diff --git a/schema/scenario_46.xsd b/schema/scenario_46.xsd new file mode 100644 index 00000000..d25930d9 --- /dev/null +++ b/schema/scenario_46.xsd @@ -0,0 +1,6472 @@ + + + + + + + + + + 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 + + + + + + + + + + + + + + + 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; + + + + + + If true, marks this allele as having deleted HRP2. + + The effect on the simulation is that any diagnostic dependent on HRP2 + behaves as if infections with deleted HRP2 have density 0. + + A diagnostic MUST explicitly set mechanism="HRP2" for this to have any + effect. + + name:HRP2 deletion; + + + + + + + + + + + + + + + + + + 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; + + + + + + + + + + + + + Mechanism by which this diagnostic functions. + + Possible values are: HRP2, Other. In the case of HRP2, infections with + an hrp2_deletion will be invisible to this diagnostic. In the case of + Other, the diagnostic is unaffected by infection genome. + + The diagnostic used for monitoring cannot use HRP2. (This is a + restriction made to simplify implementation.) + + name:Mechanism; + + + + + + + + + + + + + + + + + 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 deterministically, based on the outcome + of some type of diagnostic. + + name:Switch (diagnostic); + + + + + + + + + An optional piece of documentation attached to this node. + + name:Name; + + + + + + 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:Number of days to look back for fevers. This must be less than or equal to the healthsystem memory parameter. In general, this should be less than or equal to the repeatStep in MSAT with contiuous deployment; + + + + + + + + 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; + + + + + + This increments measure 80 (nCMDTReport) by one every time this node is visited. This can be useful to report the results of mass test and treat interventions using the decision tree. + name:DT Report; + + + + + An optional piece of documentation attached to this node. + + name:Name; + + + + + + 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); + + + + + + + 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; + + + + + + + + + + + + + + + + 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. + + If period is less than the length of the simulation's intervention phase, + then all "rate" deployments are repeated with this periodicity. + In this case, the first "rate" deployment must coincide with the start of + the intervention phase (monitoring/startDate). + + Can be specified in steps (e.g. 1t) or days (e.g. 365d). + + name:Period of repetition;units:User defined (default: steps);min:0 + + + + + + + + + Name of intervention + + name:Name of intervention; + + + + + + + + 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 + + + + + + + + + + List of interventions that modify parameters of non-human hosts described in the <entomology> <vector> <anopheles>. + + + + + + + + + + List of intervention that add new non-human hosts that have not been described in the <entomology> <vector> +<anopheles> <nonHumanHosts>. + + + + + + + + + + + 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; + + + + + + Minimum ento availability percentile. + + This option is meant to be used with heterogeneity of availability, which can be specified in the entomology section. Without heterogenity (default), all hosts have the same availability and this option will have no effect. + + The percentile must be an integer value between 0 and 100. Percentile 99th represents individuals who are more available than 99% of the population. Percentile 0 represents the least available individuals. 100 is equivalent for infinity. + + units:percent;min:0;name:Minimum ento availability; + + + + + + Maximum ento availability percentile. + + This option is meant to be used with heterogeneity of availability, which can be specified in the entomology section. Without heterogenity (default), all hosts have the same availability and this option will have no effect. + + The percentile must be an integer value between 0 and 100. Percentile 99th represents individuals who are more available than 99% of the population. Percentile 0 represents the least available individuals. 100 is equivalent for infinity. + units:percent;min:0;name:Maximum ento availability; + + + + + + + + + + Time at which this deployment occurs. + + See doc on intervention period and on monitoring/startDate for + details of how times work. Can be specified in steps, days, + years, or as a date (examples: 15t, 75d, 0.2y, 2000-03-16). + + name:Time;units:User defined (defauls to steps);min:0; + + + + + + Maximum age of eligible individuals (defaults to no limit). + + Input is rounded to the nearest time step. + + units:Years;min:0;name:Maximum age of eligible individuals; + + + + + + Minimum age of eligible individuals (defaults to 0). + + Input is rounded to the nearest time step. + + units:Years;min:0;name:Minimum age of eligible individuals; + + + + + See repeatEnd's documentation. + name:Step of repetition;units:User defined; + + + + + + Either both repeatStep and repeatEnd should be present + or neither. If present, the deployment is repeated every + repeatStep timesteps (i.e. if t0 is the initial time + and x is repeatStep, depolyments are done at times t0, + t0+x, t0+2*x, ...), ending before repeatEnd + (final repetition is the one before repeatEnd). + + Note that repeatEnd may be specified as a date but + repeatStep must be a duration (days, steps or years). + + name:End of repetition (exclusive);units:User defined; + + + + + + + + + + + + + + + + + + + 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; + + + + + + Pharmaco-Dynamic parameters for some resistance phenotype. + + To model