diff --git a/model/util/DocumentLoader.h b/model/util/DocumentLoader.h index afe42b90f..d1c01c9bc 100644 --- a/model/util/DocumentLoader.h +++ b/model/util/DocumentLoader.h @@ -35,7 +35,7 @@ namespace OM { namespace util { class DocumentLoader { public: /// Current schema version. - static const int SCHEMA_VERSION = 38; + static const int SCHEMA_VERSION = 39; DocumentLoader () : documentChanged(false) {} diff --git a/schema/CMakeLists.txt b/schema/CMakeLists.txt index 6711499cc..5160d91cf 100644 --- a/schema/CMakeLists.txt +++ b/schema/CMakeLists.txt @@ -28,7 +28,7 @@ foreach (XSD_NAME ${SCHEMA_NAMES}) COMMAND ${XSD_EXECUTABLE} cxx-tree --std c++11 --type-naming ucc --function-naming java - --namespace-map http://openmalaria.org/schema/scenario_38=scnXml + --namespace-map http://openmalaria.org/schema/scenario_39=scnXml # --generate-serialization --generate-doxygen --generate-intellisense diff --git a/schema/demography.xsd b/schema/demography.xsd index aae5ad792..8cc94dd91 100644 --- a/schema/demography.xsd +++ b/schema/demography.xsd @@ -2,8 +2,8 @@ - diff --git a/schema/entomology.xsd b/schema/entomology.xsd index 0c34dd3da..e3a9e95ac 100644 --- a/schema/entomology.xsd +++ b/schema/entomology.xsd @@ -2,8 +2,8 @@ - diff --git a/schema/healthSystem.xsd b/schema/healthSystem.xsd index e11af21c8..2857a34b8 100644 --- a/schema/healthSystem.xsd +++ b/schema/healthSystem.xsd @@ -3,8 +3,8 @@ Copyright © 2005-2011 Swiss Tropical Institute and Liverpool School Of Tropical Medicine Licence: GNU General Public Licence version 2 or later (see COPYING) --> - diff --git a/schema/interventions.xsd b/schema/interventions.xsd index 74e9deae6..fa2368338 100644 --- a/schema/interventions.xsd +++ b/schema/interventions.xsd @@ -2,8 +2,8 @@ - diff --git a/schema/monitoring.xsd b/schema/monitoring.xsd index 9c5c6a154..8ad9ed5cb 100644 --- a/schema/monitoring.xsd +++ b/schema/monitoring.xsd @@ -2,8 +2,8 @@ - diff --git a/schema/pharmacology.xsd b/schema/pharmacology.xsd index d8f563d4b..db23cab19 100644 --- a/schema/pharmacology.xsd +++ b/schema/pharmacology.xsd @@ -3,8 +3,8 @@ Copyright © 2005-2011 Swiss Tropical Institute and Liverpool School Of Tropical Medicine Licence: GNU General Public Licence version 2 or later (see COPYING) --> - diff --git a/schema/scenario.xsd b/schema/scenario.xsd index e65569985..7d1cc924b 100644 --- a/schema/scenario.xsd +++ b/schema/scenario.xsd @@ -2,8 +2,8 @@ - diff --git a/schema/scenario_39.xsd b/schema/scenario_39.xsd new file mode 100644 index 000000000..87eb74d88 --- /dev/null +++ b/schema/scenario_39.xsd @@ -0,0 +1,5897 @@ + + + + + + + + + Description of scenario + name:Scenario; + + + + + + + Description of demography + + name:Human age distribution; + + + + + + Description of surveys + + name:Measures to be reported; + + + + + + List of interventions. Generally these are either point-time + distributions of something to some subset of the population, or + continuous-time distribution targetting individuals when they + reach a certain age. + + name:Preventative interventions; + + + + + + Description of health system. + + name:Health system description; + + + + + + Description of entomological data + + name:Transmission and vector bionomics; + + + + + + A specification of genotypes of infection parasites. + + May be omitted; in this case there is no modelling of genetic + differences of infections (resistance, fitness). + + name:Parasite genetics; + + + + + + Drug model parameters and drug usage parameters + + name:Drug parameters (PK, PD and usage); + + + + + + Diagnostic model parameters + + name:Diagnostic parameters; + + + + + + Encapsulation of all parameters which describe the model according + to which fitting is done. + + name:Model options and parameters; + + + + + + + All model options (bug fixes, choices between models, etc.). + The list of recognised options can be found in the code at: + model/util/ModelOptions.h and should also be in the wiki. + + name:Model Options; + + + + + + + + This describes Vivax model parameters, and is required when using the + VIVAX_SIMPLE_MODEL model option. + + name:Vivax model parameters; + + + + + + Parameters of the epidemiological model + + name:Parameters of the model of epidemiology; + + + + + + + + + + Version of xml schema. If not equal to the current version + an error is thrown. Use SchemaTranslator to update xml files. + + name:Version of the xml schema;exposed:false; + + + + + + Unique identifier of scenario + + units: Number;min:1;max:100000000;name:Reference number of the analysis;exposed:false; + + + + + + + Name of intervention + + name:Name of intervention; + + + + + + Work unit ID. Obselete and no longer required. + + + units:Number;name:Work unit identifier;exposed:false; + + + + + + + + + + Name of parameter + units:string;name:Name of parameter; + + + + + + Reference number of input parameter + + units:Number;min:1;max:100;name:Parameter number;exposed:false; + + + + + Parameter value + units:Number;min:0;name:Parameter value;sweepable:true; + + + + + + True if parameter is to be sampled in optimization + runs. Not used in simulator app. + + units:Number;min:0;max:1;name:Sampling indicator;exposed:false; + + + + + + + + + + Simulation step + units:Days;name:Simulation step; + + + + + Seed for RNG + units:Number;name:Random number seed;sweepable:true; + + + + + + Pre-erythrocytic latent period + + Can be specified in steps (e.g. 3t) or days (e.g. 15d). + + units:User defined (default: steps);min:0;max:20;name:Pre-erythrocytic latent period; + + + + + + + + Parameters of host models. + + name:Human; + + + + + + Availability of humans to mosquitoes relative to an adult, categorized by age group + + name:Availability to mosquitoes;units:None;min:0;max:1; + + + + + + By age group data on human weight (mass). + + name:Weight;units:kg;min:0 + + + + + + + + Each human is assigned a weight multiplier from a normal distribution + with mean 1 and this standard deviation at birth. His/her weight + is this multiplier times the mean from age distribution. + A standard deviation of zero for no heterogeneity is valid; a rough + value from Tanzanian data is 0.14. + + name:Standard deviation;units:None;min:0 + + + + + + + + + + + + + + The chance of a feeding mosquito becoming infected, given that the + host is patent. (This may be adjusted by transmission-blocking vaccines.) + + name:Probability of mosquito infection;units:None;min:0;max:1; + + + + + + Describes the number and times of hypnozoite releases. + + name:Hypnozoite releases; + + + + + + The length of time after expiry of a blood-stage infection during + which relapses from the same brood are supressed by the immune + system. + + This is rounded to the nearest time-step. + + name:Blood stage protection latency;min:0; + + + + + + Parameters used to sample the length of blood-stage infections from + a Weibull distribution (scale parameter lambda, shape parameter k). + + name:Blood stage length;units:Days; + + + + + + + + + + + + + This element defines probabilites when and how many hypnozoites are released from the liverstage into the blood. + + The gap between the start of a new brood of hypnozoites and its release are defined as follows: + + latentP + latentRelapseDays + randomReleaseDelay + + randomReleaseDelay is based on one or two lognormal distributions, which are defined in firstRelease and optionally secondRelease. + + You can define 2 release distributions, which get added together and represent the probability of hypnozoites which get released before winter (first release) or after (second release). + + You can omit the secondRelease element if no release to the blood happens after winter. + + name:Hypnozoite release; + + + + + + numberHypnozoites calculates the number of hypnozoites in the liver stage based on a base which is between 0 and 1. + + This number is random based on the following distribution and normalized: + + max + ∑ (base ^ n) + n = 0 + + name:Number of Hypnozoites; + + + + + + + + + + + + + Probability of a second release. If undefined it is zero. + + name:latent relapse days; + + + + + + + + + + Usually 15 days or 10 days (3 or 2 5-day timesteps). + + name:latent relapse days; + + + + + + + + + This elements holds all information about probabilites for clinical events from infections and relapses. + + name:Vivax Clinical Events; + + + + + + + + + + + + + + + + + + + Describes a locus, or a point at which an infection may + vary. The genotype of an infection is determined by + choosing one allele at each locus. Initial frequencies of + alleles are specified independently for each locus, but + subsequent infections are selected according to success of + genotypes. + + Alleles at loci can affect fitness and resistance to any + number of drugs. + + name:Locus; + + + + + + + This controls how genotypes are determined for new infections during + the intervention period. Prior to this (in initialisation phases), + genotypes are always sampled using the specified initial frequencies. + + Mode "initial" continues to sample genotypes using initial + frequencies (i.e. independent of the success of parent generations of + parasites). + + Mode "tracking" samples genotypes based on the success parent + generations of