Terminology
Some of the terminology used by OpenMalaria project is quite specific. A quick browse through the glossary below is recommended.
| A-B | C | D-F | G-J | K-M | N-R | S | T-Z |
Each sweep must have one or (usually) more values for each of its factors. An arm is one value for one sweep (one value for one parameter)
A "bout of sickness" describes a fever, malarial or otherwise, or period of severe illness, usually lasting no more than five days.
The process of converting source code to binary code that a CPU can run (also known as compiling).
C (back to top)
Death rates among severe malaria patients. More details.
Model of patient treatment and treatment outcomes (recovery, death, sequelae). More details.
There are two models for this, with three total variants:
-
Five day model.
ImmediateOutcomesimplementation,DecisionTree5Dayimplementation -
One day model.
EventSchedulerimplementation
An intervention to change health system parameters. See here.
A list of the primary changes between OpenMalaria versions can be found here.
Encompasses anything related to case management, pathogenesis and case outcomes. See this page.
See this page for information about the OpenMalaria code.
A cohort is a sub-population which can be monitored separately and can used to target intervention deployment. See sub-populations.
The simulator is divided up into several components: e.g. within-host, transmission, health-system. From a computing perspective these may be called interfaces.
Determination of (financial) costs associated with deploying an intervention. This is calculated outside OpenMalaria. Some information
This is a module of code used to parameterise the decay of many intervention effects. Documentation.
A description of the ages and gender ratio of the simulated human population from which simulated individuals will be drawn. More ...
A test used to determine whether a person is infected [with a Plasmodium parasite]. Can be used in case-management, screen-and-treat interventions and monitoring. More on this page.
Entomological Inoculation Rate — measured as the number of infectious mosquito bytes received by a typical unprotected adult human in one year. See specifying transmission.
The study of insects. Within OpenMalaria, this means mosquitoes. Sometimes entomology is used as a pseudonym for transmission. Also see Mosquito Population Dynamics.
The health-system's reporting unit; only one malaria episode is possible in a 30-day period. Therefore, each bout is either considered the start of a new episode, or, if it occurs within 30 days of a previous bout, part of the same episode. Thus, at least in low transmission settings, an episode should roughly correspond to one malaria infection (which can cause multiple bouts). An episode's severity (non-malarial, malarial or severe) is considered to be that of its worst bout.
In clinical models, an occurrence without measurable duration. This can be a bout in the five-day time step model since the whole bout occurs on a single time step, but in the one-day time step model an event is strictly a state-change.
Largely synonymous with a study, an experiment has a base scenario with one or more factors which vary (the factors being sweeps). A complete experiment description includes all sweeps and all arms of each sweep, together with the scenarios generated by selecting combinations of arms, and the results produced. Each scenario is generated by choosing one arm for each sweep in the experiment.
A full factorial experiment is one where all possible scenarios are generated: all combinations of one arm per sweep are used.
Wiki pages generated from the internal documentation in the schema.
The pre-determined, fixed period of time, currently set at 30 days, during which all bouts of illness are considered to be related to the same infection. The health system memory has implications for reporting and for treatment practices.
Each component needs at least one implementation, describing how the relevent processes are simulated. Logically, these can also be called models.
Help on installing the OpenMalaria simulator.
The final phase of the simulation during which interventions may be deployed and monitoring happens. See here.
During the a simulation of a scenario, some type of intervention may be used, usually with the aim of reducing malaria transmission, prevalence, clinical manifestations or costs. These interventions may be deployed at a point in time (timed mode), whenever humans reach a certain age (continuous mode), or as part of treatment. See:
- Preventive interventions (IRS, screen-and-treat, larviciding, etc.)
- Pseudo interventions (import infections, change EIR, etc.)
Case management and treatment is also an intervention in the sense that it intervenes on the natural state of the system, but also not an intervention in that it may already be present in the initial state of the modelled system (however, changing CM/treatment is still an intervention). Much of the model code is written with the latter convention.
LiveGraph is a tool which can be used to visualise live outputs of running simulations via continuous monitoring.
The OpenMalaria simulator platform supports several models: each is a selection of options (including a choice of implementations) defining how scenarios are simulated.
In the past, both components and implementations have been referred to as models.
The component of OpenMalaria responsible for surveys and tracking events such as treatment seeking and intervention deployment. See here or, for configuration options, here
A febrile illness, accompanied or not by parasites in the blood, which is not caused by malaria parasites.
OpenMalaria is the name of the C++ project and is the implementation of our simulator; i.e. the source code on this website.
See here for documentation of output file format.
