31:T952,{ let links = `Data from [Walgreens COVID-19 Index dashboard](https://www.walgreens.com/businesssolutions/covid-19-index.jsp) If not working: [Direct link to the dashboard](https://app.powerbi.com/view?r=eyJrIjoiYTE2ODZmM2ItNmNjYi00YmRjLWFlNDQtMmIzOGJlNTZhMjY1IiwidCI6IjkyY2I3NzhlLThiYTctNGYzNC1hMDExLTRiYTZlNzM2Njk5NiIsImMiOjN9) `; if (showInfo) { return md`${links}

Data is automatically extracted from the Walgreens dashboard shortly after it is updated weekly on Mondays, usually around 3pm ET.

Download this data: https://labvegas.com/data/covid19/walgreens/dashboard-Tracker_Aggregation.csv
More Walgreens data:
· US Positivity by vaccination status: https://labvegas.com/data/covid19/walgreens/dashboard-Vaccination_Aggregation.csv
· US Top 20 variants https://labvegas.com/data/covid19/walgreens/dashboard-Top20.csv
· Top 5 VOCs by state https://labvegas.com/data/covid19/walgreens/dashboard-Top5_name.csv

Note: I change the default display mode and scale from time to time, to highlight differences between states.

Walgreens uses a PCR test (TaqPath) that can differentiate some COVID variants by the level of S-gene detection, and reports the results daily on a dashboard. Here are some current and former COVID lineages split by whether the S-gene was detected (non-SGTF) or failed to get detected (SGTF):

non-SGTF variants include: Original COVID-19, Delta, BA.2.x, XBB.x, BN.1, CH.1.1,
SGTF variants include: Alpha, BA.1 (Original Omicron), BA.4.x, BA.5.x, BQ.x, CQ.x, BF.x, BE.x

Full list of lineages with their SGTF prevalence from outbreak.info

For more information on this notebook, read my twitter, starting with this thread.
More of my COVID-19 pages: COVID-19 charts and Map of COVID-19 cases by zip code for Las Vegas / Clark County, Nevada