parasites have in infecting mosquitoes, tracked per + genotype. + + It is possible that in the future a recombination option will be + added to this list, however designing a suitable model is not + trivial. + + Name:Sampling mode; + + + + + + + + + + + + + + Name of the genotype; used to refer to it elsewhere. + + name:Name (for reference purposes); + + + + + + Specification of how commonly this genotype occurs during + initialisation phases of the simulation relative to other genotypes. + + name:Initial frequency; + + + + + + Fitness factor of the genotype. This is multiplication factor used to + speed up or slow down replication of parasites. + + For example, if a genotype has a fitness factor of 0.8, then the + parasites with this genotype will replicate 20% slower in the host + than the baseline. + + name:Fitness factor; + + + + + + + + + Describes an allele, or one possible genetic option + of multiple at one point of variance. + + name:Allele; + + + + + + Name of the Locus + name:Name of locus; + + + + + + + + Name of the allele; used to refer to it elsewhere. + + name:Name; + + + + + + Specification of how commonly this allele occurs during warmup + relative to other alleles of the same locus. + + During the simulation's initialisation phases, the frequency at which + each allele of each locus occurs is fixed. After the initialisation + phase, frequency of alleles is modelled as an emergent property of + the success of genotypes. + + name:Initial frequency; + + + + + + Fitness factor of the allele. This is multiplication factor used to + speed up or slow down replication of parasites. + + For example, if a genotype has an allele with a fitness factor of 1 + at one locus and another allele with a fitness factor of 0.8 at a + second locus, then the parasites with the genotype will replicate 20% + slower than the baseline. + + name:Fitness factor; + + + + + + + + + + + + + + + + + + Specify that an artificial deterministic test is used: outcome is + positive if parasite density is at least the minimum given. + + name:Deterministic detection; + + + + + + The minimum density at which parasites can be detected. If 0, + the test outcome is always positive. + + name:Minimum detectible density;units:parasites/microlitre;min:0; + + + + + + + + An improved model of detection which is non-deterministic, including + false positive results as well as false negatives. + + The probability of a positive outcome is modelled as 1 + s×(x/(x+d) - 1) + where x is the parasite density, d is the density at which the test outcome + has a 50% chance of being positive, and s is the probability of a positive + outcome given no parasites (the specificity). + + Some parameterisations: + + Microscopy sensitivity/specificity data in Africa; + Source: expert opinion — Allan Schapira + dens_50 = 20.0 + specificity = .75 + + RDT sensitivity/specificity for Plasmodium falciparum in Africa + Source: Murray et al (Clinical Microbiological Reviews, Jan. 2008) + dens_50 = 50.0; + specificity = .942; + + name:Non-deterministic detection + + + + + + The density at which the test outcome has a 50% chance of being positive. + + name:Density 50;units:parasites/microlitre;min:0; + + + + + + The probability of a positive test outcome in the absense of parasites. + + units:Dimensionless;name:Specificity;min:0;max:1; + + + + + + + + + + Name of this diagnostic (parameterisation). May be used elsewhere in + the XML document to refer to this set of diagnostic parameters. + + name:Name of diagnostic; + + + + + + Parasite densities, as estimated according to standard microscopy + methods, the Garki method, and as derived from Malariatherapy data + are not equivalent. Internally, a "bias" factor is used to convert + values estimated by one methods to values comparable with another + (see AJTMHv75 supplement 2 pp20-21). + + This option allows specification of which methodology the density + given in the diagnostic specification is measured with. Values + allowed are: Malariatherapy, Garki and Other. If not specified, + Other is assumed, unless the GARKI_DENSITY_BIAS model option is used, + in which case this option must be specified. + + name:Parasite density units / methodology; + + + + + + + + + + + + + + + + + + list of age groups included in demography + + name:Age groups; + + + + + + + Name of demography data + + name:Name of demography data; + + + + + Population size + units:Count;min:1;max:100000;name:Population size; + + + + + + Maximum age of simulated humans in years + + units:Years;min:0;max:100;name:Maximum age of simulated humans; + + + + + + Growth rate of human population. + (we should be able to implement this with non-zero values) + + units:Number;min:0;max:0;name:Growth rate of human population; + + + + + + + + list of age groups included in demography or surveys + + name:list of age groups; + + + + + + + + Lower bound of age group + + units:Years;min:0;max:100;name:Lower bound of age group + + + + + + + + Percentage of human population in age group + + units:Percentage;min:0;max:100;name:Percentage in age group + + + + + + Upper bound of age group + + units:Years;min:0;max:100;name:Upper bound of age group + + + + + + + + + + + Description of clinical parameters that are related to the health-system description, but which contain data + that cannot be changed as part of an intervention and that are not restricted to treatment. + + name:Description of clinical parameters; + + + + name:Neonatal mortality parameters; + + + + + The name of a diagnostic used to parameterise the model. + + Neonatal mortality is derived from malaria patency of a certain + sub-population of humans. This is the diagnostic used to asses + patency for this purpose. + + If this is not specified, the monitoring diagnostic is used. + + name:Diagnostic used to parameterise model; + + + + + + + + + Description of the incidence of non-malaria fever. Non-malaria fevers + are only modelled if the NON_MALARIA_FEVERS option is used. + + name:Non-malaria fevers; + + + + + + Probability that a non-malaria fever occurs given that no concurrent + malaria fever occurs. + + name:P(NMF); units:Dimensionless;min:0.0;max:1.0; + + + + + + Probability that a non-malarial fever requires treatment with + antibiotics (assuming fever is not induced by malaria, although + concurrent parasites may be present). + + name:P(need treatment | NMF);units:Dimensionless;min:0;max:1; + + + + + + Probability that a malaria fever needs treatment with + antibiotics (assuming fever is induced by malaria, although + concurrent bacteria may be present). + + Meaning partially overlaps with separate model for comorbidity + given malaria. + + name:P(need treatment | MF);units:Dimensionless;min:0;max:1; + + + + + + + + + + Follow-up period during which a recurrence is + considered to be a treatment failure + + Can be specified in steps (e.g. 6t) or days (e.g. 28d). + + units:User-defined (defaults to steps); + name:Follow-up period during which recurrence is considered a treatment failure; + + + + + + + + + + Description of case management system, used to specify the initial model + or a replacement (an intervention). Encompasses case management + data and some other data required to derive case outcomes. + + Contains a sub-element describing the particular health-system in use. + Health system data is here defined as data used to decide on a treatment + strategy, given a case requiring treatment. + + name:Case management system; + + + + + + + + + + + Case fatality rate (probability of an inpatient fatality from a + bout of severe malaria, per age-group). + + name:Case fatality rate for inpatients; + + + + + + List of age-specific probabilities of sequelae in inpatients, + during a severe bout of malaria. + + units:Dimensionless;name:Probabilities of sequelae in inpatients; + + + + + + + + + Parameters for drug treatment which have an effect on the liver-stage of parasites (Primaquine and potentially Tafenoquine); for use with the Vivax model only. + + Note: if this section is not listed, the following default values are + assumed: pHumanCannotReceive=0, pUseUncomplicated=0, + effectivenessOnUse=1. + + name:Liver stage drug treatment parameters (Vivax); + + + + + + Chance that a human is determined to be unable to receive liver-stage drug + treatment. Treatment is neither reported or given for such humans. + + This is sampled once per human at birth. + + units:Probability;min:0;max:1; + name:Probability that human is incompatible with liver-stage drug treatment; + + + + + + If true, ignore pHumanCannotReceive and consider all humans eligible + for treatment; if false (or not specified), do not treat those demed + incompatible with liver-stage drug treatment. + + The point of this is that pHumanCannotReceive cannot be altered by + changeHS interventions, but this property can be. + + name:Ignore liver-stage drug treatment incompatibility; + + + + + + This feature is deprecated; it is suggested to use the "simple + treatment" feature configured to clear liver-stage parasites, + leaving this option unset or zero. + + Chance of liver-stage drug treatment being used for routine treatment of an + uncomplicated case. + + units:Probability;min:0;max:1;name:Prob