infectionsByInfector = function( infector ){ // populate susceptibles based on number of people in infectors neighborhood and the other N neighborhoods they draw from. Populate ages of each based on age distribution. if(consoleLogging){ console.log("Infector:") console.log(infector) } let susceptibles= [] let susceptibleCounts = [ {type: 'inNeighborhood', n: susceptibleInNeighborhood}, {type: 'visitingInfector', n: susceptibleVisitingInfectorsNeighborhood}, {type: 'infectorVisiting', n: susceptibleInOtherNeighborhoods}, ] // let numSusceptibles = susceptibleInNeighborhood + susceptibleVisitingInfectorsNeighborhood + susceptibleInOtherNeighborhoods susceptibleCounts.forEach( d => { for (let ageGroup = 0 ; ageGroup < ageDistribution.length ; ageGroup++ ){ let peopleNeeded = roundProb(d.n * ageDistribution[ageGroup].portionOfPopInThisRange) while (peopleNeeded > 0) { susceptibles.push({age: ageDistribution[ageGroup].range, susceptibility: ageDistribution[ageGroup].susceptibility, worker: Math.random() < ageDistribution[ageGroup].employedProportion, housemate: 0, // this updates below - after inNeighborhood is done populating coworker: 0, // this updates below - after inNeighborhood is done populating neighborhood: d.type } ) peopleNeeded--; } } // assign housemates and coworkers from within the neighborhood if(d.type == 'inNeighborhood'){ _.sampleSize(_.keys(susceptibles), infector.nPeopleInHouse - 1).forEach(i => { susceptibles[i].housemate = 1 }) _.sampleSize(_.keys(susceptibles), roundProb(susceptibles.length / infectorDestinationsInNeighborhood)).forEach(i => { if(susceptibles[i].worker){susceptibles[i].coworker = 1} }) } }) let housemates = _.keys(_.pickBy(susceptibles, {housemate: 1})) let coworkers = _.keys(_.pickBy(susceptibles, {coworker: 1})) let inNeighborhood = _.keys(_.pickBy(susceptibles, {neighborhood: "inNeighborhood"})) let visitingInfector = _.keys(_.pickBy(susceptibles, {neighborhood: "visitingInfector"})) let infectorVisiting = _.keys(_.pickBy(susceptibles, {neighborhood: "infectorVisiting"})) // create object where all exposures will be stored. let exposures = {} // go through days of infectiousness and add to exposures Object. for(let dayNum = 1; dayNum <= daysWhileInfectious; dayNum++){ if(consoleLogging){console.log("Day: " + dayNum)} // set infectiousness to 1 for symptomatic, and to asymptomaticInfectiousness for a/pre-symptomatic let infectiousness = ( dayNum <= daysPresymptomaticInfectious || infector.asymptomatic ) ? asymptomaticInfectiousness : 1; // infect people in house if(infector.nPeopleInHouse > 1){ housemates.forEach(i => exposures[+i] = (exposures[+i] || 0) + (infectiousness * dailyHouseholdExposures)) } // now iterate through all 'go-out' decision types. Object.keys(decisionsPerWeek).forEach(type => { let baselineOutProb = decisionsPerWeek[type] / 7 if (type == 'work'){ // special case "work" if (infector.worker == 1 && Math.random() < baselineOutProb) { // if worker goes to work that day // grab proportion of coworkers also working that day and add to their exposures. //console.log(_.sampleSize(coworkers, roundProb(coworkers.length * baselineOutProb))) _.sampleSize(coworkers, roundProb(coworkers.length * baselineOutProb)).forEach(i => exposures[+i] = (exposures[+i] || 0) + infectiousness) // TO DO : need to also infect some number of other people who go to that location too. } else { if(consoleLogging){console.log("Not going out for work on day: " + dayNum)}} } else { let goOut = ( Math.random() < baselineOutProb && (infector.asymptomatic || dayNum <= daysPresymptomaticInfectious || (infector.hospitalized && dayNum <= (daysPresymptomaticInfectious + daysSymtpomaticInfectious - daysHospitalized) && Math.random() <= ChanceOfGoingOutIfSymptomatic ) || (infector.hospitalized === 0 && Math.random() <= ChanceOfGoingOutIfSymptomatic ) ) ) if(goOut){ if(consoleLogging){console.log(type + ': going out')} [...Array(type == 'large gathering' ? numLargeGatheringDestinations() : 1)].forEach(() => { let inNeighborhood = Math.random() < (infectorDestinationsInNeighborhood / (infectorDestinationsInNeighborhood + infectorDestinationsInOtherNeighborhoods)) // destinationMultipliers if(inNeighborhood){ _.concat( _.sampleSize(inNeighborhood, roundProb(inNeighborhood.length * destinationMultipliers.homeNeighborhood)), _.sampleSize(visitingInfector, roundProb(visitingInfector.length * destinationMultipliers.visitingNeighborhood)) ) .forEach(i => exposures[i] = (exposures[i] || 0) + (exposureByType[type] * infectiousness)) } else { _.concat( _.sampleSize(infectorVisiting, roundProb(infectorVisiting.length * destinationMultipliers.homeNeighborhood)), _.sampleSize(inNeighborhood, roundProb(inNeighborhood.length * destinationMultipliers.visitingNeighborhood)) ) .forEach(i => exposures[i] = (exposures[i] || 0) + (exposureByType[type] * infectiousness)) } if(consoleLogging){console.log(exposures)} }) } } }) } let cumulativeInfections = 0 let householdCumulativeInfections = 0 let coworkerCumulativeInfections = 0 Object.keys(exposures).forEach( d => { cumulativeInfections += (1 - Math.pow( ( 1 - susceptibles[d].susceptibility ), exposures[d]) ) if(susceptibles[d].housemate){ householdCumulativeInfections += (1 - Math.pow( ( 1 - susceptibles[d].susceptibility ), exposures[d]) ) } if(susceptibles[d].coworker){ coworkerCumulativeInfections += (1 - Math.pow( ( 1 - susceptibles[d].susceptibility ), exposures[d]) ) } }) //console.log(exposures) if(consoleLogging){ console.log("Infector:") console.log(infector) console.log("Susceptibles:") console.log(susceptibles) console.log('END OF INFECTOR. Infected ' + cumulativeInfections) } return { cumulativeInfections: cumulativeInfections, householdCumulativeInfections: householdCumulativeInfections, // not currently using separate workplaces in actual game so commenting this out // coworkerCumulativeInfections: coworkerCumulativeInfections, // nCoworkers: coworkers.length } }