Schema 28 documentation

Generated from: scenario_28.xsd.

Key:

  abc           required (one)
[ def ]         optional (zero or one)
( ghi )*        any number (zero or more)
( jkl )+        at least one
( mno ){2,inf}  two or more occurrences

Scenario

→ scenario

<scenario
    schemaVersion=int
    analysisNo=int
    name=string
    wuID=int
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xsi:noNamespaceSchemaLocation="scenario_28.xsd"
  >
IN ANY ORDER:
|   <demography ... /> 
|   <monitoring ... /> 
|   <interventions ... /> 
|   <healthSystem ... /> 
|   <entomology ... /> 
| [ <pharmacology ... /> ]
|   <model ... /> 
</scenario>

Documentation (element)

Units: List of elements

Description of scenario

Attributes

Version of the xml schema

schemaVersion=int

Version of xml schema. If not equal to the current version an error is thrown. Use SchemaTranslator to update xml files.

Reference number of the analysis

analysisNo=int

Units: Number Min: 1 Max: 100000000

Unique identifier of scenario

Name of intervention

name=string

Units: string

Name of intervention

Work unit identifier

wuID=int

Units: Number Min: 1 Max: 100000000

Work unit ID. Only used to validate checkpointing, to prevent checkpoint cheats.

Human age distribution

→ scenario → demography

<demography
    name=string
    popSize=int
    maximumAgeYrs=double
  [ growthRate=double ]
  >
IN THIS ORDER:
|   <ageGroup ... /> 
</demography>

Documentation (element)

Units: List of elements

Description of demography

Attributes

Name of demography data

name=string

Units: string

Name of demography data

Population size

popSize=int

Units: Count Min: 1 Max: 100000

Population size

Maximum age of simulated humans

maximumAgeYrs=double

Units: years Min: 0 Max: 100

Maximum age of simulated humans in years.

Growth rate of human population

growthRate=double

Units: Number Min: 0 Max: 0

Growth rate of human population. (we should be able to implement this with non-zero values)

Age groups

→ scenario → demography → ageGroup

<ageGroup
    lowerbound=double
  >
IN THIS ORDER:
| ( <group ... /> )+
</ageGroup>

Documentation (element)

Units: List of elements

List of age groups included in demography

Documentation (type)

Units: List of elements

List of age groups included in demography or surveys

Attributes

lower bound of age group

lowerbound=double

Units: Years Min: 0 Max: 100

Lower bound of age group

group

→ scenario → demography → ageGroup → group

<group
    poppercent=double
    upperbound=double
  />

Attributes

Percentage in age group

poppercent=double

Percentage of human population in age group

upper bound of age group

upperbound=double

Units: Years Min: 0 Max: 100

Upper bound of age group

Measures to be reported

→ scenario → monitoring

<monitoring
    name=string
  [ cohortOnly=boolean ]
  [ firstBoutOnly=boolean ]
  [ firstTreatmentOnly=boolean ]
  [ firstInfectionOnly=boolean ]
  >
IN THIS ORDER:
| [ <continuous ... /> ]
|   <SurveyOptions ... /> 
|   <surveys ... /> 
|   <ageGroup ... /> 
</monitoring>

Documentation (element)

Units: List of elements

Description of surveys

Attributes

Name of monitoring information

name=string

Units: string

Name of monitoring data

Survey only cohort

cohortOnly=boolean

If true, for many output measures, the output comes only from individuals in the cohort; otherwise output is from the entire population. Does not need to be specified if no cohort-selecting "interventions" are present.

Time to first episode only

firstBoutOnly=boolean

If true, remove individuals from the cohort at the start of the first episode (start of a clinical bout) since they were recruited into the cohort. This is intended for cohort studies that intend to measure time to first episode, using active case detection.

Time to first treatment only

firstTreatmentOnly=boolean

If true, remove individuals from the cohort when they first seek treatment since they were recruited into the cohort. This is intended for cohort studies that intend to measure time to first episode, using passive case detection.

Time to first infection only

firstInfectionOnly=boolean

If true, remove individuals from the cohort at completion of the first survey in which they present with a patent infection since they were recruited into the cohort. This intended for cohort studies that intend to measure time to first infection, using active case detection.

continuous

→ scenario → monitoring → continuous

<continuous
    period=int
  [ duringInit=boolean ]
  >
IN THIS ORDER:
| ( <option ... /> )*
</continuous>

Attributes

Days between reports

period=int

Units: Days Min: 1 Max: unbounded

Number of timesteps between reports.

During initialization

duringInit=boolean

Units: Days Min: 1 Max: unbounded

Also output during initialization. By default this is disabled (only intervention-period data is output). This should not be used for predictions, but can be useful for model validation. In this mode, 'simulation time' is output as the first column (in addition to 'timestep'), since 'timestep' is dis- continuous across the start of the intervention period.

option

→ scenario → monitoring → continuous → option

<option
    name=string
  [ value=boolean ] DEFAULT VALUE true
  />

Attributes

Model options required

name=string

Options define different model structures. Option name. Must be one of a strictly defined set. Options are not required to be listed if their default value is desired.

Indicator of whether option is required

value=boolean

Default value: true

Option value (true/false). Each option has a default value used if the option is not listed (usually false but sometimes true).

Name of quantity

→ scenario → monitoring → SurveyOptions

<SurveyOptions>
IN THIS ORDER:
| ( <option ... /> )*
</SurveyOptions>

Documentation (element)

List of all active survey options. See include/Survey.h for a list of supported outputs. Should also be on the wiki.

Survey times (time steps)

→ scenario → monitoring → surveys

<surveys
    detectionLimit=double
  >
IN THIS ORDER:
| ( <surveyTime ... /> )+
</surveys>

Documentation (element)

Units: List of elements

List of survey times

Attributes

Detection limit for parasitaemia

detectionLimit=double

Units: parasites/micolitre Min: 0 Max: 1000

Detection limit for parasitemia

Survey time

→ scenario → monitoring → surveys → surveyTime

<surveyTime>
    int
</surveyTime>

Documentation (element)

Units: Number Min: 0

Survey time; 0 means just before start of main sim and is a valid survey-point. Reported data is either from a point-time survey (immediate data) or is collected over the previous year (data from previous timesteps-per-year period). Simulation will end immediately after last survey is taken.

Age groups

→ scenario → monitoring → ageGroup

<ageGroup
    lowerbound=double
  >
IN THIS ORDER:
| ( <group ... /> )+
</ageGroup>

Documentation (element)

Units: List of elements

List of age groups included in demography or surveys

Documentation (type)

Units: List of elements

List of age groups included in surveys

Attributes

lower bound of age group

lowerbound=double

Units: Years Min: 0 Max: 100

Lower bound of age group

group

→ scenario → monitoring → ageGroup → group

<group
    upperbound=double
  />

Attributes

upper bound of age group

upperbound=double

Units: Years Min: 0 Max: 100

Upper bound of age group

Preventative interventions

→ scenario → interventions

<interventions
    name=string
  >
IN ANY ORDER:
| [ <changeHS ... /> ]
| [ <changeEIR ... /> ]
| [ <MDA ... /> ]
| [ <vaccine ... /> ]
| [ <IPT ... /> ]
| [ <ITN ... /> ]
| [ <IRS ... /> ]
| [ <vectorDeterrent ... /> ]
| [ <cohort ... /> ]
| [ <importedInfections ... /> ]
| [ <immuneSuppression ... /> ]
| [ <insertR_0Case ... /> ]
| [ <uninfectVectors ... /> ]
| [ <larviciding ... /> ]
</interventions>

Documentation (element)

Units: List of elements

List of interventions. Generally these are either point-time distributions of something to some subset of the population, or continuous-time distribution targetting individuals when they reach a certain age.

Attributes

Intervention

name=string

Units: string

Name of set of interventions

Change health system

→ scenario → interventions → changeHS

<changeHS
  [ name=string ]
  >
IN THIS ORDER:
| ( <timed ... /> )*
</changeHS>

Documentation (element)

Changes to the health system

Attributes

Name of intervention

name=string

Units: string

Name of intervention

timed

→ scenario → interventions → changeHS → timed

<timed
    time=int
  >
IN THIS ORDER:
| EXACTLY ONE OF:
| |   <EventScheduler ... /> 
| |   <ImmediateOutcomes ... /> 
|   <CFR ... /> 
|   <pSequelaeInpatient ... /> 
</timed>

Documentation (type)

A complete replacement health system. Replaces all previous properties. (Health system can be replaced multiple times if necessary.)

Documentation (base type)

Units: List of elements

Description of case management system, used to specify the initial model or a replacement (an intervention). Encompasses case management data and some other data required to derive case outcomes.

Contains a sub-element describing the particular health-system in use. Health system data is here defined as data used to decide on a treatment strategy, given a case requiring treatment.

Attributes

Time

time=int

Units: time-steps Min: 0

Time-step at which this replacement occurs, starting from 0, the first intervention-period time-step.

EventScheduler

→ scenario → healthSystem → EventScheduler

<EventScheduler>
IN THIS ORDER:
|   <uncomplicated ... /> 
|   <complicated ... /> 
|   <ClinicalOutcomes ... /> 
| [ <NonMalariaFevers ... /> ]
</EventScheduler>

uncomplicated

→ scenario → healthSystem → EventScheduler → uncomplicated

<uncomplicated>
IN THIS ORDER:
|   <decisions ... /> 
|   <treatments ... /> 
</uncomplicated>

Documentation (type)

Units: List of elements

A set of decisions and a set of treatments.

decisions

→ scenario → interventions → MDA → description → decisions

<decisions>
IN THIS ORDER:
| ( <decision ... /> )*
</decisions>

Documentation (type)

Description of decisions for a case management tree. A generic view of this tree would be that each decision is deterministic, or based on probabilities which may depend on other decisions. Probabilistic decisions are described here.

In general, each decision has a name, a defined set of outcome values, and a set of dependent decisions mentioned by name. The following decisions, with their associated outcomes, are provided by the code (and may not be included here):

  • case (uncomplicated only): Returns "UC1" if there is no recent history of a malarial case, or "UC2" if there is.
  • result: Dependent on decision "test", this performs a parasite density test. Output is one of "none" (no test performed), "positive", "negative".

The following decisions must be described here:

  • test (uncomplicated only): Outputs must be "none", "microscopy" or "RDT" to describe which test the "result" decision uses.
  • treatment: Describes which treatment to use. Values aren't restricted but must match up with a treatment described in the corresponding "treatments" section.
  • hospitalisation (complicated only): none, immediate or delayed.

decision

→ scenario → interventions → MDA → description → decisions → decision

<decision
    name=string
    depends=string
    values=string
  >
    string
</decision>

Documentation (type)

A decision describes how to choose between a set of values.

Lexically, it can contain symbols matching "[_.a-zA-Z0-9]+", round brackets: (), braces: {} and colons. Whitespace is ignored except to separate symbols.

Syntactically, it must match one TREE, where SYMBOL is a symbol described above. (Here, "x|y" means x or y, "x+" means x occurs once or more, brackets show grouping.) TREE := BRANCH_SET | OUTCOME BRANCH_SET := BRANCH+ BRANCH := DECISION '(' VALUE ')' ( ':' OUTCOME | '{' TREE '}' ) OUTCOME, DECISION, VALUE := SYMBOL

For each BRANCH_SET each BRANCH must have the same DECISION. This DECISION must be one of the dependencies mentioned in "depends". This may be:

  • another decision, in which case the VALUE immediately following in brackets must correspond to one of its output values. The BRANCH_SET immediately containing this BRANCH must represent each output value of the same decision exactly once, and no parent BRANCH_SET may be for the same DECISION.
  • "p": this indicates a probabilistic decision. In this case the value is a probability, the sum of all values for the BRANCH_SET must be 1 and the decision must be associated directly with OUTCOMEs (not sub-TREEs).
  • "age": this indicates an age-test. The VALUE must have the form "a-b", indicating that this branch will be taken for individuals aged such that a <= age < b, where a,b are non-negative real numbers or the special value "inf", and a <= b. All VALUEs in the BRANCH_SET must cover all possible (non-negative real) ages, with no overlap (hence, smallest a must be 0 and greatest b must be inf).

