The avatar for @osserman
Stephen Osserman
Data Scientist and Visualization Engineer with a background in spatial analytics and mapping.
Published
People of the Pandemic
Edited
May 14, 2020
3 stars
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// [Note] There is support in this notebook for setting a certain portion of the population as workers and assigning them workplaces, but that isn't currently being used since the current version of the game includes going to school and work as a subset of "large gatherings."
ageDistribution = [{range: '0-19', portionOfPopInThisRange: 0.26, susceptibility: 0.003, asymptomaticPortion: 0.50 , hospitalIfSymptomatic: 0.02, employedProportion: 0.95}, // employed proportion includes kids going to 'school' -- though it's not currently being used in the game.
{range: '20-39', portionOfPopInThisRange: 0.27, susceptibility: 0.008, asymptomaticPortion: 0.4 , hospitalIfSymptomatic: 0.16, employedProportion: 0.8},
{range: '40-59', portionOfPopInThisRange: 0.26, susceptibility: 0.010, asymptomaticPortion: 0.3 , hospitalIfSymptomatic: 0.25, employedProportion: 0.8},
{range: '60-79', portionOfPopInThisRange: 0.17, susceptibility: 0.025, asymptomaticPortion: 0.2, hospitalIfSymptomatic: 0.37, employedProportion: 0.5},
{range: '80+', portionOfPopInThisRange: 0.04, susceptibility: 0.035, asymptomaticPortion: 0.15, hospitalIfSymptomatic: 0.50, employedProportion: 0.05}
]
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susceptibleInOtherNeighborhoods = otherNeighborhoodsVisited * destinationsInNeighborhood * peoplePerDestination
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susceptibleVisitingInfectorsNeighborhood = susceptibleInOtherNeighborhoods
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susceptibleInNeighborhood = destinationsInNeighborhood * peoplePerDestination - 1 // -1 to remove the infector from the count
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decisionsPerWeek = ({'food':3,'exercise':5, 'small gathering':2, 'large gathering':5, 'work':0})
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exposureByType = ({'food':0.3, 'exercise':0.1, 'small gathering':1, 'large gathering':0.3, 'work':1.5})
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numLargeGatheringDestinations = function() {return _.random(1, 5)}
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numPeopleInHouseFormula = function(){ return _.random(1, 5)}
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md`### Disease Parameters`
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daysWhileInfectious = daysPresymptomaticInfectious+daysSymtpomaticInfectious
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numInfectors = 1000
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import {slider,select} from "@jashkenas/inputs"
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d3 = require("d3@5")
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_ = require("lodash")
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roundProb = function(x) {return Math.floor(x) + (Math.random() < (x - Math.floor(x))) }
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consoleLogging = 0 // if this changes to 1 there's a whole lot of console-logging in the infectionsByInfector cell -- which can get slow when 1K infectors. When I wanted to inspect the console log I'd set numInfectors to 7-10 first.
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