resistance to this drug, describe multiple infection + phenotypes (with respect to these PD parameters) and list one + or more "restrict" elements for each phenotype. + + Loci are specified elsewhere. Multiple loci may influence the + action of a single drug and each locus may influence multiple + drugs. + + name:PD parameters for some allele / resistance phenotype; + + + + + + + name:Description + + + + + + Usage of nets by humans, from 0 to 1. + + At the moment this is constant across humans and deterministic: + relative attractiveness and survival factors are + base*(1-usage*propActing) + intervention_factor*usage*propActing. + + See also "propActing" (proportion of bits for which net acts). + + units:dimensionless;min:0;max:1;name:Proportion of time nets are used by humans; + + + + + + The rate at which new holes are made in nets. + + nHoles(t) = nHoles(t-1) + X where X~Pois(R/T) where T is the number + of time-steps per year. R is sampled from + log-normal: R ~ log N( log(mean)-sigma²/2, sigma² ) and is covariant + with ripRate and insecticideDecay. (To be exact, a single Gaussian + sample is taken, adjusted for each sigma then exponentiated.) + + units:Holes per annum;min:0;name:Rate at which holes are made; + + + + + + Each existing hole has a probability of being ripped bigger according + to a Poisson process with this rate as (only) parameter. + + New rips occur in a net at rate X~Pois(h×R/T) where h is the number + of existing holes and T the number of time-steps per year. R is + sampled from log-normal: R ~ log N( log(mean)-sigma²/2, sigma² ) + and is covariant with holeRate and insecticideDecay. (To be exact, a + single Gaussian sample is taken, adjusted for the each and sigma + then exponentiated.) + + units:Rips per existing hole per annum;min:0;name:Rate at which holes are enlarged; + + + + + + This factor expresses how important rips are in increasing the hole. + + The hole index of a net is h + F×x where h and x are the total numbers + of holes and rips respectively and F is the rip factor. + + units:none;min:0;name:Rip factor; + + + + + + The insecticide concentration of new nets is Gaussian distributed with + mean "mu" and a standard deviation "sigma". The standard deviation + should be small relative to the mean to avoid negative initial + concentration. Any negative values sampled are set to 0. + + units:mg/m²;min:0;name:Initial insecticide; + + + + + + Decay curve for insecticide content of nets. Documentation: see DecayFunction + type or https://github.com/SwissTPH/openmalaria/wiki/ModelDecayFunctions + + The distribution of decay rates over nets is covariant with the + distribution of ripRate and holeRate over nets. This distribution is + generated by taking one sample per net from a Gaussian distribution + with mean 0 and standard deviation 1. For each variable, the sample + is multiplied by the respective sigma and a constant added such that, + once exponentiated, the mean of the variable over nets is 1. The + variable is then exponentiated and multiplied by the required mean + rate for the respective variable. + + units:none;name:Decay of insecticide; + + + + + + Specifies the rate at which nets are disposed of over time. + Documentation: see DecayFunction type or + https://github.com/SwissTPH/openmalaria/wiki/ModelDecayFunctions + + In the current model, nets are disposed of randomly (no correlation + with state of decay) such that the chance of each net surviving until + age t is the value of this decay function at time t. Equivalently + (where a large number of nets are distributed at the same time), the + proportion of nets remaining in use should match this decay function + over time. + + Humans are removed from the intervention component's sub-population + on disposal (attrition) of their nets. Currently this event is not + reported. + + units:dimensionless;name:Attrition of nets; + + + + + + + + + Used by logit attacking and killing models only, holeIndexMax + is a user defined maximum hole index (typically, the total surface area of a net). + + units:in same unit as holeIndex;name:maximum of holed surface area that has an effect (comparable to no net) + + + + + + + Effect of net on attractiveness of humans to mosquitoes relative to + an unprotected adult human. Parameterisations should take into + account that mosquitoes do not always bite indoors. + + Attractiveness of the human is multiplied by + exp(log(H)×h + log(P)×p + log(I)×h×p + where H, P and I are the hole, insecticide and interaction factors + respectively, h=exp(-holeIndex×holeScalingFactor) and + p=1−exp(-insecticideContent×insecticideScalingFactor). + + units:dimensionless;min:0;max:1;name:Relative attractiveness; + + + + + + Effect of net on attractiveness of humans to mosquitoes relative to + an unprotected adult human. Parameterisations should take into + account that mosquitoes do not always bite indoors. + + This deterrency model multiplies human attractiveness by + pEnt×pAtt. + + units:dimensionless;name:Relative attractiveness; + + + + + + + + pEnt represents the relative probability of entering due to + ITNs: pEnt = exp(log(P)×p) where P is the insecticide + factor and + p=1−exp(-insecticideContent×insecticideScalingFactor). + + units:dimensionless;name:Deterrency: entering; + + + + + + pEnt represents the relative probability of entering due to insecticide + in the hut: + pEnt = exp(logit.pEnt) / (exp(logit.pEnt) + 1) + logit.pEnt = B + P * p + where B is the basefactor (without net); P is insecticide factor, and + p = log(insecticideContent+1). + Without a net, probability of entering a house is + pEnt0 = exp(logit.pEnt0) / (exp(logit.pEnt0) + 1) + logit.pEnt0 = B + Entering of mosquitoes is adjusted via multiplication by pEnt / pEnt0. + To keep this in the range [0,1], we (normally) require that + pEnt ≤ pEnt0 + and thus P ≤ 0 and give a warning if this is not fulfilled. + + units:dimensionless;name:Deterrency: entering (logit model); + + + + + + + + pAtt represents the relative probability of attacking a human after + entering a house due to ITNs (i.e. of feeding/dying vs. flying off): + pAtt = B + H×h + P×p + I×h×p + where B is the base (without net) probability; H, P and I are the hole, + insecticide and interaction factors respectively, + h=exp(-holeIndex × holeScalingFactor) + and + p=1 - exp(-insecticideContent × insecticideScalingFactor). + + units:dimensionless;name:Deterrency: attacking; + + + + + + pAtt represents the relative probability of attacking a human + after entering a house due to ITNs (i.e. of feeding/dying vs. + flying off): + pAtt = exp(logit.pAtt) / (exp(logit.pAtt) + 1) + logit.pAtt = B + H×min(h, hMax) + P×p + I×min(h, hMax)×p + where B is the base factor (without net); H, P and + I are the hole, insecticide and interaction factors + respectively, and: + h = log(holeIndex + 1) + p = log(insecticideContent + 1) + Without a net, probability of attacking a human + after entering a house is + pAtt0 = exp(logit.pAtt0) / (exp(logit.pAtt0) + 1) + logit.pAtt0 = B + H×hMax + where hMax=log(holeIndexMax + 1) and holeIndexMax is a user defined + maximum hole index (typically, the total surface area of a net). + Attacking of mosquitoes is adjusted via multiplication by pAtt / pAtt0. + This may be larger and smaller than 1 (but will not be negative). + By definition (through the logit transformation) pAtt0 > 0. + + units:dimensionless;name:Deterrency: attacking (logit model); + + + + + + + + + + + + Effect of net on survival mosquitoes as they seek to bite a human + after choosing that human, relative to the same person not + sleeping under a net. Parameterisations should take into + account that mosquitoes do not always bite indoors. + + Killing proportion is calculated as K = B + H×h + P×p + I×h×p + where B is the base (without net) probability of death, + H, P and I are the hole, insecticide and interaction factors + respectively, h=exp(-holeIndex×holeScalingFactor) and + p=1−exp(-insecticideContent×insecticideScalingFactor). + + Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−B). + To keep this in the range [0,1], we require that B+H ≤ 1, B+P ≤ 1, + B+H+P+I ≤ 1, H ≥ 0, P ≥ 0 and H+P+I ≥ 0. + + units:dimensionless;min:0;max:1;name:Pre-prandial killing effect; + + + + + + Effect of net on survival mosquitoes as they seek to bite a human + after choosing that human, relative to the same person not + sleeping under a net. + Killing proportion is calculated as + K=exp(logit.K)/(exp(logit.K)+1) + logit.K = B + H×min(h,hMax) + P×p + I×min(h,hMax)×p + where B is the basefactor (without net), + H, P and I are the hole, insecticide and interaction factors + respectively, h=log(holeIndex+1) and + p=log(insecticideContent+1). + Without a net, the killing proportion + K0=exp(logit.K0)/(exp(logit.K0)+1) + logit.K0 = B + H×hMax + where hMax=log(holeIndexMax+1) and holeIndexMax is a user defined maximum hole index (typically, the total surface area of a net). + Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−K0). + To keep this in the range [0,1], we require that K ≥ K0. We enforce that P ≥ 0 (It would not make sense biologically if P were negative) and P+I*hMax ≥ 0 and H ≤ 0 and holeIndex ≤ holeIndexMax and give a warning if these conditions are not fulfilled. + + units:dimensionless;min:0;max:1;name:Pre-prandial killing effect (logit); + + + + + + + + Effect of net on survival mosquitoes as they seek to escape from + a human host and rest after a blood meal, relative to the same + person not sleeping under a net. Parameterisations should take + into account that mosquitoes do not always bite indoors. + + Killing proportion is calculated as K = B + H×h + P×p + I×h×p + where B is the base (without net) probability of death, + H, P and I are the hole, insecticide and interaction factors + respectively, h=exp(-holeIndex×holeScalingFactor) and + p=1−exp(-insecticideContent×insecticideScalingFactor). + + Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−B). + To keep this in the range [0,1], we require that B+H ≤ 1, B+P ≤ 1, + B+H+P+I ≤ 1, H ≥ 0, P ≥ 0 and H+P+I ≥ 0. + + units:dimensionless;min:0;max:1;name:Post-prandial killing effect; + + + + + + Effect of net on survival mosquitoes as they seek to escape from + a human host and rest after a blood meal, relative to the same + person not sleeping under a net. + Killing proportion is calculated as + K=exp(logit.K)/(exp(logit.K)+1) + logit.K = B + H×min(h,hMax) + P×p + I×min(h,hMax)×p + where B is the basefactor (without net), + H, P and I are the hole, insecticide and interaction factors + respectively, h=log(holeIndex+1) and + p=log(insecticideContent+1). + Without a net, the killing proportion + K0=exp(logit.K0)/(exp(logit.K0)+1) + logit.K0 = B + H×hMax + where hMax=log(holeIndexMax+1) and holeIndexMax is a user defined maximum hole index (typically, the total surface area of a net). + Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−K0). + To keep this in the range [0,1], we require that K ≥ K0. We enforce that P ≥ 0 (It would not make sense biologically if P were negative) and P+I*hMax ≥ 0 and H ≤ 0 and holeIndex ≤ holeIndexMax and give a warning if these conditions are not fulfilled. + + units:dimensionless;min:0;max:1;name:Post-prandial killing effect (logit); + + + + + + + + Effect of net on fertility of mosquitoes who survive feeding + on a protected human, relative to an unprotected human. + + Fertility (number of eggs laid) is multiplied by (1-K) / (1-B), + similar to killing effects. This is not allowed to be greater than 1. + + name:Fecundity