`; } else { return md`${links}` } } 32:T660,{ if (dataBeingFetched) { yield md`## Data being fetched for all 50 states, DC & PR (over 7MB). Thanks for your patience!`; } let titles = { "BA.4+BA.5 peak to BA.2 peak": md`## BA.4+BA.5 variant peaks to BA.2 peaks, based on Walgreens data`, "BA.4+BA.5 peak to BA.1 peak": md`## BA.4+BA.5 variant peaks to BA.1 peaks, based on Walgreens data`, Positivity: md`## COVID-19 PCR positivity rates, reported by Walgreens`, PositivityChange: md`## 7-day change in COVID-19 PCR positivity rates, reported by Walgreens`, "Positives Growth": md`## COVID-19 case growth rates, reported by Walgreens`, "BA.2 Growth": md`## Non-SGTF weekly growth rates, based on Walgreens data, minimum of 6 non-SGTF samples over last 3 days`, "BA.4+BA.5 Growth": md`## SGTF weekly growth rates, based on Walgreens data, minimum of 6 SGTF samples over last 3 days`, Proportion: md`## Non-SGTF variants fractions in the US, reported by Walgreens`, '3day': md`## Non-SGTF variant fractions over last 3 days reported by Walgreens (minimum of 2 samples)`, '9day': md`## Non-SGTF variant fractions over last 9 days reported by Walgreens (minimum of 2 samples)`, Change: md`## Change in BA.2 variants proportion, based on Walgreens data`, Growth: md`## Change in BA.1+BA.4+BA.5 variants proportion, based on Walgreens data`, Growth2: md`## Change in BA.2 variants proportion, based on Walgreens data`, growthAdvantage: md`## Weekly growth advantage of non-SGTF vs. SGTF variants, based on Walgreens data`, } yield titles[mapMode] || md`## Variant proportions in the US, reported by Walgreens`; }33:T59e,{ return md``; function getTotals(days="3day", data = currentBA4growth, weight = ()=>1) { let ba2 = d3.sum(data,d => d["BA.2 "+days]*weight(d)); let ba45 = d3.sum(data,d => d["BA.1+BA.4+BA.5 "+days]*weight(d)) || d3.sum(data,d => d["BA.4+BA.5 "+days]*weight(d)); let other = d3.sum(data,d => d["Other "+days]*weight(d)); let tot = ba2 + ba45 + other; let prop = ba45/tot; let propPerc = (100-prop*100).toFixed(2); return {ba2, ba45, other, tot, prop, propPerc, days}; } let t = getTotals("3day"); let tWeighted = getTotals("3day",currentBA4growth,d=>statePopulationFraction[d.State]); let t7 = getTotals("7day"); let t1 = getTotals("1day"); let tp = getTotals("Projected"); let projGrowth = tp.tot / t7.tot - 1; let projGrowthPerc = (projGrowth*100).toFixed(1); return md`### Nationwide non-SGTF (XBB and others) percentage: ${t.propPerc}% ${t.propPerc}% (${t.ba2}/${t.tot}; ${tWeighted.propPerc}% weighted by state population) of Walgreens' qualified TaqPath PCR test results, over the most recent 3 days of data, did not have SGTF/rSGTP, a proxy to differentiate some COVID-19 variants. Over the last 7 days, the figure was **${t7.propPerc}%** (${t7.ba2}/${t7.tot}). `//+`Over the last day, **${t1.propPerc}%** (${t1.ba45}/${t1.tot}).`//+` Over the next 7 days, the projection is ${tp.propPerc}% (${tp.ba45.toFixed(0)}/${tp.tot.toFixed(0)}) for a total growth of ${projGrowthPerc}%.`; }34:T70c,{ if (!showPvT) { return md`Check box above to show chart.`; } await visibility(); if (regionOrStateSelected === "None") return md``; let plot = multiLayerX( { ...chartConfig, style: "overflow: visible;", x: { // type: "utc", // domain: [new Date(2021, 4, 0), Date.now()], grid: true, label: "Weekly Tests", labelAnchor: "center", tickRotate: -30 }, y: { axis: "left", types: [null,"%"], grid: true, zero: true, labelAnchor: "center", label: "Weekly Positive Tests" }, }, Plot.arrow(stateDataTotals,{ y2: "test_number_pos_rolling", x2: "test_number_ALL_rolling", y1: (d,i)=>i && stateDataTotals[i-1]["test_number_pos_rolling"] || null, x1: (d,i)=>i && stateDataTotals[i-1]["test_number_ALL_rolling"] || null, opacity: (d,i)=>i+100, stroke:"#f28e2c", }), Plot.arrow(stateDataTotals,{ y2: "7day_mov_avg", x2: "test_number_ALL_rolling", y1: (d,i)=>i && stateDataTotals[i-1]["7day_mov_avg"] || null, x1: (d,i)=>i && stateDataTotals[i-1]["test_number_ALL_rolling"] || null, opacity: (d,i)=>i+100, stroke:"#cccccc" }), Plot.text(stateDataTotals, Plot.selectLast({ x: "test_number_ALL_rolling", y: "test_number_pos_rolling", fill: "#f28e2c", text: ()=>"Positive tests", fontSize: chartFontSize, textAnchor: "mid", dy: -5 })), Plot.text(stateDataTotals, Plot.selectLast({ x: "test_number_ALL_rolling", y: "7day_mov_avg", fill: "#cccccc", text: ()=>"Positivity", fontSize: chartFontSize, textAnchor: "mid", dy: -5 })) ); plot.setAttribute("font-size",chartFontSize); return scaleToFit(plot); }35:T76e,{ if (!showPvTrange) { return md`Check box above to show chart.