diff --git a/schema/scenario_47.xsd b/schema/scenario_47.xsd
index 3c1feda9..a45b0f10 100644
--- a/schema/scenario_47.xsd
+++ b/schema/scenario_47.xsd
@@ -2223,2253 +2223,1913 @@
-
-
-
-
-
+
+
+
+ A library of drug related data for the PK/PD model.
+
+ name:Pharmacology library;
+
+
+
- Changes to the health system
+ A library of drug deployment schedules and dosages.
- name:Change health system;
+ name:Treatments library;
-
-
-
-
-
-
- A complete replacement health system. Replaces all previous properties.
- (Health system can be replaced multiple times if necessary.)
-
- name:Timed replacement;
-
-
-
-
- Time at which this replacement occurs. See doc on
- intervention period and on monitoring/startDate for
- details of how times work.
-
- Can be specified in steps, days, years, or as a date
- (examples: 15t, 75d, 0.2y, 2000-03-16).
-
- name:Time;units:User defined (defauls to steps);min:0;
-
-
-
-
-
-
+
+
-
-
-
- Name of intervention
-
- name:Name of intervention;
-
-
-
+
- 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.
+ A library of drug PK/PD data.
- name:Change transmission levels;
+ name:Drug library;
-
-
-
-
-
-
- Replacement transmission levels. Disables feedback of
- human infectiousness to mosquitoes on further mosquito
- to human transmission. Must last until end of simulation.
-
- name:Timed replacement;
-
-
-
-
- Time at which this replacement occurs. See doc on
- intervention period and on monitoring/startDate for
- details of how times work.
-
- Can be specified in steps, days, years, or as a date
- (examples: 15t, 75d, 0.2y, 2000-03-16).
-
- name:Time;units:User defined (defauls to steps);min:0;
-
-
-
-
-
-
+
-
-
-
- Name of intervention
-
- name:Name of intervention;
-
-
-
-
-
- Models importation of P. falciparum infections directly into humans
- from an external source. This is infections, not inoculations or
- EIR being imported.
-
- name:Imported infections;
-
-
-
-
+
+
+
+
+
+
+
+ A schedule for the administration of drugs in a course of treatment.
+
+ Note that dose sizes are multiplied by some multiplier (see dosages)
+ and the times of all doses may be delayed.
+
+ name:Schedule of doses taken as a course of treatment;
+
+
+
+
+
+
+
+ Name for referring to this deployment schedule
+
+ name:Name;
+
+
+
+
+
+
+
+ Abbreviated name of drug compound
+
+ name:drug;
+
+
+
+
+
+ Quantity of drug compound in mg per *something*. A separate dosage
+ table must be used when medicating, which may specify multipliers of
+ this number based on patient age or weight.
+
+ units:mg per something;name:Drug dose (mg with multiplier);
+
+
+
+
+
+ Number of hours past start of timestep this drug dose is administered
+ at (first dose should be at hour 0).
+
+ units:Hours;min:0;name:Time of administration;
+
+
+
+
+
+
+ A table for selecting a dose size. There are several ways this can
+ work: using the patient's age or body mass in a look-up table to get a
+ multplier, or directly using body mass as the multiplier.
+
+ The doses specified in "mg" in the treatment schedule are then
+ multiplied by this multiplier.
+
+ name:Dosage table;
+
+
+
+
+
+
+ Select dose multiplier from a look-up table using the patient's age.
+
+ name:Look-up table (age);
+
+
+
+
+
+ Select dose multiplier from a look-up table using the patient's body mass.
+
+ name:Look-up table (weight);
+
+
+
+
+
+ Multiply the dose by some quantity, such as patient weight.
+
+ name:Multiply dose;
+
+
+
- Rate of case importation, as a step function. Each value is
- valid until replaced by the next value.
+ Quantity to multiply the dose by. Only option is "kg"
+ (patient weight in kg).
- name:Rate of importation
+ name:By what?;
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Name for referring to this dosage table
+
+ name:Name;
+
+
+
+
+
+
+ A look-up table which uses patient age (in years) or weight (in kg) to
+ find a multiplier.
+
+ name:Age/weight range;
+
+
+
+ name:Lower bound (inclusive);min:0;units:years or kg;
+
+
+
+
+
+ The dose size given in the schedule (in "mg") is multiplied by
+ this value for patients falling into this range when this
+ dosage table is used.
+
+ name:Dose multiplier;min:0;
+
+
+
+
+
+
+
+ A drug description with PK/PD parameters.
+
+ name:Drug parameters;
+
+
+
+
+
+
+
+
+ Pharmaco-Dynamic parameters for some resistance phenotype.
+
+ To model resistance to this drug, describe multiple infection
+ phenotypes (with respect to these PD parameters) and list one
+ or more "restrict" elements for each phenotype.
+
+ Loci are specified elsewhere. Multiple loci may influence the
+ action of a single drug and each locus may influence multiple
+ drugs.
+
+ name:PD parameters for some allele / resistance phenotype;
-
-
-
-
-
-
-
- A time-rate pair.
- name:Rate;units:Imported cases per thousand people per year;
-
-
-
-
- Time at which this importation rate becomes active.
-
- See doc on intervention period and on monitoring/startDate for
- details of how times work. Can be specified in steps, days,
- years, or as a date (examples: 15t, 75d, 0.2y, 2000-03-16).
-
- name:Time of start;units:User defined (defauls to steps);min:0;
-
-
-
-
-
-
-
-
-
-
- If period is 0 (or effectively infinite), the last specified
- value remains indefinitely in effect.
-
- If period is less than the length of the simulation's intervention phase,
- then all "rate" deployments are repeated with this periodicity.
- In this case, the first "rate" deployment must coincide with the start of
- the intervention phase (monitoring/startDate).
-
- Can be specified in steps (e.g. 1t) or days (e.g. 365d).
-
- name:Period of repetition;units:User defined (default: steps);min:0
-
-
-
-
+
- Name of intervention
+ Optional; if present specifies the locus corresponding to this
+ drug's PD phenotypes: each phenotype must then match one of
+ that locus's alleles. Otherwise the drug should specify only
+ one phenotype.
+
+ There is currently a one-to-many correspondance between loci
+ and drugs.
- name:Name of intervention;
+ name:Locus;
-
-
-
- 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.
-
- name:Insert R_0 case;
-
+
-
-
+
+
+
+ Concentration below which drug's effects are deemed negligible and can
+ be removed from simulation.
+
+ units:mg/l;min:0;name:Drug concentration considered negligible;
+
+
+
+
- name:Timed occurrence;
+
+ Used to calculate elimination rate λ, calculated as
+ λ = ln(2) / half_life. The basic form of decay is
+ C(t) = C0 * exp(-λ*t).
+
+ Alternatively, elimination rate can be specified via k
+ and m_exponent.
+
+ units:days;min:0;name:drug half-life;
-
+
+
+
- Time at which this intervention occurs.
+ Constant used to calculate the elimination rate λ, which
+ is calculated as λ = k / (body_mass ^ m_exponent), where
+ body_mass is the patient's weight in kg and m_exponent is
+ the next parameter. The basic form of decay is
+ C(t) = C0 * exp(-λ*t).
- See doc on intervention period and on monitoring/startDate for
- details of how times work. Can be specified in steps, days,
- years, or as a date (examples: 15t, 75d, 0.2y, 2000-03-16).
-
- name:Time;units:User defined (defauls to steps);min:0;
+ If CV > 0, k is sampled per-human from the log-normal
+ distribution: ln N( ln(mean) - σ^2 / 2, σ^2).
+
+ Alternatively, elimination rate can be specified via half_life.
+
+ units:day^-1;min:0;name:Constant associated with elimination rate (k);
-
-
-
-
-
-
-
- Name of intervention
-
- name:Name of intervention;
-
-
-
-
-
-
-
- Removes all infections from mosquitoes -- resulting in zero EIR to
- humans, until such time that mosquitoes are re-infected and become
- infectious. Only efficacious 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.
-
- units:List of elements;name:Uninfect vectors;
-
-
-
-
-
-
- name:Timed occurrence;
-
-
+
+
- Time at which this intervention occurs.
+ Constant used to calculate the elimination rate λ, which
+ is calculated as λ = k / (body_mass ^ m_exponent), where
+ body_mass is the patient's weight in kg and k is the
+ previous parameter. The basic form of decay is
+ C(t) = C0 * exp(-λ*t).
- See doc on intervention period and on monitoring/startDate for
- details of how times work. Can be specified in steps, days,
- years, or as a date (examples: 15t, 75d, 0.2y, 2000-03-16).
+ Alternatively, elimination rate can be specified via half_life.
+
+ Note that in the case of a conversion model, this applies
+ to *both* the elimination and the conversion rates.
- name:Time;units:User defined (defauls to steps);min:0;
+ units:day^-1;min:0;name:Constant associated with elimination rate (m_exponent);
-
-
+
+
+
+
+
+
+ Absorption rate parameter. Not allowed for one compartment
+ models, but required for two and three compartment models and
+ one compartment with conversion model (for the parent drug
+ only).
+
+ name:Absorption rate constant (k_a);min:0;
+
+
+
+
+
+ Configures the parent drug in a conversion model.
+
+ To use a conversion model, the parent drug should have this
+ section defined as well as half-life or k (direct
+ elimination; this may be zero) and k_a (absorption rate;
+ this may be large).
+
+ The metabolite drug should define half-life or k (elimination
+ of metabolite), but not k_a (absorption rate) or this section
+ (conversion). It is not possible for the metabolite to itself
+ undergo conversion with the current models.
+
+ name:Conversion parameters (parent drug);
+
+
+
+
+
+
+ The abbreviation of the metabolite drug (e.g. "DHA" or
+ "DHA_AR").
+
+ name:Metabolite drug (abbreviation);
+
+
+
+
+
+ Rate of conversion of parent drug to metabolite.
+
+ name:Rate of conversion;unit:Per day;
+
+
+
+
+
+ Ratio of molecular weights: molecular weight of the
+ metabolite divided by molecular weight of the parent.
+
+ name:Molecular weight ratio;unit:unitless;
+
+
+
+
+
+ The IC50 values of parent and metabolite drugs may be
+ sampled from the log-normal distribution (if CV is greater than 0).
+ This parameter controls correlation between these samples,
+ measured in log-space.
+
+ If this value is 1, samples are fully correlated: a single z-score is
+ used to calculate both samples. If this is 0, two independent
+ samples are used.
+
+ Values between 0 and 1 (partial correlation) are supported;
+ in this case IC50 values are sampled such that
+ cor(log(x), log(y)) matches this value (where x, y are parent and
+ metabolite IC50 values).
+
+ name:IC50 log correlation;min:0;max:1;
+
+
+
+
+
+
+
+
+ Volume of Distribution.
+
+ If CV > 0 this is sampled from a log-normal distribution.
+
+ units:l/kg;min:0;name:Volume of Distribution (Vd);
+
+
+
+
+
+ Optional element specifying conversion parameters to- and
+ from- a second compartment.
+
+ name:Second compartment parameters;
+
+
+
+
+
+
+ Absorption rate from the central compartment to the
+ first periphery compartment (2).
+
+ It is sampled per-patient when CV > 0.
+
+ units:day^-1;min:0;name:Absorption rate to compartment 2 (k12);
+
+
+
+
+
+ Absorption rate from the first periphery compartment
+ (2) to the central compartment.
+
+ It is sampled per-patient when CV > 0.
+
+ units:day^-1;min:0;name:Absorption rate from compartment 2 (k21);
+
+
+
+
+
+
+
+
+ Optional element specifying conversion parameters to- and
+ from- a third compartment.
+
+ name:Third compartment parameters;
+
+
+
+
+
+
+ Absorption rate from the central compartment to the
+ second periphery compartment (3).
+
+ It is sampled per-patient when CV > 0.
+
+ units:day^-1;min:0;name:Absorption rate to compartment 3 (k13);
+
+
+
+
+
+ Absorption rate from the second periphery compartment
+ (3) to the central compartment.
+
+ It is sampled per-patient when CV > 0.
+
+ units:day^-1;min:0;name:Absorption rate from compartment 3 (k31);
+
+
+
+
-
-
-
-
- Name of intervention
-
- name:Name of intervention;
-
-
-
-
-
-
- A list of parameterisations of generic vector host-inspecific interventions.
- name:Vector population intervention;units:List of elements;
-
-
-
-
-
-
-
-
-
-
-
- Traps attract and kill mosquitoes. They are modelled as a
- non-human-host where the probability of mosquitoes surviving
- feeding is zero (since otherwise the simulator would assume
- surviving mosquitoes have had a blood meal), and where this
- "host" is initially not present.
-
- Model: each type of trap has has an initial availability
- relative to a human and a decay in availability. Each
- deployment has a fixed maximum lifespan, after which the
- traps from that deployment are removed (it is up to the
- user whether this is after availability is effectively zero
- or sooner, either coinciding with a redeployment or
- causing a reduction in overall effectiveness of traps).
-
- name:Baited trap
-
-
-
-
-
+
+
+
+
+
+
- List of interventions that modify parameters of non-human hosts described in the <entomology> <vector> <anopheles>.
+
+ Specifies the mapping from genotype to phenotype. For each drug
+ type, if only one phenotype is present, restrictions need not be
+ specified, but otherwise restrictions must be specified.
+
+ The set of loci affecting phenotypes of this drug's action must be
+ fixed for any drug type. Each phenotype must list, for each of
+ these loci, a restriction to one or more alleles under the locus.
+
+ name:Restrict phenotype applicability to certain alleles;
-
-
-
+
+
+
+ A locus under which only a restricted set of alleles map to
+ this phenotype.
+
+ name:Locus relevant to the mapping of alleles to this phenotype;
+
+
+
+
+
+ One allele of a locus upon which phenotype choice depends.
+ If multiple alleles under this locus should map to the same
+ phenotype, repeat the whole "restriction onLocus..." element.
+
+ name:Alleles mapping to this phenotype;
+
+
-
+
- List of intervention that add new non-human hosts that have not been described in the <entomology> <vector>
-<anopheles> <nonHumanHosts>.
+
+ k1 — Maximal parasite killing rate.
+
+ units:1/days;min:0;name:Maximal parasite killing rate;
-
-
-
-
-
-
+
- Encapsulates all interventions whose effects are specific to the
- human host: any interventions where target humans may be selected
- via population-coverage, age limits and sub-population membership.
+ Half maximal effect concentration.
+
+ If CV > 0, the IC50 is sampled from a log-normal distribution.
- name:Human-specific interventions;
+ units:mg/l;min:0;name:IC50;
-
-
+
+
+
+ n — Slope of the concentration effect curve
+
+ units:dimensionless;name:Slope of effect curve;
+
+
+
+
- Name of set of interventions
- name:Name of intervention set;
+
+ Name of the phenotype; for documentation use only.
+
+ name:Name of phenotype;
-
-
-
-
-
- A parameterisation of an effect achieved by one component of an
- intervention. (An intervention is described as the effects of a set
- of components plus deployments of those components. This describes
- the components individually, not deployments or which components
- comprise an intervention.)
-
- Each element describes one component: its effects, decay of the(se)
- effect(s), and related stuff (e.g. description of indirect decay
- and of usage levels).
-
- Different interventions can deploy the same component to the same
- perso. In most cases this will just deploy a fresh instance (e.g. a
- new bed net will replace the old (nobody uses multiple bed nets),
- or a new drug dose will act on top of previous doses, or in the
- case of a vaccine, effect depends on the total number of previous
- inoculations (including from other interventions).
-
- Where multiple components of the same type (but with different ids)
- are deployed (whether within a single intervention or by multiple
- interventions), they act independently (e.g. two bed nets deployed
- to a single host would act to reduce attractiveness or survival of
- mosquitoes biting that host twice — this may be useful to simulate
- some novel vector intervention since the two nets may have separate
- parameters).
-
- name:Component;
-
-
-
-
-
- This element describes deployment of an intervention: which
- components are deployed, how humans are selected for deployment
- (via timed or age-based deployment) as well as a few additional
- restrictions (e.g. vaccine dosing restrictions).
-
- All components deployed by this intervention are deployed to the
- same people (each timed or continuous deployment selects recipients
- and then gives each recipient all components of the intervention).
-
- name:Deployment;
-
+
+
+
+
+
+ The list of components deployed to eligible humans.
+
+ name:Component to be deployed;
+
+
+
+
+ The identifier (short name) of a component.
+
+ name:Identifier;
+
+
+
+
+
+
+ Lists intervention components which are deployed according to some
+ external trigger (for example, screening with a negative patency
+ outcome or health-system treatment).
+
+ Components are referenced from one or more sub-lists. Each of these
+ lists is deployed independently if and only if its age constraints are
+ met by the human host and a random sample with the given probability of
+ a positive outcome is positive.
+
+ name:Triggered intervention deployment;
+
+
+
-
-
-
- If conditions are specified, deployment of this intervention will only go ahead
- if all specified conditions are true. Condition statements are evaluated only
- during surveys, so deployment is enabled or disabled depending on the results
- of the most recent survey. So called *unreported surveys* can be used to
- reevaluate conditions without increasing granularity of output.
-
- Conditions are evaluated for the whole population, not for individual age-groups
- or cohorts.
-
- This affects all types of deployment.
-
- name:Condition;
-
-
-
-
-
- The monitoring measure to test. Not all measures are available for use.
-
- name:Measure;
-
-
-
-
-
- Minimum value. If specified, the measured variable must be greater than
- or equal to this value for the condition to be satisfied.
-
- name:Minimum value;
-
-
-
-
-
- Maximum value. If specified, the measured variable must be less than or
- equal to this value for the condition to be satisfied.
