2c:null 2d:["$","title",null,{"children":"COVID Weekly Hotspot Report | US Covid Atlas | Observable"}] 32:T7d7,md` The US Covid Atlas team has assembled a weekly report notebook that presents emerging hotspots (7-day average) and stable hotspots (14-day average) based on the total number of cases and by adjusting for population. For more in-depth exploration of data over time, we invite you to explore the full US Covid Atlas. These hotspots represent counties with high COVID-19 rates surrounded by other counties with high rates, determined using spatial autocorrelation (LISA). Important: LISA statistics are calculated at each time point, with areas of higher COVID rates being compared to the rest of the country. As such, areas that are not flagged as hotspots may still have high case rates. These hotspots identify locally clustered counties with high cases, relative to all other counties. Please refer to CDC and local health department guidance for travel, return to work, and social distancing measures. For more information on LISA hotspot methods, please see the US Covid Atlas Methods Page. To download the county list and summary pivot tables, please see the data access section below. For access to the full US Covid Atlas data, please see our API page. Data analysis by Stephanie Yang and notebook by Dylan Halpern. ### For more COVID insights and spatial statistics, visit USCovidAtlas.org `33:Tb72,viewof CountyMap = { let value = null; let currentProperty = propertyDict[SelectedData][SelectedFigureUnit]; const svg = d3.create("svg") .attr("viewBox", [0, 0, 975, 610]) svg.append("g") .attr("transform", "translate(610,20)") .append(() => legend({color:countyColorScale, title: `${SelectedData}`, width: 260 })); svg.append("g") .selectAll("path") .data(topojson.feature(countiesTopojson, countiesTopojson.objects.counties).features) .enter().append("path") .attr("d", path) .attr("fill", d => d.properties[SelectedData] === 0 ? 'rgb(240,240,240)' : countyColorScale(d.properties[SelectedData])) .attr('id', d => d.properties.name) .style('opacity', d => SelectedState === "None" || parseInt(`${d.id}`.slice(0,-3)) === stateGeoid ? 1 : 0.25) .attr('class', 'county'); svg.append("g") .selectAll("path") .data(topojson.feature(statesTopojson, statesTopojson.objects.states).features) .enter().append("path") .attr("d", path) .attr("fill", 'none') .attr("stroke", d => stateGeoid === "None" ? 'white' : 'black') .attr('id', d=> d.properties.name) .style('display', d => stateGeoid === "None" || +d.id === stateGeoid ? 'initial' : 'none') .attr('class', 'state'); svg.append("path") .datum(topojson.mesh(statesTopojson, statesTopojson.objects.states, (a, b) => a !== b)) .attr("fill", "none") .attr("stroke", d => stateGeoid === null ? 'white' : 'black') .attr("stroke-linejoin", "round") .attr("pointer-events", "none") .style('display', d => stateGeoid === null || +d.id === stateGeoid ? 'initial' : 'none') .attr("d", path); // thanks! https://observablehq.com/@duynguyen1678/choropleth-with-tooltip const tooltip = svg.append("g") // svg // .selectAll(".county") // .on("touchmove mousemove", function(event, d) { // d.properties[SelectedData] !== 0 ? // tooltip.call( // callout, // `${d.properties.name} \n // ${SelectedData.split(':')[0]} Population Normalized Cases: ${Math.round(d.properties[`${SelectedData.split(':')[0]}: Population Adjusted Cases`])} \n // ${SelectedData.split(':')[0]} Total New Cases:${Math.round(d.properties[`${SelectedData.split(':')[0]}: Raw Case Count`])} \n // ` // ) : '' ; // tooltip.attr("transform", `translate(${d3.pointer(event, this)})`); // d3.select(this) // .raise(); // }) // .on("touchend mouseleave", function() { // tooltip.call(callout, null); // d3.select(this) // .attr("stroke", null) // .lower(); // }); const outline = svg.append("path") .attr("fill", "none") .attr("stroke", "black") .attr("stroke-linejoin", "round") .attr("pointer-events", "none"); return Object.assign(svg.node(), {value: null}); }34:T8d8,viewof StateMap = { let value = null; let currentProperty = propertyDict[SelectedDataDuplicate][SelectedFigureUnit]; const svg = d3.create("svg") .attr("viewBox", [0, 0, 975, 610]) svg.append("g") .attr("transform", "translate(610,20)") .append(() => legend({color:colorScale, title: [SelectedFigureUnit === "State Percentage" ? 'Percentage of Counties' : 'Number of Counties'], width: 260 })); svg.append("g") .selectAll("path") .data(topojson.feature(statesTopojson, statesTopojson.objects.states).features) .enter().append("path") .attr("d", path) .attr("fill", d => d.properties[currentProperty] === 0 ? 'rgb(240,240,240)' : colorScale(d.properties[currentProperty])) .attr('id', d=> d.properties.name) .attr('class', 'state') svg.append("path") .datum(topojson.mesh(statesTopojson, statesTopojson.objects.states, (a, b) => a !