| // SI.java |
| package org.eclipse.stem.diseasemodels.standard; |
| |
| /******************************************************************************* |
| * Copyright (c) 2006, 2008 IBM Corporation and others. |
| * All rights reserved. This program and the accompanying materials |
| * are made available under the terms of the Eclipse Public License v1.0 |
| * which accompanies this distribution, and is available at |
| * http://www.eclipse.org/legal/epl-v10.html |
| * |
| * Contributors: |
| * IBM Corporation - initial API and implementation |
| *******************************************************************************/ |
| |
| import org.eclipse.stem.core.graph.Node; |
| |
| /** |
| * A {@link DiseaseModel} with two states <em>Susceptible</em> and |
| * <em>Infectious</em> (SI). |
| * |
| * <p> |
| * The basic <em>SI</em> (Susceptible, Infectious) disease model assumes a |
| * uniform population at a single location and that the population members are |
| * well "mixed", meaning that they are equally likely to meet and infect each |
| * other. This model, for a normalized population, is defined by the two |
| * equations below: |
| * <ul> |
| * <li><em>Δs = μ − βs i + σi − μs</em> |
| * </li> |
| * <li><em>Δi = βs i − σi − i</em> </li> |
| * </ul> |
| * <p> |
| * Where: |
| * <ul> |
| * <li><em>s</em> is the normalized <em>Susceptible</em> population </li> |
| * <li> <em>i</em> is the normalized <em>Infectious</em> population</li> |
| * <li>μ is the background mortality rate, and, because it is assumed that |
| * the population was not growing or shrinking significantly before the onset of |
| * the disease, μ is also assumed to be the birth rate. </li> |
| * <li> <em>β</em> is the disease transmission (infection) rate. This |
| * coefficient determines the number of population members that become |
| * infected/exposed per population member in the <em>Infectious</em> state, |
| * assuming the entire population is in the <em>Susceptible</em> state. </li> |
| * <li> σ is the <em>Infectious</em> recovery rate. This coefficient |
| * determines the rate at which <em>Infectious</em> population members |
| * <em>Recover</em>. In this model <em>recovery</em> means becoming |
| * <em>Susceptible</em> again.</li> |
| * </ul> |
| * </p> |
| * <p> |
| * In the first equation, the <em>Susceptible</em> population increases when |
| * new members are born. This value is the birth rate μ multiplied by the |
| * total population, which, because the values are normalized, is 1. It also |
| * increases due to <em>Infectious</em> population members recovering. The |
| * <em>Susceptible</em> population decreases by members who die. That value is |
| * μ, the mortality rate, multiplied by the <em>Susceptible</em> |
| * population, <em>s</em>. The <em>Susceptible</em> population also |
| * decreases by having members become <em>infected</em>. The product of |
| * <em>β</em> and <em>i</em> gives the normalized number of |
| * <em>Susceptible</em> population members that would become infected for each |
| * <em>Infectious</em> population member assuming all population members are |
| * in the <em>Susceptible</em> state. Multiplying that by <em>s</em>, the |
| * fraction that actually are <em>Susceptible</em>, gives the normalized |
| * amount that become <em>Infectious</em>. |
| * </p> |
| * <p> |
| * In the second equation, the <em>Infectious</em> population increases by the |
| * number of <em>Susceptible</em> population members that become |
| * <em>Infectious</em> (the first term). It also decreases by the proportion |
| * that <em>Recover</em> from the disease (middle term) and by the proportion |
| * that die (last term). |
| * </p> |
| * <p> |
| * Frequently, being infected by a disease will increase the likelihood that a |