-
- name:Maximum value;
-
-
-
-
-
- Whether this condition is considered true or false before updated by a survey.
-
- name:Initial state;
-
-
-
-
-
-
- List of ages at which deployment takes place
- (through EPI, post-natal and school-based programmes, etc.).
-
- A sub-population restriction may be added as a property of the
- list of continuous deployments.
-
- name:Age-based (continuous) deployment;
-
-
-
-
-
- List of timed deployments of the intervention (that is, of
- deployment campaigns).
-
- Cumulative deployment mode can be specified for all deployments in a timed list.
- To allow multiple cumulative deployment descriptions, the entire timed list
- may be repeated.
-
- name:Mass (timed) deployment;
-
-
-
+
- Name of intervention
- name:Intervention name;
+
+ Maximum age of eligible humans (defaults to no limit).
+
+ Input is rounded to the nearest time step.
+
+ units:Years;min:0;name:Maximum age of eligible humans;
+
+
+
+
+
+ Minimum age of eligible humans (defaults to 0).
+
+ Input is rounded to the nearest time step.
+
+ units:Years;min:0;name:Minimum age of eligible humans;
+
+
+
+
+
+ Probability of this list of components being deployed, given
+ that other constraints are met.
+
+ units:dimensionless;min:0;max:1;name:Probability of delivery to eligible humans;
-
+
-
-
-
-
-
-
-
-
- Pre-erythrocytic vaccine (PEV): prevents a proportion of infections
- from commencing.
-
- name:Vaccines;
-
-
-
-
-
- Blood-stage vaccine (BSV): acts as a killing factor on blood-stage
- parasites. Exact action depends on the within host model.
-
- name:Vaccines;
-
-
-
-
-
- Transmission-blocking vaccine (TBV): one minus this scales the
- probability of transmission to mosquitoes
-
- name:Vaccines;
-
-
-
-
-
- Description of bed-net interventions (ITNs, LLINs).
-
- name:Bed nets;
-
-
-
-
-
- Description of indoor residual spraying interventions.
-
- name:Indoor residual spraying;
-
-
-
-
-
- Low-level description of intervention effects on vectors (i.e.
- mosquitoes). Can be used to describe simple ITN or IRS
- interventions (though more complex models are available for these
- interventions) or other interventions such as mosquito repellant
- or ivermectin.
-
- Note that all actions of this intervention component will decay
- according to a single decay function. If independant decay is
- wanted, a separate component can be used for each action.
-
- name:Generic vector intervention;
-
-
-
-
-
- Recruitment of a host into a sub-population.
-
- All human-targeting intervention deployments recruit simulated
- humans into a sub-population which can be used for the purposes
- of cumulative deployment, deployment only to a sub-population and
- defining a cohort. This pseudo-intervention can be used to define
- a sub-population without also deploying some intervention.
-
- name:Recruitment only;
-
-
-
-
-
-
- Removes all exposure-related immunitsy gained over time by hosts
- without removing infections (or affecting the ability to gain
- immunity through exposure).
-
- Hypothetical, but potentially useful to simulate scenarios with
- unprotected humans.
-
- name:Clear Immunity;
-
-
-
-
-
+
-
+
+
+
- A short name or code identifying the intervention component
- (used to refer to this component when describing an intervention).
- Also the id of the sub-population defined as those hosts who have
- received this intervention and who haven't subsequently been removed
- from the sub-population.
+ Name of an option (monitoring measure or model option).
- name:Component identifier;
+ name:Option name;
-
+
- An informal name/description for the component
+ Option on/off switch (true/false). Specifying value="true" is
+ the same as not specifying a value; specifying value="false"
+ explicitly turns the option off. If an option is not mentioned
+ at all, it is left at its default value (normally off, but
+ in a few cases, such as some bug-fix options, on).
- name:Name of component;
+ name:Indicator of whether option is required;
-
+
+
+
+
+
+
- Each human intervention component corresponds to a sub-population:
- those who have received or are considered to be protected by the
- intervention component. Humans automatically become members of this
- sub-population when receiving an intervention component; this element
- controls how humans are removed from the sub-population.
-
- ITN attrition also removes humans from sub-populations.
-
- Note that sub-populations do not directly correspond to an
- intervention's effects: lack of effectiveness does not imply removal
- from the sub-population (except as explicitly configured here) and
- removal from the sub-population does not halt an intervention's
- effects.
-
- Sub-populations may be used to define a cohort, to restrict deployment
- of other interventions and to use cumulative deployment mode. A sub-
- population may or may not correspond (roughly) to humans protected by
- some intervention.
+ Specification of decay or survival of a parameter.
- name:Remove from sub-population ...;
+ name:Decay or survival of a parameter
-
+
+
+
+
- If true, remove individuals from the sub-population at the start of
- the first episode (start of a clinical bout) since they were
- recruited into the sub-population. This is intended for cohort
- studies which measure time to the first episode, using active
- case detection.
+ Determines which decay function to use. Available decay functions,
+ for age t in years:
- Reports delayed due to health-system memory are forced out when this
- occurs. Note that this can increase the number of uncomplicated cases
- reported across the entire population; for this reason reports are
- not forced on recruitment or most removal options.
+ constant: 1
- This does not prevent re-recruitment in the case that recruitment
- settings could conceivably recruit the same individual twice.
+ 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
- name:Time to first episode only;
+ units:None;min:0;max:1;name:function;
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
-
+
- If true, remove individuals from the sub-population when they first
- seektreatment since they were recruited into the sub-population. This
- is intended for cohort studies which measure the time to first
- episode, using passive case detection.
-
- Reports delayed due to health-system memory are forced out when this
- occurs. Note that this can increase the number of uncomplicated cases
- reported across the entire population; for this reason reports are
- not forced on recruitment or most removal options.
+ (Time) scale parameter of distribution: this is either the age of
+ complete decay (smooth-compact, step and linear functions) or the age
+ at which the parameter has decayed to half its original value
+ (exponential, weibull and hill). Not used when function="constant"
+ (i.e. no decay).
- This does not prevent re-recruitment in the case that recruitment
- settings could conceivably recruit the same individual twice.
+ This value can be specified in years, days or steps (e.g. 2y, 180d or
+ 100t). When the unit is not specified years are assumed. The value is
+ used without rounding except when sampling an age of decay, when the
+ rounding happens as late as possible.
- name:Time to first treatment only;
+ units:User-defined (defaults to years);min:0;name:L;
-
+
- If true, remove individuals from the sub-population at completion of
- the first survey in which they present with a patent infection since
- they were recruited into the sub-population. This intended for cohort
- studies which measure time to the first infection, using active
- case detection.
-
- Reports delayed due to health-system memory are forced out when this
- occurs. Note that this can increase the number of uncomplicated cases
- reported across the entire population; for this reason reports are
- not forced on recruitment or most removal options.
-
- This does not prevent re-recruitment in the case that recruitment settings could
- conceivably recruit the same individual twice.
+ Shape parameter of distribution. If not specified, default value of
+ 1 is used. Meaning depends on function; not used in some cases.
- name:Time to first infection only;
+ min:0;name:k;units:none;
-
+
- If given, membership to the sub-population of humans who have
- received this intervention component expires after the given number of
- years. Note that future deployments renew membership (e.g. if this
- parameter is 4 years and the intervention is redeployed 3 years from
- now, expiry happens after 7 years).
-
- This provides a crude way of modelling a cohort protected by some
- intervention. A few interventions provide more detailed ways of
- modelling expiry of protection. In any case, "expiry of protection"
- is an abstract concept and does not imply that all protection has
- ceased, even in the simulator.
-
- This may also be useful for cumulative deployment.
-
- Minimum duration is zero, which implies the human is effectively
- never a member of the sub-population; a duration of one timestep
- implies the human is a member of the sub-population while any futher
- interventions are deployed on the same time as this human becomes a
- member and on the next update of the human (including transmission
- and health system events) but not beyond that. If this attribute is
- not given, the simulated human is a member until death or some other
- option triggers removal.
-
- Input is rounded to the nearest time step.
+ If CV is non-zero, heterogeneity of decay is introduced via a random
+ variable sampled from the log-normal distribution. This distribution is
+ parameterised with mean=1 and CV as given.
+
+ The effective age of decay is the real age multiplied by this variable
+ (for decay functions with a half-life, this is equivalent to dividing
+ the half-life by the variable).
+
+ min:0;name:Coefficient of Variation;
+
+
+
+
+
+ (Boolean) If True, this tells OpenMalaria to use the complement of the
+ DecayFunction defined as 1-f(x). This is useful to model increasing
+ functions that will "decay" to 1. This only works if f(x) is contained
+ between 0 and 1.
+
+ units:User-defined (defaults to years);min:0;name:L;
+
+
+
+
+
+ biphasic: Efficacy between 0 and 1.
+
+
+
+
+
+
+ biphasic: Proportion between 0 and 1, proportion of the response that is short-lived.
+
+
+
+
+
+ biphasic: halflife of short lived component (default to years).
+
+
+
+
+
+
+
+ biphasic: halflife of long lived component (default to years).
+
- name:Remove from sub-population after;units:Years;min:0;
-
+
- This can be combined with MDA to achieve mass screen and treat (MSAT)
- or other types of mass screening intervention.
-
- When deployed to a host, this simulates a test of patent malaria
- (microscopy, RDT or some such), then triggers deployment of whichever
- intervention components are configured (deployments for both positive
- and negative test outcomes can be configured).
+ A parameter with optional heterogeneity.
- The use of the screening itself is reported (if enabled), but not the
- outcome. Deployment of interventions triggered by the screening may
- be reported, however.
+ Optionally, a distribution ("distr") and standard of deviation ("SD") may be specified.
- name:(Mass) screening;
+ name:Sampled value (normal);
-
-
-
-
-
+
- Name of a parameterised diagnostic (see scenario/diagnostics).
+ The mean value.
- name:Name of diagnostic;
+ name:mean;
-
-
-
-
- An intervention which may have various effects on the vector populations as a whole. (Not host specific.)
-
- Multiple instances of this intervention class are allowed (multiple parameterisations, not just deployments).
-
- Each instance may have multiple deployments. In this case the effects of each instance
- are independent (effects are combined) but the effects of multiple deployments of a single
- instance are not independent (only the latest deployment has any effect).
-
- units:List of elements;name:Vector population intervention;
-
-
-
-
-
-
-
-
-
-
-
-
- List of timed vector population intervention deployment
-
- name:Vector population intervention deployment;
-
-
-
-
+
- Name of intervention (e.g. larviciding, sugar bait).
+ The standard deviation of variates.
- name:Name of intervention;
+ name:standard deviation;
+
+
+
+
+
+ To allow heterogeneity, a distribution must be specified.
+
+ Valid options are as follows.
+
+ "const": no variation or sampling. Specifying distr="const" has the
+ same effect as not specifying distr at all.
+
+ "normal": the parameter is sampled from a normal distribution.
+
+ name:Distribution;
+
+
+
+
+
+
-
+
- Parameters and deployment of one type of trap. In case multiple types
- of trap are needed simultaneously, multiple elements can be used. Note
- that different types of trap do not interact except that all will
- attract mosquitoes.
+ Parameters of a normal distribution, provided as mean and variance.
+
+ Variates are sampled from Be(α,β) where α and β are determined from the
+ mean and variance as follows: let v be the variance and c=mean/(1-mean).
+ Then we set α=cβ and β=((c+1)²v - c)/((c+1)³v).
- name:Vector trap intervetion;
+ name:Log-normal parameters;
-
-
-
-
- Parameters associated with a vector trap intervention, per
- mosquito species.
-
- name:Description;
-
-
-
-
-
-
- Describes the availiability of a trap to a
- host-seeking mosquito relative to an average
- unprotected adult.
-
- I.e. if this parameter is 2, then each trap will on
- average attract twice as many mosquitoes as
- unprotected adults.
-
- This is the initial availability; it may decay
- towards zero depending on the configured
- decay function.
-
- units:Proportion;name:Initial relative availability;min:0;max:inf;
-
-
-
-
-
- Describes how availability decays to zero.
-
- If decay heterogeneity/variance is used, there will be a
- sample once-per-deployment (i.e. all traps of the same
- deployment will be affected the same way). There is no
- support for variances between traps (except in this crude
- way, between deployments).
-
- name:Decay of availability;
-
-
-
-
-
-
- Name of the species/subspecies/variant.
-
- name:Species/subspecies/variant name
-
-
-
-
-
-
-
- List of timed vector trap intervention deployment
-
- name:Vector trap intervention deployment;
-
-
-
-
-
-
-
-
-
-
- The number of traps deployed, by this
- deployment, per adult human.
-
- E.g. if there are currently 100 traps and 1000
- humans, then a ratio of 0.1 will increase the
- number of traps to 200.
-
- name:Ratio to humans;unit:dimensionless;min:0;max:inf;
-
-
-
-
-
- Life of the trap until replaced or removed, e.g.
- "73t" or "1y". After this time period, these traps
- will be removed from the simulation.
-
- New deployments do not automatically remove old
- traps. Existing traps cannot be refurbished in the
- model. It may make sense to make the end-of-life
- coincide with a new deployment.
-
- name:Lifespan;units:Steps or Days or Years;
-
-
-
-
-
-
-
-
-
-
-
+
- Optional name for this type of trap
+ The mean of the beta distribution (must be in the open range (0,1)).
- name:Descriptive name for type of trap;
+ units:none;name:mean;
-
-
-
+
- Time at which this deployment occurs.
-
- See doc on intervention period and on monitoring/startDate for
- details of how times work. Can be specified in steps, days,
- years, or as a date (examples: 15t, 75d, 0.2y, 2000-03-16).
+ The standard deviation of variates.
- name:Time;units:User defined (defauls to steps);min:0;
+ units:none;name:variance;
-
-
+
+
+
+ A parameter with optional heterogeneity.
+
+ The mean cannot be specified (unless this type is extended).
+ Optionally, a distribution ("distr") and coefficient of variation ("CV") may be specified.
+
+ name:Sampled value (log normal);
+
+
- Proportion of otherwise eligible individuals who will receive this
- deployment.
+ The (linear) coefficient of variation.
+
+ This value must be specified when a (non-constant) distribution is used.
+ Note: since version 46, variance can be used instead.
+
+ Note that specifying CV="0" has the same effect as distr="const" and
+ disables sampling of this parameter, even if distr is not "const".
- units:dimensionless;min:0;max:1;name:Coverage;
+ name:Coefficient of variation;units:unitless;
-
+
- Applies to vaccines only: vaccine doses are only deployed by this
- deployment if the previous number of doses (for the component
- deployed) is at least this number.
+ To allow heterogeneity, a distribution must be specified.
- For example, if this is the second deployment opportunity for this
- vaccine and this value is 1, then this deployment cannot deploy the
- vaccine to individuals who did not receive the first deployment.
+ Valid options are as follows.
+
+ "const": no variation or sampling. Specifying distr="const" has the
+ same effect as not specifying distr at all.
+
+ "lognormal": the parameter is sampled from a log-normal distribution.
+ Note that the "mean" and "CV" values are linear (arithmetic) properties
+ of the distribution and not log-space properties.
- name:Vaccine min previous doses;units:inoculations;min:0;
+ name:Distribution;
+
+
+
+
+
+
+
-
+
- Applies to vaccines only: vaccine doses are only deployed by this
- deployment if the previous number of doses (for the component
- deployed) is less than this number.
+ The variance parameter of the distirbution.
+
+ This value can be specified when a (non-constant) distribution is used.
+
+ Note that specifying variance="0" has the same effect as distr="const" and
+ disables sampling of this parameter, even if distr is not "const".
- name:Vaccine max cumulative doses;units:inoculations;min:0;
+ name:Coefficient of variation;units:unitless;
-
-
-
- Minimum ento availability percentile.
-
- This option is meant to be used with heterogeneity of availability, which can be specified in the entomology section. Without heterogenity (default), all hosts have the same availability and this option will have no effect.
-
- The percentile must be an integer value between 0 and 100. Percentile 99th represents individuals who are more available than 99% of the population. Percentile 0 represents the least available individuals. 100 is equivalent for infinity.
-
- units:percent;min:0;name:Minimum ento availability;
-
-
-
-
-
- Maximum ento availability percentile.
-
- This option is meant to be used with heterogeneity of availability, which can be specified in the entomology section. Without heterogenity (default), all hosts have the same availability and this option will have no effect.
-
- The percentile must be an integer value between 0 and 100. Percentile 99th represents individuals who are more available than 99% of the population. Percentile 0 represents the least available individuals. 100 is equivalent for infinity.
- units:percent;min:0;name:Maximum ento availability;
-
-
-
-
-
-
-
-
-
- Time at which this deployment occurs.
-
- See doc on intervention period and on monitoring/startDate for
- details of how times work. Can be specified in steps, days,
- years, or as a date (examples: 15t, 75d, 0.2y, 2000-03-16).
-
- name:Time;units:User defined (defauls to steps);min:0;
-
-
-
-
-
- Maximum age of eligible individuals (defaults to no limit).
-
- Input is rounded to the nearest time step.
-
- units:Years;min:0;name:Maximum age of eligible individuals;
-
-
-
-
-
- Minimum age of eligible individuals (defaults to 0).
-
- Input is rounded to the nearest time step.
-
- units:Years;min:0;name:Minimum age of eligible individuals;
-
-
-
-
- See repeatEnd's documentation.
- name:Step of repetition;units:User defined;
-
-
-
-
-
- Either both repeatStep and repeatEnd should be present
- or neither. If present, the deployment is repeated every
- repeatStep timesteps (i.e. if t0 is the initial time
- and x is repeatStep, depolyments are done at times t0,
- t0+x, t0+2*x, ...), ending before repeatEnd
- (final repetition is the one before repeatEnd).