use in UC case; + + + + + + Chance that liver-stage drug treatment is effective. + + On application, a random variable is sampled against this probability. + If false, the treatment does nothing; if true, the treatment clears all + liver stage parasites. Where effectiveness is longer than a single + time step (prophylactic effect), this sample still only happens once + (thus either no effect or all liver stages cleared over multiple steps). + + units:Probability;min:0;max:1;name:Effectiveness; + + + + + + + + + + Description of "immediate outcomes" health system: + Tediosi et al case management model (Case management as + described in AJTMH 75 (suppl 2) pp90-103). + + name:Case Management (Tediosi et al); + + + + + + Description of drug regimen. + + name:Description of drug regimen; + + + + + + Code for first line drug + + units:Drug code;name:First line drug; + + + + + + Code for second line drug + + units:Drug code;name:Second line drug; + + + + + + Code for drug used for treating + inpatients + + units:Drug code;name:Drug use for treating inpatients; + + + + + + + + Initial cure rate + + + units:Dimensionless;min:0.0;max:1.0;name:Initial cure rate; + + + + + + Adherence to treatment + + units:Dimensionless;min:0.0;max:1.0;name:Adherence to treatment; + + + + + + Effectiveness of treatment for non-compliant patients + + + units:Dimensionless;min:0.0;max:1.0;name:Effectiveness of treatment in non-adherent patients; + + + + + + + + + + + + + + + + + + + + Probability that a patient with newly incident + uncomplicated disease seeks official care + + + units:Dimensionless;min:0.0;max:1.0;name:Probability that a patient with uncomplicated disease seeks official care immediately. + + + + + + + Probability that a patient with uncomplicated disease without + recent history of disease (i.e. first line) will self-treat. + + Note that in second line cases there is no probability of self-treatment. + + + units:Dimensionless;min:0.0;max:1.0;name:Probability that a patient with uncomplicated disease will self-treat. + + + + + + + Probability that a patient with recurrence of + uncomplicated disease seeks official care + + + units:Dimensionless;min:0.0;max:1.0;name:Probability that a recurring patient seeks official care; + + + + + + + Probability that a patient with severe disease + obtains appropriate care + + + units:Dimensionless;min:0.0;max:1.0;name:Probability that a patient with severe disease obtains appropriate care; + + + + + + + + + Name of health system + + name:Name of case management parameterisation; + + + + + + + + + Chloroquine + name:Chloroquine; + + + + + + Sulphadoxine-pyrimethamine + + name:Sulphadoxine-pyrimethamine; + + + + + Amodiaquine + name:Amodiaquine + + + + + + Sulphadoxine-pyrimethamine/Amodiaquine + + name:Sulphadoxine-pyrimethamine/Amodiaquine; + + + + + + Artemisinine combination therapy + + name:Artemisinine based combination therapy; + + + + + Quinine + name:Quinine; + + + + + + Probability of self-treatment + + + units:Dimensionless;min:0;max:1name:P(self-treat); + + + + + + + + + + + Description of the health system using the 5-day timestep with decision + tree model: access is configured as in the Tediosi et al case + management model (Case management as described in AJTMH 75 (suppl 2) + pp90-103) while treatment decisions are configured via decision trees. + + Besides greater flexibility, this allows treatment via PK/PD models. + + name:Case Management (Tediosi et al with programmable decision trees); + + + + + + + + Probability that a patient with newly incident + uncomplicated disease seeks official care + + + units:Dimensionless;min:0.0;max:1.0;name:Probability that a patient with uncomplicated disease seeks official care immediately. + + + + + + + Probability that a patient with uncomplicated disease without + recent history of disease (i.e. first line) will self-treat. + + Note that in second line cases there is no probability of self-treatment. + + + units:Dimensionless;min:0.0;max:1.0;name:Probability that a patient with uncomplicated disease will self-treat. + + + + + + + Probability that a patient with recurrence of + uncomplicated disease seeks official care + + + units:Dimensionless;min:0.0;max:1.0;name:Probability that a recurring patient seeks official care; + + + + + + + Probability that a patient with severe disease + obtains appropriate care + + + units:Dimensionless;min:0.0;max:1.0;name:Probability that a patient with severe disease obtains appropriate care; + + + + + + + + + + The probability of clearing parasites given access to + appropriate (hospital) care, for a severe case. + + name:Cure rate (severe cases);min:0;max:1; + + + + + + + + Name of health system + + name:Name of case management parameterisation; + + + + + + + + + + + + + + + + + Description of base parameters of the clinical model. + + name:Clinical Outcomes; + + + + + + Maximum number of timesteps (including first day of case) that an individual with an uncomplicated case of + malaria will remember he/she was sick before resetting. + + name:Max UC treatment-seeking memory;units:Days;min:0;max:unbounded + + + + + + Fixed length of an uncomplicated case of malarial or non-malarial + sickness (from treatment seeking until return to life-as-usual). + Usually 3. + + name:Uncomplicated case duration;units:Days;min:1;max:unbounded + + + + + + Fixed length of a complicated or severe case of malaria + (from treatment seeking until return to life-as-usual). + + name:Complicated case duration;units:Days;min:1;max:unbounded + + + + + + Number of days for which humans are at risk of death during a severe + or complicated case of malaria. Cannot be greater than the duration + of a complicated case or less than 1 day. + + name:Complicated risk duration;units:Days;min:1;max:unbounded + + + + + + It is sometimes desirable to model delays to treatment-seeking in + uncomplicated cases. While treatment of drugs can be delayed within + case management trees to provide a similar effect, this doesn't + delay any of the decisions, including diagnostics using the current + parasite density. + + Instead a list of dailyPrImmUCTS elements can be used, describing + successive daily probabilities of treatment (sum must be 1). For + example, with a list of two elements with values 0.8 and 0.2, for + 80% of UC cases the decision tree is evaluated immediately, and for + 20% of cases evaluation is delayed by one day. + + For no delay, use one element with a value of 1. + + name:Daily probability of immediate treatment seeking for uncomplicated cases;units:Dimensionless;min:0.0;max:1.0 + + + + + + + + Description of non-malaria fever health-system modelling (treatment, + outcomes and costing). Incidence is described by the + model->clinical->NonMalariaFevers element. Non-malaria fevers are only + modelled if the NON_MALARIA_FEVERS option is used. + + As further explanation of the parameters below, we first take: + β₀ = logit(P₀) - β₃·P(need), + and then calculate the probability of antibiotic administration, P(AB), + dependent on treatment seeking location. + No seeking: P(AB) = 0 + Informal sector: logit(P(AB)) = β₀ + β₄ + Health facility: logit(P(AB)) = β₀ + β₁·I(neg) + β₂·I(pos) + β₃·I(need) + (where I(X) is 1 when event X is true and 0 otherwise, + logit(p)=log(p/(1-p)), event "need" is the event that death may occur + without treatment, events "neg" and "pos" are the events that a malaria + parasite diagnositic was used and indicated no parasites and parasites + respectively). + + name:Non-malaria fevers; + + + + + + Probability of a non-malaria fever being treated with an antibiotic + given that no malaria diagnostic was used but independent of need. + Symbol: P₀. + + name:P(treatment|no diagnostic);units:Dimensionless;min:0.0;max:1.0; + + + + + + The effect of a negative malaria diagnostic on the odds ratio of + receiving antibiotics. Symbol: exp(β₁). + + name:Effect of a negative test; + + + + + + The effect of a positive malaria diagnostic on the odds ratio of + receiving antibiotics. Symbol: exp(β₂). + + name:Effect of a positive test; + + + + + + The effect of needing antibiotic treatment on the odds ratio of + receiving antibiotics. Symbol: exp(β₃). + + name:Effect of need; + + + + + + The effect of seeking treatment from an informal provider (i.e. + a provider untrained in NMF diagnosis) on the odds ratio of + receiving antibiotics. Symbol: exp(β₄) + + name:Effect of informal provider; + + + + + + Base case fatality rate for non-malaria fevers (probability of + death from a fever requiring antibiotic treatment given that no + antibiotic treatment is received, per age-group). + + name:Case fatality rate;units:Dimensionless;min:0.0;max:1.0; + + + + + + Probability that treatment would prevent a death (i.e. CFR is + multiplied by one minus this when treatment occurs). + + units:Dimensionless;name:Treatment efficacy;min:0.0;max:1.0; + + + + + + + + + + Describes how "decisions" are made, both probabilistically and + deterministically, and what actions are carried out. + + Quantities may also be reported as a side effect of decisions made in + the tree, for example the number of diagnostics used. + + name:Decision tree; + + + + + + + + + + + + + + + + + + + An optional