Semantically, each OUTCOME must be one of the values associated with this decision.

Attributes

Name of decision

name=string

The name of this decision. The name must match the regular expression "[_a-zA-Z0-9]+"; that is it can only contain letters, digits and _ characters (no spaces, punctuation, etc.).

Preceding decisions

depends=string

A comma-separated list of decisions that must have already been evaluated before this decision can be evaluated. Can be empty. Each must be hard-coded or described here. Can include the special decisions "p" and "age", though "age" cannot be combined with any other dependency.

Outcome values

values=string

A comma-separated list of outcome values this decision may have. The name of each value must be of the same form as decision names (i.e. only contain letters, digits and _ characters).

treatments

→ scenario → interventions → MDA → description → treatments

<treatments>
IN THIS ORDER:
| ( <treatment ... /> )*
</treatments>

Documentation (type)

Units: string

A list of drug treatment tables. Each should have a name corresponding to one of the "drug" decision's values.

treatment

→ scenario → interventions → MDA → description → treatments → treatment

<treatment
    name=string
  >
IN THIS ORDER:
|   <schedule ... /> 
| ( <modifier ... /> )*
</treatment>

Documentation (type)

Units: List of elements

A description of a base treatment schedule along with modifiers to handle delays, quality variations, etc.

Attributes

Treatment administered

name=string

Units: string

Name corresponding to one of the drug decision's output values.

schedule

→ scenario → interventions → MDA → description → treatments → treatment → schedule

<schedule>
IN THIS ORDER:
| ( <medicate ... /> )*
</schedule>

Documentation (type)

Units: List of elements

The base (unmodified) schedule of drugs administered for this treatment.

medicate

→ scenario → interventions → MDA → description → treatments → treatment → schedule → medicate

<medicate
    drug=string
    mg=double
    hour=double
  [ duration=double ]
  />

Attributes

drug

drug=string

Units: string

Abbreviated name of drug compound

drug dose

mg=double

Units: mg

Quantity of drug compound

time of administration

hour=double

Units: hours Min: 0

Number of hours past start of timestep this drug dose is administered at (first dose should be at hour 0).

duration of administration

duration=double

Units: hours Min: 0

If this attribute is given, use IV administration instead of orally. Specifies the number of hours over which the dose is administered.

modifier

→ scenario → interventions → MDA → description → treatments → treatment → modifier

<modifier
    decision=string
  >
EXACTLY ONE OF:
| ( <multiplyQty ... /> )*
| ( <delay ... /> )*
| ( <selectTimeRange ... /> )*
</modifier>

Documentation (type)

Units: Choice of elements

A modifier for this treatment, according to the outputs of a decision.

The "decision" attribute must be the name of a known decision. Then, there must be a set of multipyQty, delay or selectTimeRange sub-elements, each of which corresponds to one value output of the decision.

Attributes

decision

decision=string

Units: string

Specifies the decision that this modifier acts on.

Active ingredient multipliers

→ scenario → interventions → MDA → description → treatments → treatment → modifier → multiplyQty

<multiplyQty
    value=string
    effect=string
  [ affectsCost=boolean ]
  />

Documentation (element)

Units: Comma separated list of values

Multiplies the quantity of active ingredients of drugs administered.

The "drugs" attribute is a comma-separated list of all active ingredients administered in the base schedule (each must be listed once) and the content of this element is a comma- separated list of multipliers for each active ingredient, listed in the same order as in the "drugs" attribute. E.g. with drugs="A,B" and content "0.5,1" the quantity of drug A is halved while that of B is unchanged.

Attributes

value of decision

value=string

Units: string

Specifies a value of the decision to act on.

List of drugs affected

effect=string

Units: string

Comma-separated list of the effect the modifier has on each drug, in the form DRUG1(EFFECT1),DRUG2(EFFECT2), etc.

Affects cost?

affectsCost=boolean

Units: none

Does this affect the cost? If false, the effective drug usage (w.r.t. cost) is unaffected by this modifier; if true it is. Defaults to true (if omitted). Is meaningless for delays.

Active ingredient delays

→ scenario → interventions → MDA → description → treatments → treatment → modifier → delay

<delay
    value=string
    effect=string
  [ affectsCost=boolean ]
  />

Documentation (element)

Units: Comma separated list of values

Delays administration of drugs listed in the base schedule by so many hours.

The "drugs" attribute is a comma-separated list of all active ingredients administered in the base schedule (each must be listed once) and the content of this element is a comma- separated list of delays (in hours) for each active ingredient, listed in the same order as in the "drugs" attribute. E.g. with drugs="A,B" and content "0,6", drug A is administered as in the base schedule while drug B is administered 6 hours later than specified.

Attributes

value of decision

value=string

Units: string

Specifies a value of the decision to act on.

List of drugs affected

effect=string

Units: string

Comma-separated list of the effect the modifier has on each drug, in the form DRUG1(EFFECT1),DRUG2(EFFECT2), etc.

Affects cost?

affectsCost=boolean

Units: none

Does this affect the cost? If false, the effective drug usage (w.r.t. cost) is unaffected by this modifier; if true it is. Defaults to true (if omitted). Is meaningless for delays.

Active ingredient time-ranges

→ scenario → interventions → MDA → description → treatments → treatment → modifier → selectTimeRange

<selectTimeRange
    value=string
    effect=string
  [ affectsCost=boolean ]
  />

Documentation (element)

Units: Comma separated list of values

Selects which drug doses to administer according to time of administration (before times are modified by delays). Half-open interval: [x,y)

The "drugs" attribute is a comma-separated list of all active ingredients administered in the base schedule (each must be listed once) and the content of this element is a comma- separated list of time-ranges (in hours) for each active ingredient, listed in the same order as in the "drugs" attribute. The time-ranges should be of the form x-y and are interpreted as the half-open interval [x,y); that is a drug listed with time t will only be administered if x <= t < y.

Attributes

value of decision

value=string

Units: string

Specifies a value of the decision to act on.

List of drugs affected

effect=string

Units: string

Comma-separated list of the effect the modifier has on each drug, in the form DRUG1(EFFECT1),DRUG2(EFFECT2), etc.

Affects cost?

affectsCost=boolean

Units: none

Does this affect the cost? If false, the effective drug usage (w.r.t. cost) is unaffected by this modifier; if true it is. Defaults to true (if omitted). Is meaningless for delays.

complicated

→ scenario → healthSystem → EventScheduler → complicated

<complicated>
IN THIS ORDER:
|   <decisions ... /> 
|   <treatments ... /> 
</complicated>

Documentation (type)

Units: List of elements

A set of decisions and a set of treatments.

ClinicalOutcomes

→ scenario → healthSystem → EventScheduler → ClinicalOutcomes

<ClinicalOutcomes>
IN THIS ORDER:
|   <maxUCSeekingMemory ... /> 
|   <uncomplicatedCaseDuration ... /> 
|   <complicatedCaseDuration ... /> 
|   <complicatedRiskDuration ... /> 
| ( <dailyPrImmUCTS ... /> )+
</ClinicalOutcomes>

Documentation (type)

Description of base parameters of the clinical model.

Max UC treatment-seeking memory

→ scenario → healthSystem → EventScheduler → ClinicalOutcomes → maxUCSeekingMemory

<maxUCSeekingMemory>
    int
</maxUCSeekingMemory>

Documentation (element)

Units: days Min: 0 Max: unbounded

Maximum number of timesteps (including first of case) an individual will remember they are sick before resetting.

Uncomplicated case duration

→ scenario → healthSystem → EventScheduler → ClinicalOutcomes → uncomplicatedCaseDuration

<uncomplicatedCaseDuration>
    int
</uncomplicatedCaseDuration>

Documentation (element)

Units: days Min: 1 Max: unbounded

Fixed length of an uncomplicated case of malarial/non-malarial sickness (from treatment seeking until return to life-as-usual). Usually 3.

Complicated case duration

→ scenario → healthSystem → EventScheduler → ClinicalOutcomes → complicatedCaseDuration

<complicatedCaseDuration>
    int
</complicatedCaseDuration>

Documentation (element)

Units: days Min: 1 Max: unbounded

Fixed length of a complicated/severe case of malaria (from treatment seeking until return to life-as-usual).

Complicated risk duration

→ scenario → healthSystem → EventScheduler → ClinicalOutcomes → complicatedRiskDuration

<complicatedRiskDuration>
    int
</complicatedRiskDuration>

Documentation (element)

Units: days Min: 1 Max: unbounded

Number of days for which humans are at risk of death during a severe or complicated case of malaria. Cannot be greater than the duration of a complicated case or less than 1 day.

Daily probability of immediate treatment seeking for uncomplicated cases

→ scenario → healthSystem → EventScheduler → ClinicalOutcomes → dailyPrImmUCTS

<dailyPrImmUCTS>
    double
</dailyPrImmUCTS>

Documentation (element)

Units: none Min: 0 Max: 1

It is sometimes desirable to model delays to treatment seeking in uncomplicated cases. While treatment of drugs can be delayed within case management trees to provide a similar effect, this doesn't delay any of the decisions, including diagnostics using the current parasite density.

Instead a list of dailyPrImmUCTS elements can be used, describing successive daily probabilities of treatment (sum must be 1). For example, with a list of two elements with values 0.8 and 0.2, for 80% of UC cases the decision tree is evaluated immediately, and for 20% of cases evaluation is delayed by one day.

For no delay, use one element with a value of 1.

NonMalariaFevers

→ scenario → healthSystem → EventScheduler → NonMalariaFevers

<NonMalariaFevers>
IN THIS ORDER:
|   <prTreatment ... /> 
|   <effectNegativeTest ... /> 
|   <effectPositiveTest ... /> 
|   <effectNeed ... /> 
|   <effectInformal ... /> 
|   <CFR ... /> 
|   <TreatmentEfficacy ... /> 
</NonMalariaFevers>

Documentation (type)

Description of non-malaria fever health-system modelling (treatment, outcomes and costing). Incidence is described by the model->clinical->NonMalariaFevers element. Non-malaria fevers are only modelled if the NON_MALARIA_FEVERS option is used.

As further explanation of the parameters below, we first take: β₀ = logit(P₀) - β₃·P(need), and then calculate the probability of antibiotic administration, P(AB), dependent on treatment seeking location. No seeking: P(AB) = 0 Informal sector: logit(P(AB)) = β₀ + β₄ Health facility: logit(P(AB)) = β₀ + β₁·I(neg) + β₂·I(pos) + β₃·I(need) (where I(X) is 1 when event X is true and 0 otherwise, logit(p)=log(p/(1-p)), event "need" is the event that death may occur without treatment, events "neg" and "pos" are the events that a malaria parasite diagnositic was used and indicated no parasites and parasites respectively).

P(treatment|no diagnostic)

→ scenario → healthSystem → EventScheduler → NonMalariaFevers → prTreatment

<prTreatment>
    double
</prTreatment>

Documentation (element)

Units: none Min: 0 Max: 1

Probability of a non-malaria fever being treated with an antibiotic given that no malaria diagnostic was used but independent of need. Symbol: P₀.