-
- Note that repeatEnd may be specified as a date but
- repeatStep must be a duration (days, steps or years).
-
- name:End of repetition (exclusive);units:User defined;
-
-
-
-
-
-
-
-
-
-
-
-
+
+
+
+ A parameter with optional log-normal heterogeneity.
+
+ The mean value must be specified. Optionally, a distribution ("distr")
+ and coefficient of variation ("CV") may be specified.
+
+ name:Sampled value;
+
-
-
-
-
- Target age of intervention.
-
- Input is rounded to the nearest time step.
-
- units:Years;min:0;max:100;name:Target age;
-
-
-
-
-
- First time at which this deployment is active. If not specified,
- deployment starts at the beginning of the intervention period.
-
- See doc on intervention period and on monitoring/startDate for
- details of how times work. Can be specified in steps, days,
- years, or as a date (examples: 15t, 75d, 0.2y, 2000-03-16).
-
- name:First time active;units:User defined (defauls to steps);
-
-
-
+
+
- End of the period during which the intervention is active (to be
- exact, the first step of the intervention period at which the
- item becomes inactive). If not specified, deployment never
- ceases after starting during the simulation.
-
- See doc on intervention period and on monitoring/startDate for
- details of how times work. Can be specified in steps, days,
- years, or as a date (examples: 15t, 75d, 0.2y, 2000-03-16).
+ The (linear) mean value.
- units:User defined (defauls to steps);name:End step;
+ name:mean;
-
-
-
-
-
-
-
-
-
-
-
-
- If this element is not specified, standard deployment occurs, where
- a portion of the population as given by the coverage property of this
- campaign is selected, and interventions are deployed to all of
- these people (regardless of previous coverage).
-
- If this attribute is specified, instead, the population is divided
- into two sets: those who are a member of a certain sub-population and
- those who are not (see "subPopRemoval" element).
- If the proportion of people in the
- first set is less than the desired coverage, then the proportion of
- people from the second set needed to increase total coverage to the
- desired coverage is calculated. This proportion is then used as the
- probablity of selection from the second set into a third set of
- people who then receive all interventions deployed by this campaign.
-
- Note that selection is stochastic so the final coverage level may not
- be exactly that desired. Note also that the component used when
- selecting people need not actually be one of the components deployed
- by this intervention, although that is the intended use case.
-
- name:Cumulative coverage;
-
-
-
-
-
- The identifier (short name) of the component used when
- selecting people.
-
- name:Component identifier;
-
-
-
-
-
-
-
-
-
+
- If this element is specified, deployment is restricted to some
- sub-population (specified via the "id" attribute); otherwise the
- target population is the entire simulated population. Either way, other
- deployment restrictions (age, time, number of vaccine doeses) still
- apply.
+ Parameters of a Weibull distribution.
- name:Restrict to sub-population;
+ name:Weibull parameters;
-
+
- The identifier (short name) of the sub-population (i.e. the "id" of
- some intervention component). Also see the "complement" attribute.
+ The Weibull scale parameter (λ).
- name:Sub-population identifier;
+ name:Scale;
-
+
- If this is not specified or is false, deployment is restricted to the
- sub-population of people protected by the intervention component
- who's id is given. If complement is set to true, deployment is
- instead restricted to the complement of that sub-population, i.e. to
- those not protected by the intervention component.
+ The Weibull shape parameter (k).
- name:Complement;
+ name:shape;
+
+
+
+
+
+ To allow heterogeneity, a distribution must be specified.
+ In this case, only "weibull" is allowed.
+
+ name:Distribution;
+
+
+
+
+
-
-
- Description of a vaccine's effect
- name:Vaccine descriptions;
-
-
-
-
-
- Specification of decay of efficacy. Documentation: see DecayFunction type
- or https://github.com/SwissTPH/openmalaria/wiki/ModelDecayFunctions
-
- name:Decay of effect;
-
-
-
-
-
- Measure of variation in vaccine efficacy: efficacy is sampled from
- a beta distribution with efficacyB its beta parameter and its alpha
- parameter fixed such that the mean is that given by initialEfficacy.
-
- units:Positive real;min:0.001;max:1.00E+06;name:Variance parameter for vaccine efficacy;
-
-
-
-
-
- Mean efficacy values before decay (see efficacyB and decay parameter
- descriptions for sampling and decay). The i-th value in this list
- is used for the efficacy of the vaccine after the i-th dose. Where
- more doses are given than there are values in this list, the last
- value is repeated.
-
- units:dimensionless;min:0;max:1;name:Initial mean efficacy;
-
-
-
+
+
+
+ A double-precision floating-point value.
+ name:Input parameter value;exposed:false;
+
+
+
+
+
+
+ An integer value.
+ name:Input parameter value;exposed:false;
+
+
+
+
+
+
+ A boolean value.
+ name:Input parameter value;exposed:false;
+
+
+
+
+
+
- Pharmaco-Dynamic parameters for some resistance phenotype.
-
- To model resistance to this drug, describe multiple infection
- phenotypes (with respect to these PD parameters) and list one
- or more "restrict" elements for each phenotype.
-
- Loci are specified elsewhere. Multiple loci may influence the
- action of a single drug and each locus may influence multiple
- drugs.
-
- name:PD parameters for some allele / resistance phenotype;
+ 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).
+
+ name:age group;
+
+
+
+
+
+
+ Lower bound of age group
+
+ units:Years;min:0;max:100;name:Lower bound;
+
+
+
+
+
-
-
-
- name:Description
-
-
-
-
-
- Usage of nets by humans, from 0 to 1.
+
+
+
+
+ Interpolation algorithm. Normally it is desirable for age-based
+ values to be continuous w.r.t. age. By default linear interpolation
+ is used.
- At the moment this is constant across humans and deterministic:
- relative attractiveness and survival factors are
- base*(1-usage*propActing) + intervention_factor*usage*propActing.
+ 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).
- See also "propActing" (proportion of bits for which net acts).
+ Algorithms:
+ 1. none: input values are used directly
+ 2. linear: straight lines (on an age vs. value graph) are used to
+ interpolate data points.
- units:dimensionless;min:0;max:1;name:Proportion of time nets are used by humans;
-
-
-
+ name:interpolation;
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
- The rate at which new holes are made in nets.
-
- nHoles(t) = nHoles(t-1) + X where X~Pois(R/T) where T is the number
- of time-steps per year. R is sampled from
- log-normal: R ~ log N( log(mean)-sigma²/2, sigma² ) and is covariant
- with ripRate and insecticideDecay. (To be exact, a single Gaussian
- sample is taken, adjusted for each sigma then exponentiated.)
-
- units:Holes per annum;min:0;name:Rate at which holes are made;
+ Changes to the health system
+
+ name:Change health system;
+
+
+
+
+
+
+
+
+ A complete replacement health system. Replaces all previous properties.
+ (Health system can be replaced multiple times if necessary.)
+
+ name:Timed replacement;
+
+
+
+
+ Time at which this replacement occurs. See doc on
+ intervention period and on monitoring/startDate for
+ details of how times work.
+
+ Can be specified in steps, days, years, or as a date
+ (examples: 15t, 75d, 0.2y, 2000-03-16).
+
+ name:Time;units:User defined (defauls to steps);min:0;
+
+
+
+
+
+
+
+
+
+
+ Name of intervention
+
+ name:Name of intervention;
+
+
+
-
+
- Each existing hole has a probability of being ripped bigger according
- to a Poisson process with this rate as (only) parameter.
-
- New rips occur in a net at rate X~Pois(h×R/T) where h is the number
- of existing holes and T the number of time-steps per year. R is
- sampled from log-normal: R ~ log N( log(mean)-sigma²/2, sigma² )
- and is covariant with holeRate and insecticideDecay. (To be exact, a
- single Gaussian sample is taken, adjusted for the each and sigma
- then exponentiated.)
-
- units:Rips per existing hole per annum;min:0;name:Rate at which holes are enlarged;
+ 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.
+
+ name:Change transmission levels;
+
+
+
+
+
+
+
+
+ Replacement transmission levels. Disables feedback of
+ human infectiousness to mosquitoes on further mosquito
+ to human transmission. Must last until end of simulation.
+
+ name:Timed replacement;
+
+
+
+
+ Time at which this replacement occurs. See doc on
+ intervention period and on monitoring/startDate for
+ details of how times work.
+
+ Can be specified in steps, days, years, or as a date
+ (examples: 15t, 75d, 0.2y, 2000-03-16).
+
+ name:Time;units:User defined (defauls to steps);min:0;
+
+
+
+
+
+
+
+
+
+
+ Name of intervention
+
+ name:Name of intervention;
+
+
+
-
+
- This factor expresses how important rips are in increasing the hole.
-
- The hole index of a net is h + F×x where h and x are the total numbers
- of holes and rips respectively and F is the rip factor.
-
- units:none;min:0;name:Rip factor;
+ Models importation of P. falciparum infections directly into humans
+ from an external source. This is infections, not inoculations or
+ EIR being imported.
+
+ name:Imported infections;
-
-
-
+
+
+
+
+
+ Rate of case importation, as a step function. Each value is
+ valid until replaced by the next value.
+
+ name:Rate of importation
+
+
+
+
+
+
+
+
+ A time-rate pair.
+ name:Rate;units:Imported cases per thousand people per year;
+
+
+
+
+ Time at which this importation rate becomes active.
+
+ See doc on intervention period and on monitoring/startDate for
+ details of how times work. Can be specified in steps, days,
+ years, or as a date (examples: 15t, 75d, 0.2y, 2000-03-16).
+
+ name:Time of start;units:User defined (defauls to steps);min:0;
+
+
+
+
+
+
+
+
+
+
+ If period is 0 (or effectively infinite), the last specified
+ value remains indefinitely in effect.
+
+ If period is less than the length of the simulation's intervention phase,
+ then all "rate" deployments are repeated with this periodicity.
+ In this case, the first "rate" deployment must coincide with the start of
+ the intervention phase (monitoring/startDate).
+
+ Can be specified in steps (e.g. 1t) or days (e.g. 365d).
+
+ name:Period of repetition;units:User defined (default: steps);min:0
+
+
+
+
+
+
+
+
+ Name of intervention
+
+ name:Name of intervention;
+
+
+
+
+
+
- The insecticide concentration of new nets is Gaussian distributed with
- mean "mu" and a standard deviation "sigma". The standard deviation
- should be small relative to the mean to avoid negative initial
- concentration. Any negative values sampled are set to 0.
-
- units:mg/m²;min:0;name:Initial insecticide;
+ 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.
+
+ name:Insert R_0 case;
+
+
+
+
+
+ name:Timed occurrence;
+
+
+
+
+ Time at which this intervention occurs.
+
+ See doc on intervention period and on monitoring/startDate for
+ details of how times work. Can be specified in steps, days,
+ years, or as a date (examples: 15t, 75d, 0.2y, 2000-03-16).
+
+ name:Time;units:User defined (defauls to steps);min:0;
+
+
+
+
+
+
+
+
+ Name of intervention
+
+ name:Name of intervention;
+
+
+
-
+
- Decay curve for insecticide content of nets. Documentation: see DecayFunction
- type or https://github.com/SwissTPH/openmalaria/wiki/ModelDecayFunctions
-
- The distribution of decay rates over nets is covariant with the
- distribution of ripRate and holeRate over nets. This distribution is
- generated by taking one sample per net from a Gaussian distribution
- with mean 0 and standard deviation 1. For each variable, the sample
- is multiplied by the respective sigma and a constant added such that,
- once exponentiated, the mean of the variable over nets is 1. The
- variable is then exponentiated and multiplied by the required mean
- rate for the respective variable.
-
- units:none;name:Decay of insecticide;
+ Removes all infections from mosquitoes -- resulting in zero EIR to
+ humans, until such time that mosquitoes are re-infected and become
+ infectious. Only efficacious 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.
+
+ units:List of elements;name:Uninfect vectors;
+
+
+
+
+
+
+ name:Timed occurrence;
+
+
+
+
+ Time at which this intervention occurs.
+
+ See doc on intervention period and on monitoring/startDate for
+ details of how times work. Can be specified in steps, days,
+ years, or as a date (examples: 15t, 75d, 0.2y, 2000-03-16).
+
+ name:Time;units:User defined (defauls to steps);min:0;
+
+
+
+
+
+
+
+
+ Name of intervention
+
+ name:Name of intervention;
+
+
+
+
+
+
+ A list of parameterisations of generic vector host-inspecific interventions.
+ name:Vector population intervention;units:List of elements;
+
+
+
+
+
+
-
+
- Specifies the rate at which nets are disposed of over time.
- Documentation: see DecayFunction type or
- https://github.com/SwissTPH/openmalaria/wiki/ModelDecayFunctions
-
- In the current model, nets are disposed of randomly (no correlation
- with state of decay) such that the chance of each net surviving until
- age t is the value of this decay function at time t. Equivalently
- (where a large number of nets are distributed at the same time), the
- proportion of nets remaining in use should match this decay function
- over time.
-
- Humans are removed from the intervention component's sub-population
- on disposal (attrition) of their nets. Currently this event is not
- reported.
-
- units:dimensionless;name:Attrition of nets;
+ Traps attract and kill mosquitoes. They are modelled as a
+ non-human-host where the probability of mosquitoes surviving
+ feeding is zero (since otherwise the simulator would assume
+ surviving mosquitoes have had a blood meal), and where this
+ "host" is initially not present.
+
+ Model: each type of trap has has an initial availability
+ relative to a human and a decay in availability. Each
+ deployment has a fixed maximum lifespan, after which the
+ traps from that deployment are removed (it is up to the
+ user whether this is after availability is effectively zero
+ or sooner, either coinciding with a redeployment or
+ causing a reduction in overall effectiveness of traps).
+
+ name:Baited trap
+
+
+
+
+
-
+
+
+ List of interventions that modify parameters of non-human hosts described in the <entomology> <vector> <anopheles>.
+
-
-
-
- Used by logit attacking and killing models only, holeIndexMax
- is a user defined maximum hole index (typically, the total surface area of a net).
-
- units:in same unit as holeIndex;name:maximum of holed surface area that has an effect (comparable to no net)
-
-
-
-
-
-
- Effect of net on attractiveness of humans to mosquitoes relative to
- an unprotected adult human. Parameterisations should take into
- account that mosquitoes do not always bite indoors.
-
- Attractiveness of the human is multiplied by
- exp(log(H)×h + log(P)×p + log(I)×h×p
- where H, P and I are the hole, insecticide and interaction factors
- respectively, h=exp(-holeIndex×holeScalingFactor) and
- p=1−exp(-insecticideContent×insecticideScalingFactor).
-
- units:dimensionless;min:0;max:1;name:Relative attractiveness;
-
-
-
-
-
- Effect of net on attractiveness of humans to mosquitoes relative to
- an unprotected adult human. Parameterisations should take into
- account that mosquitoes do not always bite indoors.
-
- This deterrency model multiplies human attractiveness by
- pEnt×pAtt.
-
- units:dimensionless;name:Relative attractiveness;
-
-
-
-
-
-
-
- pEnt represents the relative probability of entering due to
- ITNs: pEnt = exp(log(P)×p) where P is the insecticide
- factor and
- p=1−exp(-insecticideContent×insecticideScalingFactor).
-
- units:dimensionless;name:Deterrency: entering;
-
-
-
-
-
- pEnt represents the relative probability of entering due to insecticide
- in the hut:
- pEnt = exp(logit.pEnt) / (exp(logit.pEnt) + 1)
- logit.pEnt = B + P * p
- where B is the basefactor (without net); P is insecticide factor, and
- p = log(insecticideContent+1).
- Without a net, probability of entering a house is
- pEnt0 = exp(logit.pEnt0) / (exp(logit.pEnt0) + 1)
- logit.pEnt0 = B
- Entering of mosquitoes is adjusted via multiplication by pEnt / pEnt0.
- To keep this in the range [0,1], we (normally) require that
- pEnt ≤ pEnt0
- and thus P ≤ 0 and give a warning if this is not fulfilled.
-
- units:dimensionless;name:Deterrency: entering (logit model);
-
-
-
-
-
-
-
- pAtt represents the relative probability of attacking a human after
- entering a house due to ITNs (i.e. of feeding/dying vs. flying off):
- pAtt = B + H×h + P×p + I×h×p
- where B is the base (without net) probability; H, P and I are the hole,
- insecticide and interaction factors respectively,
- h=exp(-holeIndex × holeScalingFactor)
- and
- p=1 - exp(-insecticideContent × insecticideScalingFactor).
-
- units:dimensionless;name:Deterrency: attacking;
-
-
-
-
-
- pAtt represents the relative probability of attacking a human
- after entering a house due to ITNs (i.e. of feeding/dying vs.
- flying off):
- pAtt = exp(logit.pAtt) / (exp(logit.pAtt) + 1)
- logit.pAtt = B + H×min(h, hMax) + P×p + I×min(h, hMax)×p
- where B is the base factor (without net); H, P and
- I are the hole, insecticide and interaction factors
- respectively, and:
- h = log(holeIndex + 1)
- p = log(insecticideContent + 1)
- Without a net, probability of attacking a human
- after entering a house is
- pAtt0 = exp(logit.pAtt0) / (exp(logit.pAtt0) + 1)
- logit.pAtt0 = B + H×hMax
- where hMax=log(holeIndexMax + 1) and holeIndexMax is a user defined
- maximum hole index (typically, the total surface area of a net).
- Attacking of mosquitoes is adjusted via multiplication by pAtt / pAtt0.