== b)) .attr("fill", "none") .attr("stroke", "white") .attr("stroke-linejoin", "round") .attr("pointer-events", "none") .attr("d", path); // // thanks! https://observablehq.com/@duynguyen1678/choropleth-with-tooltip // const tooltip = svg.append("g") // svg // .selectAll(".state") // .on("touchmove mousemove", function(event, d) { // d.properties[currentProperty] !== 0 ? // tooltip.call( // callout, // `${d.properties.name} \n // ${SelectedData.split(':')[0]} Counties:\n${(d.properties[`${SelectedData.split(' ')[0].toLowerCase()}Num`])} \n // ${SelectedData.split(':')[0]} Counties \n(Population Adjusted): \n${d.properties[`${SelectedData.split(' ')[0].toLowerCase()}AdjustedNum`]} \n // ` // ) : '' ; // tooltip.attr("transform", `translate(${d3.pointer(event, this)})`); // d3.select(this) // .raise(); // }) // .on("touchend mouseleave", function() { // tooltip.call(callout, null); // d3.select(this) // .attr("stroke", null) // .lower(); // }); const outline = svg.append("path") .attr("fill", "none") .attr("stroke", "black") .attr("stroke-linejoin", "round") .attr("pointer-events", "none"); return Object.assign(svg.node(), {value: null}); }35:T501,// adapted from https://observablehq.com/@jashkenas/inputs function blockRadio(config = {}) { let { value: formValue, title, description, submit, options, disabled } = Array.isArray(config) ? { options: config } : config; options = options.map(o => typeof o === "string" ? { value: o, label: o } : o ); const form = input({ type: "radio", title, description, submit, getValue: input => { if (input.checked) return input.value; const checked = Array.prototype.find.call(input, radio => radio.checked); return checked ? checked.value : undefined; }, form: html` ` }); form.output.remove(); return form; }36:T463,getStateData = (state) => { let emerging = pivotAverage[_.findIndex(pivotAverage, f => f.State === state)] let emergingAdjusted = pivotAverageAdjusted[_.findIndex(pivotAverageAdjusted, f => f.State === state)] let stable = pivotStableHotspotsUnadjusted[_.findIndex(pivotStableHotspotsUnadjusted, f => f.State === state)] let stableAdjusted = pivotStableHotspotsAdjusted[_.findIndex(pivotStableHotspotsAdjusted, f => f.State === state)] return { emergingNum: emerging !== undefined ? emerging['Number of Counties'] : 0, emergingPct: emerging !== undefined ? emerging['Percentage'] : 0, emergingAdjustedNum: emergingAdjusted !== undefined ? emergingAdjusted['Number of Counties'] : 0, emergingAdjustedPct: emergingAdjusted !== undefined ? emergingAdjusted['Percentage'] : 0, stableNum: stable !== undefined ? stable['Number of Counties'] : 0, stablePct: stable !== undefined ? stable['Percentage'] : 0, stableAdjustedNum: stableAdjusted !== undefined ? stableAdjusted['Number of Counties'] : 0, stableAdjustedPct: stableAdjusted !== undefined ? stableAdjusted['Percentage'] : 0 } }37:[] 30:{"id":"2ef700939f9e7937","slug":"covid-weekly-hotspot-report","title":"COVID Weekly Hotspot Report","thumbnail":"8004c113bc1c093bb51c1088f073262c7c3a3e3df3e98af31b795611a31108e8","access_level":"public","create_time":"$D2021-01-26T14:14:14.627Z","update_time":"$D2021-11-10T17:42:41.022Z","view_time":null,"first_public_time":"$D2021-01-26T14:32:47.021Z","has_unpublished_edits":null,"fork":true,"stars":2,"starred":false,"owner":{"type":"team","id":"4dc4fbd64737052c","login":"uscovidatlas","name":"US Covid Atlas","avatar_url":"https://avatars-next.observableusercontent.com/bfb7cd47a84b0863345144ac2bcb88913efa39af89b14b52e95fbb2f154250c3","tier":"starter_2024","bio":"The US COVID Atlas is a near real-time visualization tool that helps you access county-level COVID data for longitudinal exploration and spatial analysis. \n\nThe Atlas is a project of the Center for Spatial Data Science at University of Chicago."},"version":1151,"publish_version":1151,"role":null,"authored":false,"authors":[{"type":"individual","id":"6d95e296026ed58f","login":"uscovidatlas","name":"US Covid Atlas","avatar_url":"https://avatars-next.observableusercontent.com/bfb7cd47a84b0863345144ac2bcb88913efa39af89b14b52e95fbb2f154250c3","tier":null,"bio":"The US COVID Atlas is a near real-time visualization tool that helps you access county-level COVID data for longitudinal exploration and spatial analysis. \n\nThe Atlas is a project of the Center for Spatial Data Science at University of Chicago."}],"members":[{"type":"individual","id":"6d95e296026ed58f","login":"uscovidatlas","name":"US Covid Atlas","avatar_url":"https://avatars-next.observableusercontent.com/bfb7cd47a84b0863345144ac2bcb88913efa39af89b14b52e95fbb2f154250c3","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":null,"type":"notebook","body":{"titling":"auto","title":"COVID Weekly Hotspot Report","cells":[{"id":0,"value":"COVIDWeeklyHotpsotReport = {\n return html`