piece of documentation attached to this node. + + name:Name; + + + + + + + A special node allowing multiple sub-trees to be evaluated. + + This is different from an ordinary decision tree node in that: + + a) multiple types of child can occur simultaneously (e.g. multiple + types of treatment or treatment plus a 'random' sub-tree) + + b) the 'noTreatment' and 'treatFailure' nodes are not allowed + + name:Decision tree; + + + + + + + + + + + + + + + + An optional piece of documentation attached to this node. + + name:Name; + + + + + + + A switch which choses a branch deterministically, based on whether the + patient was treated recently (second line) or not (first line). + + For uncomplicated cases only. + + name:Switch (first/second line); + + + + + + + + + An optional piece of documentation attached to this node. + + name:Name; + + + + + + + A switch which choses a branch deterministically, based on the outcome + of some type of diagnostic. + + name:Switch (diagnostic); + + + + + + + + + Should match the name of some parameterised diagnostic (see + scenario/diagnostics). + + name:Name of diagnostic; + + + + + + An optional piece of documentation attached to this node. + + name:Name; + + + + + + + A switch which choses a branch randomly. + + Each branch must be listed with a probability; the sum of all these + probabilities must equal 1. + + name:Switch (probabilistic); + + + + + + + + + + Probability of selecting this outcome. The sum of + probabilities across all outcomes must be 1. + + units:None;min:0;max:1;name:Probability; + + + + + + + + + + + An optional piece of documentation attached to this node. + + name:Name; + + + + + + + A switch which choses a branch deterministically, based on the + patient's age (in years). + + Categories must uniquely cover all ages from birth, with no upper + bound. Categories must be listed in order of age, increasing; the first + must have lower bound 0. Upper bounds are equal to the lower bound of + the next category, (but are exclusive where lower bounds are + inclusive); the last category has no upper bound. + + name:Switch (age of patient); + + + + + + Describes a branch, selected for patients of a certain age. + + name:Age range; + + + + + + + name:Lower bound (inclusive);min:0; + + + + + + + + + + + An optional piece of documentation attached to this node. + + name:Name; + + + + + + + An end node doing nothing. This exists to explicitly state that no + treatment happens and to prevent trees from accidentally being left + incomplete. + + name:No treatment; + + + + + An optional piece of documentation attached to this node. + + name:Name; + + + + + + + An end node which reports treatment but does not change parasitalogical + status. This allows correct labelling of second-line cases. + + name:Failed treatment; + + + + + An optional piece of documentation attached to this node. + + name:Name; + + + + + + + A command to administer drugs according to a given schedule and + dosage table, optionally with a delay. + + name:Treatment (PK/PD model); + + + + + The name of a schedule to use for treatment. + + name:Name of treatment schedule; + + + + + + The name of a dosage table to use for treatment. + + name:Name of dosage table; + + + + + + Optionally, this can be given to delay the start of treatment by a + given number of hours. If not specified, treatment is not delayed. If + a delay is given, all medications within the treatment schedule used + are delayed by this number of hours. + + name:Delay (hours); + + + + + + + Simple treatment model, targetting liver- and/or blood-stage + infections. This is all-or-nothing treatment which, when deploymed, + completely clears all infections of the targetted stages. This makes it + unsuitable for modeling resistance, but suitable for use with simple + infection models. + + Infections are considered liver-stage when less than five days old and + blood-stage after that. Effects are described independently for the two + stages. + + name:Simple treatment; + + + + + Controls action on liver-stage infections. 0 means no action, -1 step + is a compatibility option to act like treatment before schema version + 32 (which removed infections retrospectively), 1 step or any duration + which equals some whole number of steps n>0 means to clear all + liver-stage infections found on the next 1 or n steps. + + Note on -1 compatibility option: the main difference to 1 step + (clearing on the next timestep) is that parasite densities will be + reduced immediately, and thus from the point of view of surveys and + mass screen and treat interventions a peak in density which is + immediately treated through case management will not be seen. + + Can be specified in steps (e.g. 1t, -1t) or days (e.g. 5d). + + name:Length of liver-stage effect;units:User defined; + + + + + + Controls action on blood-stage infections. 0 means no action, -1 step + is a compatibility option to act like treatment before schema version + 32 (which removed infections retrospectively), 1 step or any duration + which equals some whole number of steps n>0 means to clear all + blood-stage infections found on the next 1 or n steps. + + Note on -1 compatibility option: the main difference to 1 step + (clearing on the next timestep) is that parasite densities will be + reduced immediately, and thus from the point of view of surveys and + mass screen and treat interventions a peak in density which is + immediately treated through case management will not be seen. + + Can be specified in steps (e.g. 1t, -1t) or days (e.g. 5d). + + name:Length of blood-stage effect;units:User defined; + + + + + + + Deploy one or more intervention components. + + name:Deploy intervention; + + + + + The identifier (short name) of a component. + + name:Component identifier; + + + + + + + + + + Describes the effects of the treatment, assuming this + compliance/adherence/... option is selected. Effects are described + in terms of a list of options, each of which acts independently but + with all effects being activated simultaneously. + + name:Group (for compliance/adherence/drug effect); + + + + + + + + This clears infections according to several options: it can clear + all blood stage infections, all liver stage infections or both, and + it can act on multiple timesteps. To have a probability of no + action add another treatment option (which does nothing) and set + the probabilities of selection appropriately. + + This allows immediate (legacy) or delayed action, a prophylactic + period, and selection of which stages are targeted. It is a simple + model but appropriate enough for use with the five day timestep + when assuming no resistance and that drug + failure is mainly caused by bad drugs or compliance. + + The old treatment action for the five-day timestep model is + essentially this, with immediateAction (timesteps=-1) and + stage=both, except for the IPT model's SP action, which was more + like with timesteps>1 and stage=blood. + + name:Prophylactic treatment; + + + + + + The number of timesteps during which this action remains + in effect (e.g. 2 means clear infections during the next + two timestep updates). Full clearance of the targeted stages + occurs during this time. + + A special value of -1 means act immediately (retrospectively); + this the old behaviour. A value of 1 means act on the next + timestep only. + + Both of these can be thought of as a model for short-acting + effective drug treatment; the main differences are that the + latter means parasite densities will remain high from the point + of view of surveys and diagnostics (i.e. mass screen and treat) + used before the next timestep and that the latter will also + remove infections starting the next timestep. Arguably the + latter is a better model, but the differences are perhaps + small, excepting where immediate treatment of fevers (i.e. + through the health system) can hide high parasite densities + from reporting and mass-screen-and-treat diagnostics. For + use by interventions, the latter model has nicer behaviour in + that the order of deployment of multiple interventions + deployed at the same time does not matter, and that the former + model retrospectively treats infections which may already have + caused fever, thus may have a lower health impact than it + should. + + It is recommended to use the new model (value 1, or greater + than 1 if prophylactic effect is desired) unless wanting to + emulate the old behaviour. + + Values of 0 or less than -1 are not allowed. + + Can be specified in steps (e.g. 1t, -1t) or days (e.g. 5d). + + name:Length of effect;units:User defined (defaults to steps); + + + + + + Controls whether liver-stage or blood-stage infections + are cleared, or both. + + Infections are considered liver-stage for one 5-day timestep, + blood-stage but pre-patent for some number of timesteps + (latentp - 1), then start the patent blood stage. If stage is + set to "liver", infections are only cleared during their first + timestep; if stage is set to "blood", infections are cleared + during pre-patent and patent blood stages; if stage is set to + "both" all infections are cleared. + + The old behaviour (oddly considering the drugs it is meant to + emulate) is