- This may be larger and smaller than 1 (but will not be negative).
- By definition (through the logit transformation) pAtt0 > 0.
-
- units:dimensionless;name:Deterrency: attacking (logit model);
-
-
-
-
-
-
-
-
-
-
-
- Effect of net on survival mosquitoes as they seek to bite a human
- after choosing that human, relative to the same person not
- sleeping under a net. Parameterisations should take into
- account that mosquitoes do not always bite indoors.
-
- Killing proportion is calculated as K = B + H×h + P×p + I×h×p
- where B is the base (without net) probability of death,
- H, P and I are the hole, insecticide and interaction factors
- respectively, h=exp(-holeIndex×holeScalingFactor) and
- p=1−exp(-insecticideContent×insecticideScalingFactor).
-
- Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−B).
- To keep this in the range [0,1], we require that B+H ≤ 1, B+P ≤ 1,
- B+H+P+I ≤ 1, H ≥ 0, P ≥ 0 and H+P+I ≥ 0.
-
- units:dimensionless;min:0;max:1;name:Pre-prandial killing effect;
-
-
-
-
-
- Effect of net on survival mosquitoes as they seek to bite a human
- after choosing that human, relative to the same person not
- sleeping under a net.
- Killing proportion is calculated as
- K=exp(logit.K)/(exp(logit.K)+1)
- logit.K = B + H×min(h,hMax) + P×p + I×min(h,hMax)×p
- where B is the basefactor (without net),
- H, P and I are the hole, insecticide and interaction factors
- respectively, h=log(holeIndex+1) and
- p=log(insecticideContent+1).
- Without a net, the killing proportion
- K0=exp(logit.K0)/(exp(logit.K0)+1)
- logit.K0 = B + H×hMax
- where hMax=log(holeIndexMax+1) and holeIndexMax is a user defined maximum hole index (typically, the total surface area of a net).
- Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−K0).
- To keep this in the range [0,1], we require that K ≥ K0. We enforce that P ≥ 0 (It would not make sense biologically if P were negative) and P+I*hMax ≥ 0 and H ≤ 0 and holeIndex ≤ holeIndexMax and give a warning if these conditions are not fulfilled.
-
- units:dimensionless;min:0;max:1;name:Pre-prandial killing effect (logit);
-
-
-
-
-
-
-
- Effect of net on survival mosquitoes as they seek to escape from
- a human host and rest after a blood meal, relative to the same
- person not sleeping under a net. Parameterisations should take
- into account that mosquitoes do not always bite indoors.
-
- Killing proportion is calculated as K = B + H×h + P×p + I×h×p
- where B is the base (without net) probability of death,
- H, P and I are the hole, insecticide and interaction factors
- respectively, h=exp(-holeIndex×holeScalingFactor) and
- p=1−exp(-insecticideContent×insecticideScalingFactor).
-
- Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−B).
- To keep this in the range [0,1], we require that B+H ≤ 1, B+P ≤ 1,
- B+H+P+I ≤ 1, H ≥ 0, P ≥ 0 and H+P+I ≥ 0.
-
- units:dimensionless;min:0;max:1;name:Post-prandial killing effect;
-
-
-
-
-
- Effect of net on survival mosquitoes as they seek to escape from
- a human host and rest after a blood meal, relative to the same
- person not sleeping under a net.
- Killing proportion is calculated as
- K=exp(logit.K)/(exp(logit.K)+1)
- logit.K = B + H×min(h,hMax) + P×p + I×min(h,hMax)×p
- where B is the basefactor (without net),
- H, P and I are the hole, insecticide and interaction factors
- respectively, h=log(holeIndex+1) and
- p=log(insecticideContent+1).
- Without a net, the killing proportion
- K0=exp(logit.K0)/(exp(logit.K0)+1)
- logit.K0 = B + H×hMax
- where hMax=log(holeIndexMax+1) and holeIndexMax is a user defined maximum hole index (typically, the total surface area of a net).
- Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−K0).
- To keep this in the range [0,1], we require that K ≥ K0. We enforce that P ≥ 0 (It would not make sense biologically if P were negative) and P+I*hMax ≥ 0 and H ≤ 0 and holeIndex ≤ holeIndexMax and give a warning if these conditions are not fulfilled.
-
- units:dimensionless;min:0;max:1;name:Post-prandial killing effect (logit);
-
-
-
-
-
-
-
- Effect of net on fertility of mosquitoes who survive feeding
- on a protected human, relative to an unprotected human.
-
- Fertility (number of eggs laid) is multiplied by (1-K) / (1-B),
- similar to killing effects. This is not allowed to be greater than 1.
-
- name:Fecundity reduction;
-
-
-
-
-
- Effect of net on fertility of mosquitoes who survive feeding
- on a protected human, relative to an unprotected human.
-
- Fertility (number of eggs laid) is multiplied by (1-K) / (1-K0),
- similar to killing effects. This is not allowed to be greater than 1.
-
- name:Fecundity reduction (logit);
-
-
-
-
-
-
-
- Name of the affected anopheles-mosquito species.
-
- name:Mosquito species;
-
-
-
-
-
- Deprecated: propActive can still be used but its value must be set to either 0 or 1.
- Any other value will result in an error at initialization.
-
- The proportion of bites, when nets are in use, for which the net
- has any action whatsoever on the mosquito.
-
- At the moment this is constant across humans and deterministic:
- relative attractiveness and survival factors are
- base*(1-usage*propActing) + intervention_factor*usage*propActing.
-
- See also "usage" (proportion of time nets are used by humans).
-
- units:dimensionless;min:0;max:1;name:Proportion of bites for which net acts;
-
-
-
-
-
-
-
-
-
-
-
- Usage of Generic vector interventions, from 0 to 1.
-
- units:dimensionless;min:0;max:1;name:Proportion of generic vector interventions;
-
-
-
-
-
- Description of decay of all intervention effects.
- Documentation: see DecayFunction type or
- https://github.com/SwissTPH/openmalaria/wiki/ModelDecayFunctions
-
- name:Decay;
-
-
-
-
- name:Per-mosquito species parameters;
-
-
-
-
-
-
- Effect of intervention on attractiveness of humans to mosquitoes relative to
- an unprotected adult human. Parameterisations should take into
- account that mosquitoes do not always bite indoors.
-
- Attractiveness of the human is multiplied this factor times
- survival of effect.
-
- units:dimensionless;min:0;max:1;name:Relative attractiveness
-
-
-
-
-
- Effect of intervention on survival of mosquitoes as they seek to bite a human
- after choosing that human, relative to the same person not
- protected by the intervention. Parameterisations should take into account
- that mosquitoes do not always bite indoors. This parameter has
- been added since some data shows IRS to have a preprandial
- killing effect.
-
- Killing proportion is this factor multiplied by survival of effect.
-
- units:dimensionless;min:0;max:1;name:Pre-prandial killing effect
-
-
-
-
-
- Effect of intervention on survival of mosquitoes as they seek to escape from
- a human host and rest after a blood meal, relative to the same
- person not protected by the intervention. Parameterisations should take
- into account that mosquitoes do not always bite indoors.
-
- Killing proportion is this factor multiplied by survival of effect.
-
- units:dimensionless;min:0;max:1;name:Post-prandial killing effect
-
-
-
-
-
- Effect of intervention on fertility mosquitoes after successfully feeding on
- a human host, relative to an unproteced human. Parameterisations should take
- into account that mosquitoes do not always bite indoors.
-
- Fertility is multiplied by 1 - (fecundityReduction * decay).
-
- min:0;name:Fecundity reduction effect
-
-
-
-
-
-
- Name of the affected anopheles-mosquito species.
-
- name:Mosquito species
-
-
-
-
-
- The proportion of bites for which the IRS
- has any action whatsoever on the mosquito.
-
- At the moment this is constant across humans and deterministic:
- relative attractiveness and survival factors are
- base*(1-propActing) + intervention_factor*propActing.
-
- units:dimensionless;min:0;max:1;name:Proportion of bites for which IRS acts;
-
-
-
-
-
-
-
-
-
- Description of effect for the more complex and probably more realistic
- Briet model: IRS has three effects, whos strength is calculated as a
- function of surviving insecticide content.
-
- name:Description (based on decay of insecticide);
-
-
-
-
-
- Usage of Indoor residual spraying (IRS) interventions, from 0 to 1.
-
- units:dimensionless;min:0;max:1;name:Proportion of Indoor residual spraying (IRS) interventions;
-
-
-
-
-
- The insecticide concentration of IRS (at time of spraying) is
- Gaussian distributed with mean "mu" and a standard deviation "sigma".
- The standard deviation should be small relative to the mean to avoid
- negative initial concentration. Any negative values sampled are set
- to 0.
-
- units:μg/cm²;min:0;name:Initial insecticide
-
-
-
-
-
- Decay curve for insecticide content of IRS. Documentation: see DecayFunction
- type or https://github.com/SwissTPH/openmalaria/wiki/ModelDecayFunctions
-
- units:none;name:Decay of insecticide
-
-
-
-
- name:Per-mosquito species parameters;
-
-
-
-
-
-
- Effect of IRS on attractiveness of humans to mosquitoes relative to
- an unprotected adult human. Parameterisations should take into
- account that mosquitoes do not always bite indoors.
-
- Attractiveness of the human is multiplied by exp(P×log(p))
- where P is the insecticide factor,
- p=1−exp(-insecticideContent×insecticideScalingFactor).
-
- units:dimensionless;min:0;max:1;name:Relative attractiveness
-
-
-
-
-
- Effect of IRS on survival mosquitoes as they seek to bite a human
- after choosing that human, relative to the same person not
- protected by IRS. Parameterisations should take into account
- that mosquitoes do not always bite indoors. This parameter has
- been added since some data shows IRS to have a preprandial
- killing effect.
-
- Killing proportion is calculated as K = B + P×p where B is the
- base (without protection) probability of death, and P is the
- insecticide factor,
- p=1−exp(-insecticideContent×insecticideScalingFactor).
-
- Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−B).
- To keep this in the range [0,1], we require that B+P ≤ 1 and P ≥ 0.
-
- units:dimensionless;min:0;max:1;name:Pre-prandial killing effect
-
-
-
-
-
- Effect of IRS on survival mosquitoes as they seek to escape from
- a human host and rest after a blood meal, relative to the same
- person not protected by IRS. Parameterisations should take
- into account that mosquitoes do not always bite indoors.
-
- Killing proportion is calculated as K = B + P×p where B is the
- base (without protection) probability of death, and P is the
- insecticide factor,
- p=1−exp(-insecticideContent×insecticideScalingFactor).
-
- Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−B).
- To keep this in the range [0,1], we require that B+P ≤ 1 and P ≥ 0.
-
- units:dimensionless;min:0;max:1;name:Post-prandial killing effect
-
-
-
-
-
- Effect of IRS on fertility mosquitoes after successfully feeding on
- a human host, relative to an unproteced human. Parameterisations should take
- into account that mosquitoes do not always bite indoors.
-
- First, we calculate K = B + P×p where B is the
- base (without protection) probability of death, and P is the
- insecticide factor,
- p=1−exp(-insecticideContent×insecticideScalingFactor).
-
- Fecundity is multiplied by (1−K) / (1−B). It is not allowed to be greater than 1.
- To keep this in the range [0,1], we require that B+P ≤ 1 and P ≥ 0.
-
- name:Fecundity reduction
-
-
+
-
-
-
- Name of the affected anopheles-mosquito species.
-
- name:Mosquito species
-
-
-
-
-
- The proportion of bites for which the IRS
- has any action whatsoever on the mosquito.
-
- At the moment this is constant across humans and deterministic:
- relative attractiveness and survival factors are
- base*(1-propActing) + intervention_factor*propActing.
-
- units:dimensionless;min:0;max:1;name:Proportion of bites for which IRS acts;
-
-
-
-
-
-
-
-
- Value expected to be at least 0. Negative values are not
- necessarily invalid, but allow nets to increase transmission.
-
- units:none;name:Insecticide factor;max:1
-
-
-
-
- units:none;name:Insecticide scaling factor;min:0
-
-
-
-
-
-
-
- See parent element documentation
-
- units:none;name:Base factor;
-
-
-
-
-
- See parent element documentation
-
- units:none;name:Insecticide factor;
-
-
-
-
-
-
-
-
- units:dimensionless;name:Probability of mosquito death without intervention
-
-
-
-
-
-
-
-
-
-
-
- Value expected to be at least 0. Negative values are not
- necessarily invalid, but allow nets to increase transmission.
-
- units:none;name:Hole factor;max:1
-
-
-
-
-
- holeFactor + insecticideFactor + interactionFactor must not be greater
- than 1, and is expected to be at least 0. A negative value is not
- necessarily invalid, but allows nets to increase transmission.
-
- units:none;name:Interaction factor;max:1
-
-
-
-
- units:none;name:Hole scaling factor;min:0
-
-
-
-
-
-
-
-
-
-
- units:dimensionless;name:Probability of mosquito death without intervention
-
-
-
-
-
-
-
-
-
- Logit of the probability (e.g. of death, of entry, of attacking) without intervention.
-
- units:dimensionless;name:Base factor;
-
-
-
-
-
- Coefficient of log(insecticide content+1) in a generalized linear model with logit link
- function.
-
- units:none;name:Insecticide factor;
-
-
-
-
-
- Coefficient of log(total holed surface area (in cm2) +1) in a generalized linear model
- with logit link function.
-
- units:none;name:Hole factor;
-
-
-
-
-
- Coefficient of the interaction term of log(total holed surface area (in cm2) +1) with
- log(insecticide content+1) in a generalized linear model with logit link function.
-
- units:none;name:Interaction factor;
-
-
-
-
-
-
- Descriptions of the effects of vector interventions with per-species effects.
-
- units:dimensionless;min:0;max:1;name:Vector population intervention;
-
-
-
+
-
- Describe an effect on the increase in the death rate while host
- seeking (mu_vA) due to this intervention.
-
- Enter the rate increase (i.e. if rate increases to 120% of normal,
- give 0.2). New death rate while seeking is old × (1 + increase)
- where increase is this factor given. Must have increas ≥ -1.
-
- units:dimensionless;name:Proportional increase in deaths while host searching;
+ List of intervention that add new non-human hosts that have not been described in the <entomology> <vector>
+<anopheles> <nonHumanHosts>.
-
+
-
-
- units:dimensionless;min:-1;max:inf;name:Initial proportion increase
-
-
-
+
- Describe an effect of increased mortality while ovipositing
- due to this intervention. Enter the probability of dying due to
- this intervention.
+ Encapsulates all interventions whose effects are specific to the
+ human host: any interventions where target humans may be selected
+ via population-coverage, age limits and sub-population membership.
- units:dimensionless;name:Proportion ovipositing mosquitoes killed;
+ name:Human-specific interventions;
-
-
-
-
-
-
- units:dimensionless;min:0;max:1;name:Initial probability of killing
-
-
-
-
+
+
+
+ Name of set of interventions
+ name:Name of intervention set;
+
+
+
+
+
+
- Describe an effect on emergence of pupa into adults: this value is the
- proportion of emerging pupa which are killed by this intervention.
+ A parameterisation of an effect achieved by one component of an
+ intervention. (An intervention is described as the effects of a set
+ of components plus deployments of those components. This describes
+ the components individually, not deployments or which components
+ comprise an intervention.)
- This can be used as a crude way of modelling larviciding. It ca
- also be used to increase emergence by giving a negative value.
- The emergence rate is "old rate" × (1 - factor) where factor is the
- value given here; thus, for example, using -1 will double emergence.
+ Each element describes one component: its effects, decay of the(se)
+ effect(s), and related stuff (e.g. description of indirect decay
+ and of usage levels).
+
+ Different interventions can deploy the same component to the same
+ perso. In most cases this will just deploy a fresh instance (e.g. a
+ new bed net will replace the old (nobody uses multiple bed nets),
+ or a new drug dose will act on top of previous doses, or in the
+ case of a vaccine, effect depends on the total number of previous
+ inoculations (including from other interventions).
+
+ Where multiple components of the same type (but with different ids)
+ are deployed (whether within a single intervention or by multiple
+ interventions), they act independently (e.g. two bed nets deployed
+ to a single host would act to reduce attractiveness or survival of
+ mosquitoes biting that host twice — this may be useful to simulate
+ some novel vector intervention since the two nets may have separate
+ parameters).
- units:dimensionless;name:Proportion of emerging pupa killed;
+ name:Component;
-
-
-
-
-
-
- units:dimensionless;min:-inf;max:1;name:Initial proportion reduction
-
-
-
-
+
- Describe an effect on the increase in the death rate while host
- seeking (mu_vA) due to this intervention. This works like
- adding an non-human host with its own availability. The
- difference is that biting this sugar bait is associated with a
- probability of dying of 1: all mosquitoes biting the sugar bait
- will die. OpenMalaria will automatically compute the
- availability for this host so that the probability of biting this
- 'host' (and thus dying) is equal to the input parameter.
+ This element describes deployment of an intervention: which
+ components are deployed, how humans are selected for deployment
+ (via timed or age-based deployment) as well as a few additional
+ restrictions (e.g. vaccine dosing restrictions).
- Enter the probability of dying while host seeking due to this
- intervention. If multiple interventions overlap, the cumulative
- probability will be used. Note that it cannot exceed 1, and
- OpenMalaria will return an error during the simulation if this
- ever happens.
-
- OpenMalaria will dynamically compute the necessary increase
- in mu_vA based on the given probability. Note that this is done
- by solving an equation numerically every timestep, which can
- cause a small drop in performance.