| * population member will die. The model above needs to be enhanced to include |
| * the likelihood of a fatal infection and a potentially different rate at which |
| * infected members die. |
| * </p> |
| * <p> |
| * Let |
| * <ul> |
| * <li><em>x</em> be the <em>Infectious Mortality</em> which is the |
| * proportion of the population members who become <em>Infectious</em> that |
| * will eventually die.</li> |
| * <li><em>μ<sub>i</sub></em> be the <em>Infectious Mortality Rate</em>. |
| * This is the rate at which fatally infected population members die |
| * specifically due to the disease. </li> |
| * </ul> |
| * Thus, we now have two types of <em>Infectious</em> population members, |
| * those that will eventually recover at rate <em>σ</em>, and those |
| * that will eventually die at rate <em>μ<sub>i</sub></em> (of course, |
| * members in both states still die at the background rate <em>μ</em>). |
| * </p> |
| * <p> |
| * Let |
| * <ul> |
| * <li><em> i <sup>R</sup></em> be the normalized infectious population that |
| * will recover.</li> |
| * <li><em> i <sup>F</sup></em> be the normalized infectious population that |
| * will die from the disease.</li> |
| * <li><em> i = i <sup>R</sup> + i <sup>F</sup></em> be the total normalized |
| * infectious population (as before).</li> |
| * </ul> |
| * </p> |
| * |
| * <p> |
| * We modify our model to include these additional states and rates. |
| * <ul> |
| * <li><em>Δs = μ − βs i + σi <sup>R</sup> − μ s</em> |
| * </li> |
| * <li><em>Δi <sup>R</sup> = (1-x)βs i − σi <sup>R</sup> − μi <sup>R</sup></em> |
| * </li> |
| * <li><em>Δi <sup>F</sup> = x βs i − (μ + μ<sub>i</sub>) i <sup>F</sup></em> |
| * </li> |
| * </ul> |
| * </p> |
| * <h3>Spatial Adaptation</h3> |
| * <p> |
| * The "SI" disease model computations in STEM enhance these equations by |
| * adapting them to populations that are spatially distributed. This relaxes the |
| * assumption that the populations are at a single location and opens up the |
| * possibility that different locations could have different areas and numbers |
| * of population members (i.e., different population densities). To accommodate |
| * this situation STEM maintains separate disease state values for each location |
| * and uses unnormalized versions of the equations presented above. We develop |
| * those below. |
| * <p> |
| * To account for population differences at different locations, we define a new |
| * parameter <em>P<sub>l</sub></em> which is the number of population |
| * members at location <em>l</em> (Note: <em>P<sub>l</sub> = S + I</em>). |
| * We also need to account for variability in the disease transmission |
| * (infection) rate, β, due to potentially different population densities. |
| * This modification is based upon the assumption that locations with greater |
| * population densities will have a higher effective transmission rates than |
| * locations with lower densities (i.e., one value can't be used for all |
| * locations). Thus, we need to replace the <em>β</em> in the non-spatial |
| * versions of the equations with a <em>β <sub>l</sub></em> that is |
| * specific to the location. |
| * </p> |
| * Making the substitution for <em>β</em> and multiply both sides of the |
| * equations by <em>P<sub>l</sub></em>, we obtain: |
| * </p> |
| * |
| * <ul> |
| * <li><em>Δs P<sub>l</sub>= μP<sub>l</sub> − β<sub>l</sub> s i P<sub>l</sub> + σ i <sup>R</sup>P<sub>l</sub> − μ s P<sub>l</sub></em> |
| * </li> |
| * <li><em>Δi <sup>R</sup> P<sub>l</sub> = (1-x)β<sub>l</sub> s i P<sub>l</sub> − σ i <sup>R</sup> P<sub>l</sub> − μi <sup>R</sup> P<sub>l</sub></em> |
| * </li> |
| * <li><em>Δi <sup>F</sup> P<sub>l</sub> = x β<sub>l</sub>s i P<sub>l</sub> − (μ + μ<sub>i</sub>) i <sup>F</sup> P<sub>l</sub></em> |
| * </li> |
| * </ul> |
| * |