to clear both stages, except for the IPT model of + SP action, which cleared only patent blood-stage infections. + + name:Target stage; + + + + + + + + + + + + + + + + Describes what this compliance option represents (e.g. + "good compliance", "poor compliance with good drugs", ...). + + name:Name; + + + + + + + + + + + + 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; + + + + + + + + + + + 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; + + + + + + + + + + + + + + + + Name of an option (monitoring measure or model option). + + name:Option name; + + + + + + 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; + + + + + + + + + + + + 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 + + units:None;min:0;max:1;name:function; + + + + + + + + + + + + + + + + + (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. + + units:User-defined (defaults to years);min:0;name:L; + + + + + + Shape parameter of distribution. If not specified, default value of + 1 is used. Meaning depends on function; not used in some cases. + + min:0;name:k;units:none; + + + + + + If sigma is non-zero, heterogeneity of decay is introduced via a random + variable sampled from the log-normal distribution with mu and sigma as + specified. Both mu and sigma default to zero when not specified. + + The decay rate is multiplied by this variable (effectively, the + half-life is divided by it). + + Note that with m=0, the median of the variable and the median value of + L is unchanged, and thus the time at which the median decay amongst the + population of decaying objects reaches half (assuming exponential, + Weibull or Hill decay) is L. With m=-½σ² (negative half sigma squared) + the mean of the variable will be 1 and mean of the half-life L, but the + time at which mean decay of the population has reached half may not be + L. + + min:0;name:μ (mu); + + + + + + If sigma is non-zero, heterogeneity of decay is introduced via a random + variable sampled from the log-normal distribution with mu and sigma as + specified. Both mu and sigma default to zero when not specified. + + The decay rate is multiplied by this variable (effectively, the + half-life is divided by it). + + min:0;name:σ (sigma); + + + + + + + Parameters of a log-normal distribution. + + Variates are sampled as: X ~ ln N( log(mean)-sigma²/2, sigma² ). + + Equivalent R sample: rlnorm(n, log(m) - s*s/2, s) + + name:Log-normal parameters; + + + + + The mean of the lognormal distribution. + + units:(same as base units);name:mean; + + + + + + Sigma parameter of the lognormal distribution; sigma squared is the + variance of the log of samples. + + name:sigma; + + + + + + + Parameters of a normal distribution. + + Variates are sampled as: X ~ N( mu, sigma² ). + + name:Log-normal parameters; + + + + + The mean of the normal distribution. + + units:(same as base units);name:mu; + + + + + + The standard deviation of variates. + + units:(same as base units);name:sigma; + + + + + + + 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:Log-normal parameters; + + + + + The mean of the beta distribution (must be in the open range (0,1)). + + units:none;name:mean; + + + + + + The standard deviation of variates. + + units:none;name:variance; + + + + + + + Parameters of some distribution. The mean is that provided and the + standard deviation is cv*mean. + + Log-normal: + σ = cv * mean ; + μ = ln(mean) - σ² / 2 ; + X ~ ln N( μ, σ² ) ; + equivalent R sample: rlnorm(1, log(mean) - ((cv * mean)^2) / 2, cv * mean). + + name:Distribution parameters; + + + + + The mean of the distribution. + + units:(same as base units);name:mean; + + + + + + Coefficient of variance (mean * cv gives standard deviation). + + Must be specified when distribution is not constant. + + name:Coefficient of variance;units:unitless; + + + + + + Selects the distribution to use. + + const: constant (no distribution). Setting cv=0 has the same behaviour. + + lnorm: log-normal distribution + + 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; + + + + + + + + + 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; + + + + + + + + + + + + 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:interpolation; + + + + + + + + + + + + + + + + + + + + + Delay between reports; typically one time step but can be + greater. + + Can be specified in steps (e.g. 1t) or days (e.g. 5d). + + units:User defined (default: steps);name:Delay between reports; + + + + + + Also output during initialization. By default this is + disabled (only intervention-period data is output). This + should not be used for predictions, but can be useful for + model validation. + + In this mode, 'simulation time' is output as the first + column (in addition to 'timestep'), since 'timestep' is dis- + continuous across the start of the intervention period. + + units:Days;min:1;max:unbounded;name:During initialization; + + + + + + + + + + List of all active survey options. See model/mon/OutputMeasures.h for a list of + supported outputs. Should also be on the wiki. + + name:Name of quantity; + + + + + + List of survey times + + name:Survey times (time steps); + + + + + + + Time of a survey. A report will be made for those measures + enabled under SurveyOptions. Reported data is either from the + moment the survey is done (immediate data) or is collected + over the time since the previous survey, or in some cases + over a fixed time span (usually one year). + + Times can be specified in time steps, starting from 0, or as + a date (see monitoring/startDate), or in days (e.g. 15d) or + years (e.g. 1y). Relative times mean the time since the start + of the intervention period, and must be non-negative (zero is + valid, but some measures, e.g. nUncomp, will be zero). + + The simulation ends immediately after the last survey is taken. + + units:User defined (defaults to steps);min:0;name:Survey time; + + + + + + + + See repeatEnd's documentation. + name:Step of repetition;units:User defined; + + + + + + Either both repeatStep and repeatEnd should be present + or neither. If present, the survey is repeated every + repeatStep timesteps (i.e. if t0 is the initial time + and x is repeatStep, surveys 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; + + + + + For normal surveys, reporting=true. If set false, + quantities are measured but not reported. The reason for doing this is + to update conditions set on reportable measures. + + Multiple surveys may be given here for the same date, e.g. if using + "repeatStep" for both reporting and non-reporting surveys. These are + combined such that a maximum of one survey is carried out per time-step, + and the survey is reported if any of the listed surveys for this date is + configured as "reporting". + + Note that adding non-reporting surveys will not affect value output by + reported surveys, with the exception that generated psuedo-random numbers + may be altered (specifically, when any stochastic diagnostics are used in + surveys). + + + + + + + + + + + + Deprecated: limit above which a human's infection is reported + as patent. + + Alternative: do not specify this; instead specify "diagnostic". + + units:parasites/microlitre;min:0;name:Detection limit for parasitaemia; + + + + + + Name of a parameterised diagnostic to use in surveys (see + scenario/diagnostics). + + name:Name of monitoring diagnostic; + + + + + + + + List of age groups included in demography or surveys + + name:Age groups; + + + + + + Allows the configuration of multiple cohorts (output segregated + according to membership within specific sub-populations). + + If this element is omitted, monitoring surveys cover the entire + simulated human population. + + It does not affect the "continuous" outputs (these never take + cohorts into account). + + name:Cohorts; + + + + + + + Name of monitoring settings + + name:Name of monitoring settings; + + + + + + An optional date for the start of monitoring. If given, dates may be + used to specify when other events (surveys, intervention deployments) + occur; alternately times relative to the start of the intervention + period may be used to specify event times. + + Setting this to 1st January of some year might simplify usage of + dates, and putting the start a couple of years before the start of + intervention deployment (along with some extra surveys) may be useful + to check transmission stabilises to the expected pre-intervention + levels. + + As an example, if this date is set to 2000-01-01, then the following + event times are equivalent (assuming 1t=5d): + 15t, 75d, 0.2y, 2000-03-16. + + Must be in the form YYYY-MM-DD, e.g. 2003-01-01. + + name:Start of monitoring; + + + + + + + + + + + Lower bound of age group + + units:Years;min:0;max:100;name:lower bound of age group + + + + + + + + Upper bound of age group + + units:Years;min:0;max:100;name:upper bound of age group + + + + + + + + + Consider a certain sup-population a cohort, and segregate outputs + according to membership. Where multiple sub-populations are listed, + segregate output according to all combinations of membership: e.g. + if sub-populations A and B are listed, there will be outputs for + "member of A and B", "member of A but not B", "B but not A" and + "not a member of A or