reduction; + + + + + + Effect of net on fertility of mosquitoes who survive feeding + on a protected human, relative to an unprotected human. + + Fertility (number of eggs laid) is multiplied by (1-K) / (1-K0), + similar to killing effects. This is not allowed to be greater than 1. + + name:Fecundity reduction (logit); + + + + + + + + Name of the affected anopheles-mosquito species. + + name:Mosquito species; + + + + + + Deprecated: propActive can still be used but its value must be set to either 0 or 1. + Any other value will result in an error at initialization. + + The proportion of bites, when nets are in use, for which the net + has any action whatsoever on the mosquito. + + At the moment this is constant across humans and deterministic: + relative attractiveness and survival factors are + base*(1-usage*propActing) + intervention_factor*usage*propActing. + + See also "usage" (proportion of time nets are used by humans). + + units:dimensionless;min:0;max:1;name:Proportion of bites for which net acts; + + + + + + + + + + + + Usage of Generic vector interventions, from 0 to 1. + + units:dimensionless;min:0;max:1;name:Proportion of generic vector interventions; + + + + + + Description of decay of all intervention effects. + Documentation: see DecayFunction type or + https://github.com/SwissTPH/openmalaria/wiki/ModelDecayFunctions + + name:Decay; + + + + + name:Per-mosquito species parameters; + + + + + + + Effect of intervention on attractiveness of humans to mosquitoes relative to + an unprotected adult human. Parameterisations should take into + account that mosquitoes do not always bite indoors. + + Attractiveness of the human is multiplied this factor times + survival of effect. + + units:dimensionless;min:0;max:1;name:Relative attractiveness + + + + + + Effect of intervention on survival of mosquitoes as they seek to bite a human + after choosing that human, relative to the same person not + protected by the intervention. Parameterisations should take into account + that mosquitoes do not always bite indoors. This parameter has + been added since some data shows IRS to have a preprandial + killing effect. + + Killing proportion is this factor multiplied by survival of effect. + + units:dimensionless;min:0;max:1;name:Pre-prandial killing effect + + + + + + Effect of intervention on survival of mosquitoes as they seek to escape from + a human host and rest after a blood meal, relative to the same + person not protected by the intervention. Parameterisations should take + into account that mosquitoes do not always bite indoors. + + Killing proportion is this factor multiplied by survival of effect. + + units:dimensionless;min:0;max:1;name:Post-prandial killing effect + + + + + + Effect of intervention on fertility mosquitoes after successfully feeding on + a human host, relative to an unproteced human. Parameterisations should take + into account that mosquitoes do not always bite indoors. + + Fertility is multiplied by 1 - (fecundityReduction * decay). + + min:0;name:Fecundity reduction effect + + + + + + + Name of the affected anopheles-mosquito species. + + name:Mosquito species + + + + + + The proportion of bites for which the IRS + has any action whatsoever on the mosquito. + + At the moment this is constant across humans and deterministic: + relative attractiveness and survival factors are + base*(1-propActing) + intervention_factor*propActing. + + units:dimensionless;min:0;max:1;name:Proportion of bites for which IRS acts; + + + + + + + + + + Description of effect for the more complex and probably more realistic + Briet model: IRS has three effects, whos strength is calculated as a + function of surviving insecticide content. + + name:Description (based on decay of insecticide); + + + + + + Usage of Indoor residual spraying (IRS) interventions, from 0 to 1. + + units:dimensionless;min:0;max:1;name:Proportion of Indoor residual spraying (IRS) interventions; + + + + + + The insecticide concentration of IRS (at time of spraying) is + Gaussian distributed with mean "mu" and a standard deviation "sigma". + The standard deviation should be small relative to the mean to avoid + negative initial concentration. Any negative values sampled are set + to 0. + + units:μg/cm²;min:0;name:Initial insecticide + + + + + + Decay curve for insecticide content of IRS. Documentation: see DecayFunction + type or https://github.com/SwissTPH/openmalaria/wiki/ModelDecayFunctions + + units:none;name:Decay of insecticide + + + + + name:Per-mosquito species parameters; + + + + + + + Effect of IRS on attractiveness of humans to mosquitoes relative to + an unprotected adult human. Parameterisations should take into + account that mosquitoes do not always bite indoors. + + Attractiveness of the human is multiplied by exp(P×log(p)) + where P is the insecticide factor, + p=1−exp(-insecticideContent×insecticideScalingFactor). + + units:dimensionless;min:0;max:1;name:Relative attractiveness + + + + + + Effect of IRS on survival mosquitoes as they seek to bite a human + after choosing that human, relative to the same person not + protected by IRS. Parameterisations should take into account + that mosquitoes do not always bite indoors. This parameter has + been added since some data shows IRS to have a preprandial + killing effect. + + Killing proportion is calculated as K = B + P×p where B is the + base (without protection) probability of death, and P is the + insecticide factor, + p=1−exp(-insecticideContent×insecticideScalingFactor). + + Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−B). + To keep this in the range [0,1], we require that B+P ≤ 1 and P ≥ 0. + + units:dimensionless;min:0;max:1;name:Pre-prandial killing effect + + + + + + Effect of IRS on survival mosquitoes as they seek to escape from + a