| * We choose the value for <em>β<sub>l</sub></em> to be original |
| * <em>β</em> scaled by the ratio between the population density at the |
| * location and the average population density of all locations. |
| * <ul> |
| * <li> <em> β<sub>l</sub> = β d<sub>l</sub>/APD</em></li> |
| * </ul> |
| * Where <em>d<sub>l</sub></em> is the population density at location |
| * <em>l</em>, and <em>APD</em> is the average population density for all |
| * locations. |
| * |
| * |
| * |
| * |
| * <p> |
| * Let <em>S<sub>l</sub> = s P<sub>l</sub></em> be the number of |
| * <em>Susceptible</em> population members at location <em>l</em>. , let |
| * <em>I<sub>l</sub> = i P<sub>l</sub></em> be the number of population |
| * members at location <em>l</em> that are <em>Infectious</em> (both states |
| * combined). For readability, we drop the <em>l</em> subscript and |
| * substitute. |
| * </p> |
| * |
| * |
| * <ul> |
| * <li><em>ΔS = μP<sub>l</sub> − β<sub>l</sub> S i + σI <sup>R</sup> − μ S</em> |
| * </li> |
| * <li><em>ΔI <sup>R</sup> = (1-x)β<sub>l</sub> S i − σI <sup>R</sup> − μI <sup>R</sup> </em> |
| * </li> |
| * <li><em>ΔI <sup>F</sup> = x β<sub>l</sub>S i − (μ + μ<sub>i</sub>) I <sup>F</sup> </em> |
| * </li> |
| * </ul> |
| * |
| * Continuing with <em> i = I/P<sub>l</sub></em>, we have: |
| * <ul> |
| * <li><em>ΔS = μP<sub>l</sub> − (β<sub>l</sub>/P<sub>l</sub>) S I + σI <sup>R</sup> − μ S</em> |
| * </li> |
| * <li><em>ΔI <sup>R</sup> = (1-x)(β<sub>l</sub>/P<sub>l</sub>) S I − σI <sup>R</sup> − μI <sup>R</sup> </em> |
| * </li> |
| * <li><em>ΔI <sup>F</sup> = x (β<sub>l</sub>/P<sub>l</sub>) S I − (μ + μ<sub>i</sub>) I <sup>F</sup> </em> |
| * </li> |
| * </ul> |
| * |
| * Letting |
| * <em>β<sup>*</sup> = β<sub>l</sub>/P<sub>l</sub> = β (d<sub>l</sub>/(APD * P<sub>l</sub>)) |
| * </em> |
| * gives: |
| * |
| * <ul> |
| * <li><em>ΔS = μP<sub>l</sub> − β<sup>*</sup> S I + σI <sup>R</sup> − μ S</em> |
| * </li> |
| * <li><em>ΔI <sup>R</sup> = (1-x)β<sup>*</sup> S I − σI <sup>R</sup> − μI <sup>R</sup> </em> |
| * </li> |
| * <li><em>ΔI <sup>F</sup> = x β<sup>*</sup> S I − (μ + μ<sub>i</sub>) I <sup>F</sup> </em> |
| * </li> |
| * </ul> |
| * |
| * <p> |
| * Computing <em>β<sup>*</sup></em> is straightforward. Let |
| * <em>TSF<sub>l</sub> = (d<sub>l</sub>/(APD * P<sub>l</sub>)</em> be |
| * the <em>transmission scale factor</em> at location <em>l</em>. |
| * </p> |
| * <p> |
| * Thus |
| * <ul> |
| * <li><em>β<sup>*</sup> = β TSF<sub>l</sub></em></li> |
| * </ul> |
| * </p> |
| * <p> |
| * Substituting <em>P<sub>l</sub> = S + I</em>, <em>APD = P/Area</em> and |
| * <em>d<sub>l</sub> = (S+I)/Area<sub>l</sub></em>, where <em>P</em> is |
| * the total population for all locations, <em>Area<sub>l</sub></em> is the |
| * area of location <em>l</em>, and <em>Area</em> is the total area of all |
| * locations, we get: |
| * <ul> |
| * <li><em>TSF<sub>l</sub> = ((S+I)/Area<sub>l</sub>) / (P/Area * (S+I))</em></li> |
| * <li><em>TSF<sub>l</sub> = (1/Area<sub>l</sub>) / (P/Area )</em></li> |
| * <li><em>TSF<sub>l</sub> = Area / (P *Area<sub>l</sub> )</em></li> |
| * <li><em>TSF<sub>l</sub> = (1 / P)* (Area/Area<sub>l</sub> )</em></li> |
| * </ul> |
| * So the <em>TSF<sub>l</sub></em> is the product of the reciprocal of the |
| * total population of all locations and the constant ratio between the area of |
| * the location and the total area of all locations. The former can be computed |
| * by accumulating the population of all locations as they are generated and the |
| * later ratio can be computed once at the start of the simulation. |
| * </p> |
| * |
| * <h3>Neighboring Infectious Populations</h3> |
| * <p> |
| * The extension of the non-spatial model into a spatial one in STEM also needs |
| * to account for infectious population members that reside in a location's |