B". Listing n sub-populations implies 2^n + sets of outputs (each is further segregated by age groups, survey + times and enabled output measures, which could lead to excessive + program memory usage and output file size). + + To identify outputs, each sub-population has a power of two number + as identifier (see "number" attribute). Each of the 2^n output sets + is identified by a number: the output set is the output from humans + who are members in some set of sub-populations (S1, S2, ...) and + not members in some others (T1, T2, ...); the number identifying + the set is the sum of the numbers identifying the sets S1, S2, etc. + + In the output file, the output set is identified by multiplying + this number by 1000 then adding it to the age group column. + + name:Sub-population; + + + + + + + + + Textual identifier for the sub-population (i.e. for an intervention + component, since sub-populations are defined as the hosts an + intervention component is deployed to). + + name:Sub-population identifier; + + + + + + Number identifying a sub-population; used to define identifiers of + output sets. This number must be a power of 2 (i.e. 1, 2, 4, 8, ...). + See documentation of subPop element. + + name:Sub-population number;units:dimensionless;min:1;max:2097152; + + + + + + + + + + + If set, some statistics exclude humans who have been treated in the + recent past (precisely, when the time of last treatment was before + the current step and no more than health-system-memory days/steps + ago). + + This is a rough replacement for the REPORT_ONLY_AT_RISK option, + with one difference: the maximum age of treatment for + REPORT_ONLY_AT_RISK was fixed at 20 days. + + Affected measures include (as of version 35): + nHost (0), + nInfect(1), + nExpectd (2), + nPatent (3), + sumLogPyrogenThres (4), + sumlogDens (5), + totalInfs (6), + totalPatentInf (8), + sumPyrogenThresh (10), + nSubPopRemovalFirstEvent (62), + sumAge (68), + nInfectByGenotype (69), + nPatentByGenotype (70), + logDensByGenotype (71), + nHostDrugConcNonZero (72), + sumLogDrugConcNonZero (73). + + name:Report only for new cases; + + + + + + + + + + Number identifying this monitoring measure in the output + file (3rd column). Normally this is determined from the + measure, but it can be set manually, e.g. for when the same + measure is recorded twice (to accumulate across different + categories). + + name:Number identifying measure in output; + + + + + + If true, the measure is reported for each age category. If + false, values are summed across all age categories and only + the sum reported. If not specified, separate categories + will be reported if the measure supports this. + + name:Report by age category; + + + + + + If true, the measure is reported for each cohort separately. + If false, values are summed across all cohorts and only + the sum reported. If not specified, separate categories + will be reported if the measure supports this. + + name:Report by cohort; + + + + + + If true, the measure is reported for each mosquito species + separately. If false, values are summed across all species + and only the sum reported. If not specified, separate + categories will be reported if the measure supports this. + + name:Report by mosquito species; + + + + + + If true, the measure is reported for each parasite genotype + separately. If false, values are summed across all genotypes + and only the sum reported. If not specified, separate + categories will be reported if the measure supports this. + + name:Report by parasite genotype; + + + + + + If true, the measure is reported for each drug type + separately. If false, values are summed across all drug types + and only the sum reported. If not specified, separate + categories will be reported if the measure supports this. + + name:Report by drug type; + + + + + + + + + + + + + + + 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; + + + + + + + + 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; + + + + + + + + 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, otherwise the times of + all values specified must be less than the period, and values + are repeated modulo period (the step at time 'period+2t' + has same value as the step at '2t', etc.). + + 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; + + + + + + + + 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; + + + + + + + + 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; + + + + + + + + + + + + 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 + + + + + + + + + + + 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. + + name:Human-specific interventions; + + + + + + Name of set of interventions + name:Name of intervention set; + + + + + + + + + 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; + + + + + + + + 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; + + + + + + + + + + + + + + + + + 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:Component identifier; + + + + + + An informal name/description for the component + + name:Name of component; + + + + + + + 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 ...; + + + + + 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:Time to first episode only; + + + + + + 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: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; + + + + + + + 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; + + + + + + + + + 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; + + + + + + + + + + + + + List of timed vector population intervention deployment + + name:Vector population intervention deployment; + + + + + + + Name of intervention (e.g. larviciding, sugar bait). + + name:Name of intervention; + + + + + + + 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 + + + + + + + + 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 + + name:Descriptive name for type of trap; + + + + + + + + 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; + + + + + + + + Proportion of otherwise eligible individuals who will receive this + deployment. + + units:dimensionless;min:0;max:1;name:Coverage; + + + + + + 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. + + name:Vaccine min previous doses;units:inoculations;min:0; + + + + + + 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; + + + + + + + + + + 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; + + + + + + + + + + + + + + + + + + + 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). + + units:User defined (defauls to steps);name:End step; + + + + + + + + + + + + + + + + + + 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. + + name:Restrict to sub-population; + + + + + 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; + + + + + + 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:Complement; + + + + + + 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; + + + + + + + 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; + + + + + + + + + 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; + + + + + + 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; + + + + + + + + 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 + + + + + + + + + Name of the species/subspecies/variant. + + name:Species/subspecies/variant name + + + + + + + + + + + + Description of transmission setting for models without vector control interventions + (included for backward compatibility) + + name:Transmission setting (vector control not enabled); + + + + + Parameters of the transmission model + name:Transmission setting (vector control enabled); + + + + + + + + + + Name of this species of non human hosts (must match up + with those described per anopheles section). + + name:Species of alternative host; + + + + + + Population size of this non-human host. + + Note: the availability of the population of this type of non-human host is + determined by mosqRelativeEntoAvailability and mosqHumanBloodIndex. + NHHs are not modelled individually, thus this parameter is not used. It + might be useful in the future if there is ever an intervention to change + the number of non-human hosts. + + units:Animals;name:Population size of non-human host species; + + + + + + + + + + + + + Name of entomology data + + name:Entomology dataset name; + + + + + + Transmission simulation mode: may be forced (in which case interventions + and changes to human infectiousness cannot affect EIR) or dynamic (in + which the above can affect EIR). The full vector model is only used in + dynamic mode. This can not be changed by interventions, except for the + changeEIR intervention for the non-vector model which replaces the EIR + with a new description (used in forced mode). + + name:Transmission model mode; + + + + + + + + + + + + If set, the annual EIR (for all species of vector) is scaled to this + level; can be omitted if not needed. + + units:Infectious bites per adult per year;name:Override annual EIR; + + + + + + + + + + The duration of sporogony in days + units:Days;name:Duration of sporogony; + + + + + + + In the non-vector model, EIR is input as a sequence of daily values. + There must be at least one years' worth of entries (365), and if there + are more, values are wrapped and averaged (i.e. value for first