Effect of a negative test

→ scenario → healthSystem → EventScheduler → NonMalariaFevers → effectNegativeTest

<effectNegativeTest>
    double
</effectNegativeTest>

Documentation (element)

The effect of a negative malaria diagnostic on the odds ratio of receiving antibiotics. Symbol: exp(β₁).

Effect of a positive test

→ scenario → healthSystem → EventScheduler → NonMalariaFevers → effectPositiveTest

<effectPositiveTest>
    double
</effectPositiveTest>

Documentation (element)

The effect of a positive malaria diagnostic on the odds ratio of receiving antibiotics. Symbol: exp(β₂).

Effect of need

→ scenario → healthSystem → EventScheduler → NonMalariaFevers → effectNeed

<effectNeed>
    double
</effectNeed>

Documentation (element)

The effect of needing antibiotic treatment on the odds ratio of receiving antibiotics. Symbol: exp(β₃).

Effect of informal provider

→ scenario → healthSystem → EventScheduler → NonMalariaFevers → effectInformal

<effectInformal>
    double
</effectInformal>

Documentation (element)

The effect of seeking treatment from an informal provider (i.e. a provider untrained in NMF diagnosis) on the odds ratio of receiving antibiotics. Symbol: exp(β₄)

Case fatality rate

→ scenario → healthSystem → EventScheduler → NonMalariaFevers → CFR

<CFR
  [ interpolation=("none" or "linear") ] DEFAULT VALUE linear
  >
IN THIS ORDER:
| ( <group ... /> )+
</CFR>

Documentation (element)

Units: none Min: 0 Max: 1

Base case fatality rate for non-malaria fevers (probability of death from a fever requiring antibiotic treatment given that no antibiotic treatment is received, per age-group).

Attributes

interpolation

interpolation=("none" or "linear")

Units: none

Default value: linear

Interpolation algorithm. Normally it is desirable for age-based values to be continuous w.r.t. age. By default linear interpolation is used. With all algorithms except "none", the age groups are converted to a set of points centred within each age range. Extra points are added at each end (zero and infinity) to keep value constant at both ends of the function. A zero-length age group may be used as a kind of barrier to adjust the distribution; e.g. with age group boundaries at 15, 20 and 25 years, a (linear) spline would be drawn between ages 17.5 and 22.5, whereas with boundaries at 15, 20 and 20 years, a spline would be drawn between ages 17.5 and 20 years (may be desired if individuals are assumed to reach adult size at 20). Algorithms:

  1. none: input values are used directly
  2. linear: straight lines (on an age vs. value graph) are used to interpolate data points.

age group

→ scenario → healthSystem → CFR → group

<group
    value=double
    lowerbound=double
  />

Documentation (element)

A series of values according to age groups, each specified with a lower-bound and a value. The first lower-bound specified must be zero; a final upper-bound of infinity is added to complete the last age group. At least one age group is required. Normally these are interpolated by a continuous function (see interpolation attribute).

Attributes

Input parameter value

value=double

A double-precision floating-point value.

Lower bound

lowerbound=double

Units: Years Min: 0 Max: 100

Lower bound of age group

Treatment efficacy

→ scenario → healthSystem → EventScheduler → NonMalariaFevers → TreatmentEfficacy

<TreatmentEfficacy>
    double
</TreatmentEfficacy>

Documentation (element)

Units: none Min: 0 Max: 1

Probability that treatment would prevent a death (i.e. CFR is multiplied by one minus this when treatment occurs).

ImmediateOutcomes

→ scenario → healthSystem → ImmediateOutcomes

<ImmediateOutcomes
    name=string
  >
IN THIS ORDER:
|   <drugRegimen ... /> 
|   <initialACR ... /> 
|   <compliance ... /> 
|   <nonCompliersEffective ... /> 
|   <pSeekOfficialCareUncomplicated1 ... /> 
|   <pSelfTreatUncomplicated ... /> 
|   <pSeekOfficialCareUncomplicated2 ... /> 
|   <pSeekOfficialCareSevere ... /> 
</ImmediateOutcomes>

Documentation (type)

Units: List of elements

Description of "immediate outcomes" health system: Tediosi et al case management model (Case management as described in AJTMH 75 (suppl 2) pp90-103).

Attributes

Case Management model

name=string

Units: string

Name of health system

Description of drug regimen

→ scenario → healthSystem → ImmediateOutcomes → drugRegimen

<drugRegimen
    firstLine=string
    secondLine=string
    inpatient=string
  />

Documentation (element)

Units: List of elements

Description of drug regimen

Attributes

First line drug

firstLine=string

Units: Drug code

Code for first line drug

Second line drug

secondLine=string

Units: Drug code

Code for second line drug

Drug use for treating inpatients

inpatient=string

Units: Drug code

Code for drug used for treating inpatients

Initial cure rate

→ scenario → healthSystem → ImmediateOutcomes → initialACR

<initialACR>
IN THIS ORDER:
| [ <CQ ... /> ]
| [ <SP ... /> ]
| [ <AQ ... /> ]
| [ <SPAQ ... /> ]
| [ <ACT ... /> ]
| [ <QN ... /> ]
|   <selfTreatment ... /> 
</initialACR>

Documentation (element)

Units: Proportion Min: 0 Max: 1

Initial cure rate

Chloroquine

→ scenario → healthSystem → ImmediateOutcomes → initialACR → CQ

<CQ
    value=double
  />

Documentation (element)

Units: List of elements

Chloroquine

Attributes

Input parameter value

value=double

A double-precision floating-point value.

Sulphadoxine-pyrimethamine

→ scenario → healthSystem → ImmediateOutcomes → initialACR → SP

<SP
    value=double
  />

Documentation (element)

Units: List of elements

Sulphadoxine-pyrimethamine

Attributes

Input parameter value

value=double

A double-precision floating-point value.

Amodiaquine

→ scenario → healthSystem → ImmediateOutcomes → initialACR → AQ

<AQ
    value=double
  />

Documentation (element)

Units: List of elements

Amodiaquine

Attributes

Input parameter value

value=double

A double-precision floating-point value.

Sulphadoxine-pyrimethamine/Amodiaquine

→ scenario → healthSystem → ImmediateOutcomes → initialACR → SPAQ

<SPAQ
    value=double
  />

Documentation (element)

Units: List of elements

Sulphadoxine-pyrimethamine/Amodiaquine

Attributes

Input parameter value

value=double

A double-precision floating-point value.

ACT

→ scenario → healthSystem → ImmediateOutcomes → initialACR → ACT

<ACT
    value=double
  />

Documentation (element)

Units: List of elements

Artemisinine combination therapy

Attributes

Input parameter value

value=double

A double-precision floating-point value.

QN

→ scenario → healthSystem → ImmediateOutcomes → initialACR → QN

<QN
    value=double
  />

Documentation (element)

Units: List of elements

Quinine

Attributes

Input parameter value

value=double

A double-precision floating-point value.

selfTreatment

→ scenario → healthSystem → ImmediateOutcomes → initialACR → selfTreatment

<selfTreatment
    value=double
  />

Documentation (element)

Units: Proportion Min: 0 Max: 1

Probability of self-treatment

Attributes

Input parameter value

value=double

A double-precision floating-point value.

Adherence to treatment

→ scenario → healthSystem → ImmediateOutcomes → compliance

<compliance>
IN THIS ORDER:
| [ <CQ ... /> ]
| [ <SP ... /> ]
| [ <AQ ... /> ]
| [ <SPAQ ... /> ]
| [ <ACT ... /> ]
| [ <QN ... /> ]
|   <selfTreatment ... /> 
</compliance>

Documentation (element)

Units: Proportion Min: 0 Max: 1

Adherence to treatment

Effectiveness of treatment in non-adherent patients

→ scenario → healthSystem → ImmediateOutcomes → nonCompliersEffective

<nonCompliersEffective>
IN THIS ORDER:
| [ <CQ ... /> ]
| [ <SP ... /> ]
| [ <AQ ... /> ]
| [ <SPAQ ... /> ]
| [ <ACT ... /> ]
| [ <QN ... /> ]
|   <selfTreatment ... /> 
</nonCompliersEffective>

Documentation (element)

Units: Proportion Min: 0 Max: 1

Effectiveness of treatment of non compliers

Probability that a patient with uncomplicated disease seeks official care immediately

→ scenario → healthSystem → ImmediateOutcomes → pSeekOfficialCareUncomplicated1

<pSeekOfficialCareUncomplicated1
    value=double
  />

Documentation (element)

Units: Proportion Min: 0 Max: 1

Probability that a patient with newly incident uncomplicated disease seeks official care

Attributes

Input parameter value

value=double

A double-precision floating-point value.

Probability that a patient with uncomplicated disease self-treats

→ scenario → healthSystem → ImmediateOutcomes → pSelfTreatUncomplicated

<pSelfTreatUncomplicated
    value=double
  />

Documentation (element)

Units: Proportion Min: 0 Max: 1

Probability that a patient with uncomplicated disease self-treats

Attributes

Input parameter value

value=double

A double-precision floating-point value.

Probability that a recurring patient seeks official care

→ scenario → healthSystem → ImmediateOutcomes → pSeekOfficialCareUncomplicated2

<pSeekOfficialCareUncomplicated2
    value=double
  />

Documentation (element)

Units: Proportion Min: 0 Max: 1

Probability that a patient with recurrence of uncomplicated disease seeks official care

Attributes

Input parameter value

value=double

A double-precision floating-point value.

Probability that a patient with severe disease obtains appropriate care

→ scenario → healthSystem → ImmediateOutcomes → pSeekOfficialCareSevere

<pSeekOfficialCareSevere
    value=double
  />

Documentation (element)

Units: Proportion Min: 0 Max: 1

Probability that a patient with severe disease obtains appropriate care

Attributes

Input parameter value

value=double

A double-precision floating-point value.

Case fatality rate in inpatients

→ scenario → healthSystem → CFR

<CFR
  [ interpolation=("none" or "linear") ] DEFAULT VALUE linear
  >
IN THIS ORDER:
| ( <group ... /> )+
</CFR>

Documentation (element)

Units: List of elements

Case fatality rate (probability of an inpatient fatality from a bout of severe malaria, per age-group).

Attributes

interpolation

interpolation=("none" or "linear")

Units: none

Default value: linear

Interpolation algorithm. Normally it is desirable for age-based values to be continuous w.r.t. age. By default linear interpolation is used. With all algorithms except "none", the age groups are converted to a set of points centred within each age range. Extra points are added at each end (zero and infinity) to keep value constant at both ends of the function. A zero-length age group may be used as a kind of barrier to adjust the distribution; e.g. with age group boundaries at 15, 20 and 25 years, a (linear) spline would be drawn between ages 17.5 and 22.5, whereas with boundaries at 15, 20 and 20 years, a spline would be drawn between ages 17.5 and 20 years (may be desired if individuals are assumed to reach adult size at 20). Algorithms:

  1. none: input values are used directly
  2. linear: straight lines (on an age vs. value graph) are used to interpolate data points.

Probabilities of sequelae in inpatients

→ scenario → healthSystem → pSequelaeInpatient

<pSequelaeInpatient
  [ interpolation=("none" or "linear") ] DEFAULT VALUE linear
  >
IN THIS ORDER:
| ( <group ... /> )+
</pSequelaeInpatient>

Documentation (element)

Units: List of elements

List of age specific probabilities of sequelae in inpatients, during a severe bout.