human host and rest after a blood meal, relative to the same + person not protected by IRS. Parameterisations should take + into account that mosquitoes do not always bite indoors. + + Killing proportion is calculated as K = B + P×p where B is the + base (without protection) probability of death, and P is the + insecticide factor, + p=1−exp(-insecticideContent×insecticideScalingFactor). + + Survival of mosquitoes is adjusted via multiplication by (1−K) / (1−B). + To keep this in the range [0,1], we require that B+P ≤ 1 and P ≥ 0. + + units:dimensionless;min:0;max:1;name:Post-prandial killing effect + + + + + + Effect of IRS on fertility mosquitoes after successfully feeding on + a human host, relative to an unproteced human. Parameterisations should take + into account that mosquitoes do not always bite indoors. + + First, we calculate K = B + P×p where B is the + base (without protection) probability of death, and P is the + insecticide factor, + p=1−exp(-insecticideContent×insecticideScalingFactor). + + Fecundity is multiplied by (1−K) / (1−B). It is not allowed to be greater than 1. + To keep this in the range [0,1], we require that B+P ≤ 1 and P ≥ 0. + + name:Fecundity reduction + + + + + + + Name of the affected anopheles-mosquito species. + + name:Mosquito species + + + + + + The proportion of bites for which the IRS + has any action whatsoever on the mosquito. + + At the moment this is constant across humans and deterministic: + relative attractiveness and survival factors are + base*(1-propActing) + intervention_factor*propActing. + + units:dimensionless;min:0;max:1;name:Proportion of bites for which IRS acts; + + + + + + + + + + + Value expected to be at least 0. Negative values are not + necessarily invalid, but allow nets to increase transmission. + + units:none;name:Insecticide factor;max:1 + + + + + units:none;name:Insecticide scaling factor;min:0 + + + + + + + + See parent element documentation + + units:none;name:Base factor; + + + + + + See parent element documentation + + units:none;name:Insecticide factor; + + + + + + + + + units:dimensionless;name:Probability of mosquito death without intervention + + + + + + + + + + + + Value expected to be at least 0. Negative values are not + necessarily invalid, but allow nets to increase transmission. + + units:none;name:Hole factor;max:1 + + + + + + holeFactor + insecticideFactor + interactionFactor must not be greater + than 1, and is expected to be at least 0. A negative value is not + necessarily invalid, but allows nets to increase transmission. + + units:none;name:Interaction factor;max:1 + + + + + units:none;name:Hole scaling factor;min:0 + + + + + + + + + + + units:dimensionless;name:Probability of mosquito death without intervention + + + + + + + + + + Logit of the probability (e.g. of death, of entry, of attacking) without intervention. + + units:dimensionless;name:Base factor; + + + + + + Coefficient of log(insecticide content+1) in a generalized linear model with logit link + function. + + units:none;name:Insecticide factor; + + + + + + Coefficient of log(total holed surface area (in cm2) +1) in a generalized linear model + with logit link function. + + units:none;name:Hole factor; + + + + + + Coefficient of the interaction term of log(total holed surface area (in cm2) +1) with + log(insecticide content+1) in a generalized linear model with logit link function. + + units:none;name:Interaction factor; + + + + + + + Descriptions of the effects of vector interventions with per-species effects. + + units:dimensionless;min:0;max:1;name:Vector population intervention; + + + + + + Describe an effect on the increase in the death rate while host + seeking (mu_vA) due to this intervention. + + Enter the rate increase (i.e. if rate increases to 120% of normal, + give 0.2). New death rate while seeking is old × (1 + increase) + where increase is this factor given. Must have increas ≥ -1. + + units:dimensionless;name:Proportional increase in deaths while host searching; + + + + + + + + units:dimensionless;min:-1;max:inf;name:Initial proportion increase + + + + + + + + Describe an effect of increased mortality while ovipositing + due to this intervention. Enter the probability of dying due to + this intervention. + + units:dimensionless;name:Proportion ovipositing mosquitoes killed; + + + + + + + + units:dimensionless;min:0;max:1;name:Initial probability of killing + + + + + + + + Describe an effect on emergence of pupa into adults: this value is the + proportion of emerging pupa which are killed by this intervention. + + This can be used as a crude way of modelling larviciding. It ca + also be used to increase emergence by giving a negative value. + The emergence rate is "old rate" × (1 - factor) where factor is the + value given here; thus, for example, using -1 will double emergence. + + units:dimensionless;name:Proportion of emerging pupa killed; + + + + + + + + units:dimensionless;min:-inf;max:1;name:Initial proportion reduction + + + + + + + + Describe an effect on the increase in the death rate while host + seeking (mu_vA) due to this intervention. This works like + adding an non-human host with its own availability. The + difference is that biting this sugar bait is associated with a + probability of dying of 1: all mosquitoes biting the sugar bait + will die. OpenMalaria will automatically compute the + availability for this host so that the probability of biting this + 'host' (and thus dying) is equal to the input parameter. + + Enter the probability of dying while host seeking due to this + intervention. If multiple interventions overlap, the cumulative + probability will be used. Note that it cannot exceed 1, and + OpenMalaria will return an error during the simulation if this + ever happens. + + OpenMalaria