day + of year is taken as the mean of values for days 0, 365+0, 2*365+0, + etc.). + + units:Infectious bites per adult per day;name:Daily Entomological Inoculation Rate;exposed:false; + + + + + + + + name:Time origin of EIR sequence;exposed:false; + + + + + + + + Description of input EIR for + one specific vector species in terms of a Fourier approximation + to the ln of the EIR during the burn in period + name:Description of input EIR for one vector; + + + + + Specifies the seasonality of transmission + and optionally the level of annual transmission. + name:Seasonality of transmission; + + + + + + + + Seasonality is reproduced from the exponential of a fourier + series specified by the following coefficients. Note that + the a0 term is not needed; the annualEIR attribute of the + seasonality element should be used to scale EIR instead. + + units:Infectious bites per adult per day;name:Fourier approximation to pre-intervention EIR; + + + + + + + A pair of Fourier series coefficients. The first element + specifies a1 and b1, the second a2 and b2, etc. Any number + (from 0 up) of pairs may be given. + + name:Pair of Fourier coefficients; + + + + + + a_n parameter of Fourier approximation to ln(EIR) for + some natural number n. + + name:a_n parameter of Fourier approximation to ln(EIR); + + + + + + b_n parameter of Fourier approximation to ln(EIR) for + some natural number n. + + name:b_n parameter of Fourier approximation to ln(EIR); + + + + + + + + + Rotation angle defining the origin of the Fourier approximation to ln (EIR) + + units:Radians;name:Rotation angle defining the origin of the Fourier approximation to ln (EIR); + + + + + + + + Description of seasonality from monthly values. Multiple + smoothing methods are possible (see smoothing attribute). + + List should contain twelve entries: January to December. + + name:List of monthly values; + + + + + + + Monthly value + + units:(see "seasonality input" parameter);name:Monthly value; + + + + + + + How the monthly values are converted into a daily + sequence of values: + + 1) none: no smoothing (step function) + + 2) Fourier: a Fourier series (with terms up to a2/b2) + is fit to the sequence of monthly values and used to + generate a smoothed list of daily values. + + name:Smoothing function; + + + + + + + + + + + + + + Description of seasonality from daily values. + + List should contain 365 entries: 1st January to 31st December. + + name:List of daily values; + + + + + + + Daily value + + units:(see "seasonality input" parameter);name:Daily value; + + + + + + + + + + Specify what seasonality measure is given. + + At the moment, only EIR is supported, but in the future, all the + below should be supported. + + EIR: seasonality of entomological inoculations is input. + Units: entomological inoculations per adult per annum. + + hostSeeking: seasonality of densities of flying host-seeking + mosquitoes is input (in the model this is notated N_v). + Units: mosquitoes. + + emergence: seasonality of emergence pupa into adults. + Units: mosquitoes. + + larvalResources: seasonality of larval resources. Units: X. + + name:Seasonality input; + + + + + + + + + + If this attribute is included, EIR for this + species is scaled to this level. Note that if the scaledAnnualEIR + attribute of the entomology element is also used, EIR is scaled + again, making this attribute the EIR relative to other species. + + With some seasonality inputs, this attribute is optional, in which + case (if scaledAnnualEIR is also not specified) transmission depends + on all parameters of the vector. With some seasonality inputs, + however, this parameter must be specified. + name:Annual EIR;units:Inoculations per adult per annum;min:0; + + + + + + + Parameters describing the feeding cycle and human + mosquito interaction of a single species of anopheles mosquito. + + name:Mosquito feeding cycle parameters; + + + + + + name:Duration of the resting period of the vector (days); + units:Days;name:Duration of the resting period of the vector; + + + + + name:Extrinsic incubation period (days) + units:Days;name:Extrinsic incubation period; + + + + + Proportion of mosquitoes host seeking on same day as ovipositing + units:Proportion;name:Proportion of mosquitoes host seeking on same day as ovipositing; + + + + + Duration of the host-seeking period of the vector (days) + units:Days;name:Duration of the host-seeking period of the vector; + + + + + Probability that the mosquito survives the feeding cycle + units:Proportion;name:Probability that the mosquito survives the feeding cycle; + + + + + Variance in availability rate of humans to + mosquitoes. The mean rate is calculated based on other parameters. + + name:Variance in human availability rate + + + + + Probability that the mosquito succesfully bites chosen host + name:Probability that the mosquito succesfully bites chosen host; + + + + + Probability that the mosquito escapes host and finds a resting place after biting + name:Probability that the mosquito escapes host and finds a resting place after biting; + + + + + Probability of mosquito successfully resting after finding a resting site + name:Probability of mosquito successfully resting after finding a resting site; + + + + + Probability of a mosquito successfully laying eggs given that it has rested + name:Probability of a mosquito successfully laying eggs given that it has rested; + + + + + The proportion of resting mosquitoes which fed on human blood during the last feed. + units:Proportion;name:Human blood index; + + + + + + If less than this many mosquitoes remain infected, transmission is interrupted. + name:Mininum infected threshold for mosquitos;min:0; + + + + + + + + Parameters describing the life-cycle of this species of mosquito + + name:Mosquito life cycle parameters; + + + + + + + Parameters for the egg stage of development + + name:Egg stage; + + + + + + + + + Parameters for the larval stage of development + + name:Larval stage; + + + + + + List of parameters which apply during the larval + stage of development. List length must equal stage + duration, with first item corresponding to first + 24 hours after hatching, second item to hours + 24-48, and so on. + + name:Daily development; + + + + + + Resource usage during larval stage of development. + Units are arbitrary. + + name:Resource usage;units:X; + + + + + + Effect of competition over resources on development. + + name:Effect of competition;units:none; + + + + + + + + + + + + + Parameters for the pupal stage of development + + name:Pupal stage; + + + + + + The total number of female eggs laid by a female mosquito at + the conclusion to a feeding cycle, after feeding on an + unprotected human (non-human hosts and protected humans + use a multiplication factor to adjust this number for + mosquitoes feeding on them). + + units: Eggs per feeding cycle; name:Eggs laid by ovipositing mosquito; + + + + + + + An estimate of mean annual availability of resources to larvae. + Used to get the resource usage fitting algorithm going; if the + algorithm fails to fit the resource availability then tweaking + this parameter may help. In other cases tweaking this parameter + shouldn't be necessary. + + Default value is 10⁸ (1e8). Units are arbitrary but must be the same as + those used by the resourceUsage parameter. + + units: see resourceUsage;name:Estimate of larval resources;units:X + + + + + + + + Parameters describing the simple mosquito population dynamics model. + + This is a simpler version of the life-cycle model, requiring less + parameters and with much simpler initialisation. + + name:Simple Mosq-Pop-Dynamics parameters; + + + + + + + Duration from egg laying to emergence in days. + + units: Days; name:Duration; min:1; + + + + + + Probability that mosquito survives from the egg being laid to emergence, + given no resouce limitations (no density constraints). + + units:Proportion; name:Probability of survival; min:0; max:1; + + + + + + The total number of female eggs laid by a female + mosquito at the conclusion to a feeding cycle. + + units: Eggs per feeding cycle; name:Eggs laid by ovipositing mosquito; + + + + + + + + Non human host parameters, per type of host (must + match up with non-species-specific parameters). + min:0; name:Alternative (non-human) host paramters; + + + + + + + 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:Relative fecundity of biting mosquitoes; + + + + + + Identifier for this category of non-human hosts + name:Identifier for this category of non-human hosts; + + + + + + + + Identifier for this anopheles species + name:Identifier for this anopheles species; + + + + + Initial guess of the proportion of mosquitoes which are infected, o: O_v(t) = o*N_v(t). Only used as a starting value. + units:Proportion;min:0;max:1;name:Initial estimate of proportion of mosquitoes infected (ρ_O);exposed:false; + + + + + Initial estimate of the proportion of mosquitoes which are infectious, s: S_v(t) = s*N_v(t). Used as a starting value and then fit. + units:Proportion;min:0;max:1;name:Initial estimate of proportion of mosquitoes infectious (ρ_S);exposed:false; + + + + + + + Parameters associated with a mosquito development stage. + + name:Mosquito