination on the internet. Malaria Journal. Vol.10, (2011). doi:10.1186/1475-2875-10-191 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/12024
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Title
Modelling malaria elimination on the internet
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Abstract
Background: Unprecedented efforts are underway to eliminate malaria. Mathematical modelling can help to determine the optimal strategies for malaria elimination in different epidemiological settings. This is necessary as there is limited scope for expensive and time-consuming field studies and failure of planned elimination strategies is likely to discourage ongoing investment by funders. However, there has been very little modelling of malaria elimination and little direct involvement of policymakers in its development. There is thus an urgent need for user-friendly and accessible models purpose-designed in collaboration with policymakers to answer pertinent questions arising from the field. Results: An internet site is presented with a simple mathematical modelling platform for population level models of malaria elimination. It is freely accessible to all and designed to be flexible so both the platform and models can be developed through interaction with users. The site is an accessible introduction to modelling for a non-mathematical audience, and lessons learned from the project will help inform future development of mathematical models and improve communication of modelling results. Currently it hosts a simple model of strategies for malaria elimination and this will be developed, and more models added, over time. The iterative process of feedback and development will result in an educational and planning tool for non-modellers to assist with malaria elimination efforts worldwide. Conclusions: By collaboration with end users, iterative development of mathematical models of malaria elimination through this internet platform will maximize its potential as an educational and public health policy planning tool. It will also assist with preliminary optimisation of local malaria elimination strategies before commitment of valuable resources. © 2011 Maude et al; licensee BioMed Central Ltd.