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Welcome to the OpenMalaria wiki on GitHub.
OpenMalaria is an open-source C++ program for simulating malaria epidemiology and the impacts on that epidemiology of interventions against malaria. OpenMalaria is a microsimulation, individual-based model of Plasmodium falciparum malaria in humans, developed initially for simulating malaria vaccines. The models have been extended to include simulation of the dynamics of malaria in the mosquito vector and capture the delivery and impact of many malaria interventions (including for example, treatment, chemoprevention, and vector control). These models simulate the dynamics of malaria parasitaemia in the course of an infection, of transmission, of immunity, and of the processes leading to illness and death. The system is set up to simulate malaria in village, or district size human populations. OpenMalaria is now meant to be run as stand-alone program.
This wiki details the model components required to capture the transmission of malaria, the processes leading to malaria disease and the action of interventions.
The core program is written in C++ with a GNU GPL 2 licence. To run this program a configuration file written in Extensible Markup Language (XML) is also needed.
Development of OpenMalaria is lead by two modelling teams:
- The Intervention and Infectious Disease Modelling Team at The Kids Research Institute Australia/University of Western Australia
- The Disease Modelling Unit of Swiss Tropical and Public Health Institute (Swiss TPH)
along with the SciCORE Center for Scientific Computing, University of Basel.
The development team in the past also includes collaborators from the Liverpool School of Tropical Medicine.
Financial support is from the Bill & Melinda Gates Foundation.
Disclaimer: the recommended way to use the OpenMalaria software is via command-line and automated scripts. At this time, there is no officially supported GUI for OpenMalaria.
There is a User Guide to help you downloading, installing, and running OpenMalaria.
A glossary of useful terms related to OpenMalaria can be found here
Selected publications can be found here.
In case you wish to have access to the documentation on this wiki without an internet connection, you can clone this repository:
git clone https://github.com/SwissTPH/openmalaria.wiki.git
If you want to be able to change wiki pages with git you need to clone the wiki via git clone git@github.com:SwissTPH/openmalaria.wiki.git and provide an SSH-key in your user options.
The original models were designed for simulating the impact of interventions acting on humans (for example, chemotherapy, or vaccines). OpenMalaria has subsequently been extended to include simulation of the dynamics of malaria in the mosquito vector, and of interventions that act on mosquitoes. It also offers alternative model structures for many of the components of the human models. The models allow for variations among humans in their exposure to mosquitoes, and in their responses to the parasite.
OpenMalaria provides a way of relating different malaria indicators, such as prevalence, inoculation rates, clinical incidence, and mortality. Simulations of status quo malaria situations can be used to estimate parameters that have not been measured from field data. For instance, models can be used to predict mortality rates from entomological data. Such simulations are also useful for validating the relationships in models, and for improving their calibration to data.
Prediction of epidemiological impacts of interventions is used to:
- analyze novel interventions to inform the development of target product profiles
- analyze the effects of different deployment strategies for existing interventions
- analysis of the potential effects for new interventions or planned malaria control programs.
The outputs from predictive simulations can be linked to cost data from endemic countries to analyze the economics of malaria interventions.
The value of a point estimate is greatly enhanced when the variability associated with that point estimate is also available. The project analyzes different components of uncertainty associated with sets of model predictions, considering stochastic uncertainty, parameter uncertainty, and model uncertainty.
A guide on how to apply OpenMalaria to field sites can be found here.
| Download openmalaria | Installation instructions | XML Schema Documentation |
| XML Schema Version | Program version | master |
develop |
|---|---|---|---|
| 43 | schema-43.0 |
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