development-stage parameters; + + + + + Duration of the stage (i.e. length of time mosquito is an + egg/larva/pupa). + + units: Days; name:Duration; + + + + + + Probability that mosquito survives this size (probability of egg + hatching, a larva becoming a pupa or a pupa emerging as an adult, + at the start of that stage). + + units:Proportion; name:Probability of survival; + + + + + + + + + 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; + + + + + + + + + + + + + + + + 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; + + + + + + Quantity to multiply the dose by. Only option is "kg" + (patient weight in kg). + + 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; + + + + + + + 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:Locus; + + + + + + + + + + + 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 sigma > 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. + + 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; + + + + + + + + + Volume of Distribution + + units:l/kg;min:0;name:Volume of Distribution (Vd); + + + + + + + + Distribution parameter describing per-human variation of + volume of distribution. If zero or not specified, + the parameter is not sampled. See documentation of + parent element. + + name:Sigma parameter for per-human variation of 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). The parameter + k12 = a12 / m where m is the body mass (kg). + + It is sampled per-patient when sigma > 0. + + units:day^-1;min:0;name:Absorption rate to compartment 2 (a12); + + + + + + Absorption rate from the first periphery compartment + (2) to the central compartment. The parameter + k21 = a21 / m where m is the body mass (kg). + + It is sampled per-patient when sigma > 0. + + units:day^-1;min:0;name:Absorption rate from compartment 2 (a21); + + + + + + + + + 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). The parameter + k13 = a13 / m where m is the body mass (kg). + + It is sampled per-patient when sigma > 0. + + units:day^-1;min:0;name:Absorption rate to compartment 3 (a13); + + + + + + Absorption rate from the second periphery compartment + (3) to the central compartment. The parameter + k31 = a31 / m where m is the body mass (kg). + + It is sampled per-patient when sigma > 0. + + units:day^-1;min:0;name:Absorption rate from compartment 3 (a31); + + + + + + + + + + + + + + + + + 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; + + + + + + + + k1 — Maximal parasite killing rate. + + units:1/days;min:0;name:Maximal parasite killing rate; + + + + + + Half maximal effect concentration. If sigma > 0, the IC50 is + sampled for each infection from a log-normal distribution with mean + of this value and the sigma value specified, i.e. + X ~ log N( log(mean) - s^2 / 2, s^2 ) . + + units:mg/l;min:0;name:IC50; + + + + + + + + Distribution parameter describing per-infection variation of + IC50. If zero or not specified, the IC50 is not sampled. See + documentation of parent element. + + name:Sigma parameter for per-infection variation of IC50; + + + + + + + + + + n — Slope of the concentration effect curve + + units:dimensionless;name:Slope of effect curve; + + + + + + + Name of the phenotype; for documentation use only. + + name:Name of phenotype; + + + + \ No newline at end of file diff --git a/schema/util.xsd b/schema/util.xsd index 6bf4cc484..99f53f5b2 100644 --- a/schema/util.xsd +++ b/schema/util.xsd @@ -3,8 +3,8 @@ Copyright © 2005-2011 Swiss Tropical Institute and Liverpool School Of Tropical Medicine Licence: GNU General Public Licence version 2 or later (see COPYING) --> - diff --git a/test/scenario1.xml b/test/scenario1.xml index e63302bae..6779a5944 100644 --- a/test/scenario1.xml +++ b/test/scenario1.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenario10.xml b/test/scenario10.xml index edaa52d0c..a31fbf71f 100644 --- a/test/scenario10.xml +++ b/test/scenario10.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenario11.xml b/test/scenario11.xml index d1de0baea..719517b5e 100644 --- a/test/scenario11.xml +++ b/test/scenario11.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenario12.xml b/test/scenario12.xml index 95b4285c1..400061b10 100644 --- a/test/scenario12.xml +++ b/test/scenario12.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenario2ITNs.xml b/test/scenario2ITNs.xml index 2160e98ad..01c6f1b74 100644 --- a/test/scenario2ITNs.xml +++ b/test/scenario2ITNs.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenario4.xml b/test/scenario4.xml index 45cd130f9..18d4242d0 100644 --- a/test/scenario4.xml +++ b/test/scenario4.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenario5.xml b/test/scenario5.xml index 4a236d13e..885fbae9a 100644 --- a/test/scenario5.xml +++ b/test/scenario5.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenario6.xml b/test/scenario6.xml index 4f013d63f..b496928f2 100644 --- a/test/scenario6.xml +++ b/test/scenario6.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenario9.xml b/test/scenario9.xml index 1a474de4e..e552c7dfd 100644 --- a/test/scenario9.xml +++ b/test/scenario9.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioCohort.xml b/test/scenarioCohort.xml index 926c0c73b..617143d0f 100644 --- a/test/scenarioCohort.xml +++ b/test/scenarioCohort.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioESTS.xml b/test/scenarioESTS.xml index ed75c610b..0de419269 100644 --- a/test/scenarioESTS.xml +++ b/test/scenarioESTS.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioEffectiveDrug.xml b/test/scenarioEffectiveDrug.xml index c708fff79..788785c0f 100644 --- a/test/scenarioEffectiveDrug.xml +++ b/test/scenarioEffectiveDrug.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioEmpirical.xml b/test/scenarioEmpirical.xml index 00f25c50c..167bd1a38 100644 --- a/test/scenarioEmpirical.xml +++ b/test/scenarioEmpirical.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioGenotypes.xml b/test/scenarioGenotypes.xml index dabd057fc..1192e9a8f 100644 --- a/test/scenarioGenotypes.xml +++ b/test/scenarioGenotypes.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioIRS30.xml b/test/scenarioIRS30.xml index 7645f96d3..5dd68fdb8 100644 --- a/test/scenarioIRS30.xml +++ b/test/scenarioIRS30.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioKK_20150612.xml b/test/scenarioKK_20150612.xml index a609d0cbd..9b0b26728 100644 --- a/test/scenarioKK_20150612.xml +++ b/test/scenarioKK_20150612.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioLifeNet1.xml b/test/scenarioLifeNet1.xml index 72313ee9e..5d32abcce 100644 --- a/test/scenarioLifeNet1.xml +++ b/test/scenarioLifeNet1.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioLifeNet2.xml b/test/scenarioLifeNet2.xml index fb764adbe..952cad7b0 100644 --- a/test/scenarioLifeNet2.xml +++ b/test/scenarioLifeNet2.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioMSAT.xml b/test/scenarioMSAT.xml index 7560aa15c..f11e014d2 100644 --- a/test/scenarioMSAT.xml +++ b/test/scenarioMSAT.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioMolPairwise.xml b/test/scenarioMolPairwise.xml index 6e2a63d61..d57a21761 100644 --- a/test/scenarioMolPairwise.xml +++ b/test/scenarioMolPairwise.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioMolineaux.xml b/test/scenarioMolineaux.xml index b8cf10684..29fa2a7df 100644 --- a/test/scenarioMolineaux.xml +++ b/test/scenarioMolineaux.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioNamawalaArabiensis.xml b/test/scenarioNamawalaArabiensis.xml index 224b5800f..dd1040a86 100644 --- a/test/scenarioNamawalaArabiensis.xml +++ b/test/scenarioNamawalaArabiensis.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioNoInterv.xml b/test/scenarioNoInterv.xml index 0ab576189..8de6dedfa 100644 --- a/test/scenarioNoInterv.xml +++ b/test/scenarioNoInterv.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioNoMPDLarviciding.xml b/test/scenarioNoMPDLarviciding.xml index 11abf990e..fa150ae69 100644 --- a/test/scenarioNoMPDLarviciding.xml +++ b/test/scenarioNoMPDLarviciding.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioPenny.xml b/test/scenarioPenny.xml index 3b7f2addb..a4478f5b5 100644 --- a/test/scenarioPenny.xml +++ b/test/scenarioPenny.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioRach5IC.xml b/test/scenarioRach5IC.xml index 729446c9e..9a27e4ace 100644 --- a/test/scenarioRach5IC.xml +++ b/test/scenarioRach5IC.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioSimpleMPDLarviciding.xml b/test/scenarioSimpleMPDLarviciding.xml index bbb5994d2..439798419 100644 --- a/test/scenarioSimpleMPDLarviciding.xml +++ b/test/scenarioSimpleMPDLarviciding.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioSimpleMPDTest.xml b/test/scenarioSimpleMPDTest.xml index 220acf5d2..7618f1e6e 100644 --- a/test/scenarioSimpleMPDTest.xml +++ b/test/scenarioSimpleMPDTest.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioSubPopRemoval.xml b/test/scenarioSubPopRemoval.xml index 496595538..856f21d79 100644 --- a/test/scenarioSubPopRemoval.xml +++ b/test/scenarioSubPopRemoval.xml @@ -1,5 +1,5 @@ - + diff --git a/test/scenarioTrapTest.xml b/test/scenarioTrapTest.xml index 0da791bdf..d997e71c4 100644 --- a/test/scenarioTrapTest.xml +++ b/test/scenarioTrapTest.xml @@ -1,5 +1,5 @@ - +