- units:dimensionless;name:Probability of death while host searching as a result of feeding on a sugar bait (used to dynamically adjust mu_vA);
+ All components deployed by this intervention are deployed to the
+ same people (each timed or continuous deployment selects recipients
+ and then gives each recipient all components of the intervention).
+
+ name:Deployment;
-
+
+
+
+
+ If conditions are specified, deployment of this intervention will only go ahead
+ if all specified conditions are true. Condition statements are evaluated only
+ during surveys, so deployment is enabled or disabled depending on the results
+ of the most recent survey. So called *unreported surveys* can be used to
+ reevaluate conditions without increasing granularity of output.
+
+ Conditions are evaluated for the whole population, not for individual age-groups
+ or cohorts.
+
+ This affects all types of deployment.
+
+ name:Condition;
+
+
+
+
+
+ The monitoring measure to test. Not all measures are available for use.
+
+ name:Measure;
+
+
+
+
+
+ Minimum value. If specified, the measured variable must be greater than
+ or equal to this value for the condition to be satisfied.
+
+ name:Minimum value;
+
+
+
+
+
+ Maximum value. If specified, the measured variable must be less than or
+ equal to this value for the condition to be satisfied.
+
+ name:Maximum value;
+
+
+
+
+
+ Whether this condition is considered true or false before updated by a survey.
+
+ name:Initial state;
+
+
+
+
+
+
+ List of ages at which deployment takes place
+ (through EPI, post-natal and school-based programmes, etc.).
+
+ A sub-population restriction may be added as a property of the
+ list of continuous deployments.
+
+ name:Age-based (continuous) deployment;
+
+
+
+
+
+ List of timed deployments of the intervention (that is, of
+ deployment campaigns).
+
+ Cumulative deployment mode can be specified for all deployments in a timed list.
+ To allow multiple cumulative deployment descriptions, the entire timed list
+ may be repeated.
+
+ name:Mass (timed) deployment;
+
+
-
+
- units:dimensionless;min:-1;max:inf;name:Initial proportion increase
+ Name of intervention
+ name:Intervention name;
-
-
+
+
+
+
+
+
+
+
+
+
+
+
+ Pre-erythrocytic vaccine (PEV): prevents a proportion of infections
+ from commencing.
+
+ name:Vaccines;
+
+
+
+
+
+ Blood-stage vaccine (BSV): acts as a killing factor on blood-stage
+ parasites. Exact action depends on the within host model.
+
+ name:Vaccines;
+
+
+
+
+
+ Transmission-blocking vaccine (TBV): one minus this scales the
+ probability of transmission to mosquitoes
+
+ name:Vaccines;
+
+
+
+
+
+ Description of bed-net interventions (ITNs, LLINs).
+
+ name:Bed nets;
+
+
+
+
+
+ Description of indoor residual spraying interventions.
+
+ name:Indoor residual spraying;
+
+
+
+
+
+ Low-level description of intervention effects on vectors (i.e.
+ mosquitoes). Can be used to describe simple ITN or IRS
+ interventions (though more complex models are available for these
+ interventions) or other interventions such as mosquito repellant
+ or ivermectin.
+
+ Note that all actions of this intervention component will decay
+ according to a single decay function. If independant decay is
+ wanted, a separate component can be used for each action.
+
+ name:Generic vector intervention;
+
+
+
+
+
+ Recruitment of a host into a sub-population.
+
+ All human-targeting intervention deployments recruit simulated
+ humans into a sub-population which can be used for the purposes
+ of cumulative deployment, deployment only to a sub-population and
+ defining a cohort. This pseudo-intervention can be used to define
+ a sub-population without also deploying some intervention.
+
+ name:Recruitment only;
+
+
+
+
+
+
+ Removes all exposure-related immunitsy gained over time by hosts
+ without removing infections (or affecting the ability to gain
+ immunity through exposure).
+
+ Hypothetical, but potentially useful to simulate scenarios with
+ unprotected humans.
+
+ name:Clear Immunity;
+
+
+
+
+
+
+
- Name of the species/subspecies/variant.
+ A short name or code identifying the intervention component
+ (used to refer to this component when describing an intervention).
+ Also the id of the sub-population defined as those hosts who have
+ received this intervention and who haven't subsequently been removed
+ from the sub-population.
- name:Species/subspecies/variant name
+ name:Component identifier;
+
+
+
+
+
+ An informal name/description for the component
+
+ name:Name of component;
-
+
- This intervention modifies parameters of non-human hosts described in the <entomology> <vector> <anopheles>
-<nonHumanHosts> section of the input scenario file.
-
-The intervention is described by 5 parameters that define the change in each of non-human host parameters:
-
-reduceAvailability: Reduction in the availability rate, αi. For example a value of 0 will result in no change; a value of 0.2 will reduce the availability to 0.8 of its initial value; and a value of 1 will set the availability to 0;
-
-prePrandialKillingEffect: Reduction in the pre-prandial survival probability, PBi. For example a value of 0 will result in no change; a value of 0.2 will reduce PBi to 0.8 of its initial value; and a value of 1 will set PBi to 0;
-
-postPrandialKillingEffect: Reduction in the post-prandial survival probability, PCi. For example a value of 0 will result in no change; a value of 0.2 will reduce PCi to 0.8 of its initial value; and a value of 1 will set PCi to 0;
-
-restingKillingEffect: Reduction in the survival probability of the resting period, PDi. For example a value of 0 will result in no change; a value of 0.2 will reduce PDi to 0.8 of its initial value; and a value of 1 will set PDi to 0;
+
+ Each human intervention component corresponds to a sub-population:
+ those who have received or are considered to be protected by the
+ intervention component. Humans automatically become members of this
+ sub-population when receiving an intervention component; this element
+ controls how humans are removed from the sub-population.
+
+ ITN attrition also removes humans from sub-populations.
+
+ Note that sub-populations do not directly correspond to an
+ intervention's effects: lack of effectiveness does not imply removal
+ from the sub-population (except as explicitly configured here) and
+ removal from the sub-population does not halt an intervention's
+ effects.
+
+ Sub-populations may be used to define a cohort, to restrict deployment
+ of other interventions and to use cumulative deployment mode. A sub-
+ population may or may not correspond (roughly) to humans protected by
+ some intervention.
+
+ name:Remove from sub-population ...;
-
-
-
-
-
-
-
-
-
-
-
-
- List of timed vector population intervention deployment
-
- name:Vector population intervention deployment;
-
-
-
-
+
- Name of intervention (e.g. larviciding, sugar bait).
+ If true, remove individuals from the sub-population at the start of
+ the first episode (start of a clinical bout) since they were
+ recruited into the sub-population. This is intended for cohort
+ studies which measure time to the first episode, using active
+ case detection.
+
+ Reports delayed due to health-system memory are forced out when this
+ occurs. Note that this can increase the number of uncomplicated cases
+ reported across the entire population; for this reason reports are
+ not forced on recruitment or most removal options.
+
+ This does not prevent re-recruitment in the case that recruitment
+ settings could conceivably recruit the same individual twice.
- name:Name of intervention;
+ name:Time to first episode only;
-
+
- Name of intervention (e.g. larviciding, sugar bait).
+ If true, remove individuals from the sub-population when they first
+ seektreatment since they were recruited into the sub-population. This
+ is intended for cohort studies which measure the time to first
+ episode, using passive case detection.
+
+ Reports delayed due to health-system memory are forced out when this
+ occurs. Note that this can increase the number of uncomplicated cases
+ reported across the entire population; for this reason reports are
+ not forced on recruitment or most removal options.
+
+ This does not prevent re-recruitment in the case that recruitment
+ settings could conceivably recruit the same individual twice.
- name:Name of intervention;
+ name:Time to first treatment only;
+
+
+
+
+
+ If true, remove individuals from the sub-population at completion of
+ the first survey in which they present with a patent infection since
+ they were recruited into the sub-population. This intended for cohort
+ studies which measure time to the first infection, using active
+ case detection.
+
+ Reports delayed due to health-system memory are forced out when this
+ occurs. Note that this can increase the number of uncomplicated cases
+ reported across the entire population; for this reason reports are
+ not forced on recruitment or most removal options.
+
+ This does not prevent re-recruitment in the case that recruitment settings could
+ conceivably recruit the same individual twice.
+
+ name:Time to first infection only;
+
+
+
+
+
+ If given, membership to the sub-population of humans who have
+ received this intervention component expires after the given number of
+ years. Note that future deployments renew membership (e.g. if this
+ parameter is 4 years and the intervention is redeployed 3 years from
+ now, expiry happens after 7 years).
+
+ This provides a crude way of modelling a cohort protected by some
+ intervention. A few interventions provide more detailed ways of
+ modelling expiry of protection. In any case, "expiry of protection"
+ is an abstract concept and does not imply that all protection has
+ ceased, even in the simulator.
+
+ This may also be useful for cumulative deployment.
+
+ Minimum duration is zero, which implies the human is effectively
+ never a member of the sub-population; a duration of one timestep
+ implies the human is a member of the sub-population while any futher
+ interventions are deployed on the same time as this human becomes a
+ member and on the next update of the human (including transmission
+ and health system events) but not beyond that. If this attribute is
+ not given, the simulated human is a member until death or some other
+ option triggers removal.
+
+ Input is rounded to the nearest time step.
+
+ name:Remove from sub-population after;units:Years;min:0;
-
+
- Descriptions of the effects of non human hosts interventions with per-species effects.
+ This can be combined with MDA to achieve mass screen and treat (MSAT)
+ or other types of mass screening intervention.
+
+ When deployed to a host, this simulates a test of patent malaria
+ (microscopy, RDT or some such), then triggers deployment of whichever
+ intervention components are configured (deployments for both positive
+ and negative test outcomes can be configured).
+
+ The use of the screening itself is reported (if enabled), but not the
+ outcome. Deployment of interventions triggered by the screening may
+ be reported, however.
+ name:(Mass) screening;
-
-
-
- Reduction in the availability rate, αi. For example a value of 0 will result in no change; a value of 0.2 will reduce the availability to 0.8 of its initial value; and a value of 1 will set the availability to 0;
-
-
-
-
- units:dimensionless;min:-1;max:inf;name:Initial proportion increase
-
-
-
-
-
-
- Reduction in the pre-prandial survival probability, PBi. For example a value of 0 will result in no change; a value of 0.2 will reduce PBi to 0.8 of its initial value; and a value of 1 will set PBi to 0;
-
-
-
-
- units:dimensionless;min:-1;max:inf;name:Initial proportion increase
-
-
-
-
-
-
- Reduction in the post-prandial survival probability, PCi. For example a value of 0 will result in no change; a value of 0.2 will reduce PCi to 0.8 of its initial value; and a value of 1 will set PCi to 0;
-
-
-
-
- units:dimensionless;min:-1;max:inf;name:Initial proportion increase
-
-
-
-
-
-
- Reduction in the survival probability of the resting period, PDi. For example a value of 0 will result in no change; a value of 0.2 will reduce PDi to 0.8 of its initial value; and a value of 1 will set PDi to 0;
-
-
-
-
- units:dimensionless;min:-1;max:inf;name:Initial proportion increase
-
-
+
+
+
+
+
+
+
+ Name of a parameterised diagnostic (see scenario/diagnostics).
+
+ name:Name of diagnostic;
+
+
+
+
+
+
+ An intervention which may have various effects on the vector populations as a whole. (Not host specific.)
+
+ Multiple instances of this intervention class are allowed (multiple parameterisations, not just deployments).
+
+ Each instance may have multiple deployments. In this case the effects of each instance
+ are independent (effects are combined) but the effects of multiple deployments of a single
+ instance are not independent (only the latest deployment has any effect).
+
+ units:List of elements;name:Vector population intervention;
+
+
+
+
+
+
+
-
+
- Reduction in the number of fertile eggs laid by a mosquito after biting this type of host, relative to an unprotected human. For example a value of 0 will result in no change; a value of 0.2 will reduce the fecundity factor to 0.8 of its initial value; and a value of 1 will set the fecundity factor to 0;
+
+ List of timed vector population intervention deployment
+
+ name:Vector population intervention deployment;
-
-
-
- units:dimensionless;min:-1;max:inf;name:Initial proportion increase
-
-
-
-
-
+
+
- Name of the species/subspecies/variant.
+ Name of intervention (e.g. larviciding, sugar bait).
- name:Species/subspecies/variant name
+ name:Name of intervention;
-
+
- Describes a new non-human hosts that have not been described in the <entomology> <vector> <anopheles> <nonHumanHosts>.
+
+ Parameters and deployment of one type of trap. In case multiple types
+ of trap are needed simultaneously, multiple elements can be used. Note
+ that different types of trap do not interact except that all will
+ attract mosquitoes.
+
+ name:Vector trap intervetion;
-
+
+
+
+ Parameters associated with a vector trap intervention, per
+ mosquito species.
+
+ name:Description;
+
-
+
+
+
+ Describes the availiability of a trap to a
+ host-seeking mosquito relative to an average
+ unprotected adult.
+
+ I.e. if this parameter is 2, then each trap will on
+ average attract twice as many mosquitoes as
+ unprotected adults.
+
+ This is the initial availability; it may decay
+ towards zero depending on the configured
+ decay function.
+
+ units:Proportion;name:Initial relative availability;min:0;max:inf;
+
+
+
+
+
+ Describes how availability decays to zero.
+
+ If decay heterogeneity/variance is used, there will be a
+ sample once-per-deployment (i.e. all traps of the same
+ deployment will be affected the same way). There is no
+ support for variances between traps (except in this crude
+ way, between deployments).
+
+ name:Decay of availability;
+
+
+
+
+
+ Name of the species/subspecies/variant.
+
+ name:Species/subspecies/variant name
+
+
@@ -4485,6 +4145,19 @@ restingKillingEffect: Reduction in the survival probability of the resting perio
+
+
+
+ The number of traps deployed, by this
+ deployment, per adult human.
+
+ E.g. if there are currently 100 traps and 1000
+ humans, then a ratio of 0.1 will increase the
+ number of traps to 200.
+
+ name:Ratio to humans;unit:dimensionless;min:0;max:inf;
+
+
@@ -4508,1172 +4181,1499 @@ restingKillingEffect: Reduction in the survival probability of the resting perio
-
-
-
- Name of intervention (e.g. larviciding, sugar bait).
-
- name:Name of intervention;
-
-
-
-
-
- Descriptions of the effects of new non human hosts with per-species effects.
-
-
-
-
-
-
- Relative availability of the population of non-human hosts of
- type i to other non-human hosts; the sum of this across all
- non-human hosts must be 1.
-
- units:Proportion; name:Relative availability of non-human host (ξ_i);
-
-
-
-
- Probability of mosquito successfully biting host
- units:Proportion;name:Probability of mosquito successfully biting host;
-
-
-
-
- Probability that the mosquito escapes host and finds a resting place after biting
- units:Proportion;name:Probability that the mosquito escapes host and finds a resting place after biting;
-
-
-
-
- Probability of mosquito successfully resting after finding a resting site
- units:Proportion;name:Probability of mosquito successfully resting after finding a resting site;
-
-
-
-
- Multiplicative factor for the number of fertile eggs laid by a mosquito after biting this type of host, relative to an unprotected human.
- units:Proportion;name:Probability of mosquito successfully resting after finding a resting site;
-
-
-
-
-
-
- Name of the species/subspecies/variant.
-
- name:Species/subspecies/variant name
-
-
-
-
-
-
- Specifies the mapping from genotype to phenotype. For each drug
- type, if only one phenotype is present, restrictions need not be
- specified, but otherwise restrictions must be specified.
-
- The set of loci affecting phenotypes of this drug's action must be
- fixed for any drug type. Each phenotype must list, for each of
- these loci, a restriction to one or more alleles under the locus.
-
- name:Restrict phenotype applicability to certain alleles;
-
-
-
-
- A locus under which only a restricted set of alleles map to
- this phenotype.
-
- name:Locus relevant to the mapping of alleles to this phenotype;
-
-
-
-
-
- One allele of a locus upon which phenotype choice depends.
- If multiple alleles under this locus should map to the same
- phenotype, repeat the whole "restriction onLocus..." element.
-
- name:Alleles mapping to this phenotype;
-
-
-
-
-
-
-
-
-
- Mean efficacy values before decay (see efficacyB and decay parameter
- descriptions for sampling and decay). The i-th value in this list
- is used for the efficacy of the vaccine after the i-th dose. Where
- more doses are given than there are values in this list, the last
- value is repeated.
-
- units:dimensionless;min:0;max:1;name:Initial mean efficacy;
-
-
-
-
-
-
- Name of the phenotype; for documentation use only.
-
- name:Name of phenotype;
-
-
-
-
-
-
-
-
- A library of drug related data for the PK/PD model.
-
- name:Pharmacology library;
-
-
-
-
-
- A library of drug deployment schedules and dosages.
-
- name:Treatments library;
-
-
-
-
-
-
-
-
-
-
-
- A library of drug PK/PD data.
-
- name:Drug library;
-
-
-
-
-
-
-
-
+
+
+
+ Optional name for this type of trap
+
+ name:Descriptive name for type of trap;
+
+
-
-
-
-
-
- A schedule for the administration of drugs in a course of treatment.
-
- Note that dose sizes are multiplied by some multiplier (see dosages)
- and the times of all doses may be delayed.
-
- name:Schedule of doses taken as a course of treatment;
-
-
-
-
-
+
+
- Name for referring to this deployment schedule
+ Time at which this deployment occurs.
+
+ See doc on intervention period and on monitoring/startDate for
+ details of how times work. Can be specified in steps, days,
+ years, or as a date (examples: 15t, 75d, 0.2y, 2000-03-16).