| * "neighbors". Consider a location with no infections that is physically |
| * adjacent to several locations that have large infectious populations. This |
| * physical adjacency would naturally lead to population-to-population contact |
| * and eventually to disease transmission. We need to further extend the |
| * equations we are here to incorporate this aspect of a spatially distributed |
| * population. |
| * </p> |
| * <p> |
| * In STEM, a location has another location as a neighbor <em>Relationship</em> |
| * that links it to that location. If the <em>Relationship</em> represents the |
| * exchange of of population members (i.e., some kind of |
| * {@link TransportRelationshipLabel transportation relationship} like pathways, |
| * roads or air travel) then it would be possible for <em>Infectious</em> |
| * population members from a neighbor to "visit" a location. We need to account |
| * for this potential by increasing the "effective" <em>Infectious</em> |
| * population at a location when doing our computations. Each Relationship has a |
| * rate at which population members travel from one location to another. It is |
| * assumed that the visitors would have the same level of "infectious contact" |
| * as an infectious member of the population at the current location (i.e., that |
| * they could could be counted as an infectious member of the population at the |
| * current location). |
| * </p> |
| * <p> |
| * The equations become: |
| * </p> |
| * <ul> |
| * <li><em>ΔS = μP<sub>l</sub> − β<sup>*</sup> S (I + I<sub>neighbor</sub>() ) + σI <sup>R</sup> − μ S</em> |
| * </li> |
| * <li><em>ΔI <sup>R</sup> = (1-x)β<sup>*</sup> S (I + I<sub>neighbor</sub>() ) − σI <sup>R</sup> − μI <sup>R</sup> </em> |
| * </li> |
| * <li><em>ΔI <sup>F</sup> = x β<sup>*</sup> S (I + I<sub>neighbor</sub>() ) − (μ + μ<sub>i</sub>) I <sup>F</sup> </em> |
| * </li> |
| * </ul> |
| * </p> |
| * <p> |
| * Where |
| * <ul> |
| * <li> |
| * <em>I<sub>neighbor</sub>() = ∑ <sub>m</sub> I <sub>m</sub>transport(m)/P<sub>m</sub></em> |
| * is the number of <em>Infectious</em> visitors from neighbor <em>m</em>.</li> |
| * <li>transport(m) = the the number of population members are transported from |
| * neighbor <em>m</em></li> |
| * <li>P<sub>m</sub> is the number of population members at neighbor |
| * <em>m</em></li> |
| * <li>I<sub>m</sub> is the number of <em>Infectious</em> population |
| * members at neighbor <em>m</em></li> |
| * </ul> |
| * </p> |
| * <p> |
| * Specific statistics on the total number of births, deaths and deaths due to |
| * the disease can be computed by adding the appropriate terms of the equations |
| * above. |
| * <ul> |
| * <li><em>B= μ (S + I)</em>, is the number of <em>Births</em> </li> |
| * <li><em>D = μ S + (μ + μ<sub>i</sub> )I<sup>F</sup> + μI<sup>R</sup></em>,is |
| * the total number of <em>Deaths</em></li> |
| * <li><em>DD= μ<sub>i</sub> I<sup>F</sup></em>, is the number of |
| * <em>Disease Deaths</em> </li> |
| * </ul> |
| * </p> |
| * |
| * @see SIImpl#computeInfectiousMortalityRate(double, double) |
| * @see SIRLabel |
| * @see SIRLabel |
| * @see SIRLabelValue |
| * @see SEIR |
| * @see SEIRLabel |
| * @see SEIRLabelValue |
| * |
| * @model abstract="true" |
| */ |
| public interface SI extends StandardDiseaseModel { |
| /** |
| * This is the segment of the type URI that prefixes all other segments in a |
| * standard disease model type URI. |
| */ |
| String URI_TYPE_STANDARD_SI_DISEASE_MODEL_SEGMENT = URI_TYPE_STANDARD_DISEASEMODEL_SEGMENT |
| + "/si"; |
| |
| /** |
| * This is the proportion which <em>Infectious</em> population |
| * members die per time period. This is <em>μ<sub>i</sub></em>. |
| * |
| * @return the increased rate at which infected population members that die per |
| * time period. |
| * @see DiseaseModel#getBackgroundMortalityRate() |