Attributes

interpolation

interpolation=("none" or "linear")

Units: none

Default value: linear

Interpolation algorithm. Normally it is desirable for age-based values to be continuous w.r.t. age. By default linear interpolation is used. With all algorithms except "none", the age groups are converted to a set of points centred within each age range. Extra points are added at each end (zero and infinity) to keep value constant at both ends of the function. A zero-length age group may be used as a kind of barrier to adjust the distribution; e.g. with age group boundaries at 15, 20 and 25 years, a (linear) spline would be drawn between ages 17.5 and 22.5, whereas with boundaries at 15, 20 and 20 years, a spline would be drawn between ages 17.5 and 20 years (may be desired if individuals are assumed to reach adult size at 20). Algorithms:

  1. none: input values are used directly
  2. linear: straight lines (on an age vs. value graph) are used to interpolate data points.

Change transmission levels

→ scenario → interventions → changeEIR

<changeEIR
  [ name=string ]
  >
IN THIS ORDER:
| ( <timed ... /> )*
</changeEIR>

Documentation (element)

New description of transmission level for models not supporting vector control interventions. Use of this overrides previous transmission levels such that human infectiousness no longer has any feedback effect on transmission. Supplied EIR data must last until end of simulation.

Attributes

Name of intervention

name=string

Units: string

Name of intervention

timed

→ scenario → interventions → changeEIR → timed

<timed
    eipDuration=int
    time=int
  >
IN THIS ORDER:
| ( <EIRDaily ... /> )+
</timed>

Documentation (type)

Replacement transmission levels. Disables feedback of human infectiousness to mosquitoes on further mosquito to human transmission. Must last until end of simulation.

Attributes

Duration of sporogony (days)

eipDuration=int

The duration of sporogony in days

Time

time=int

Units: time-steps Min: 0

Time-step at which this replacement occurs, starting from 0, the first intervention-period time-step.

EIRDaily

→ scenario → entomology → nonVector → EIRDaily

<EIRDaily
  [ origin=string ]
  >
    double
</EIRDaily>

Documentation (type)

Units: Infectious bites per adult per day

In the non-vector model, EIR is input as a sequence of daily values. There must be at least a years' worth of entries (365), and if there are more, values are wrapped and averaged (i.e. value for first day of year is taken as the mean of values for days 0, 365+0, 2*365+0, etc.).

Attributes

Time origin of EIR sequence

origin=string

Mass drug administration

→ scenario → interventions → MDA

<MDA
  [ name=string ]
  >
IN THIS ORDER:
| [ <description ... /> ]
| ( <timed ... /> )*
</MDA>

Documentation (element)

Description and deployment of MDA interventions (can also be configured as screen and treat or intermittent preventative treatment with 1-day time-step models).

Attributes

Name of intervention

name=string

Units: string

Name of intervention

Description of MDA

→ scenario → interventions → MDA → description

<description
  [ name=string ]
  >
IN THIS ORDER:
|   <decisions ... /> 
|   <treatments ... /> 
</description>

Documentation (element)

Description of treatment type used by mass treatment option of one-day case management model. Can be used to describe one-size-fits-all mass drug dosing, age-based mass drug dosing and screen-and-treat. Number of treatments given can be reported by the nMDAs option.

Documentation (base type)

Units: List of elements

A set of decisions and a set of treatments.

Attributes

Intervention

name=string

Units: string

Name of set of interventions

Mass administration

→ scenario → interventions → MDA → timed

<timed
    time=int
  [ maxAge=double ] DEFAULT VALUE 100
  [ minAge=double ] DEFAULT VALUE 0
    coverage=double
  [ cohort=boolean ] DEFAULT VALUE false
  />

Documentation (element)

List of timed deployments of mass-drug-administration.

Attributes

Time

time=int

Units: time-steps Min: 0

Time-step at which this intervention occurs, starting from 0, the first intervention-period time-step.

Maximum age of eligible individuals

maxAge=double

Units: Years Min: 0 Max: 100

Default value: 100

Maximum age of eligible individuals (defaults to 100)

Minimum age of eligible individuals

minAge=double

Units: Years Min: 0 Max: 100

Default value: 0

Minimum age of eligible individuals (defaults to 0)

Coverage

coverage=double

Units: Proportion Min: 0 Max: 1

Coverage of intervention

Cohort only

cohort=boolean

Units: Proportion Min: 0 Max: 1

Default value: false

Restrict distribution to chosen cohort.

Vaccines

→ scenario → interventions → vaccine

<vaccine
  [ name=string ]
  >
IN THIS ORDER:
| ( <description ... /> ){0,3}
| ( <continuous ... /> )*
| ( <timed ... /> )*
</vaccine>

Documentation (element)

Description and deployment of vaccine interventions.

Attributes

Name of intervention

name=string

Units: string

Name of intervention

description

→ scenario → interventions → vaccine → description

<description
    vaccineType=("PEV" or "BSV" or "TBV")
  [ name=string ]
  >
IN THIS ORDER:
|   <decay ... /> 
|   <efficacyB ... /> 
| ( <initialEfficacy ... /> )+
</description>

Documentation (type)

List of vaccine descriptions

Attributes

Type of vaccine

vaccineType=("PEV" or "BSV" or "TBV")

Units: Code

Type of vaccine

Vaccine

name=string

Units: string

Name of vaccine

Decay of effect

→ scenario → interventions → vaccine → description → decay

<decay
    function=("constant" or "step" or "linear" or "exponential" or "weibull" or "hill" or "smooth-compact")
    L=double
  [ k=double ] DEFAULT VALUE 1.0
  [ sigma=double ] DEFAULT VALUE 0
  />

Documentation (element)

Specification of decay of efficacy

Documentation (type)

Specification of decay or survival of a parameter.

Attributes

function

function=("constant" or "step" or "linear" or "exponential" or "weibull" or "hill" or "smooth-compact")

Units: None Min: 0 Max: 1

Determines which decay function to use. Available decay functions, for age t in years: constant: 1 step: 1 for t less than L, otherwise 0 linear: 1 - t/L for t less than L, otherwise 0 exponential: exp( - t/L * log(2) ) weibull: exp( -(t/L)^k * log(2) ) hill: 1 / (1 + (t/L)^k) smooth-compact: exp( k - k / (1 - (t/L)^2) ) for t less than L, otherwise 0

L

L=double

Units: Years Min: 0

Scale parameter of distribution. With the smooth-compact (smooth function with compact support), step and linear functions, this is the age at which the parameter has decayed to 0; with the other three functions, this is the age at which the parameter has decayed to half its original value. Not used for constant decay (though must be specified anyway).

k

k=double

Units: none Min: 0

Default value: 1.0

Shape parameter of distribution. If not specified, default value of 1 is used. Meaning depends on function; not used in some cases.

σ (sigma)

sigma=double

Units: none Min: 0

Default value: 0

If non-zero, heterogeneity of decay is introduced via a variate sampled from the log-normal distribution with mu zero (i.e. median is 1) and this sigma. Age is then divided by this variate before being passed to the decay function.

Variance parameter for vaccine efficacy

→ scenario → interventions → vaccine → description → efficacyB

<efficacyB
    value=double
  />

Documentation (element)

Units: Positive real Min: 0.001 Max: 1.00E+06

Measure of variation in vaccine efficacy

Attributes

Input parameter value

value=double

A double-precision floating-point value.

initialEfficacy

→ scenario → interventions → vaccine → description → initialEfficacy

<initialEfficacy
    value=double
  />

Attributes

Input parameter value

value=double

A double-precision floating-point value.

Age-based vaccination

→ scenario → interventions → vaccine → continuous

<continuous
    targetAgeYrs=double
    coverage=double
  [ cohort=boolean ] DEFAULT VALUE false
  [ begin=int ] DEFAULT VALUE 0
  [ end=int ] DEFAULT VALUE 2147483647
  />

Documentation (element)

List of ages at which vaccination takes place (through EPI, post-natal and school-based programmes, etc.).

Attributes

Target age

targetAgeYrs=double

Units: Years Min: 0 Max: 100

Target age of intervention

Proportion covered

coverage=double

Units: Proportion Min: 0 Max: 1

Coverage of intervention

Cohort only

cohort=boolean

Units: Proportion Min: 0 Max: 1

Default value: false

Restrict distribution to chosen cohort (default: false).

First timestep active

begin=int

Units: Timesteps Min: 0 Max: 2147483647

Default value: 0

First timestep (from 0 at the beginning of the intervention period) this item is active. Defaults to 0.

End timestep

end=int

Units: Timesteps Min: 0 Max: 2147483647

Default value: 2147483647

End of the period during which the intervention is active (to be exact, the first timestep of the intervention period at which the item becomes inactive). Defaults to 2147483647.

Mass vaccination

→ scenario → interventions → vaccine → timed

<timed
    time=int
  [ maxAge=double ] DEFAULT VALUE 100
  [ minAge=double ] DEFAULT VALUE 0
    coverage=double
  [ cohort=boolean ] DEFAULT VALUE false
  [ cumulativeWithMaxAge=double ]
  />

Documentation (element)

List of timed mass vaccinations in the community

Attributes

Time

time=int

Units: time-steps Min: 0

Time-step at which this intervention occurs, starting from 0, the first intervention-period time-step.

Maximum age of eligible individuals

maxAge=double

Units: Years Min: 0 Max: 100

Default value: 100

Maximum age of eligible individuals (defaults to 100)

Minimum age of eligible individuals

minAge=double

Units: Years Min: 0 Max: 100

Default value: 0

Minimum age of eligible individuals (defaults to 0)

Coverage

coverage=double

Units: Proportion Min: 0 Max: 1

Coverage of intervention

Cohort only

cohort=boolean

Units: Proportion Min: 0 Max: 1

Default value: false

Restrict distribution to chosen cohort.

Cumulative deployment: maximum age

cumulativeWithMaxAge=double

Units: Years Min: 0

If present, activate cumulate deployment mode where intervention is only deployed to individuals not already considered protected in sufficient quantity to bring the total proportion of people covered up to level described by "coverage". Individuals are considered already protected by this intervention when the age of the last net/dose/etc. received is less than "maximum age" (this attribute) years old (i.e. when timeLastDeployment+maximumAge>currentTimeStep).

Intermittent preventative treatment

→ scenario → interventions → IPT

<IPT
  [ name=string ]
  >
IN THIS ORDER:
|   <description ... /> 
| ( <continuous ... /> )*
| ( <timed ... /> )*
</IPT>

Documentation (element)

Description and deployment of IPT interventions.

Attributes

Name of intervention

name=string

Units: string

Name of intervention

description

→ scenario → interventions → IPT → description

<description
    iptiEffect=int
  [ name=string ]
  >
IN THIS ORDER:
| ( <infGenotype ... /> )+
</description>

Attributes

Description of ipti effect

iptiEffect=int

Units: List of Elementes

Description of ipti effect

IPT name

name=string

Units: string

Name of IPT intervention

infGenotype

→ scenario → interventions → IPT → description → infGenotype

<infGenotype
    name=string
    freq=double
    ACR=double
    proph=int
    tolPeriod=int
    atten=double
  />

Attributes

Age specific intervention

name=string

Units: string

Name of age specific intervention

Frequency

freq=double

Frequency of parasite genotype

ACR

ACR=double

Adequate clinical response (proportion)

Prophylactic period

proph=int

Prophylactic period

Tolerance period

tolPeriod=int

Tolerance period

Tolerance period

atten=double

Tolerance period

Age-based IPT deployment

→ scenario → interventions → IPT → continuous

<continuous
    targetAgeYrs=double
    coverage=double
  [ cohort=boolean ] DEFAULT VALUE false
  [ begin=int ] DEFAULT VALUE 0
  [ end=int ] DEFAULT VALUE 2147483647
  />

Documentation (element)

List of ages at which IPTi/IPTc deployment takes place (through EPI, post-natal and school-based programmes, etc.).