- name:Name;
+ name:Time;units:User defined (defauls to steps);min:0;
-
-
+
+
- Abbreviated name of drug compound
+ Proportion of otherwise eligible individuals who will receive this
+ deployment.
- name:drug;
+ units:dimensionless;min:0;max:1;name:Coverage;
-
+
- Quantity of drug compound in mg per *something*. A separate dosage
- table must be used when medicating, which may specify multipliers of
- this number based on patient age or weight.
+ Applies to vaccines only: vaccine doses are only deployed by this
+ deployment if the previous number of doses (for the component
+ deployed) is at least this number.
+
+ For example, if this is the second deployment opportunity for this
+ vaccine and this value is 1, then this deployment cannot deploy the
+ vaccine to individuals who did not receive the first deployment.
- units:mg per something;name:Drug dose (mg with multiplier);
+ name:Vaccine min previous doses;units:inoculations;min:0;
-
+
- Number of hours past start of timestep this drug dose is administered
- at (first dose should be at hour 0).
-
- units:Hours;min:0;name:Time of administration;
+ Applies to vaccines only: vaccine doses are only deployed by this
+ deployment if the previous number of doses (for the component
+ deployed) is less than this number.
+
+ name:Vaccine max cumulative doses;units:inoculations;min:0;
+
+
+
+
+
+ Minimum ento availability percentile.
+
+ This option is meant to be used with heterogeneity of availability, which can be specified in the entomology section. Without heterogenity (default), all hosts have the same availability and this option will have no effect.
+
+ The percentile must be an integer value between 0 and 100. Percentile 99th represents individuals who are more available than 99% of the population. Percentile 0 represents the least available individuals. 100 is equivalent for infinity.
+
+ units:percent;min:0;name:Minimum ento availability;
+
+
+
+
+
+ Maximum ento availability percentile.
+
+ This option is meant to be used with heterogeneity of availability, which can be specified in the entomology section. Without heterogenity (default), all hosts have the same availability and this option will have no effect.
+
+ The percentile must be an integer value between 0 and 100. Percentile 99th represents individuals who are more available than 99% of the population. Percentile 0 represents the least available individuals. 100 is equivalent for infinity.
+ units:percent;min:0;name:Maximum ento availability;
-
-
-
- A table for selecting a dose size. There are several ways this can
- work: using the patient's age or body mass in a look-up table to get a
- multplier, or directly using body mass as the multiplier.
-
- The doses specified in "mg" in the treatment schedule are then
- multiplied by this multiplier.
-
- name:Dosage table;
-
+
+
+
+
+
+
+ Time at which this deployment occurs.
+
+ See doc on intervention period and on monitoring/startDate for
+ details of how times work. Can be specified in steps, days,
+ years, or as a date (examples: 15t, 75d, 0.2y, 2000-03-16).
+
+ name:Time;units:User defined (defauls to steps);min:0;
+
+
+
+
+
+ Maximum age of eligible individuals (defaults to no limit).
+
+ Input is rounded to the nearest time step.
+
+ units:Years;min:0;name:Maximum age of eligible individuals;
+
+
+
+
+
+ Minimum age of eligible individuals (defaults to 0).
+
+ Input is rounded to the nearest time step.
+
+ units:Years;min:0;name:Minimum age of eligible individuals;
+
+
+
+
+ See repeatEnd's documentation.
+ name:Step of repetition;units:User defined;
+
+
+
+
+
+ Either both repeatStep and repeatEnd should be present
+ or neither. If present, the deployment is repeated every
+ repeatStep timesteps (i.e. if t0 is the initial time
+ and x is repeatStep, depolyments are done at times t0,
+ t0+x, t0+2*x, ...), ending before repeatEnd
+ (final repetition is the one before repeatEnd).
+
+ Note that repeatEnd may be specified as a date but
+ repeatStep must be a duration (days, steps or years).
+
+ name:End of repetition (exclusive);units:User defined;
+
+
+
+
+
+
-
-
+
+
+
+
+
+
+
+
+
- Select dose multiplier from a look-up table using the patient's age.
+ Target age of intervention.
+
+ Input is rounded to the nearest time step.
- name:Look-up table (age);
+ units:Years;min:0;max:100;name:Target age;
-
-
+
+
- Select dose multiplier from a look-up table using the patient's body mass.
+ First time at which this deployment is active. If not specified,
+ deployment starts at the beginning of the intervention period.
+
+ See doc on intervention period and on monitoring/startDate for
+ details of how times work. Can be specified in steps, days,
+ years, or as a date (examples: 15t, 75d, 0.2y, 2000-03-16).
- name:Look-up table (weight);
+ name:First time active;units:User defined (defauls to steps);
-
-
+
+
- Multiply the dose by some quantity, such as patient weight.
+ End of the period during which the intervention is active (to be
+ exact, the first step of the intervention period at which the
+ item becomes inactive). If not specified, deployment never
+ ceases after starting during the simulation.
+
+ See doc on intervention period and on monitoring/startDate for
+ details of how times work. Can be specified in steps, days,
+ years, or as a date (examples: 15t, 75d, 0.2y, 2000-03-16).
- name:Multiply dose;
+ units:User defined (defauls to steps);name:End step;
-
-
-
-
- Quantity to multiply the dose by. Only option is "kg"
- (patient weight in kg).
-
- name:By what?;
-
-
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ If this element is not specified, standard deployment occurs, where
+ a portion of the population as given by the coverage property of this
+ campaign is selected, and interventions are deployed to all of
+ these people (regardless of previous coverage).
+
+ If this attribute is specified, instead, the population is divided
+ into two sets: those who are a member of a certain sub-population and
+ those who are not (see "subPopRemoval" element).
+ If the proportion of people in the
+ first set is less than the desired coverage, then the proportion of
+ people from the second set needed to increase total coverage to the
+ desired coverage is calculated. This proportion is then used as the
+ probablity of selection from the second set into a third set of
+ people who then receive all interventions deployed by this campaign.
+
+ Note that selection is stochastic so the final coverage level may not
+ be exactly that desired. Note also that the component used when
+ selecting people need not actually be one of the components deployed
+ by this intervention, although that is the intended use case.
+
+ name:Cumulative coverage;
+
+
+
+
+
+ The identifier (short name) of the component used when
+ selecting people.
+
+ name:Component identifier;
+
+
+
+
+
+
-
-
-
- Name for referring to this dosage table
-
- name:Name;
-
-
-
+
- A look-up table which uses patient age (in years) or weight (in kg) to
- find a multiplier.
+ If this element is specified, deployment is restricted to some
+ sub-population (specified via the "id" attribute); otherwise the
+ target population is the entire simulated population. Either way, other
+ deployment restrictions (age, time, number of vaccine doeses) still
+ apply.
- name:Age/weight range;
+ name:Restrict to sub-population;
-
+
- name:Lower bound (inclusive);min:0;units:years or kg;
+
+ The identifier (short name) of the sub-population (i.e. the "id" of
+ some intervention component). Also see the "complement" attribute.
+
+ name:Sub-population identifier;
-
+
- The dose size given in the schedule (in "mg") is multiplied by
- this value for patients falling into this range when this
- dosage table is used.
+ If this is not specified or is false, deployment is restricted to the
+ sub-population of people protected by the intervention component
+ who's id is given. If complement is set to true, deployment is
+ instead restricted to the complement of that sub-population, i.e. to
+ those not protected by the intervention component.
- name:Dose multiplier;min:0;
+ name:Complement;
-
-
+
-
- A drug description with PK/PD parameters.
-
- name:Drug parameters;
+ Description of a vaccine's effect
+ name:Vaccine descriptions;
-
+
+
+
+ Specification of decay of efficacy. Documentation: see DecayFunction type
+ or https://github.com/SwissTPH/openmalaria/wiki/ModelDecayFunctions
+
+ name:Decay of effect;
+
+
+
+
+
+ Measure of variation in vaccine efficacy: efficacy is sampled from
+ a beta distribution with efficacyB its beta parameter and its alpha
+ parameter fixed such that the mean is that given by initialEfficacy.
+
+ units:Positive real;min:0.001;max:1.00E+06;name:Variance parameter for vaccine efficacy;
+
+
+
+
+
+ Mean efficacy values before decay (see efficacyB and decay parameter
+ descriptions for sampling and decay). The i-th value in this list
+ is used for the efficacy of the vaccine after the i-th dose. Where
+ more doses are given than there are values in this list, the last
+ value is repeated.
+
+ units:dimensionless;min:0;max:1;name:Initial mean efficacy;
+
+
+
+
+
+ Pharmaco-Dynamic parameters for some resistance phenotype.
+
+ To model resistance to this drug, describe multiple infection
+ phenotypes (with respect to these PD parameters) and list one
+ or more "restrict" elements for each phenotype.
+
+ Loci are specified elsewhere. Multiple loci may influence the
+ action of a single drug and each locus may influence multiple
+ drugs.
+
+ name:PD parameters for some allele / resistance phenotype;
+
+
+
+
+
+
+ name:Description
+
+
+
+
+
+ Usage of nets by humans, from 0 to 1.
+
+ At the moment this is constant across humans and deterministic:
+ relative attractiveness and survival factors are
+ base*(1-usage*propActing) + intervention_factor*usage*propActing.
+
+ See also "propActing" (proportion of bits for which net acts).
+
+ units:dimensionless;min:0;max:1;name:Proportion of time nets are used by humans;
+
+
+
+
+
+ The rate at which new holes are made in nets.
+
+ nHoles(t) = nHoles(t-1) + X where X~Pois(R/T) where T is the number
+ of time-steps per year. R is sampled from
+ log-normal: R ~ log N( log(mean)-sigma²/2, sigma² ) and is covariant
+ with ripRate and insecticideDecay. (To be exact, a single Gaussian
+ sample is taken, adjusted for each sigma then exponentiated.)
+
+ units:Holes per annum;min:0;name:Rate at which holes are made;
+
+
+
+
+
+ Each existing hole has a probability of being ripped bigger according
+ to a Poisson process with this rate as (only) parameter.
+
+ New rips occur in a net at rate X~Pois(h×R/T) where h is the number
+ of existing holes and T the number of time-steps per year. R is
+ sampled from log-normal: R ~ log N( log(mean)-sigma²/2, sigma² )
+ and is covariant with holeRate and insecticideDecay. (To be exact, a
+ single Gaussian sample is taken, adjusted for the each and sigma
+ then exponentiated.)
+
+ units:Rips per existing hole per annum;min:0;name:Rate at which holes are enlarged;
+
+
+
+
+
+ This factor expresses how important rips are in increasing the hole.
+
+ The hole index of a net is h + F×x where h and x are the total numbers
+ of holes and rips respectively and F is the rip factor.
+
+ units:none;min:0;name:Rip factor;
+
+
+
+
+
+ The insecticide concentration of new nets is Gaussian distributed with
+ mean "mu" and a standard deviation "sigma". The standard deviation
+ should be small relative to the mean to avoid negative initial
+ concentration. Any negative values sampled are set to 0.
+
+ units:mg/m²;min:0;name:Initial insecticide;
+
+
+
+
+
+ Decay curve for insecticide content of nets. Documentation: see DecayFunction
+ type or https://github.com/SwissTPH/openmalaria/wiki/ModelDecayFunctions
+
+ The distribution of decay rates over nets is covariant with the
+ distribution of ripRate and holeRate over nets. This distribution is
+ generated by taking one sample per net from a Gaussian distribution
+ with mean 0 and standard deviation 1. For each variable, the sample
+ is multiplied by the respective sigma and a constant added such that,
+ once exponentiated, the mean of the variable over nets is 1. The
+ variable is then exponentiated and multiplied by the required mean
+ rate for the respective variable.
+
+ units:none;name:Decay of insecticide;
+
+
+
+
+
+ Specifies the rate at which nets are disposed of over time.
+ Documentation: see DecayFunction type or
+ https://github.com/SwissTPH/openmalaria/wiki/ModelDecayFunctions
+
+ In the current model, nets are disposed of randomly (no correlation
+ with state of decay) such that the chance of each net surviving until
+ age t is the value of this decay function at time t. Equivalently
+ (where a large number of nets are distributed at the same time), the
+ proportion of nets remaining in use should match this decay function
+ over time.
+
+ Humans are removed from the intervention component's sub-population
+ on disposal (attrition) of their nets. Currently this event is not
+ reported.
+
+ units:dimensionless;name:Attrition of nets;
+
+
+
-
+
- Pharmaco-Dynamic parameters for some resistance phenotype.
+ Used by logit attacking and killing models only, holeIndexMax
+ is a user defined maximum hole index (typically, the total surface area of a net).
+
+ units:in same unit as holeIndex;name:maximum of holed surface area that has an effect (comparable to no net)
+
+
+
+
+
+
+ Effect of net on attractiveness of humans to mosquitoes relative to
+ an unprotected adult human. Parameterisations should take into
+ account that mosquitoes do not always bite indoors.
+
+ Attractiveness of the human is multiplied by
+ exp(log(H)×h + log(P)×p + log(I)×h×p
+ where H, P and I are the hole, insecticide and interaction factors
+ respectively, h=exp(-holeIndex×holeScalingFactor) and
+ p=1−exp(-insecticideContent×insecticideScalingFactor).
+
+ units:dimensionless;min:0;max:1;name:Relative attractiveness;
+
+
+
+
+
+ Effect of net on attractiveness of humans to mosquitoes relative to
+ an unprotected adult human. Parameterisations should take into
+ account that mosquitoes do not always bite indoors.
- To model resistance to this drug, describe multiple infection
- phenotypes (with respect to these PD parameters) and list one
- or more "restrict" elements for each phenotype.
+ This deterrency model multiplies human attractiveness by
+ pEnt×pAtt.
+
+ units:dimensionless;name:Relative attractiveness;
+
+
+
+
+
+
+
+ pEnt represents the relative probability of entering due to
+ ITNs: pEnt = exp(log(P)×p) where P is the insecticide
+ factor and
+ p=1−exp(-insecticideContent×insecticideScalingFactor).
+
+ units:dimensionless;name:Deterrency: entering;
+
+
+
+
+
+ pEnt represents the relative probability of entering due to insecticide
+ in the hut:
+ pEnt = exp(logit.pEnt) / (exp(logit.pEnt) + 1)
+ logit.pEnt = B + P * p
+ where B is the basefactor (without net); P is insecticide factor, and
+ p = log(insecticideContent+1).
+ Without a net, probability of entering a house is
+ pEnt0 = exp(logit.pEnt0) / (exp(logit.pEnt0) + 1)
+ logit.pEnt0 = B
+ Entering of mosquitoes is adjusted via multiplication by pEnt / pEnt0.
+ To keep this in the range [0,1], we (normally) require that
+ pEnt ≤ pEnt0
+ and thus P ≤ 0 and give a warning if this is not fulfilled.
+
+ units:dimensionless;name:Deterrency: entering (logit model);
+
+
+
+
+
+
+
+ pAtt represents the relative probability of attacking a human after
+ entering a house due to ITNs (i.e. of feeding/dying vs. flying off):
+ pAtt = B + H×h + P×p + I×h×p
+ where B is the base (without net) probability; H, P and I are the hole,
+ insecticide and interaction factors respectively,
+ h=exp(-holeIndex × holeScalingFactor)
+ and
+ p=1 - exp(-insecticideContent × insecticideScalingFactor).
+
+ units:dimensionless;name:Deterrency: attacking;
+
+
+
+
+
+ pAtt represents the relative probability of attacking a human
+ after entering a house due to ITNs (i.e. of feeding/dying vs.
+ flying off):
+ pAtt = exp(logit.pAtt) / (exp(logit.pAtt) + 1)
+ logit.pAtt = B + H×min(h, hMax) + P×p + I×min(h, hMax)×p
+ where B is the base factor (without net); H, P and
+ I are the hole, insecticide and interaction factors
+ respectively, and:
+ h = log(holeIndex + 1)
+ p = log(insecticideContent + 1)
+ Without a net, probability of attacking a human
+ after entering a house is
+ pAtt0 = exp(logit.pAtt0) / (exp(logit.pAtt0) + 1)
+ logit.pAtt0 = B + H×hMax
+ where hMax=log(holeIndexMax + 1) and holeIndexMax is a user defined
+ maximum hole index (typically, the total surface area of a net).
+ Attacking of mosquitoes is adjusted via multiplication by pAtt / pAtt0.
+ This may be larger and smaller than 1 (but will not be negative).
+ By definition (through the logit transformation) pAtt0 > 0.
+
+ units:dimensionless;name:Deterrency: attacking (logit model);
+
+
+
+
+
+
+
+
+
+
+
+ Effect of net on survival mosquitoes as they seek to bite a human
+ after choosing that human, relative to the same person not
+ sleeping under a net. Parameterisations should take into
+ account that mosquitoes do not always bite indoors.
- Loci are specified elsewhere. Multiple loci may influence the
- action of a single drug and each locus may influence multiple
- drugs.
+ Killing proportion is calculated as K = B + H×h + P×p + I×h×p
+ where B is the base (without net) probability of death,
+ H, P and I are the hole, insecticide and interaction factors
+ respectively, h=exp(-holeIndex×holeScalingFactor) and
+ p=1−exp(-insecticideContent×insecticideScalingFactor).
+
+ Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−B).
+ To keep this in the range [0,1], we require that B+H ≤ 1, B+P ≤ 1,
+ B+H+P+I ≤ 1, H ≥ 0, P ≥ 0 and H+P+I ≥ 0.
+
+ units:dimensionless;min:0;max:1;name:Pre-prandial killing effect;
+
+
+
+
+
+ Effect of net on survival mosquitoes as they seek to bite a human
+ after choosing that human, relative to the same person not
+ sleeping under a net.