| * @model default="0.0" |
| */ |
| double getInfectiousMortalityRate(); |
| |
| /** |
| * Sets the value of the '{@link org.eclipse.stem.diseasemodels.standard.SI#getInfectiousMortalityRate <em>Infectious Mortality Rate</em>}' attribute. |
| * <!-- begin-user-doc --> <!-- end-user-doc --> |
| * @param value the new value of the '<em>Infectious Mortality Rate</em>' attribute. |
| * @see #getInfectiousMortalityRate() |
| * @generated |
| */ |
| void setInfectiousMortalityRate(double value); |
| |
| /** |
| * Compute the infectious mortality rate adjusted for a time delta |
| * potentially different from the time period specified for the rate. |
| * |
| * @param timeDelta |
| * the time period (milliseconds) to which the rate is to be |
| * adjusted. |
| * @return the adjusted rate |
| * |
| * @model volatile="true" transient="true" changeable="false" |
| */ |
| double getAdjustedInfectiousMortalityRate(final long timeDelta); |
| |
| /** |
| * This is the proportion of population members that become infected/exposed |
| * per population member in the <em>Infectious</em> state, assuming the |
| * entire population is in the <em>Susceptible</em> state, per time |
| * period. |
| * <p> |
| * In the rate equation this coefficient is normalize by the ratio of the |
| * Susceptible population to the total population. The final value may also |
| * be rescaled based on variations in local population density (above or |
| * below average). This is <em>β</em>. |
| * </p> |
| * |
| * @return the number of population members that become infected per time |
| * period |
| * @model default="0.0" |
| */ |
| double getTransmissionRate(); |
| |
| /** |
| * Sets the value of the '{@link org.eclipse.stem.diseasemodels.standard.SI#getTransmissionRate <em>Transmission Rate</em>}' attribute. |
| * <!-- begin-user-doc --> <!-- end-user-doc --> |
| * @param value the new value of the '<em>Transmission Rate</em>' attribute. |
| * @see #getTransmissionRate() |
| * @generated |
| */ |
| void setTransmissionRate(double value); |
| |
| /** |
| * Compute the transmission rate adjusted for a time delta potentially |
| * different from the time period specified for the rate. |
| * |
| * @param timeDelta |
| * the time period (milliseconds) to which the rate is to be |
| * adjusted. |
| * @return the adjusted rate |
| * |
| * @model volatile="true" transient="true" changeable="false" |
| */ |
| double getAdjustedTransmissionRate(final long timeDelta); |
| |
| /** |
| * By default this exponent is one (1.0) and the rate of infection scales as |
| * the product of the Susceptible population and the Infectious population. |
| * In a nonlinear model (which captures saturation of the immune system for |
| * Susceptible population), the Infectious term is raise to this power (>= |
| * 1.0) This exponent should never be less than one (that would imply |
| * Susceptible population would become less susceptible as their probability |
| * of exposure increases. |
| * |
| * @return the non-linearity coefficient |
| * @model default="1.0" |
| */ |
| double getNonLinearityCoefficient(); |
| |
| /** |
| * Sets the value of the '{@link org.eclipse.stem.diseasemodels.standard.SI#getNonLinearityCoefficient <em>Non Linearity Coefficient</em>}' attribute. |
| * <!-- begin-user-doc --> <!-- end-user-doc --> |
| * @param value the new value of the '<em>Non Linearity Coefficient</em>' attribute. |
| * @see #getNonLinearityCoefficient() |
| * @generated |
| */ |
| void setNonLinearityCoefficient(double value); |
| |
| /** |
| * This coefficient determines the number of population members that recover |
| * from the disease per population member in the <em>Infectious</em> |
| * state. This is <em>σ</em>. |
| * |
| * @return the number of population members that recover per time period |
