Volume 9 Supplement 2

Parasite to Prevention: Advances in the understanding of malaria

Open Access

Predicted impact of mosquito-stage transmission-blocking vaccines using an ensemble of microsimulations

  • Aurelio Di Pasquale1, 2,
  • Nicolas Maire1, 2 and
  • Thomas Smith1, 2
Malaria Journal20109(Suppl 2):O11

https://doi.org/10.1186/1475-2875-9-S2-O11

Published: 20 October 2010

Dynamic models of infectious diseases have played an important role in the rational planning of control programs for a long time. We have developed a comprehensive microsimulation approach to investigate the potential of many of the currently possible and future interventions against P. falciparum malaria. The outputs of the stochastic individual-based simulations are predictions of the epidemiological impact and comparative cost-effectiveness of conceivable control measures, alone or in combination.

The analysis of such simulation studies is challenging because they can produce very large numbers of outputs. Usually a large number of scenarios need to be investigated, especially if the focus is on how different control intervention act in combination. In addition, uncertainty analysis requires the re-running of the model with a number of differing model formulations or parameters.

We are developing a web-based platform to be able to efficiently design, run and analyze simulation experiments. Here we present an overview of the architecture of the platform, including the underlying database design, the workflow of running simulations, and the tools for analyzing predictions. The platform will greatly improve the accessibility of the model predictions to end-users from a range of disciplines, such as program managers or policy makers. We also discuss as a case study the results from a simulation experiment aimed a predicting the potential value of deploying a mosquito-stage transmission-blocking vaccine (MSTBV) against P. falciparum malaria. These results suggest how a MSTBV can best be combined with other control measures to achieve elimination, considering factors like the initial level of transmission, the proportion of the population covered by the intervention, and the key properties of the vaccine.

Authors’ Affiliations

(1)
Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute
(2)
University of Basel

Copyright

© Di Pasquale et al; licensee BioMed Central Ltd. 2010

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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