Attributes

Target age

targetAgeYrs=double

Units: Years Min: 0 Max: 100

Target age of intervention

Proportion covered

coverage=double

Units: Proportion Min: 0 Max: 1

Coverage of intervention

Cohort only

cohort=boolean

Units: Proportion Min: 0 Max: 1

Default value: false

Restrict distribution to chosen cohort (default: false).

First timestep active

begin=int

Units: Timesteps Min: 0 Max: 2147483647

Default value: 0

First timestep (from 0 at the beginning of the intervention period) this item is active. Defaults to 0.

End timestep

end=int

Units: Timesteps Min: 0 Max: 2147483647

Default value: 2147483647

End of the period during which the intervention is active (to be exact, the first timestep of the intervention period at which the item becomes inactive). Defaults to 2147483647.

Mass IPT administration

→ scenario → interventions → IPT → timed

<timed
    time=int
  [ maxAge=double ] DEFAULT VALUE 100
  [ minAge=double ] DEFAULT VALUE 0
    coverage=double
  [ cohort=boolean ] DEFAULT VALUE false
  [ cumulativeWithMaxAge=double ]
  />

Documentation (element)

List of timed IPTi/IPTc distribution

Attributes

Time

time=int

Units: time-steps Min: 0

Time-step at which this intervention occurs, starting from 0, the first intervention-period time-step.

Maximum age of eligible individuals

maxAge=double

Units: Years Min: 0 Max: 100

Default value: 100

Maximum age of eligible individuals (defaults to 100)

Minimum age of eligible individuals

minAge=double

Units: Years Min: 0 Max: 100

Default value: 0

Minimum age of eligible individuals (defaults to 0)

Coverage

coverage=double

Units: Proportion Min: 0 Max: 1

Coverage of intervention

Cohort only

cohort=boolean

Units: Proportion Min: 0 Max: 1

Default value: false

Restrict distribution to chosen cohort.

Cumulative deployment: maximum age

cumulativeWithMaxAge=double

Units: Years Min: 0

If present, activate cumulate deployment mode where intervention is only deployed to individuals not already considered protected in sufficient quantity to bring the total proportion of people covered up to level described by "coverage". Individuals are considered already protected by this intervention when the age of the last net/dose/etc. received is less than "maximum age" (this attribute) years old (i.e. when timeLastDeployment+maximumAge>currentTimeStep).

Bed nets

→ scenario → interventions → ITN

<ITN
  [ name=string ]
  >
IN THIS ORDER:
|   <decay ... /> 
| ( <anophelesParams ... /> )+
| ( <continuous ... /> )*
| ( <timed ... /> )*
</ITN>

Documentation (element)

Description and deployment of bed-net interventions (ITNs, LLINs).

Attributes

Name of intervention

name=string

Units: string

Name of intervention

decay

→ scenario → interventions → ITN → decay

<decay
    function=("constant" or "step" or "linear" or "exponential" or "weibull" or "hill" or "smooth-compact")
    L=double
  [ k=double ] DEFAULT VALUE 1.0
  [ sigma=double ] DEFAULT VALUE 0
  />

Documentation (type)

Specification of decay or survival of a parameter.

Attributes

function

function=("constant" or "step" or "linear" or "exponential" or "weibull" or "hill" or "smooth-compact")

Units: None Min: 0 Max: 1

Determines which decay function to use. Available decay functions, for age t in years: constant: 1 step: 1 for t less than L, otherwise 0 linear: 1 - t/L for t less than L, otherwise 0 exponential: exp( - t/L * log(2) ) weibull: exp( -(t/L)^k * log(2) ) hill: 1 / (1 + (t/L)^k) smooth-compact: exp( k - k / (1 - (t/L)^2) ) for t less than L, otherwise 0

L

L=double

Units: Years Min: 0

Scale parameter of distribution. With the smooth-compact (smooth function with compact support), step and linear functions, this is the age at which the parameter has decayed to 0; with the other three functions, this is the age at which the parameter has decayed to half its original value. Not used for constant decay (though must be specified anyway).

k

k=double

Units: none Min: 0

Default value: 1.0

Shape parameter of distribution. If not specified, default value of 1 is used. Meaning depends on function; not used in some cases.

σ (sigma)

sigma=double

Units: none Min: 0

Default value: 0

If non-zero, heterogeneity of decay is introduced via a variate sampled from the log-normal distribution with mu zero (i.e. median is 1) and this sigma. Age is then divided by this variate before being passed to the decay function.

anophelesParams

→ scenario → interventions → ITN → anophelesParams

<anophelesParams
    mosquito=string
  >
IN THIS ORDER:
|   <deterrency ... /> 
</anophelesParams>

Documentation (base type)

Units: None Min: 0 Max: 1

Descriptions of initial effectiveness of each of the effects of interventions. Decay is specified by a separate element (ITNDecay etc.)

Attributes

Mosquito species

mosquito=string

Name of the affected anopheles-mosquito species.

Deterrency

→ scenario → interventions → ITN → anophelesParams → deterrency

<deterrency
    value=double
  />

Documentation (element)

Units: None Min: 0 Max: 1

One minus this multiplies the host's availability.

Attributes

Input parameter value

value=double

A double-precision floating-point value.

Pre-prandial killing effect

→ scenario → interventions → ITN → anophelesParams → preprandialKillingEffect

<preprandialKillingEffect
    value=double
  />

Documentation (element)

Units: None Min: 0 Max: 1

One minus this multiplies the survival rate of mosquitoes attempting to bite a host.

Attributes

Input parameter value

value=double

A double-precision floating-point value.

Post-prandial killing effect

→ scenario → interventions → ITN → anophelesParams → postprandialKillingEffect

<postprandialKillingEffect
    value=double
  />

Documentation (element)

Units: None Min: 0 Max: 1

One minus this multiplies the survival rate of mosquitoes attempting to escape after biting a host.

Attributes

Input parameter value

value=double

A double-precision floating-point value.

Age-based bed-net deployment

→ scenario → interventions → ITN → continuous

<continuous
    targetAgeYrs=double
    coverage=double
  [ cohort=boolean ] DEFAULT VALUE false
  [ begin=int ] DEFAULT VALUE 0
  [ end=int ] DEFAULT VALUE 2147483647
  />

Documentation (element)

List of ages at which bed-net deployment takes place (through EPI, post-natal and school-based programmes, etc.).

Attributes

Target age

targetAgeYrs=double

Units: Years Min: 0 Max: 100

Target age of intervention

Proportion covered

coverage=double

Units: Proportion Min: 0 Max: 1

Coverage of intervention

Cohort only

cohort=boolean

Units: Proportion Min: 0 Max: 1

Default value: false

Restrict distribution to chosen cohort (default: false).

First timestep active

begin=int

Units: Timesteps Min: 0 Max: 2147483647

Default value: 0

First timestep (from 0 at the beginning of the intervention period) this item is active. Defaults to 0.

End timestep

end=int

Units: Timesteps Min: 0 Max: 2147483647

Default value: 2147483647

End of the period during which the intervention is active (to be exact, the first timestep of the intervention period at which the item becomes inactive). Defaults to 2147483647.

Mass ITN deployment

→ scenario → interventions → ITN → timed

<timed
    time=int
  [ maxAge=double ] DEFAULT VALUE 100
  [ minAge=double ] DEFAULT VALUE 0
    coverage=double
  [ cohort=boolean ] DEFAULT VALUE false
  [ cumulativeWithMaxAge=double ]
  />

Documentation (element)

List of timed ITN deployment in the community

Attributes

Time

time=int

Units: time-steps Min: 0

Time-step at which this intervention occurs, starting from 0, the first intervention-period time-step.

Maximum age of eligible individuals

maxAge=double

Units: Years Min: 0 Max: 100

Default value: 100

Maximum age of eligible individuals (defaults to 100)

Minimum age of eligible individuals

minAge=double

Units: Years Min: 0 Max: 100

Default value: 0

Minimum age of eligible individuals (defaults to 0)

Coverage

coverage=double

Units: Proportion Min: 0 Max: 1

Coverage of intervention

Cohort only

cohort=boolean

Units: Proportion Min: 0 Max: 1

Default value: false

Restrict distribution to chosen cohort.

Cumulative deployment: maximum age

cumulativeWithMaxAge=double

Units: Years Min: 0

If present, activate cumulate deployment mode where intervention is only deployed to individuals not already considered protected in sufficient quantity to bring the total proportion of people covered up to level described by "coverage". Individuals are considered already protected by this intervention when the age of the last net/dose/etc. received is less than "maximum age" (this attribute) years old (i.e. when timeLastDeployment+maximumAge>currentTimeStep).

Indoor residual spraying

→ scenario → interventions → IRS

<IRS
  [ name=string ]
  >
IN THIS ORDER:
|   <decay ... /> 
| ( <anophelesParams ... /> )+
| ( <timed ... /> )*
</IRS>

Documentation (element)

Description and deployment of indoor insecticide interventions (IRS, durable wall linings, insecticide-treated-paint, etc.)

Attributes

Name of intervention

name=string

Units: string

Name of intervention

decay

→ scenario → interventions → IRS → decay

<decay
    function=("constant" or "step" or "linear" or "exponential" or "weibull" or "hill" or "smooth-compact")
    L=double
  [ k=double ] DEFAULT VALUE 1.0
  [ sigma=double ] DEFAULT VALUE 0
  />

Documentation (type)

Specification of decay or survival of a parameter.

Attributes

function

function=("constant" or "step" or "linear" or "exponential" or "weibull" or "hill" or "smooth-compact")

Units: None Min: 0 Max: 1

Determines which decay function to use. Available decay functions, for age t in years: constant: 1 step: 1 for t less than L, otherwise 0 linear: 1 - t/L for t less than L, otherwise 0 exponential: exp( - t/L * log(2) ) weibull: exp( -(t/L)^k * log(2) ) hill: 1 / (1 + (t/L)^k) smooth-compact: exp( k - k / (1 - (t/L)^2) ) for t less than L, otherwise 0

L

L=double

Units: Years Min: 0

Scale parameter of distribution. With the smooth-compact (smooth function with compact support), step and linear functions, this is the age at which the parameter has decayed to 0; with the other three functions, this is the age at which the parameter has decayed to half its original value. Not used for constant decay (though must be specified anyway).

k

k=double

Units: none Min: 0

Default value: 1.0

Shape parameter of distribution. If not specified, default value of 1 is used. Meaning depends on function; not used in some cases.

σ (sigma)

sigma=double

Units: none Min: 0

Default value: 0

If non-zero, heterogeneity of decay is introduced via a variate sampled from the log-normal distribution with mu zero (i.e. median is 1) and this sigma. Age is then divided by this variate before being passed to the decay function.

anophelesParams

→ scenario → interventions → IRS → anophelesParams

<anophelesParams
    mosquito=string
  >
IN THIS ORDER:
|   <deterrency ... /> 
</anophelesParams>

Documentation (base type)

Units: None Min: 0 Max: 1

Descriptions of initial effectiveness of each of the effects of interventions. Decay is specified by a separate element (ITNDecay etc.)

Attributes

Mosquito species

mosquito=string

Name of the affected anopheles-mosquito species.

killing effect

→ scenario → interventions → IRS → anophelesParams → killingEffect

<killingEffect
    value=double
  />

Documentation (element)

Units: None Min: 0 Max: 1

One minus this multiplies the survival rate of resting mosquitoes.

Attributes

Input parameter value

value=double

A double-precision floating-point value.