A model in OpenMalaria determining, at each time point when a human is otherwise healthy, whether the individual becomes sick and whether this sickness is classified as "uncomplicated" or "severe". See this page.
Each model has several parameters. A choice of values for each of these parameters leads to a parameterization of a model. We usually use a fitting process involving several scenarios modelling field trials in order to find an optimal parameterizations.
In OpenMalaria, pharmacology concerns models of drug absorption and action within the body (parameterising), drug resistance and parasite genotypes and treatment doses and schedules.
The simulation is divided into several phases: warm-up, transmission stabilisation and intervention deployment. More ...
A script which allows some simple visualisations of one or a few scenario output files to be rapidly produced (useful for quickly checking a couple of outputs but not for full analysis). See here.
This page lists publications made regarding OpenMalaria models or their applications.
See this page for help on running simulations and this page for more instructions.
A script used to run OpenMalaria's test scenarios (and potentially other simulations). See this page.
S (back to top)
A scenario is a single simulation run by the model. Encoded in XML, the scenario file includes a description of what exactly OpenMalaria should the simulate: the model and its parameterization,the demographic_setting,interventionsapplied, and information about the healthsystem, if relevant to thestudy*.*
OpenMalaria simulations are described in an XML document. XML supports a schema format, XSD, describing what content is allowed in XML files. Schema files for released versions are named after the version, e.g. scenario_35.xsd. These "release versions" are generated from several smaller schema files, starting with schema/scenario.xsd.
The schema serves several purposes:
- Allows generation of C++ code to read XML files via Code Synthesis's XSD
- Documents what is allowed in XML scenario files without requiring reading the C++ code (however, there are a few additional restrictions enforced by the C++ code which cannot be enforced in the XSD schema)
- Houses user-facing documentation (see generated documentation)
A tool previously used to update XML files to a more recent OpenMalaria version.
In stochastic modeling, we have a bit of conundrum, we need to be able to generate a random sequence but we also need to be able to reproduce our results in order to test them. In order to achieve both goals simultaneously, we must declare the starting point for the (pseudo-) random number generator when it is called. This starting point, or seed is generally a positive integer. If no seed is given, the simulator will take the initial value from the computer's cpu clock - the simulation would run, but we would not be able to repeat it. Additionally, when we say that an experiment was run with 5 seeds, we mean that each scenario was run 5 times, each time with a different random seed.
Clinical malaria illness that is life-threatening if left untreated.
There has been some effort put into collecting "template" snippets of XML to ease writing new XML files. See this page.
A simulation study comprises a set of scenarios used to make a specific set of comparisons between settings or interventions. A field study is conducted on location with real patients. Results from field studies are used to parameterize models.
A monitoring "event" which reports on the state of the simulation (e.g. number of infected humans) and statistics accumulated since the last reporting "event" (e.g. number of fevers). See here for a description or here for a list of measures available.
A sweep is one factor (parameter) which varies in an experiment.
Sometimes referred to as timestep or time-step, this refers to the discrete time intervals used in the simulation. Existing models use a time step 1, 2 or 5 days long. Many parts of the XML support a unit suffix — e.g. 10d (days) or 2t (steps). See more on time steps, especially here.
Transfer of a parasite from one host (usually a human in our context) to another. Documentation of our models.
Certain parts of the code require a precise definition of what is considered treatment (this affects reporting and what is considered a second-line case). We define treatment as occurring during case management when:
Severe cases: when the patient visits hospital (irrespective of outcome).
Uncomplicated cases, using the DecisionTree5Day code: when any of the following happens
- "treatment failure" is selected as the case management outcome
- "simple treatment" is used to clear blood-stage parasites (but not otherwise, if the only action is to liver stages)
- PK/PD treatment is administered (even if the treatment schedule happens to be empty)
- any intervention (or pseudo-intervention) is deployed to the patient (irrespective of what kind of intervention this is)
Uncomplicated cases, using the ImmediateOutcomes code: when all of:
- the patient seeks treatment
- and the patient access any provider (including self treatment if the case is first-line)
- and, if diagnostics are used for UC treatment seeking, the diagnostic returns positive for infection
(1-day / EventScheduler should be similar to DecisionTree5Day, but the code needs checking.)
The action of treatment: usually administration of a drug, but may include other interventions such as distribution of bed-nets. More details.
These are models of parasite replication (and thus density) within humans. See this page.
A data storage format defined by the World Wide Web Consortium (W3C), which is used to describe OpenMalaria scenarios. XML basics.
See schema.
| Download openmalaria | Installation instructions | XML Schema Documentation |
| XML Schema Version | Program version | master |
develop |
|---|---|---|---|
| 43 | schema-43.0 |
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