+ Killing proportion is calculated as
+ K=exp(logit.K)/(exp(logit.K)+1)
+ logit.K = B + H×min(h,hMax) + P×p + I×min(h,hMax)×p
+ where B is the basefactor (without net),
+ H, P and I are the hole, insecticide and interaction factors
+ respectively, h=log(holeIndex+1) and
+ p=log(insecticideContent+1).
+ Without a net, the killing proportion
+ K0=exp(logit.K0)/(exp(logit.K0)+1)
+ logit.K0 = B + H×hMax
+ where hMax=log(holeIndexMax+1) and holeIndexMax is a user defined maximum hole index (typically, the total surface area of a net).
+ Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−K0).
+ To keep this in the range [0,1], we require that K ≥ K0. We enforce that P ≥ 0 (It would not make sense biologically if P were negative) and P+I*hMax ≥ 0 and H ≤ 0 and holeIndex ≤ holeIndexMax and give a warning if these conditions are not fulfilled.
+
+ units:dimensionless;min:0;max:1;name:Pre-prandial killing effect (logit);
+
+
+
+
+
+
+
+ Effect of net on survival mosquitoes as they seek to escape from
+ a human host and rest after a blood meal, relative to the same
+ person not sleeping under a net. Parameterisations should take
+ into account that mosquitoes do not always bite indoors.
+
+ Killing proportion is calculated as K = B + H×h + P×p + I×h×p
+ where B is the base (without net) probability of death,
+ H, P and I are the hole, insecticide and interaction factors
+ respectively, h=exp(-holeIndex×holeScalingFactor) and
+ p=1−exp(-insecticideContent×insecticideScalingFactor).
+
+ Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−B).
+ To keep this in the range [0,1], we require that B+H ≤ 1, B+P ≤ 1,
+ B+H+P+I ≤ 1, H ≥ 0, P ≥ 0 and H+P+I ≥ 0.
+
+ units:dimensionless;min:0;max:1;name:Post-prandial killing effect;
+
+
+
+
+
+ Effect of net on survival mosquitoes as they seek to escape from
+ a human host and rest after a blood meal, relative to the same
+ person not sleeping under a net.
+ Killing proportion is calculated as
+ K=exp(logit.K)/(exp(logit.K)+1)
+ logit.K = B + H×min(h,hMax) + P×p + I×min(h,hMax)×p
+ where B is the basefactor (without net),
+ H, P and I are the hole, insecticide and interaction factors
+ respectively, h=log(holeIndex+1) and
+ p=log(insecticideContent+1).
+ Without a net, the killing proportion
+ K0=exp(logit.K0)/(exp(logit.K0)+1)
+ logit.K0 = B + H×hMax
+ where hMax=log(holeIndexMax+1) and holeIndexMax is a user defined maximum hole index (typically, the total surface area of a net).
+ Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−K0).
+ To keep this in the range [0,1], we require that K ≥ K0. We enforce that P ≥ 0 (It would not make sense biologically if P were negative) and P+I*hMax ≥ 0 and H ≤ 0 and holeIndex ≤ holeIndexMax and give a warning if these conditions are not fulfilled.
- name:PD parameters for some allele / resistance phenotype;
-
-
+ units:dimensionless;min:0;max:1;name:Post-prandial killing effect (logit);
+
+
+
+
+
+
+
+ Effect of net on fertility of mosquitoes who survive feeding
+ on a protected human, relative to an unprotected human.
+
+ Fertility (number of eggs laid) is multiplied by (1-K) / (1-B),
+ similar to killing effects. This is not allowed to be greater than 1.
+
+ name:Fecundity reduction;
+
+
+
+
+
+ Effect of net on fertility of mosquitoes who survive feeding
+ on a protected human, relative to an unprotected human.
+
+ Fertility (number of eggs laid) is multiplied by (1-K) / (1-K0),
+ similar to killing effects. This is not allowed to be greater than 1.
+
+ name:Fecundity reduction (logit);
+
+
+
-
+
- Optional; if present specifies the locus corresponding to this
- drug's PD phenotypes: each phenotype must then match one of
- that locus's alleles. Otherwise the drug should specify only
- one phenotype.
-
- There is currently a one-to-many correspondance between loci
- and drugs.
+ Name of the affected anopheles-mosquito species.
- name:Locus;
+ name:Mosquito species;
+
+
+
+
+
+ Deprecated: propActive can still be used but its value must be set to either 0 or 1.
+ Any other value will result in an error at initialization.
+
+ The proportion of bites, when nets are in use, for which the net
+ has any action whatsoever on the mosquito.
+
+ At the moment this is constant across humans and deterministic:
+ relative attractiveness and survival factors are
+ base*(1-usage*propActing) + intervention_factor*usage*propActing.
+
+ See also "usage" (proportion of time nets are used by humans).
+
+ units:dimensionless;min:0;max:1;name:Proportion of bites for which net acts;
-
+
+
+
+
+
+
+
+ Usage of Generic vector interventions, from 0 to 1.
+
+ units:dimensionless;min:0;max:1;name:Proportion of generic vector interventions;
+
+
+
+
+
+ Description of decay of all intervention effects.
+ Documentation: see DecayFunction type or
+ https://github.com/SwissTPH/openmalaria/wiki/ModelDecayFunctions
+
+ name:Decay;
+
+
+
+
+ name:Per-mosquito species parameters;
+
-
-
-
- Concentration below which drug's effects are deemed negligible and can
- be removed from simulation.
-
- units:mg/l;min:0;name:Drug concentration considered negligible;
-
-
-
-
-
-
- Used to calculate elimination rate λ, calculated as
- λ = ln(2) / half_life. The basic form of decay is
- C(t) = C0 * exp(-λ*t).
-
- Alternatively, elimination rate can be specified via k
- and m_exponent.
-
- units:days;min:0;name:drug half-life;
-
-
-
-
-
-
- Constant used to calculate the elimination rate λ, which
- is calculated as λ = k / (body_mass ^ m_exponent), where
- body_mass is the patient's weight in kg and m_exponent is
- the next parameter. The basic form of decay is
- C(t) = C0 * exp(-λ*t).
-
- If CV > 0, k is sampled per-human from the log-normal
- distribution: ln N( ln(mean) - σ^2 / 2, σ^2).
-
- Alternatively, elimination rate can be specified via half_life.
-
- units:day^-1;min:0;name:Constant associated with elimination rate (k);
-
-
-
-
-
- Constant used to calculate the elimination rate λ, which
- is calculated as λ = k / (body_mass ^ m_exponent), where
- body_mass is the patient's weight in kg and k is the
- previous parameter. The basic form of decay is
- C(t) = C0 * exp(-λ*t).
-
- Alternatively, elimination rate can be specified via half_life.
-
- Note that in the case of a conversion model, this applies
- to *both* the elimination and the conversion rates.
-
- units:day^-1;min:0;name:Constant associated with elimination rate (m_exponent);
-
-
-
-
-
-
-
- Absorption rate parameter. Not allowed for one compartment
- models, but required for two and three compartment models and
- one compartment with conversion model (for the parent drug
- only).
-
- name:Absorption rate constant (k_a);min:0;
-
-
-
+
- Configures the parent drug in a conversion model.
-
- To use a conversion model, the parent drug should have this
- section defined as well as half-life or k (direct
- elimination; this may be zero) and k_a (absorption rate;
- this may be large).
-
- The metabolite drug should define half-life or k (elimination
- of metabolite), but not k_a (absorption rate) or this section
- (conversion). It is not possible for the metabolite to itself
- undergo conversion with the current models.
+ Effect of intervention on attractiveness of humans to mosquitoes relative to
+ an unprotected adult human. Parameterisations should take into
+ account that mosquitoes do not always bite indoors.
+
+ Attractiveness of the human is multiplied this factor times
+ survival of effect.
- name:Conversion parameters (parent drug);
-
-
-
-
-
-
- The abbreviation of the metabolite drug (e.g. "DHA" or
- "DHA_AR").
-
- name:Metabolite drug (abbreviation);
-
-
-
-
-
- Rate of conversion of parent drug to metabolite.
-
- name:Rate of conversion;unit:Per day;
-
-
-
-
-
- Ratio of molecular weights: molecular weight of the
- metabolite divided by molecular weight of the parent.
-
- name:Molecular weight ratio;unit:unitless;
-
-
-
-
-
- The IC50 values of parent and metabolite drugs may be
- sampled from the log-normal distribution (if CV is greater than 0).
- This parameter controls correlation between these samples,
- measured in log-space.
-
- If this value is 1, samples are fully correlated: a single z-score is
- used to calculate both samples. If this is 0, two independent
- samples are used.
-
- Values between 0 and 1 (partial correlation) are supported;
- in this case IC50 values are sampled such that
- cor(log(x), log(y)) matches this value (where x, y are parent and
- metabolite IC50 values).
-
- name:IC50 log correlation;min:0;max:1;
-
-
-
-
-
-
-
-
- Volume of Distribution.
-
- If CV > 0 this is sampled from a log-normal distribution.
-
- units:l/kg;min:0;name:Volume of Distribution (Vd);
+ units:dimensionless;min:0;max:1;name:Relative attractiveness
-
+
- Optional element specifying conversion parameters to- and
- from- a second compartment.
+ Effect of intervention on survival of mosquitoes as they seek to bite a human
+ after choosing that human, relative to the same person not
+ protected by the intervention. Parameterisations should take into account
+ that mosquitoes do not always bite indoors. This parameter has
+ been added since some data shows IRS to have a preprandial
+ killing effect.
+
+ Killing proportion is this factor multiplied by survival of effect.
- name:Second compartment parameters;
+ units:dimensionless;min:0;max:1;name:Pre-prandial killing effect
-
-
-
-
-
- Absorption rate from the central compartment to the
- first periphery compartment (2).
-
- It is sampled per-patient when CV > 0.
-
- units:day^-1;min:0;name:Absorption rate to compartment 2 (k12);
-
-
-
-
-
- Absorption rate from the first periphery compartment
- (2) to the central compartment.
-
- It is sampled per-patient when CV > 0.
-
- units:day^-1;min:0;name:Absorption rate from compartment 2 (k21);
-
-
-
-
-
+
- Optional element specifying conversion parameters to- and
- from- a third compartment.
-
- name:Third compartment parameters;
-
-
-
-
-
-
- Absorption rate from the central compartment to the
- second periphery compartment (3).
-
- It is sampled per-patient when CV > 0.
-
- units:day^-1;min:0;name:Absorption rate to compartment 3 (k13);
-
-
-
-
-
- Absorption rate from the second periphery compartment
- (3) to the central compartment.
-
- It is sampled per-patient when CV > 0.
-
- units:day^-1;min:0;name:Absorption rate from compartment 3 (k31);
-
-
-
-
+ Effect of intervention on survival of mosquitoes as they seek to escape from
+ a human host and rest after a blood meal, relative to the same
+ person not protected by the intervention. Parameterisations should take
+ into account that mosquitoes do not always bite indoors.
+
+ Killing proportion is this factor multiplied by survival of effect.
+
+ units:dimensionless;min:0;max:1;name:Post-prandial killing effect
+
+
+
+
+
+ Effect of intervention on fertility mosquitoes after successfully feeding on
+ a human host, relative to an unproteced human. Parameterisations should take
+ into account that mosquitoes do not always bite indoors.
+
+ Fertility is multiplied by 1 - (fecundityReduction * decay).
+
+ min:0;name:Fecundity reduction effect
+
-
-
-
-
-
-
-
-
-
-
- Specifies the mapping from genotype to phenotype. For each drug
- type, if only one phenotype is present, restrictions need not be
- specified, but otherwise restrictions must be specified.
-
- The set of loci affecting phenotypes of this drug's action must be
- fixed for any drug type. Each phenotype must list, for each of
- these loci, a restriction to one or more alleles under the locus.
-
- name:Restrict phenotype applicability to certain alleles;
-
-
-
+
- A locus under which only a restricted set of alleles map to
- this phenotype.
+ Name of the affected anopheles-mosquito species.
- name:Locus relevant to the mapping of alleles to this phenotype;
+ name:Mosquito species
-
+
- One allele of a locus upon which phenotype choice depends.
- If multiple alleles under this locus should map to the same
- phenotype, repeat the whole "restriction onLocus..." element.
-
- name:Alleles mapping to this phenotype;
+ The proportion of bites for which the IRS
+ has any action whatsoever on the mosquito.
+
+ At the moment this is constant across humans and deterministic:
+ relative attractiveness and survival factors are
+ base*(1-propActing) + intervention_factor*propActing.
+
+ units:dimensionless;min:0;max:1;name:Proportion of bites for which IRS acts;
-
+
+
+
+
+
+ Description of effect for the more complex and probably more realistic
+ Briet model: IRS has three effects, whos strength is calculated as a
+ function of surviving insecticide content.
+
+ name:Description (based on decay of insecticide);
+
+
+
- k1 — Maximal parasite killing rate.
-
- units:1/days;min:0;name:Maximal parasite killing rate;
+ Usage of Indoor residual spraying (IRS) interventions, from 0 to 1.
+
+ units:dimensionless;min:0;max:1;name:Proportion of Indoor residual spraying (IRS) interventions;
-
+
- Half maximal effect concentration.
-
- If CV > 0, the IC50 is sampled from a log-normal distribution.
-
- units:mg/l;min:0;name:IC50;
+ The insecticide concentration of IRS (at time of spraying) is
+ Gaussian distributed with mean "mu" and a standard deviation "sigma".
+ The standard deviation should be small relative to the mean to avoid
+ negative initial concentration. Any negative values sampled are set
+ to 0.
+
+ units:μg/cm²;min:0;name:Initial insecticide
-
+
- n — Slope of the concentration effect curve
-
- units:dimensionless;name:Slope of effect curve;
+ Decay curve for insecticide content of IRS. Documentation: see DecayFunction
+ type or https://github.com/SwissTPH/openmalaria/wiki/ModelDecayFunctions
+
+ units:none;name:Decay of insecticide
-
-
-
-
- Name of the phenotype; for documentation use only.
-
- name:Name of phenotype;
-
-
-
-
-
-
-
-
- The list of components deployed to eligible humans.
-
- name:Component to be deployed;
-
-
-
-
- The identifier (short name) of a component.
-
- name:Identifier;
-
-
-
-
-
-
- Lists intervention components which are deployed according to some
- external trigger (for example, screening with a negative patency
- outcome or health-system treatment).
-
- Components are referenced from one or more sub-lists. Each of these
- lists is deployed independently if and only if its age constraints are
- met by the human host and a random sample with the given probability of
- a positive outcome is positive.
-
- name:Triggered intervention deployment;
-
-
-
+
+
+ name:Per-mosquito species parameters;
+
-
-
-
-
-
- Maximum age of eligible humans (defaults to no limit).
+
+
+
+ Effect of IRS on attractiveness of humans to mosquitoes relative to
+ an unprotected adult human. Parameterisations should take into
+ account that mosquitoes do not always bite indoors.
- Input is rounded to the nearest time step.
-
- units:Years;min:0;name:Maximum age of eligible humans;
-
-
-
+ Attractiveness of the human is multiplied by exp(P×log(p))
+ where P is the insecticide factor,
+ p=1−exp(-insecticideContent×insecticideScalingFactor).
+
+ units:dimensionless;min:0;max:1;name:Relative attractiveness
+
+
+
+
+
+ Effect of IRS on survival mosquitoes as they seek to bite a human
+ after choosing that human, relative to the same person not
+ protected by IRS. Parameterisations should take into account
+ that mosquitoes do not always bite indoors. This parameter has
+ been added since some data shows IRS to have a preprandial
+ killing effect.
+
+ Killing proportion is calculated as K = B + P×p where B is the
+ base (without protection) probability of death, and P is the
+ insecticide factor,
+ p=1−exp(-insecticideContent×insecticideScalingFactor).
+
+ Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−B).
+ To keep this in the range [0,1], we require that B+P ≤ 1 and P ≥ 0.
+
+ units:dimensionless;min:0;max:1;name:Pre-prandial killing effect
+
+
+
+
+
+ Effect of IRS on survival mosquitoes as they seek to escape from
+ a human host and rest after a blood meal, relative to the same
+ person not protected by IRS. Parameterisations should take
+ into account that mosquitoes do not always bite indoors.
+
+ Killing proportion is calculated as K = B + P×p where B is the
+ base (without protection) probability of death, and P is the
+ insecticide factor,
+ p=1−exp(-insecticideContent×insecticideScalingFactor).
+
+ Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−B).
+ To keep this in the range [0,1], we require that B+P ≤ 1 and P ≥ 0.
+
+ units:dimensionless;min:0;max:1;name:Post-prandial killing effect
+
+
+
+
+
+ Effect of IRS on fertility mosquitoes after successfully feeding on
+ a human host, relative to an unproteced human. Parameterisations should take
+ into account that mosquitoes do not always bite indoors.
+
+ First, we calculate K = B + P×p where B is the
+ base (without protection) probability of death, and P is the
+ insecticide factor,
+ p=1−exp(-insecticideContent×insecticideScalingFactor).
+
+ Fecundity is multiplied by (1−K) / (1−B). It is not allowed to be greater than 1.
+ To keep this in the range [0,1], we require that B+P ≤ 1 and P ≥ 0.
+
+ name:Fecundity reduction
+
+
+
+
- Minimum age of eligible humans (defaults to 0).
-
- Input is rounded to the nearest time step.
+ Name of the affected anopheles-mosquito species.
- units:Years;min:0;name:Minimum age of eligible humans;
+ name:Mosquito species
-
+
- Probability of this list of components being deployed, given
- that other constraints are met.