Mass IRS deployment

→ scenario → interventions → IRS → timed

<timed
    time=int
  [ maxAge=double ] DEFAULT VALUE 100
  [ minAge=double ] DEFAULT VALUE 0
    coverage=double
  [ cohort=boolean ] DEFAULT VALUE false
  [ cumulativeWithMaxAge=double ]
  />

Documentation (element)

List of timed IRS deployment in the community

Attributes

Time

time=int

Units: time-steps Min: 0

Time-step at which this intervention occurs, starting from 0, the first intervention-period time-step.

Maximum age of eligible individuals

maxAge=double

Units: Years Min: 0 Max: 100

Default value: 100

Maximum age of eligible individuals (defaults to 100)

Minimum age of eligible individuals

minAge=double

Units: Years Min: 0 Max: 100

Default value: 0

Minimum age of eligible individuals (defaults to 0)

Coverage

coverage=double

Units: Proportion Min: 0 Max: 1

Coverage of intervention

Cohort only

cohort=boolean

Units: Proportion Min: 0 Max: 1

Default value: false

Restrict distribution to chosen cohort.

Cumulative deployment: maximum age

cumulativeWithMaxAge=double

Units: Years Min: 0

If present, activate cumulate deployment mode where intervention is only deployed to individuals not already considered protected in sufficient quantity to bring the total proportion of people covered up to level described by "coverage". Individuals are considered already protected by this intervention when the age of the last net/dose/etc. received is less than "maximum age" (this attribute) years old (i.e. when timeLastDeployment+maximumAge>currentTimeStep).

Vector deterrents

→ scenario → interventions → vectorDeterrent

<vectorDeterrent
  [ name=string ]
  >
IN THIS ORDER:
|   <decay ... /> 
| ( <anophelesParams ... /> )+
| ( <timed ... /> )*
</vectorDeterrent>

Documentation (element)

Description and deployment of interventions affecting only human-mosquito availability (deterrents).

Attributes

Name of intervention

name=string

Units: string

Name of intervention

decay

→ scenario → interventions → vectorDeterrent → decay

<decay
    function=("constant" or "step" or "linear" or "exponential" or "weibull" or "hill" or "smooth-compact")
    L=double
  [ k=double ] DEFAULT VALUE 1.0
  [ sigma=double ] DEFAULT VALUE 0
  />

Documentation (type)

Specification of decay or survival of a parameter.

Attributes

function

function=("constant" or "step" or "linear" or "exponential" or "weibull" or "hill" or "smooth-compact")

Units: None Min: 0 Max: 1

Determines which decay function to use. Available decay functions, for age t in years: constant: 1 step: 1 for t less than L, otherwise 0 linear: 1 - t/L for t less than L, otherwise 0 exponential: exp( - t/L * log(2) ) weibull: exp( -(t/L)^k * log(2) ) hill: 1 / (1 + (t/L)^k) smooth-compact: exp( k - k / (1 - (t/L)^2) ) for t less than L, otherwise 0

L

L=double

Units: Years Min: 0

Scale parameter of distribution. With the smooth-compact (smooth function with compact support), step and linear functions, this is the age at which the parameter has decayed to 0; with the other three functions, this is the age at which the parameter has decayed to half its original value. Not used for constant decay (though must be specified anyway).

k

k=double

Units: none Min: 0

Default value: 1.0

Shape parameter of distribution. If not specified, default value of 1 is used. Meaning depends on function; not used in some cases.

σ (sigma)

sigma=double

Units: none Min: 0

Default value: 0

If non-zero, heterogeneity of decay is introduced via a variate sampled from the log-normal distribution with mu zero (i.e. median is 1) and this sigma. Age is then divided by this variate before being passed to the decay function.

anophelesParams

→ scenario → interventions → vectorDeterrent → anophelesParams

<anophelesParams
    mosquito=string
  >
IN THIS ORDER:
|   <deterrency ... /> 
</anophelesParams>

Documentation (base type)

Units: None Min: 0 Max: 1

Descriptions of initial effectiveness of each of the effects of interventions. Decay is specified by a separate element (ITNDecay etc.)

Attributes

Mosquito species

mosquito=string

Name of the affected anopheles-mosquito species.

Mass deployment

→ scenario → interventions → vectorDeterrent → timed

<timed
    time=int
  [ maxAge=double ] DEFAULT VALUE 100
  [ minAge=double ] DEFAULT VALUE 0
    coverage=double
  [ cohort=boolean ] DEFAULT VALUE false
  [ cumulativeWithMaxAge=double ]
  />

Documentation (element)

List of timed mosquito deterrent deployment in the community

Attributes

Time

time=int

Units: time-steps Min: 0

Time-step at which this intervention occurs, starting from 0, the first intervention-period time-step.

Maximum age of eligible individuals

maxAge=double

Units: Years Min: 0 Max: 100

Default value: 100

Maximum age of eligible individuals (defaults to 100)

Minimum age of eligible individuals

minAge=double

Units: Years Min: 0 Max: 100

Default value: 0

Minimum age of eligible individuals (defaults to 0)

Coverage

coverage=double

Units: Proportion Min: 0 Max: 1

Coverage of intervention

Cohort only

cohort=boolean

Units: Proportion Min: 0 Max: 1

Default value: false

Restrict distribution to chosen cohort.

Cumulative deployment: maximum age

cumulativeWithMaxAge=double

Units: Years Min: 0

If present, activate cumulate deployment mode where intervention is only deployed to individuals not already considered protected in sufficient quantity to bring the total proportion of people covered up to level described by "coverage". Individuals are considered already protected by this intervention when the age of the last net/dose/etc. received is less than "maximum age" (this attribute) years old (i.e. when timeLastDeployment+maximumAge>currentTimeStep).

Cohort recruitment

→ scenario → interventions → cohort

<cohort
  [ name=string ]
  >
IN THIS ORDER:
| ( <continuous ... /> )*
| ( <timed ... /> )*
</cohort>

Documentation (element)

Recruitment of cohort as a pseudo-intervention.

Attributes

Name of intervention

name=string

Units: string

Name of intervention

Age-based cohort recruitment

→ scenario → interventions → cohort → continuous

<continuous
    targetAgeYrs=double
    coverage=double
  [ cohort=boolean ] DEFAULT VALUE false
  [ begin=int ] DEFAULT VALUE 0
  [ end=int ] DEFAULT VALUE 2147483647
  />

Documentation (element)

List of ages at which cohort recruitment takes place.

Attributes

Target age

targetAgeYrs=double

Units: Years Min: 0 Max: 100

Target age of intervention

Proportion covered

coverage=double

Units: Proportion Min: 0 Max: 1

Coverage of intervention

Cohort only

cohort=boolean

Units: Proportion Min: 0 Max: 1

Default value: false

Restrict distribution to chosen cohort (default: false).

First timestep active

begin=int

Units: Timesteps Min: 0 Max: 2147483647

Default value: 0

First timestep (from 0 at the beginning of the intervention period) this item is active. Defaults to 0.

End timestep

end=int

Units: Timesteps Min: 0 Max: 2147483647

Default value: 2147483647

End of the period during which the intervention is active (to be exact, the first timestep of the intervention period at which the item becomes inactive). Defaults to 2147483647.

Mass cohort selection

→ scenario → interventions → cohort → timed

<timed
    time=int
  [ maxAge=double ] DEFAULT VALUE 100
  [ minAge=double ] DEFAULT VALUE 0
    coverage=double
  [ cohort=boolean ] DEFAULT VALUE false
  [ cumulativeWithMaxAge=double ]
  />

Documentation (element)

List of times of mass cohort selection.

Attributes

Time

time=int

Units: time-steps Min: 0

Time-step at which this intervention occurs, starting from 0, the first intervention-period time-step.

Maximum age of eligible individuals

maxAge=double

Units: Years Min: 0 Max: 100

Default value: 100

Maximum age of eligible individuals (defaults to 100)

Minimum age of eligible individuals

minAge=double

Units: Years Min: 0 Max: 100

Default value: 0

Minimum age of eligible individuals (defaults to 0)

Coverage

coverage=double

Units: Proportion Min: 0 Max: 1

Coverage of intervention

Cohort only

cohort=boolean

Units: Proportion Min: 0 Max: 1

Default value: false

Restrict distribution to chosen cohort.

Cumulative deployment: maximum age

cumulativeWithMaxAge=double

Units: Years Min: 0

If present, activate cumulate deployment mode where intervention is only deployed to individuals not already considered protected in sufficient quantity to bring the total proportion of people covered up to level described by "coverage". Individuals are considered already protected by this intervention when the age of the last net/dose/etc. received is less than "maximum age" (this attribute) years old (i.e. when timeLastDeployment+maximumAge>currentTimeStep).

Imported infections

→ scenario → interventions → importedInfections

<importedInfections
  [ name=string ]
  >
IN THIS ORDER:
|   <timed ... /> 
</importedInfections>

Documentation (element)

Models importation of P. falciparum infections directly into humans from an external source. This is infections, not inoculations or EIR being imported.

Attributes

Name of intervention

name=string

Units: string

Name of intervention

Rate of importation

→ scenario → interventions → importedInfections → timed

<timed
  [ period=int ] DEFAULT VALUE 0
  >
IN THIS ORDER:
| ( <rate ... /> )+
</timed>

Documentation (element)

Rate of case importation, as a step function. Each value is valid until replaced by the next value.

Attributes

Period of repetition

period=int

Units: time-steps Min: 0

Default value: 0

If period is 0 (or effectively infinite), the last specified value remains indefinitely in effect, otherwise the times of all values specified must be less than the period, and values are repeated modulo period (timestep period+2 has same value as timestep 2, etc.).

rate

→ scenario → interventions → importedInfections → timed → rate

<rate
    value=double
    time=int
  />

Documentation (type)

Units: Imported cases per thousand people per year

A time-rate pair.

Attributes

Input parameter value

value=double

A double-precision floating-point value.

Time

time=int

Units: time-steps Min: 0

Immune suppression

→ scenario → interventions → immuneSuppression

<immuneSuppression>
IN THIS ORDER:
| ( <timed ... /> )*
</immuneSuppression>

Documentation (element)

Removes all exposure-related immunity gained over time by hosts without removing infections.

Hypothetical, but potentially useful to simulate scenarios with unprotected humans.

timed

→ scenario → interventions → immuneSuppression → timed

<timed
    time=int
  [ maxAge=double ] DEFAULT VALUE 100
  [ minAge=double ] DEFAULT VALUE 0
    coverage=double
  [ cohort=boolean ] DEFAULT VALUE false
  />

Attributes

Time

time=int

Units: time-steps Min: 0

Time-step at which this intervention occurs, starting from 0, the first intervention-period time-step.

Maximum age of eligible individuals

maxAge=double

Units: Years Min: 0 Max: 100

Default value: 100

Maximum age of eligible individuals (defaults to 100)

Minimum age of eligible individuals

minAge=double

Units: Years Min: 0 Max: 100

Default value: 0

Minimum age of eligible individuals (defaults to 0)

Coverage

coverage=double

Units: Proportion Min: 0 Max: 1

Coverage of intervention

Cohort only

cohort=boolean

Units: Proportion Min: 0 Max: 1

Default value: false

Restrict distribution to chosen cohort.

Insert R_0 case

→ scenario → interventions → insertR_0Case

<insertR_0Case>
IN THIS ORDER:
| ( <timed ... /> )*
</insertR_0Case>

Documentation (element)

Used to simulate R_0. First, infections should be eliminated, immunity removed, and the population given an effective transmission- blocking vaccine (not done by this intervention). Then this intervention may be used to: pick one human, infect him, administer a fully effective Preerythrocytic vaccine and remove transmission-blocking vaccine effect on this human. Thus only this one human will be a source of infections in an unprotected population, and will not reinfected himself.

timed

→ scenario → interventions → insertR_0Case → timed

<timed
    time=int
  />

Attributes

Time

time=int

Units: time-steps Min: 0

Time-step at which this intervention occurs, starting from 0, the first intervention-period time-step.