will dynamically compute the necessary increase + in mu_vA based on the given probability. Note that this is done + by solving an equation numerically every timestep, which can + cause a small drop in performance. + units:dimensionless;name:Probability of death while host searching as a result of feeding on a sugar bait (used to dynamically adjust mu_vA); + + + + + + + + units:dimensionless;min:-1;max:inf;name:Initial proportion increase + + + + + + + + + Name of the species/subspecies/variant. + + name:Species/subspecies/variant name + + + + + + This intervention modifies parameters of non-human hosts described in the <entomology> <vector> <anopheles> +<nonHumanHosts> section of the input scenario file. + +The intervention is described by 5 parameters that define the change in each of non-human host parameters: + +reduceAvailability: Reduction in the availability rate, αi. For example a value of 0 will result in no change; a value of 0.2 will reduce the availability to 0.8 of its initial value; and a value of 1 will set the availability to 0; + +prePrandialKillingEffect: Reduction in the pre-prandial survival probability, PBi. For example a value of 0 will result in no change; a value of 0.2 will reduce PBi to 0.8 of its initial value; and a value of 1 will set PBi to 0; + +postPrandialKillingEffect: Reduction in the post-prandial survival probability, PCi. For example a value of 0 will result in no change; a value of 0.2 will reduce PCi to 0.8 of its initial value; and a value of 1 will set PCi to 0; + +restingKillingEffect: Reduction in the survival probability of the resting period, PDi. For example a value of 0 will result in no change; a value of 0.2 will reduce PDi to 0.8 of its initial value; and a value of 1 will set PDi to 0; + + + + + + + + + + + + + + List of timed vector population intervention deployment + + name:Vector population intervention deployment; + + + + + + + Name of intervention (e.g. larviciding, sugar bait). + + name:Name of intervention; + + + + + + Name of intervention (e.g. larviciding, sugar bait). + + name:Name of intervention; + + + + + + + Descriptions of the effects of non human hosts interventions with per-species effects. + + + + + + Reduction in the availability rate, αi. For example a value of 0 will result in no change; a value of 0.2 will reduce the availability to 0.8 of its initial value; and a value of 1 will set the availability to 0; + + + + + units:dimensionless;min:-1;max:inf;name:Initial proportion increase + + + + + + + Reduction in the pre-prandial survival probability, PBi. For example a value of 0 will result in no change; a value of 0.2 will reduce PBi to 0.8 of its initial value; and a value of 1 will set PBi to 0; + + + + + units:dimensionless;min:-1;max:inf;name:Initial proportion increase + + + + + + + Reduction in the post-prandial survival probability, PCi. For example a value of 0 will result in no change; a value of 0.2 will reduce PCi to 0.8 of its initial value; and a value of 1 will set PCi to 0; + + + + + units:dimensionless;min:-1;max:inf;name:Initial proportion increase + + + + + + + Reduction in the survival probability of the resting period, PDi. For example a value of 0 will result in no change; a value of 0.2 will reduce PDi to 0.8 of its initial value; and a value of 1 will set PDi to 0; + + + + + units:dimensionless;min:-1;max:inf;name:Initial proportion increase + + + + + + + Reduction in the number of fertile eggs laid by a mosquito after biting this type of host, relative to an unprotected human. For example a value of 0 will result in no change; a value of 0.2 will reduce the fecundity factor to 0.8 of its initial value; and a value of 1 will set the fecundity factor to 0; + + + + + units:dimensionless;min:-1;max:inf;name:Initial proportion increase + + + + + + + + + Name of the species/subspecies/variant. + + name:Species/subspecies/variant name + + + + + + Describes a new non-human hosts that have not been described in the <entomology> <vector> <anopheles> <nonHumanHosts>. + + + + + + + + + + + + + List of timed vector trap intervention deployment + + name:Vector trap intervention deployment; + + + + + + + + + + + Life of the trap until replaced or removed, e.g. + "73t" or "1y". After this time period, these traps + will be removed from the simulation. + + New deployments do not automatically remove old + traps. Existing traps cannot be refurbished in the + model. It may make sense to make the end-of-life + coincide with a new deployment. + + name:Lifespan;units:Steps or Days or Years; + + + + + + + + + + + + + + Name of intervention (e.g. larviciding, sugar bait). + + name:Name of intervention; + + + + + + Descriptions of the effects of new non human hosts with per-species effects. + + + + + + + Relative availability of the population of non-human hosts of + type i to other non-human hosts; the sum of this across all + non-human hosts must be 1. + + units:Proportion; name:Relative availability of non-human host (ξ_i); + + + + + Probability of mosquito successfully biting host + units:Proportion;name:Probability of mosquito successfully biting host; + + + + + Probability that the mosquito escapes host and finds a resting place after biting + units:Proportion;name:Probability that the mosquito escapes host and finds a resting place after biting; + + + + + Probability of mosquito successfully resting after finding a resting site + units:Proportion;name:Probability of mosquito successfully resting after finding a resting site; + + + + + Multiplicative factor for the number of fertile eggs laid by a mosquito after biting this type of host, relative to an unprotected human. + units:Proportion;name:Probability of mosquito successfully resting after finding a resting site; + + + + + + + Name of the