COVID Weekly Hotspot Report

${lastUpdate}

\n`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":89,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":93,"value":"md`## Data Selection: Choose a hotspot type`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":75,"value":"viewof SelectedData = blockRadio({options: ['Emerging Hotspots: Population Adjusted Cases','Emerging Hotspots: Raw Case Count', 'Stable Hotspots: Population Adjusted Cases','Stable Hotspots: Raw Case Count'],value:\"Emerging Hotspots: Population Adjusted Cases\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":144,"value":"md`## Hotspot Counties\n\nThis map shows the counties in ${SelectedData.split(':')[0].toLowerCase()} based on ${SelectedData.split(':')[1].toLowerCase()}. Use the buttons menu below to filter by states with high counts of ${SelectedData.split(':')[0].toLowerCase()}.\n\n\n##### Filter by State:`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":199,"value":"viewof SelectedState = radio({options: ['None', ...stateNames],value:\"None\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":836,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":209,"value":"{\n if (SelectedState === 'None') {\n return md`#### Select a State to view the County Level Table`\n } else { \n return table(_.filter(accessDict[SelectedData]['full'], o => o.state_name === SelectedState), {\n sortable: true\n })\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1008,"value":"html`

Summary Table

\n\nThe table below ranks the states containing the highest number of ${SelectedDataDuplicate.split(':')[0].toLowerCase()} counties within, based on weekly averages of ${SelectedDataDuplicate.split(':')[1].toLowerCase()}.\n\nClick on the table headers to sort the columns.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":971,"value":"table(accessDict[SelectedDataDuplicate]['pivot'], {\n sortable: true\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":392,"value":"DataAccess = {\n return html`\n

Data Access

Below is the parsed hotspot data for the 4 different data configurations, emerging and stable hotspots and population-adjusted and unadjusted data. Hover over a dataset and click the three dots on the left of the cell to download available as a CSV or JSON file. For more complete data, please see our API page.