Uninfect vectors

→ scenario → interventions → uninfectVectors

<uninfectVectors>
IN THIS ORDER:
| ( <timed ... /> )*
</uninfectVectors>

Documentation (element)

Units: List of elements

Removes all infections from mosquitoes -- resulting in zero EIR to humans, until such time that mosquitoes are re-infected and become infectious. Only effectious in dynamic EIR mode (when changeEIR was not used).

Hypothetical, but potentially useful to simulate a setting starting from no infections, but with enough mosquitoes to reach a set equilibrium of exposure.

timed

→ scenario → interventions → uninfectVectors → timed

<timed
    time=int
  />

Attributes

Time

time=int

Units: time-steps Min: 0

Time-step at which this intervention occurs, starting from 0, the first intervention-period time-step.

Simple larviciding intervention

→ scenario → interventions → larviciding

<larviciding
  [ name=string ]
  >
IN THIS ORDER:
| ( <anopheles ... /> )+
</larviciding>

Documentation (element)

Units: List of elements

Simple larviciding intervention description.

Attributes

Name of intervention

name=string

Units: string

Name of intervention

anopheles

→ scenario → interventions → larviciding → anopheles

<anopheles
    mosquito=string
    effectiveness=double
    duration=int
  />

Attributes

Mosquito to be larvicided

mosquito=string

Mosquito to be larvicided

Proportionate reduction in emergence

effectiveness=double

Units: none Min: 0 Max: 1

Proportional reduction in emergence rate

Duration of activity

duration=int

Units: days Min: 0 Max: inf

Number of days for which the intervention is active.

Health system description

→ scenario → healthSystem

<healthSystem>
IN THIS ORDER:
| EXACTLY ONE OF:
| |   <EventScheduler ... /> 
| |   <ImmediateOutcomes ... /> 
|   <CFR ... /> 
|   <pSequelaeInpatient ... /> 
</healthSystem>

Documentation (element)

Units: List of elements

Description of health system.

Documentation (type)

Units: List of elements

Description of case management system, used to specify the initial model or a replacement (an intervention). Encompasses case management data and some other data required to derive case outcomes.

Contains a sub-element describing the particular health-system in use. Health system data is here defined as data used to decide on a treatment strategy, given a case requiring treatment.

Transmission and vector bionomics

→ scenario → entomology

<entomology
    name=string
    mode=("2" or "4")
  [ annualEIR=double ]
  >
IN THIS ORDER:
| EXACTLY ONE OF:
| |   <nonVector ... /> 
| |   <vector ... /> 
</entomology>

Documentation (element)

Units: List of elements

Description of entomological data

Attributes

Entomology dataset

name=string

Units: string

Name of entomology data

Transmission simulation mode

mode=("2" or "4")

Units: Code

Transmission simulation mode -- enter dynamic mode (4) or forced mode (2) at start of intervention period. Mode 3 (transient EIR from data provided as intervention) is set when intervention data is applied, and is no longer a valid value to specify here.

Override annual EIR

annualEIR=double

Units: Infectious bites per adult per year

If set, overrides the annual EIR by scaling it to this level. If ommitted, EIR levels are as specified elsewhere.

Transmission setting (vector control not enabled)

→ scenario → entomology → nonVector

<nonVector
    eipDuration=int
  >
IN THIS ORDER:
| ( <EIRDaily ... /> )+
</nonVector>

Documentation (element)

Units: List of elements

Description of transmission setting for models without vector control interventions (included for backward compatibility)

Attributes

Duration of sporogony (days)

eipDuration=int

The duration of sporogony in days

Transmission setting (vector control enabled)

→ scenario → entomology → vector

<vector>
IN THIS ORDER:
| ( <anopheles ... /> )+
| ( <nonHumanHosts ... /> )*
</vector>

Documentation (element)

Units: List of elements

Parameters of the transmission model.

anopheles

→ scenario → entomology → vector → anopheles

<anopheles
    mosquito=string
    propInfected=double
    propInfectious=double
  >
IN THIS ORDER:
| EXACTLY ONE OF:
| |   <EIR ... /> 
| |   <monthlyEIR ... /> 
|   <mosq ... /> 
| ( <nonHumanHosts ... /> )*
</anopheles>

Documentation (type)

Description of input EIR for one specific vector species in terms of a Fourier approximation to the ln of the EIR during the burn in period

Attributes

Identifier for this anopheles species

mosquito=string

Identifier for this anopheles species

Initial guess of proportion of mosquitoes infected (ρ_O)

propInfected=double

Units: Proportion Min: 0 Max: 1

Initial guess of the proportion of mosquitoes which are infected, o: O_v(t) = o*N_v(t). Only used as a starting value.

Initial guess of proportion of mosquitoes infectious (ρ_S)

propInfectious=double

Units: Proportion Min: 0 Max: 1

Initial guess of the proportion of mosquitoes which are infectious, s: S_v(t) = s*N_v(t). Used as a starting value and then fit.

Fourier approximation to pre-intervention EIR

→ scenario → entomology → vector → anopheles → EIR

<EIR
    a0=double
    a1=double
    b1=double
    a2=double
    b2=double
    EIRRotateAngle=double
  />

Documentation (element)

Units: Infectious bites per adult per day

Description of target entomological inoculation rate as a Fourier series. This is used to estimate a suitible vector emergence rate. The annual (target) EIR is thus the exponent of the fourier series with these parameters, with period scaled to 365 days.

Attributes

a0 parameter of Fourier approximation to ln(EIR)

a0=double

a0 parameter of Fourier approximation to ln(EIR)

a1 parameter of Fourier approximation to ln(EIR)

a1=double

a1 parameter of Fourier approximation to ln(EIR)

b1 parameter of Fourier approximation to ln(EIR)

b1=double

b1 parameter of Fourier approximation to ln(EIR)

a2 parameter of Fourier approximation to ln(EIR)

a2=double

a2 parameter of Fourier approximation to ln(EIR)

b2 parameter of Fourier approximation to ln(EIR)

b2=double

b2 parameter of Fourier approximation to ln(EIR)

Rotation angle defining the origin of the Fourier approximation to ln (EIR)

EIRRotateAngle=double

Units: radians

Rotation angle defining the origin of the Fourier approximation to ln (EIR)

Monthly values for pre-intervention EIR

→ scenario → entomology → vector → anopheles → monthlyEIR

<monthlyEIR
    annualEIR=double
  >
IN THIS ORDER:
| ( <item ... /> ){12,12}
</monthlyEIR>

Documentation (element)

Units: Infectious bites per adult per month

Description of target entomological inoculation rate as monthly values plus an annual override (monthly values are scaled to fit the annual EIR described). This is used to estimate a suitible vector emergence rate. The annual (target) EIR is derived from a Fourier series fit to these monthly values (used as a smoothing factor). List should contain twelve entries: January to December.

Attributes

Annual EIR

annualEIR=double

Units: Infectious bites per adult per year Min: 0

Scales the monthly values to give this annual innoculation rate.

Monthly pre-intervention EIR

→ scenario → entomology → vector → anopheles → monthlyEIR → item

<item>
    double
</item>

Documentation (element)

Units: Inoculations per person per month

Inoculations per person per month

Vector Species

→ scenario → entomology → vector → anopheles → mosq

<mosq
    mosqRestDuration=int
    extrinsicIncubationPeriod=int
    mosqLaidEggsSameDayProportion=double
    mosqSeekingDuration=double
    mosqSurvivalFeedingCycleProbability=double
    mosqProbBiting=double
    mosqProbFindRestSite=double
    mosqProbResting=double
    mosqProbOvipositing=double
    mosqHumanBloodIndex=double
    minInfectedThreshold=double
  />

Documentation (element)

Units: List of elements

Vector species

Attributes

Duration of the resting period of the vector (days)

mosqRestDuration=int

name:Duration of the resting period of the vector (days);

Extrinsic incubation period (days)

extrinsicIncubationPeriod=int

name:Extrinsic incubation period (days)

Proportion of mosquitoes host seeking on same day as ovipositing

mosqLaidEggsSameDayProportion=double

Proportion of mosquitoes host seeking on same day as ovipositing

Duration of the host-seeking period of the vector (days)

mosqSeekingDuration=double

Duration of the host-seeking period of the vector (days)

Probability that the mosquito survives the feeding cycle

mosqSurvivalFeedingCycleProbability=double

Probability that the mosquito survives the feeding cycle

Probability that the mosquito succesfully bites chosen host

mosqProbBiting=double

Probability that the mosquito succesfully bites chosen host

Probability that the mosquito escapes host and finds a resting place after biting

mosqProbFindRestSite=double

Probability that the mosquito escapes host and finds a resting place after biting

Probability of mosquito successfully resting after finding a resting site

mosqProbResting=double

Probability of mosquito successfully resting after finding a resting site

Probability of a mosquito successfully laying eggs given that it has rested

mosqProbOvipositing=double

Probability of a mosquito successfully laying eggs given that it has rested

Human blood index

mosqHumanBloodIndex=double

The proportion of resting mosquitoes which fed on human blood during the last feed.

Min infected threshold

minInfectedThreshold=double

Min: 0

If less than this many mosquitoes remain infected, transmission is interrupted.

nonHumanHosts

→ scenario → entomology → vector → anopheles → nonHumanHosts

<nonHumanHosts
    name=string
    mosqRelativeEntoAvailability=double
    mosqProbBiting=double
    mosqProbFindRestSite=double
    mosqProbResting=double
  />

Documentation (element)

Units: List of elements

Non human host parameters, per type of host (must match up with non-species-specific parameters).

Attributes

Identifier for this category of non-human hosts

name=string

Identifier for this category of non-human hosts

Relative availability of nonhuman hosts of type i (to other nonhuman hosts)

mosqRelativeEntoAvailability=double

Relative availability of nonhuman hosts of type i (to other nonhuman hosts)

Probability of mosquito successfully biting host

mosqProbBiting=double

Probability of mosquito successfully biting host

Probability that the mosquito escapes host and finds a resting place after biting

mosqProbFindRestSite=double

Probability that the mosquito escapes host and finds a resting place after biting

Probability of mosquito successfully resting after finding a resting site

mosqProbResting=double

Probability of mosquito successfully resting after finding a resting site

nonHumanHosts

→ scenario → entomology → vector → nonHumanHosts

<nonHumanHosts
    name=string
    number=double
  />

Attributes

Species of alternative host

name=string

Units: List of elements

Name of this species of non human hosts (must match up with those described per anopheles section)

number

number=double

Pharmacokinetics and pharmacodynamics

→ scenario → pharmacology

<pharmacology>
IN THIS ORDER:
| ( <drug ... /> )+
</pharmacology>

Documentation (element)

Units: List of elements

Drug model parameters

Library of drug parameters

→ scenario → pharmacology → drug

<drug
    abbrev=string
  >
IN THIS ORDER:
|   <PD ... /> 
|   <PK ... /> 
</drug>

Documentation (element)

Sequence of drug descriptions forming a library of drug parameters.

Attributes

abbrev

abbrev=string

PD

→ scenario → pharmacology → drug → PD

<PD>
IN THIS ORDER:
| ( <allele ... /> )+
</PD>

PD parameters per allele

→ scenario → pharmacology → drug → PD → allele

<allele
    name=string
  >
IN THIS ORDER:
|   <initial_frequency ... /> 
|   <max_killing_rate ... /> 
|   <IC50 ... /> 
|   <slope ... /> 
</allele>

Documentation (element)

PD parameters per allele, plus initial frequency of each allele.