species/subspecies/variant. + + name:Species/subspecies/variant name + + + + + + + Specifies the mapping from genotype to phenotype. For each drug + type, if only one phenotype is present, restrictions need not be + specified, but otherwise restrictions must be specified. + + The set of loci affecting phenotypes of this drug's action must be + fixed for any drug type. Each phenotype must list, for each of + these loci, a restriction to one or more alleles under the locus. + + name:Restrict phenotype applicability to certain alleles; + + + + + A locus under which only a restricted set of alleles map to + this phenotype. + + name:Locus relevant to the mapping of alleles to this phenotype; + + + + + + One allele of a locus upon which phenotype choice depends. + If multiple alleles under this locus should map to the same + phenotype, repeat the whole "restriction onLocus..." element. + + name:Alleles mapping to this phenotype; + + + + + + + + + + Mean efficacy values before decay (see efficacyB and decay parameter + descriptions for sampling and decay). The i-th value in this list + is used for the efficacy of the vaccine after the i-th dose. Where + more doses are given than there are values in this list, the last + value is repeated. + + units:dimensionless;min:0;max:1;name:Initial mean efficacy; + + + + + + + Name of the phenotype; for documentation use only. + + name:Name of phenotype; + + + + + + + + + A library of drug related data for the PK/PD model. + + name:Pharmacology library; + + + + + + A library of drug deployment schedules and dosages. + + name:Treatments library; + + + + + + + + + + + + A library of drug PK/PD data. + + name:Drug library; + + + + + + + + + + + + + + + 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 CV > 0, k is sampled per-human from the log-normal + distribution: ln N( ln(mean) - σ^2 / 2, σ^2). + + Alternatively, elimination rate can be specified via half_life. + + units:day^-1;min:0;name:Constant associated with elimination rate (k); + + + + + + Constant used to calculate the elimination rate λ, which + is calculated as λ = k / (body_mass ^ m_exponent), where + body_mass is the patient's weight in kg and k is the + previous parameter. The basic form of decay is + C(t) = C0 * exp(-λ*t). + + Alternatively, elimination rate can be specified via half_life. + + Note that in the case of a conversion model, this applies + to *both* the elimination and the conversion rates. + + units:day^-1;min:0;name:Constant associated with elimination rate (m_exponent); + + + + + + + + Absorption rate parameter. Not allowed for one compartment + models, but required for two and three compartment models and + one compartment with conversion model (for the parent drug + only). + + name:Absorption rate constant (k_a);min:0; + + + + + + Configures the parent drug in a conversion model. + + To use a conversion model, the parent drug should have this + section defined as well as half-life or k (direct + elimination; this may be zero) and k_a (absorption rate; + this may be large). + + The metabolite drug should define half-life or k (elimination + of metabolite), but not k_a (absorption rate) or this section + (conversion). It is not possible for the metabolite to itself + undergo conversion with the current models. + + name:Conversion parameters (parent drug); + + + + + + + The abbreviation of the metabolite drug (e.g. "DHA" or + "DHA_AR"). + + name:Metabolite drug (abbreviation); + + + + + + Rate of conversion of parent drug to metabolite. + + name:Rate of conversion;unit:Per day; + + + + + + Ratio of molecular weights: molecular weight of the + metabolite divided by molecular weight of the parent. + + name:Molecular weight ratio;unit:unitless; + + + + + + The IC50 values of parent and metabolite drugs may be + sampled from the log-normal distribution (if CV is greater than 0). + This parameter controls correlation between these samples, + measured in log-space. + + If this value is 1, samples are fully correlated: a single z-score is + used to calculate both samples. If this is 0, two independent + samples are used. + + Values between 0 and 1 (partial correlation) are supported; + in this case IC50 values are sampled such that + cor(log(x), log(y)) matches this value (where x, y are parent and + metabolite IC50 values). + + name:IC50 log correlation;min:0;max:1; + + + + + + + + + Volume of Distribution. + + If CV > 0 this is sampled from a log-normal distribution. + + units:l/kg;min:0;name:Volume of Distribution (Vd); + + + + + + Optional element specifying conversion parameters to- and + from- a second compartment. + + name:Second compartment parameters; + + + + + + + Absorption rate from the central compartment to the + first periphery compartment (2). + + It is sampled per-patient when CV > 0. + + units:day^-1;min:0;name:Absorption rate to compartment 2 (k12); + + + + + + Absorption rate from the first periphery compartment + (2) to the central compartment. + + It is sampled per-patient when CV > 0. + + units:day^-1;min:0;name:Absorption rate from compartment 2 (k21); + + + + + + + + + Optional element specifying conversion parameters to- and + from- a third compartment. + + name:Third compartment parameters; + + + + + + + Absorption rate from the central compartment to the + second periphery compartment (3). + + It is sampled per-patient when CV > 0. + + units:day^-1;min:0;name:Absorption rate to compartment 3 (k13); + + + + + + Absorption rate from the second periphery compartment + (3) to the central compartment. + + It is sampled per-patient when CV > 0. + + units:day^-1;min:0;name:Absorption rate from compartment 3 (k31); + + + + + + + + + + + + + + + + + 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 CV > 0, the IC50 is sampled from a log-normal