| * @model default="0.0" |
| */ |
| double getRecoveryRate(); |
| |
| /** |
| * Sets the value of the '{@link org.eclipse.stem.diseasemodels.standard.SI#getRecoveryRate <em>Recovery Rate</em>}' attribute. |
| * <!-- begin-user-doc --> <!-- end-user-doc --> |
| * @param value the new value of the '<em>Recovery Rate</em>' attribute. |
| * @see #getRecoveryRate() |
| * @generated |
| */ |
| void setRecoveryRate(double value); |
| |
| /** |
| * Compute the recovery rate adjusted for a time delta potentially different |
| * from the time period specified for the rate. |
| * |
| * @param timeDelta |
| * the time period (milliseconds) to which the rate is to be |
| * adjusted. |
| * @return the adjusted rate |
| * |
| * @model volatile="true" transient="true" changeable="false" |
| */ |
| double getAdjustedRecoveryRate(final long timeDelta); |
| |
| /** |
| * <!-- begin-user-doc --> |
| * <!-- end-user-doc --> |
| * @model |
| * @generated |
| */ |
| double getEffectiveInfectious(Node node, StandardDiseaseModelLabel diseaseLabel, double onsiteInfectious); |
| |
| /** |
| * Two <code>Node</code>s that share a border exchange population members |
| * through otherwise un-modeled transportation routes. This is the proportion |
| * of the infectious population members in any adjacent <code>Node</code> |
| * to include in the computations of another <code>Node</code>. |
| * |
| * @return the proportion of the infectious population in physically |
| * adjacent <code>Node</code>s that contribute to the effective |
| * infectious population at the current <code>Node</code>. |
| * @model default="0.05" |
| */ |
| double getPhysicallyAdjacentInfectiousProportion(); |
| |
| |
| /** |
| * Sets the value of the '{@link org.eclipse.stem.diseasemodels.standard.SI#getPhysicallyAdjacentInfectiousProportion <em>Physically Adjacent Infectious Proportion</em>}' attribute. |
| * <!-- begin-user-doc --> |
| * <!-- end-user-doc --> |
| * @param value the new value of the '<em>Physically Adjacent Infectious Proportion</em>' attribute. |
| * @see #getPhysicallyAdjacentInfectiousProportion() |
| * @generated |
| */ |
| void setPhysicallyAdjacentInfectiousProportion(double value); |
| |
| /** |
| * This parameter adjust the strength of mixing of people between |
| * adjacent nodes <code>Node</code>s that are connected by one or more roads. |
| * Exchange of population members by the road network can add or, or augment, mixing |
| * based on physical adjacency based on the relative strength of these independent |
| * mixing proportions. Two <code>Node</code>s that are connected by one or more roads exchange population members |
| * by road transport. This is the the proportion exchanged PER ROAD. |
| * An road transport edge may represent multiple roads in which case the value returned |
| * is scaled (multiplied) by the number of roads encoded by that edge. |
| * This product is then the proportion of the infectious population members in any adjacent <code>Node</code> |
| * to include in the computations of another <code>Node</code>. |
| * |
| * @return the proportion of the infectious population in physically |
| * adjacent <code>Node</code>s that contribute to the effective |
| * infectious population at the current <code>Node</code>. |
| * @model default="0.01" |
| */ |
| double getRoadNetworkInfectiousProportion(); |
| |
| /** |
| * Sets the value of the '{@link org.eclipse.stem.diseasemodels.standard.SI#getRoadNetworkInfectiousProportion <em>Road Network Infectious Proportion</em>}' attribute. |
| * <!-- begin-user-doc --> |
| * <!-- end-user-doc --> |
| * @param value the new value of the '<em>Road Network Infectious Proportion</em>' attribute. |
| * @see #getRoadNetworkInfectiousProportion() |
| * @generated |
| */ |
| void setRoadNetworkInfectiousProportion(double value); |