\n\n

For more COVID insights and spatial statistics, visit USCovidAtlas.org

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":295,"value":"md`## Raw Count (Unadjusted) Emerging Hotspots`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":300,"value":"md`#### Full Data`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":21,"value":"fullAverage = d3.csv('https://raw.githubusercontent.com/GeoDaCenter/covid/master/weekly-report/csvs/full_data_emerging_hotspot.csv', d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":302,"value":"md`#### State Pivot Table`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":35,"value":"pivotAverage = d3.csv('https://raw.githubusercontent.com/GeoDaCenter/covid/master/weekly-report/csvs/pivot_data_emerging_hotspot.csv', d3.autoType).then(data => {\n let rtn = [];\n \n data.map(f => {\n rtn.push({\n 'State': f.state_name,\n 'Number of Counties': f['number of county'],\n 'Percentage': parseFloat(f['percentage'])\n })\n })\n \n return rtn\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":312,"value":"md`## Population Adjusted Emerging Hotspots`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":316,"value":"md`#### Full Data`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":7,"value":"fullAverageAdjusted = d3.csv('https://raw.githubusercontent.com/GeoDaCenter/covid/master/weekly-report/csvs/full_data_emerging_hotspot_adjusted.csv', d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":317,"value":"md`#### State Pivot Table`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":40,"value":"pivotAverageAdjusted = d3.csv('https://raw.githubusercontent.com/GeoDaCenter/covid/master/weekly-report/csvs/pivot_data_emerging_hotspot_adjusted.csv', d3.autoType).then(data => {\n let rtn = [];\n \n data.map(f => {\n rtn.push({\n 'State': f.state_name,\n 'Number of Counties': f['number of county'],\n 'Percentage': parseFloat(f['percentage'])\n })\n })\n \n return rtn\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":322,"value":"md`## Raw Count (Unadjusted) Stable Hotspots`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":327,"value":"md`#### Full Data`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":30,"value":"fullStableHotspotsUnadjusted = d3.csv('https://raw.githubusercontent.com/GeoDaCenter/covid/master/weekly-report/csvs/full_data_stable_hotspot.csv', d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":330,"value":"md`#### Pivot Data`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":50,"value":"pivotStableHotspotsUnadjusted = d3.csv('https://raw.githubusercontent.com/GeoDaCenter/covid/master/weekly-report/csvs/pivot_data_stable_hotspot.csv', d3.autoType).then(data => {\n let rtn = [];\n \n data.map(f => {\n rtn.push({\n 'State': f.state_name,\n 'Number of Counties': f['number of county'],\n 'Percentage': parseFloat(f['percentage'])\n })\n })\n \n return rtn\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":333,"value":"md`## Population Adjusted Stable Hotspots`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":336,"value":"md`#### Full Data`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":15,"value":"fullStableHotspotsAdjusted = d3.csv('https://raw.githubusercontent.com/GeoDaCenter/covid/master/weekly-report/csvs/full_data_stable_hotspot_adjusted.csv', d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":339,"value":"md`#### Pivot Data`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":43,"value":"pivotStableHotspotsAdjusted = d3.csv('https://raw.githubusercontent.com/GeoDaCenter/covid/master/weekly-report/csvs/pivot_data_stable_hotspot_adjusted.csv', d3.autoType).then(data => {\n let rtn = [];\n \n data.map(f => {\n rtn.push({\n 'State': f.state_name,\n 'Number of Counties': f['number of county'],\n 'Percentage': parseFloat(f['percentage'])\n })\n })\n \n return rtn\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":340,"value":"md`###### Helper Objects and Imports`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":115,"value":"accessDict = {\n const accessDict = {\n 'Emerging Hotspots: Raw Case Count': {\n 'full': fullAverage,\n 'pivot': pivotAverage\n },\n 'Emerging Hotspots: Population Adjusted Cases':{\n 'full': fullAverageAdjusted,\n 'pivot': pivotAverageAdjusted\n },\n 'Stable Hotspots: Population Adjusted Cases':{\n 'full': fullStableHotspotsAdjusted,\n 'pivot': pivotStableHotspotsAdjusted\n }, \n 'Stable Hotspots: Raw Case Count':{\n 'full': fullStableHotspotsUnadjusted,\n 'pivot': pivotStableHotspotsUnadjusted\n },\n }\n return accessDict\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":592,"value":"propertyDict = {\n const accessDict = {\n 'Emerging Hotspots: Raw Case Count': {\n \"Hotspot County Number\":'emergingNum',\n \"State Percentage\":'emergingPct'\n },\n 'Emerging Hotspots: Population Adjusted Cases':{\n \"Hotspot County Number\":'emergingAdjustedNum',\n \"State Percentage\":'emergingAdjustedPct'\n },\n 'Stable Hotspots: Population Adjusted Cases':{\n \"Hotspot County Number\":'stableAdjustedNum',\n \"State Percentage\":'stableAdjustedPct'\n }, \n 'Stable Hotspots: Raw Case Count':{\n \"Hotspot County Number\":'stableNum',\n \"State Percentage\":'stablePct'\n },\n }\n return accessDict\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":190,"value":"stateNames = _.sortBy(accessDict[SelectedData]['pivot'].map(f => f['State']))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":187,"value":"_ = require(\"lodash\");","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"d3 = require('d3')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":508,"value":"path = d3.geoPath()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":503,"value":"d3geo = require(\"d3-geo@2\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":58,"value":"import {printTable} from '@uwdata/data-utilities'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":967,"value":"import {table} from '@tmcw/tables'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":612,"value":"// import { callout } from \"@d3/line-chart-with-tooltip\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1016,"value":"import {input, radio} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1028,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":498,"value":"topojson = require(\"topojson-client@3\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":645,"value":"import {legend} from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":714,"value":"colorScale = d3.scaleLinear([0, currentMax/2, currentMax], d3.schemeReds[3])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":901,"value":"countyColorScale = d3.scaleLinear([0, currentCountyMax/2, currentCountyMax], d3.schemeReds[3])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":360,"value":"lastUpdate = fetch('https://api.github.com/repos/geodacenter/covid/commits?path=weekly-report').then(r => r.json()).then(r => r[0].commit.committer.date.split('T')[0])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":795,"value":"currentMax = _.maxBy(accessDict[SelectedData].pivot, f => f[SelectedFigureUnit === \"State Percentage\" ? 'Percentage' : 'Number of Counties'])[SelectedFigureUnit === \"State Percentage\" ? 'Percentage' : 'Number of Counties']","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":905,"value":"currentCountyMax = _.maxBy(accessDict[SelectedData].full, f => f['average']).average","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":859,"value":"stateGeoid = {\n if (SelectedState === \"None\") {\n return null\n } else {\n return +statesTopojson.objects.states.geometries[_.findIndex(statesTopojson.objects.states.geometries, d => d.properties.name === SelectedState)].id\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":828,"value":"countiesTopojson = fetch('https://cdn.jsdelivr.net/npm/us-atlas@3/counties-albers-10m.json')\n .then(r => r.json()\n .then(r => {\n // join data to pivot tables\n for (let i = 0; i < r.objects.counties.geometries.length; i++) {\n let county = +r.objects.counties.geometries[i].id;\n let countyData = getCountyData(county);\n \n r.objects.counties.geometries[i].properties = {\n ...r.objects.counties.geometries[i].properties,\n ...countyData\n }\n }\n \n return r\n }))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":404,"value":"statesTopojson = fetch('https://cdn.jsdelivr.net/npm/us-atlas@3/counties-albers-10m.json')\n .then(r => r.json()\n .then(r => {\n // join data to pivot tables\n for (let i = 0; i < r.objects.states.geometries.length; i++) {\n let state = r.objects.states.geometries[i].properties.name;\n let stateData = getStateData(state);\n \n r.objects.states.geometries[i].properties = {\n ...r.objects.states.geometries[i].properties,\n ...stateData\n }\n }\n \n return r\n }))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":818,"value":"getCountyData = (GEOID) => {\n let emerging = fullAverage[_.findIndex(fullAverage, f => f.GEOID === GEOID)]\n let emergingAdjusted = fullAverageAdjusted[_.findIndex(fullAverageAdjusted, f => f.GEOID === GEOID)]\n let stable = fullStableHotspotsUnadjusted[_.findIndex(fullStableHotspotsUnadjusted, f => f.GEOID === GEOID)]\n let stableAdjusted = fullStableHotspotsAdjusted[_.findIndex(fullStableHotspotsAdjusted, f => f.GEOID === GEOID)]\n return { \n 'Emerging Hotspots: Raw Case Count': emerging !== undefined ? emerging['average'] : 0,\n 'Emerging Hotspots: Population Adjusted Cases': emergingAdjusted !== undefined ? emergingAdjusted['average'] : 0,\n 'Stable Hotspots: Population Adjusted Cases': stableAdjusted !== undefined ? stableAdjusted['average'] : 0,\n 'Stable Hotspots: Raw Case Count': stable !== undefined ? stable['average'] : 0,\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":410,"value":"$36","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W37","stdlib":"1"}} 31:"$30:body"