Note: we assume a one-to-one correspondance of drugs to loci, hence each drug has an independent set of alleles here.

Attributes

name

name=string

Relative frequency

→ scenario → pharmacology → drug → PD → allele → initial_frequency

<initial_frequency>
    double
</initial_frequency>

Documentation (element)

Units: relative frequency Min: 0

Frequency, relative to the total frequency of all alleles for this drug/locus.

Maximal parasite killing rate

→ scenario → pharmacology → drug → PD → allele → max_killing_rate

<max_killing_rate>
    double
</max_killing_rate>

Documentation (element)

Units: 1/days Min: 0

k1 — Maximal parasite killing rate.

IC50

→ scenario → pharmacology → drug → PD → allele → IC50

<IC50>
    double
</IC50>

Documentation (element)

Units: mg/l Min: 0

Half maximal effect concentration.

Slope of effect curve

→ scenario → pharmacology → drug → PD → allele → slope

<slope>
    double
</slope>

Documentation (element)

Units: no units

n — Slope of the concentration effect curve

PK

→ scenario → pharmacology → drug → PK

<PK>
IN THIS ORDER:
|   <negligible_concentration ... /> 
|   <half_life ... /> 
|   <vol_dist ... /> 
</PK>

Drug concentration considered negligible

→ scenario → pharmacology → drug → PK → negligible_concentration

<negligible_concentration>
    double
</negligible_concentration>

Documentation (element)

Units: mg/l Min: 0

Concentration below which drug's effects are deemed negligible and can be removed from simulation.

drug half-life

→ scenario → pharmacology → drug → PK → half_life

<half_life>
    double
</half_life>

Documentation (element)

Units: days Min: 0

Used to calculate elimination rate (which is: ln(2) / half_life).

Volume of Distribution

→ scenario → pharmacology → drug → PK → vol_dist

<vol_dist>
    double
</vol_dist>

Documentation (element)

Units: l/kg Min: 0

Volume of Distribution

Model options and parameters

→ scenario → model

<model>
IN ANY ORDER:
|   <ModelOptions ... /> 
|   <clinical ... /> 
|   <human ... /> 
|   <parameters ... /> 
</model>

Documentation (element)

Units: List of elements

Encapsulation of all parameters which describe the model according to which fitting is done.

Model Options

→ scenario → model → ModelOptions

<ModelOptions>
IN THIS ORDER:
| ( <option ... /> )*
</ModelOptions>

Documentation (element)

Units: List of elements

All model options (bug fixes, choices between models, etc.).
The list of recognised options can be found in the code at: include/util/ModelOptions.h and should also be in the wiki.

clinical

→ scenario → model → clinical

<clinical
    healthSystemMemory=int
  >
IN THIS ORDER:
| [ <NonMalariaFevers ... /> ]
</clinical>

Documentation (type)

Units: List of elements

Description of clinical parameters.

This is related to the health-system description, but contains data which can't be changed as part of an intervention and is not restricted to treatment.

Attributes

Follow-up period during which recurrence is treated as a failure

healthSystemMemory=int

Units: Time steps Min: 1 Max: 100

Follow-up period during which a recurrence is considered to be a treatment failure

NonMalariaFevers

→ scenario → model → clinical → NonMalariaFevers

<NonMalariaFevers>
IN THIS ORDER:
|   <incidence ... /> 
|   <prNeedTreatmentNMF ... /> 
|   <prNeedTreatmentMF ... /> 
</NonMalariaFevers>

Documentation (type)

Description of non-malaria fever incidence. Non-malaria fevers are only modelled if the NON_MALARIA_FEVERS option is used.

P(NMF)

→ scenario → model → clinical → NonMalariaFevers → incidence

<incidence
  [ interpolation=("none" or "linear") ] DEFAULT VALUE linear
  >
IN THIS ORDER:
| ( <group ... /> )+
</incidence>

Documentation (element)

Units: none Min: 0 Max: 1

Probability that a non-malaria fever occurs given that no concurrent malaria fever occurs.

Attributes

interpolation

interpolation=("none" or "linear")

Units: none

Default value: linear

Interpolation algorithm. Normally it is desirable for age-based values to be continuous w.r.t. age. By default linear interpolation is used. With all algorithms except "none", the age groups are converted to a set of points centred within each age range. Extra points are added at each end (zero and infinity) to keep value constant at both ends of the function. A zero-length age group may be used as a kind of barrier to adjust the distribution; e.g. with age group boundaries at 15, 20 and 25 years, a (linear) spline would be drawn between ages 17.5 and 22.5, whereas with boundaries at 15, 20 and 20 years, a spline would be drawn between ages 17.5 and 20 years (may be desired if individuals are assumed to reach adult size at 20). Algorithms:

  1. none: input values are used directly
  2. linear: straight lines (on an age vs. value graph) are used to interpolate data points.

P(need treatment | NMF)

→ scenario → model → clinical → NonMalariaFevers → prNeedTreatmentNMF

<prNeedTreatmentNMF
  [ interpolation=("none" or "linear") ] DEFAULT VALUE linear
  >
IN THIS ORDER:
| ( <group ... /> )+
</prNeedTreatmentNMF>

Documentation (element)

Units: none Min: 0 Max: 1

Probability that a non-malaria fever needs treatment with antibiotics (assuming fever is not induced by malaria, although concurrent parasites may be present).

Attributes

interpolation

interpolation=("none" or "linear")

Units: none

Default value: linear

Interpolation algorithm. Normally it is desirable for age-based values to be continuous w.r.t. age. By default linear interpolation is used. With all algorithms except "none", the age groups are converted to a set of points centred within each age range. Extra points are added at each end (zero and infinity) to keep value constant at both ends of the function. A zero-length age group may be used as a kind of barrier to adjust the distribution; e.g. with age group boundaries at 15, 20 and 25 years, a (linear) spline would be drawn between ages 17.5 and 22.5, whereas with boundaries at 15, 20 and 20 years, a spline would be drawn between ages 17.5 and 20 years (may be desired if individuals are assumed to reach adult size at 20). Algorithms:

  1. none: input values are used directly
  2. linear: straight lines (on an age vs. value graph) are used to interpolate data points.

P(need treatment | MF)

→ scenario → model → clinical → NonMalariaFevers → prNeedTreatmentMF

<prNeedTreatmentMF
  [ interpolation=("none" or "linear") ] DEFAULT VALUE linear
  >
IN THIS ORDER:
| ( <group ... /> )+
</prNeedTreatmentMF>

Documentation (element)

Units: none Min: 0 Max: 1

Probability that a malaria fever needs treatment with antibiotics (assuming fever is induced by malaria, although concurrent bacteria may be present).

Meaning partially overlaps with separate model for comorbidity given malaria.

Attributes

interpolation

interpolation=("none" or "linear")

Units: none

Default value: linear

Interpolation algorithm. Normally it is desirable for age-based values to be continuous w.r.t. age. By default linear interpolation is used. With all algorithms except "none", the age groups are converted to a set of points centred within each age range. Extra points are added at each end (zero and infinity) to keep value constant at both ends of the function. A zero-length age group may be used as a kind of barrier to adjust the distribution; e.g. with age group boundaries at 15, 20 and 25 years, a (linear) spline would be drawn between ages 17.5 and 22.5, whereas with boundaries at 15, 20 and 20 years, a spline would be drawn between ages 17.5 and 20 years (may be desired if individuals are assumed to reach adult size at 20). Algorithms:

  1. none: input values are used directly
  2. linear: straight lines (on an age vs. value graph) are used to interpolate data points.

human

→ scenario → model → human

<human>
IN THIS ORDER:
|   <availabilityToMosquitoes ... /> 
| [ <weight ... /> ]
</human>

Documentation (type)

Parameters of host models.

Availability to mosquitoes

→ scenario → model → human → availabilityToMosquitoes

<availabilityToMosquitoes
  [ interpolation=("none" or "linear") ] DEFAULT VALUE linear
  >
IN THIS ORDER:
| ( <group ... /> )+
</availabilityToMosquitoes>

Documentation (element)

Units: None Min: 0 Max: 1

By age group data on availability of humans to mosquitoes relative to an adult.

Attributes

interpolation

interpolation=("none" or "linear")

Units: none

Default value: linear

Interpolation algorithm. Normally it is desirable for age-based values to be continuous w.r.t. age. By default linear interpolation is used. With all algorithms except "none", the age groups are converted to a set of points centred within each age range. Extra points are added at each end (zero and infinity) to keep value constant at both ends of the function. A zero-length age group may be used as a kind of barrier to adjust the distribution; e.g. with age group boundaries at 15, 20 and 25 years, a (linear) spline would be drawn between ages 17.5 and 22.5, whereas with boundaries at 15, 20 and 20 years, a spline would be drawn between ages 17.5 and 20 years (may be desired if individuals are assumed to reach adult size at 20). Algorithms:

  1. none: input values are used directly
  2. linear: straight lines (on an age vs. value graph) are used to interpolate data points.

Weight

→ scenario → model → human → weight

<weight
  [ interpolation=("none" or "linear") ] DEFAULT VALUE linear
    multStdDev=double
  >
IN THIS ORDER:
| ( <group ... /> )+
</weight>

Documentation (element)

Units: kg Min: 0

By age group data on human weight (mass).

Attributes

interpolation

interpolation=("none" or "linear")

Units: none

Default value: linear

Interpolation algorithm. Normally it is desirable for age-based values to be continuous w.r.t. age. By default linear interpolation is used. With all algorithms except "none", the age groups are converted to a set of points centred within each age range. Extra points are added at each end (zero and infinity) to keep value constant at both ends of the function. A zero-length age group may be used as a kind of barrier to adjust the distribution; e.g. with age group boundaries at 15, 20 and 25 years, a (linear) spline would be drawn between ages 17.5 and 22.5, whereas with boundaries at 15, 20 and 20 years, a spline would be drawn between ages 17.5 and 20 years (may be desired if individuals are assumed to reach adult size at 20). Algorithms:

  1. none: input values are used directly
  2. linear: straight lines (on an age vs. value graph) are used to interpolate data points.

Standard deviation

multStdDev=double

Units: None Min: 0

Each human is assigned a weight multiplier from a normal distribution with mean 1 and this standard deviation at birth. His/her weight is this multiplier times the mean from age distribution. A standard deviation of zero for no heterogeneity is valid; a rough value from Tanzanian data is 0.14.

Parameters of the model of epidemiology

→ scenario → model → parameters

<parameters
    interval=int
    iseed=int
    latentp=int
  >
IN THIS ORDER:
| ( <parameter ... /> )+
</parameters>

Documentation (element)

Units: List of elements

Parameters of the epidemiological model

Attributes

Simulation step

interval=int

Units: Days

Simulation step

Random number seed

iseed=int

Units: Number

Seed for RNG

Pre-erythrocytic latent period

latentp=int

Units: Time steps Min: 0 Max: 20

pre-erythrocytic latent period, in time steps

parameter

→ scenario → model → parameters → parameter

<parameter
    name=string
    number=int
    value=double
  [ include=boolean ]
  />

Attributes

Name of parameter

name=string

Units: string

Name of parameter

Parameter number

number=int

Units: Number Min: 1 Max: 100

Reference number of input parameter

Parameter value

value=double

Units: Number Min: 0

Parameter value

Sampling indicator

include=boolean

Units: Number Min: 0 Max: 1

True if parameter is to be sampled in optimization runs. Not used in simulator app.