| |
| /** |
| * Returns the value of the '<em><b>Infectious Mortality</b></em>' attribute. |
| * <!-- begin-user-doc --> |
| * <p> |
| * If the meaning of the '<em>Infectious Mortality</em>' attribute isn't clear, |
| * there really should be more of a description here... |
| * </p> |
| * <!-- end-user-doc --> |
| * @return the value of the '<em>Infectious Mortality</em>' attribute. |
| * @see #setInfectiousMortality(double) |
| * @see org.eclipse.stem.diseasemodels.standard.StandardPackage#getSI_InfectiousMortality() |
| * @model |
| * @generated |
| */ |
| double getInfectiousMortality(); |
| |
| /** |
| * Sets the value of the '{@link org.eclipse.stem.diseasemodels.standard.SI#getInfectiousMortality <em>Infectious Mortality</em>}' attribute. |
| * <!-- begin-user-doc --> |
| * <!-- end-user-doc --> |
| * @param value the new value of the '<em>Infectious Mortality</em>' attribute. |
| * @see #getInfectiousMortality() |
| * @generated |
| */ |
| void setInfectiousMortality(double value); |
| |
| /** |
| * Returns the value of the '<em><b>Characteristic Mixing Distance</b></em>' attribute. |
| * The default value is <code>"2.25"</code>. |
| * <!-- begin-user-doc --> |
| * <p> |
| * If the meaning of the '<em>Characteristic Mixing Distance</em>' attribute isn't clear, |
| * there really should be more of a description here... |
| * </p> |
| * <!-- end-user-doc --> |
| * @return the value of the '<em>Characteristic Mixing Distance</em>' attribute. |
| * @see #setCharacteristicMixingDistance(double) |
| * @see org.eclipse.stem.diseasemodels.standard.StandardPackage#getSI_CharacteristicMixingDistance() |
| * @model default="2.25" |
| * @generated |
| */ |
| double getCharacteristicMixingDistance(); |
| |
| /** |
| * Sets the value of the '{@link org.eclipse.stem.diseasemodels.standard.SI#getCharacteristicMixingDistance <em>Characteristic Mixing Distance</em>}' attribute. |
| * <!-- begin-user-doc --> |
| * <!-- end-user-doc --> |
| * @param value the new value of the '<em>Characteristic Mixing Distance</em>' attribute. |
| * @see #getCharacteristicMixingDistance() |
| * @generated |
| */ |
| void setCharacteristicMixingDistance(double value); |
| |
| /** |
| * This method replaces the onsiteInfectious value with an effectiveInfectious population |
| * size based on mixing with other sites. For example, |
| * an implementation of this method replaces the onsiteInfectious value with an effectiveInfectious population |
| * size based on mixing with neighhboring sites. In this implementation the edges are bidirectional |
| * and have a fixed weight based on getPhysicallyAdjacentInfectiousProportion() (called in the helper method |
| * getInfectiousChangeFromMixing(). But the mixing is also weighted by the areas and populations of a site relative |
| * to the area and population of it's neighbors. Note that the value returned must be NORMALIZED by the total |
| * population because the product beta * S * Ieffective must have units of persons. Since S has units of persons |
| * the Ieffective must be dimensionless (normalized to the population). beta is the infection rate and has units |
| * of inverse time. |
| * @param node the node we are currently looking at to compute the next disease state |
| * @param diseaseLabel the label for the current disease computation |
| * @param onsiteInfectious the number of infectious people on site (at the node above) |
| * @return the number of infectious population members in <code>Node</code>s |
| * that share a {@link CommonBorderRelationshipLabel} with this |
| * <code>Node</code>. |
| * @model volatile="true" transient="true" changeable="false" |
| */ |
| double getNormalizedEffectiveInfectious(final Node node, final StandardDiseaseModelLabel diseaseLabel, final double onsiteInfectious); |
| |
| } // SI |