distribution. + + units:mg/l;min:0;name: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; + + + + + + + + + + + + + + + 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; + + + + + + + + + + + + + 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 + latentRelapse + 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; + + + + + + + Hypnozoites are released after a delay, calculated as: + roundToTSFromDays(delay + latentRelapse) + + Here, roundToTSFromDays rounds the input (in days) to the nearest timestep, + delay is sampled from a log-normal, and latentRelapse is the + parameter specified here. + + The delay is sampled from a log-normal distribution, parameterised via + the (linear) mean and CV (coefficient of variation) given here. + + name:Hypnozoite release delay; + + + + + + + Usually between 10 and 15 days. + + name:latent relapse days; + + + + + + + + + This elements holds all information about probabilites for clinical events from infections and relapses. + + name:Vivax Clinical Events; + + + + + + + + + + + + + + + + + + + + + + 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; + + + + + + Optionally, entomological availability rate may be sampled per-human from a + distribution. The distribution and coefficient of variability may be set here. + The mean rate is calculated based on other parameters and not set directly. + + If no attributes are specified or distr="const" or CV="0" then there will be + no heterogeneity. + + name:Human availability rate heterogeneity + + + + + 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; + + + + + + + + + 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 CV is non-zero, heterogeneity of decay is introduced via a random + variable sampled from the log-normal distribution. This distribution is + parameterised with mean=1 and CV as given. + + The effective age of decay is the real age multiplied by this variable + (for decay functions with a half-life, this is equivalent to dividing + the half-life by the variable). + + min:0;name:Coefficient of Variation; + + + + + + (Boolean) If True, this tells OpenMalaria to use the complement of the + DecayFunction defined as 1-f(x). This is useful to model increasing + functions that will "decay" to 1. This only works if f(x) is contained + between 0 and 1. + + units:User-defined (defaults to years);min:0;name:L; + + + + + + biphasic: Efficacy between 0 and 1. + + + + + + + biphasic: Proportion between 0 and 1, proportion of the response that is short-lived. + + + + + + biphasic: halflife of short lived component (default to years). + + + + + + + + biphasic: halflife of long lived component (default to years). + + + + + + + + + A parameter with optional heterogeneity. + + Optionally, a distribution ("distr") and standard of deviation ("SD") may be specified. + + name:Sampled value (normal); + + + + + The mean value. + + name:mean; + + + + + + The standard deviation of variates. + + name:standard deviation; + + + + + + To allow heterogeneity, a distribution must be specified. + + Valid options are as follows. + + "const": no variation or sampling. Specifying distr="const" has the + same effect as not specifying distr at all. + + "normal": the parameter is sampled from a normal distribution. + + name:Distribution; + + + + + + + + + + + + + Parameters 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; + + + + + + + A parameter with optional heterogeneity. + + The mean cannot be specified (unless this type is extended). + Optionally, a distribution ("distr") and coefficient of variation ("CV") may be specified. + + name:Sampled value (log normal); + + + + + The (linear) coefficient of variation. + + This value must be specified when a (non-constant) distribution is used. + Note: since version 46, variance can be used instead. + + Note that specifying CV="0" has the same effect as distr="const" and + disables sampling of this parameter, even if distr is not "const". + + name:Coefficient of variation;units:unitless; + + + + + + To allow heterogeneity, a distribution must be specified. + + Valid options are as follows. + + "const": no variation or sampling. Specifying distr="const" has the + same effect as not specifying distr at all. + + "lognormal": the parameter is sampled from a log-normal distribution. + Note that the "mean" and "CV" values are linear (arithmetic) properties + of the distribution and not log-space properties. + + name:Distribution; + + + + + + + + + + + + + The variance parameter of the distirbution. + + This value can be specified when a (non-constant) distribution is used. + + Note that specifying variance="0" has the same effect as distr="const" and + disables sampling of this parameter, even if distr is not "const". + + name:Coefficient of variation;units:unitless; + + + + + + + A parameter with optional log-normal heterogeneity. + + The mean value must be specified. Optionally, a distribution ("distr") + and coefficient of variation ("CV") may be specified. + + name:Sampled value; + + + + + + + The (linear) mean value. + + name:mean; + + + + + + + + + Parameters of a Weibull distribution. + + name:Weibull parameters; + + + + + The Weibull scale parameter (λ). + + name:Scale; + + + + + + The Weibull shape parameter (k). + + name:shape; + + + + + + To allow heterogeneity, a distribution must be specified. + In this case, only "weibull" is allowed. + + name:Distribution; + + + + + + + + + + + + A double-precision floating-point value. + name:Input parameter value;exposed:false; + + + + + + + An integer value. + name:Input parameter value;exposed:false; + + + + + + + A boolean value. + name:Input parameter value;exposed:false; + + + + + + + + + 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; + + + + + + + + + + \ No newline at end of file