-
- units:dimensionless;min:0;max:1;name:Probability of delivery to eligible humans;
+ The proportion of bites for which the IRS
+ has any action whatsoever on the mosquito.
+
+ At the moment this is constant across humans and deterministic:
+ relative attractiveness and survival factors are
+ base*(1-propActing) + intervention_factor*propActing.
+
+ units:dimensionless;min:0;max:1;name:Proportion of bites for which IRS acts;
-
-
-
-
-
-
-
+
+
- Name of an option (monitoring measure or model option).
+ Value expected to be at least 0. Negative values are not
+ necessarily invalid, but allow nets to increase transmission.
- name:Option name;
+ units:none;name:Insecticide factor;max:1
-
+
-
- Option on/off switch (true/false). Specifying value="true" is
- the same as not specifying a value; specifying value="false"
- explicitly turns the option off. If an option is not mentioned
- at all, it is left at its default value (normally off, but
- in a few cases, such as some bug-fix options, on).
-
- name:Indicator of whether option is required;
+ units:none;name:Insecticide scaling factor;min:0
-
-
-
-
-
-
-
-
- Specification of decay or survival of a parameter.
-
- name:Decay or survival of a parameter
-
-
-
-
-
+
+
- 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
+ See parent element documentation
- units:None;min:0;max:1;name:function;
+ units:none;name:Base factor;
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
+
- (Time) scale parameter of distribution: this is either the age of
- complete decay (smooth-compact, step and linear functions) or the age
- at which the parameter has decayed to half its original value
- (exponential, weibull and hill). Not used when function="constant"
- (i.e. no decay).
-
- This value can be specified in years, days or steps (e.g. 2y, 180d or
- 100t). When the unit is not specified years are assumed. The value is
- used without rounding except when sampling an age of decay, when the
- rounding happens as late as possible.
+ See parent element documentation
- units:User-defined (defaults to years);min:0;name:L;
+ units:none;name:Insecticide factor;
-
+
+
+
+
+
+
+ units:dimensionless;name:Probability of mosquito death without intervention
+
+
+
+
+
+
+
+
+
+
+
+ Value expected to be at least 0. Negative values are not
+ necessarily invalid, but allow nets to increase transmission.
+
+ units:none;name:Hole factor;max:1
+
+
+
+
+
+ holeFactor + insecticideFactor + interactionFactor must not be greater
+ than 1, and is expected to be at least 0. A negative value is not
+ necessarily invalid, but allows nets to increase transmission.
+
+ units:none;name:Interaction factor;max:1
+
+
+
+
+ units:none;name:Hole scaling factor;min:0
+
+
+
+
+
+
+
+
+
+
+ units:dimensionless;name:Probability of mosquito death without intervention
+
+
+
+
+
+
+
- Shape parameter of distribution. If not specified, default value of
- 1 is used. Meaning depends on function; not used in some cases.
+ Logit of the probability (e.g. of death, of entry, of attacking) without intervention.
- min:0;name:k;units:none;
+ units:dimensionless;name:Base factor;
-
+
- If CV is non-zero, heterogeneity of decay is introduced via a random
- variable sampled from the log-normal distribution. This distribution is
- parameterised with mean=1 and CV as given.
-
- The effective age of decay is the real age multiplied by this variable
- (for decay functions with a half-life, this is equivalent to dividing
- the half-life by the variable).
+ Coefficient of log(insecticide content+1) in a generalized linear model with logit link
+ function.
- min:0;name:Coefficient of Variation;
-
-
-
-
-
- (Boolean) If True, this tells OpenMalaria to use the complement of the
- DecayFunction defined as 1-f(x). This is useful to model increasing
- functions that will "decay" to 1. This only works if f(x) is contained
- between 0 and 1.
-
- units:User-defined (defaults to years);min:0;name:L;
+ units:none;name:Insecticide factor;
-
+
- biphasic: Efficacy between 0 and 1.
+ Coefficient of log(total holed surface area (in cm2) +1) in a generalized linear model
+ with logit link function.
+ units:none;name:Hole factor;
-
+
- biphasic: Proportion between 0 and 1, proportion of the response that is short-lived.
+ Coefficient of the interaction term of log(total holed surface area (in cm2) +1) with
+ log(insecticide content+1) in a generalized linear model with logit link function.
+
+ units:none;name:Interaction factor;
-
-
-
- biphasic: halflife of short lived component (default to years).
+
+
+
+
+ Descriptions of the effects of vector interventions with per-species effects.
+
+ units:dimensionless;min:0;max:1;name:Vector population intervention;
+
+
+
+
+
+ Describe an effect on the increase in the death rate while host
+ seeking (mu_vA) due to this intervention.
+
+ Enter the rate increase (i.e. if rate increases to 120% of normal,
+ give 0.2). New death rate while seeking is old × (1 + increase)
+ where increase is this factor given. Must have increas ≥ -1.
+
+ units:dimensionless;name:Proportional increase in deaths while host searching;
+
+
+
+
+
+
+
+ units:dimensionless;min:-1;max:inf;name:Initial proportion increase
+
+
+
+
+
+
+
+ Describe an effect of increased mortality while ovipositing
+ due to this intervention. Enter the probability of dying due to
+ this intervention.
+
+ units:dimensionless;name:Proportion ovipositing mosquitoes killed;
+
+
+
+
+
+
+
+ units:dimensionless;min:0;max:1;name:Initial probability of killing
+
+
+
+
+
+
+
+ Describe an effect on emergence of pupa into adults: this value is the
+ proportion of emerging pupa which are killed by this intervention.
+
+ This can be used as a crude way of modelling larviciding. It ca
+ also be used to increase emergence by giving a negative value.
+ The emergence rate is "old rate" × (1 - factor) where factor is the
+ value given here; thus, for example, using -1 will double emergence.
+
+ units:dimensionless;name:Proportion of emerging pupa killed;
+
+
+
+
+
+
+
+ units:dimensionless;min:-inf;max:1;name:Initial proportion reduction
+
+
+
+
+
+
+
+ Describe an effect on the increase in the death rate while host
+ seeking (mu_vA) due to this intervention. This works like
+ adding an non-human host with its own availability. The
+ difference is that biting this sugar bait is associated with a
+ probability of dying of 1: all mosquitoes biting the sugar bait
+ will die. OpenMalaria will automatically compute the
+ availability for this host so that the probability of biting this
+ 'host' (and thus dying) is equal to the input parameter.
+
+ Enter the probability of dying while host seeking due to this
+ intervention. If multiple interventions overlap, the cumulative
+ probability will be used. Note that it cannot exceed 1, and
+ OpenMalaria will return an error during the simulation if this
+ ever happens.
-
-
-
-
+ OpenMalaria will dynamically compute the necessary increase
+ in mu_vA based on the given probability. Note that this is done
+ by solving an equation numerically every timestep, which can
+ cause a small drop in performance.
+ units:dimensionless;name:Probability of death while host searching as a result of feeding on a sugar bait (used to dynamically adjust mu_vA);
+
+
+
+
+
+
+
+ units:dimensionless;min:-1;max:inf;name:Initial proportion increase
+
+
+
+
+
+
- biphasic: halflife of long lived component (default to years).
-
+ Name of the species/subspecies/variant.
+ name:Species/subspecies/variant name
-
+
-
- A parameter with optional heterogeneity.
-
- Optionally, a distribution ("distr") and standard of deviation ("SD") may be specified.
-
- name:Sampled value (normal);
+ This intervention modifies parameters of non-human hosts described in the <entomology> <vector> <anopheles>
+<nonHumanHosts> section of the input scenario file.
+
+The intervention is described by 5 parameters that define the change in each of non-human host parameters:
+
+reduceAvailability: Reduction in the availability rate, αi. For example a value of 0 will result in no change; a value of 0.2 will reduce the availability to 0.8 of its initial value; and a value of 1 will set the availability to 0;
+
+prePrandialKillingEffect: Reduction in the pre-prandial survival probability, PBi. For example a value of 0 will result in no change; a value of 0.2 will reduce PBi to 0.8 of its initial value; and a value of 1 will set PBi to 0;
+
+postPrandialKillingEffect: Reduction in the post-prandial survival probability, PCi. For example a value of 0 will result in no change; a value of 0.2 will reduce PCi to 0.8 of its initial value; and a value of 1 will set PCi to 0;
+
+restingKillingEffect: Reduction in the survival probability of the resting period, PDi. For example a value of 0 will result in no change; a value of 0.2 will reduce PDi to 0.8 of its initial value; and a value of 1 will set PDi to 0;
-
-
-
- The mean value.
-
- name:mean;
-
-
-
+
+
+
+
+
+
+
+
+
+
+
+
+ List of timed vector population intervention deployment
+
+ name:Vector population intervention deployment;
+
+
+
+
- The standard deviation of variates.
+ Name of intervention (e.g. larviciding, sugar bait).
- name:standard deviation;
+ name:Name of intervention;
-
+
- To allow heterogeneity, a distribution must be specified.
-
- Valid options are as follows.
-
- "const": no variation or sampling. Specifying distr="const" has the
- same effect as not specifying distr at all.
-
- "normal": the parameter is sampled from a normal distribution.
+ Name of intervention (e.g. larviciding, sugar bait).
- name:Distribution;
+ name:Name of intervention;
-
-
-
-
-
-
-
+
- Parameters of a normal distribution, provided as mean and variance.
-
- Variates are sampled from Be(α,β) where α and β are determined from the
- mean and variance as follows: let v be the variance and c=mean/(1-mean).
- Then we set α=cβ and β=((c+1)²v - c)/((c+1)³v).
+ Descriptions of the effects of non human hosts interventions with per-species effects.
- name:Log-normal parameters;
-
+
+
+
+ Reduction in the availability rate, αi. For example a value of 0 will result in no change; a value of 0.2 will reduce the availability to 0.8 of its initial value; and a value of 1 will set the availability to 0;
+
+
+
+
+ units:dimensionless;min:-1;max:inf;name:Initial proportion increase
+
+
+
+
+
+
+ Reduction in the pre-prandial survival probability, PBi. For example a value of 0 will result in no change; a value of 0.2 will reduce PBi to 0.8 of its initial value; and a value of 1 will set PBi to 0;
+
+
+
+
+ units:dimensionless;min:-1;max:inf;name:Initial proportion increase
+
+
+
+
+
+
+ Reduction in the post-prandial survival probability, PCi. For example a value of 0 will result in no change; a value of 0.2 will reduce PCi to 0.8 of its initial value; and a value of 1 will set PCi to 0;
+
+
+
+
+ units:dimensionless;min:-1;max:inf;name:Initial proportion increase
+
+
+
+
+
+
+ Reduction in the survival probability of the resting period, PDi. For example a value of 0 will result in no change; a value of 0.2 will reduce PDi to 0.8 of its initial value; and a value of 1 will set PDi to 0;
+
+
+
+
+ units:dimensionless;min:-1;max:inf;name:Initial proportion increase
+
+
+
+
+
+
+ Reduction in the number of fertile eggs laid by a mosquito after biting this type of host, relative to an unprotected human. For example a value of 0 will result in no change; a value of 0.2 will reduce the fecundity factor to 0.8 of its initial value; and a value of 1 will set the fecundity factor to 0;
+
+
+
+
+ units:dimensionless;min:-1;max:inf;name:Initial proportion increase
+
+
+
+
+
+
- The mean of the beta distribution (must be in the open range (0,1)).
+ Name of the species/subspecies/variant.
- units:none;name:mean;
+ name:Species/subspecies/variant name
-
+
+
+
+ Describes a new non-human hosts that have not been described in the <entomology> <vector> <anopheles> <nonHumanHosts>.
+
+
+
+
+
+
+
+
+
+
+
+
+ List of timed vector trap intervention deployment
+
+ name:Vector trap intervention deployment;
+
+
+
+
+
+
+
+
+
+
+ Life of the trap until replaced or removed, e.g.
+ "73t" or "1y". After this time period, these traps
+ will be removed from the simulation.
+
+ New deployments do not automatically remove old
+ traps. Existing traps cannot be refurbished in the
+ model. It may make sense to make the end-of-life
+ coincide with a new deployment.
+
+ name:Lifespan;units:Steps or Days or Years;
+
+
+
+
+
+
+
+
+
+
+
- The standard deviation of variates.
+ Name of intervention (e.g. larviciding, sugar bait).
- units:none;name:variance;
+ name:Name of intervention;
-
+
-
- A parameter with optional heterogeneity.
-
- The mean cannot be specified (unless this type is extended).
- Optionally, a distribution ("distr") and coefficient of variation ("CV") may be specified.
+ Descriptions of the effects of new non human hosts with per-species effects.
- name:Sampled value (log normal);
-
-
-
- The (linear) coefficient of variation.
-
- This value must be specified when a (non-constant) distribution is used.
- Note: since version 46, variance can be used instead.
-
- Note that specifying CV="0" has the same effect as distr="const" and
- disables sampling of this parameter, even if distr is not "const".
-
- name:Coefficient of variation;units:unitless;
-
-
-
-
-
- To allow heterogeneity, a distribution must be specified.
-
- Valid options are as follows.
-
- "const": no variation or sampling. Specifying distr="const" has the
- same effect as not specifying distr at all.
-
- "lognormal": the parameter is sampled from a log-normal distribution.
- Note that the "mean" and "CV" values are linear (arithmetic) properties
- of the distribution and not log-space properties.
-
- name:Distribution;
-
-
-
-
-
-
-
-
-
-
+
+
+
+
+ Relative availability of the population of non-human hosts of
+ type i to other non-human hosts; the sum of this across all
+ non-human hosts must be 1.
+
+ units:Proportion; name:Relative availability of non-human host (ξ_i);
+
+
+
+
+ Probability of mosquito successfully biting host
+ units:Proportion;name:Probability of mosquito successfully biting host;
+
+
+
+
+ Probability that the mosquito escapes host and finds a resting place after biting
+ units:Proportion;name:Probability that the mosquito escapes host and finds a resting place after biting;
+
+
+
+
+ Probability of mosquito successfully resting after finding a resting site
+ units:Proportion;name:Probability of mosquito successfully resting after finding a resting site;
+
+
+
+
+ Multiplicative factor for the number of fertile eggs laid by a mosquito after biting this type of host, relative to an unprotected human.
+ units:Proportion;name:Probability of mosquito successfully resting after finding a resting site;
+
+
+
+
- The variance parameter of the distirbution.
-
- This value can be specified when a (non-constant) distribution is used.
-
- Note that specifying variance="0" has the same effect as distr="const" and
- disables sampling of this parameter, even if distr is not "const".
+ Name of the species/subspecies/variant.
- name:Coefficient of variation;units:unitless;
+ name:Species/subspecies/variant name
-
-
-
- A parameter with optional log-normal heterogeneity.
-
- The mean value must be specified. Optionally, a distribution ("distr")
- and coefficient of variation ("CV") may be specified.
-
- name:Sampled value;
-
-
-
-
-
-
- The (linear) mean value.
-
- name:mean;
-
-
-
-
-
-
+
- Parameters of a Weibull distribution.
-
- name:Weibull parameters;
+ Specifies the mapping from genotype to phenotype. For each drug
+ type, if only one phenotype is present, restrictions need not be
+ specified, but otherwise restrictions must be specified.
+
+ The set of loci affecting phenotypes of this drug's action must be
+ fixed for any drug type. Each phenotype must list, for each of
+ these loci, a restriction to one or more alleles under the locus.
+
+ name:Restrict phenotype applicability to certain alleles;
-
-
-
- The Weibull scale parameter (λ).
-
- name:Scale;
-
-
-
+
- The Weibull shape parameter (k).
-
- name:shape;
+ A locus under which only a restricted set of alleles map to
+ this phenotype.
+
+ name:Locus relevant to the mapping of alleles to this phenotype;
-
+
- To allow heterogeneity, a distribution must be specified.
- In this case, only "weibull" is allowed.
-
- name:Distribution;
-
-
-
-
-
-
-
-
-
-
-
- A double-precision floating-point value.
- name:Input parameter value;exposed:false;
-
-
-
-
-
-
- An integer value.
- name:Input parameter value;exposed:false;
-
-
-
-
-
-
- A boolean value.
- name:Input parameter value;exposed:false;
+ One allele of a locus upon which phenotype choice depends.
+ If multiple alleles under this locus should map to the same
+ phenotype, repeat the whole "restriction onLocus..." element.
+
+ name:Alleles mapping to this phenotype;
-
+
-
+
+
- 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).
+ Mean efficacy values before decay (see efficacyB and decay parameter
+ descriptions for sampling and decay). The i-th value in this list
+ is used for the efficacy of the vaccine after the i-th dose. Where
+ more doses are given than there are values in this list, the last
+ value is repeated.
- name:age group;
+ units:dimensionless;min:0;max:1;name:Initial mean efficacy;
-
-
-
-
-
-
- Lower bound of age group
-
- units:Years;min:0;max:100;name:Lower bound;
-
-
-
-
-
-
-
+
- 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.
+ Name of the phenotype; for documentation use only.
- name:interpolation;
+ name:Name of phenotype;
-
-
-
-
-
-
@@ -5892,6 +5892,7 @@ restingKillingEffect: Reduction in the survival probability of the resting perio
+
diff --git a/test/expected/outputVivax.txt b/test/expected/outputVivax.txt
index b604319f..1f8d6538 100644
--- a/test/expected/outputVivax.txt
+++ b/test/expected/outputVivax.txt
@@ -1,7452 +1,14580 @@
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diff --git a/test/scenarioVivax.xml b/test/scenarioVivax.xml
index 61c8d3c7..0ef2e140 100644
--- a/test/scenarioVivax.xml
+++ b/test/scenarioVivax.xml
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