`; } await visibility(); if (regionOrStateSelected === "None") return md``; let plot = multiLayerX( { ...chartConfig, style: "overflow: visible;", x: { // type: "utc", // domain: [new Date(2021, 4, 0), Date.now()], grid: true, tickRotate: -30, labelAnchor: "center", label: "Weekly Tests" }, y: { axis: "left", types: [null,"%"], grid: true, zero: true, labelAnchor: "center", label: "Weekly Positive Tests" }, }, Plot.arrow(data2,{ y2: "test_number_pos_rolling", x2: "test_number_ALL_rolling", y1: (d,i)=>i && data2[i-1]["test_number_pos_rolling"] || null, x1: (d,i)=>i && data2[i-1]["test_number_ALL_rolling"] || null, opacity: (d,i)=>i, stroke: "#f28e2c", title: (d) => "Weekly positivity to " + new Date(d.Date).toDateString().slice(0,15) }), Plot.arrow(data2,{ y2: "7day_mov_avg", x2: "test_number_ALL_rolling", y1: (d,i)=>i && data2[i-1]["7day_mov_avg"] || null, x1: (d,i)=>i && data2[i-1]["test_number_ALL_rolling"] || null, opacity: (d,i)=>i, stroke: "#cccccc", title: (d) => "Weekly positive tests to " + new Date(d.Date).toDateString().slice(0,15) }), Plot.text(data2, Plot.selectLast({ x: "test_number_ALL_rolling", y: "test_number_pos_rolling", fill: "#f28e2c", text: ()=>"Positive tests", fontSize: chartFontSize, textAnchor: "mid", dy: -5 })), Plot.text(data2, Plot.selectLast({ x: "test_number_ALL_rolling", y: "7day_mov_avg", fill: "#cccccc", text: ()=>"Positivity", fontSize: chartFontSize, textAnchor: "mid", dy: -5 })) ); plot.setAttribute("font-size",chartFontSize); return scaleToFit(plot); } 36:T403,ba45_peak_study = md`---- https://observablehq.com/@andy-bloch/walgreens-covid-19-tracker ### How were the size of the BA.4+BA.5 waves related to the previous BA.2 waves? If a BA.2 infection results in robust immunity against BA.4 and BA.5 (and vice-versa), there would be a competition between the variants to infect people with low immunity. The earlier that BA.4+BA.5 become dominant in a state relative to the earlier BA.2 wave, a greater number of BA.2 cases should be displaced by BA.4+BA.5 cases. We should expect the relative size of the waves to be correlated with the timing. Here, I chart the relative peak of BA.4+BA.5 compared to how far BA.2 had descended from its peak when BA.4+BA.5 became predominant. The dots for each state are color-coded and sized based on number of samples, and a separate trend line is shown for large and small states. There's a fairly strong correlation for the larger states. #### Ratio of peaks versus the relative level of BA.2 when BA.4+BA.5 became dominant `37:T718,{ if (!showPeakvBA2) { return md`Check box above to show chart.`; } await visibility(); let threshold = 600; function thresholdFunction(d) { return d["BA.2 peak"]+d["BA.4+BA.5 peak"] >= threshold; } let data1 = transitions.filter(thresholdFunction); let data2 = transitions.filter(d=> !thresholdFunction(d)); let x = "BA.2 to BA.2 peak"; let y = "BA.4+BA.5 peak to BA.2 peak"; return Plot.plot({ height: 400, width: 1000, marginLeft: 75, marginRight: 25, marginTop: 25, marginBottom: 45, style: { fontSize: 15, }, color: { //legend: "swatches", //columns: "11em", //range: colorRange }, //x: {type: "label"}, x: { label: "(BA.2 at transition) / (BA.2 peak)", labelAnchor: "center", nice:true, //type: "band", //domain: d3.sort(data, d=> d.numcrew + d.numpax).map(d=>d["Ship Name"]) }, y: { labelAnchor: "center", label: "(BA.4+BA.5 peak) / (BA.2 peak)", tickPadding: 1, tickSize: 3, nice:true, }, grid: true, marks: [ Plot.ruleY([0]), Plot.circle(transitions, { x, y, r: d=>Math.sqrt(d["BA.2 peak"]), title: d=>d.State , fill: d=>!thresholdFunction(d), stroke: d=>!thresholdFunction(d), }), Plot.text(transitions, { x, y, dx: 7, dy: 0, fill: d=>d.State, fontSize: d=>Math.sqrt(d["BA.2 peak"])/4 + 2, text: d=>d.State, textAnchor: "start", }), Plot.linearRegressionY(data1, { x, y, stroke: "steelblue", ci: 0.95}), Plot.linearRegressionY(data2, { x, y, stroke: "rgb(255, 155, 57)", ci: 0.95}), ] }) }38:T759,{ if (!showPeakvBA2) { return md`Check box above to show chart.`; } await visibility(); let threshold = 600; function thresholdFunction(d) { return d["BA.2 3day"]+d["BA.4+BA.5 3day"] >= threshold; } let data = Object.values(variantPeaks); let data1 = data.filter(thresholdFunction); let data2 = data.filter(d=> !thresholdFunction(d)); let x = d=>(d["BA.4+BA.5 3day date"] - d["BA.2 3day date"])/(1000*60*60*24); let y = "BA.4+BA.5 peak to BA.2 peak"; return Plot.plot({ height: 400, width: 1000, marginLeft: 75, marginRight: 25, marginTop: 25, marginBottom: 45, style: { fontSize: 15, }, color: { //legend: "swatches", //columns: "11em", //range: colorRange }, //x: {type: "label"}, x: { label: "Days between BA.2 peak and BA.4+BA.5 peak", labelAnchor: "center", nice:true, //type: "band", //domain: d3.sort(data, d=> d.numcrew + d.numpax).map(d=>d["Ship Name"]) }, y: { labelAnchor: "center", label: "BA.4+BA.5 peak to BA.2 peak", tickPadding: 1, tickSize: 3, nice:true, }, grid: true, marks: [ Plot.ruleY([0]), Plot.circle(data, { x, y, r: d=>Math.sqrt(d["BA.2 3day"]), title: d=>d.State , fill: d=>!thresholdFunction(d), stroke: d=>!thresholdFunction(d), }), Plot.text(data, { x, y, dx: 7, dy: 0, fill: d=>d.State, fontSize: d=>Math.sqrt(d["BA.2 3day"])/4 + 2, text: d=>d.State, textAnchor: "start", }), Plot.linearRegressionY(data1, { x, y, stroke: "steelblue", ci: 0.95}), Plot.linearRegressionY(data2, { x, y, stroke: "rgb(255, 155, 57)", ci: 0.95}), ] }) }39:T939,{ if (!showPeakvBA2) { return md`Check box above to show chart.`; } await visibility(); let threshold = 1500; let v1 = "BA.1+BA.4+BA.5" ; let v2 = "BA.2"; //let denom = d=>statePopulation[d.State]/1000000; let denom = d=>d[`${v1} peak`]; let transitions = getTransitions(v1,v2); console.log(transitions); function thresholdFunction(d) { return d[v1 + " peak"] >= threshold; } //let data = Object.values(variantPeaks).filter(d=>d.State !== "North Dakota"); let data = transitions.filter(d=>d.State !== "North Dakota"); let data1 = data.filter(thresholdFunction); let data2 = data.filter(d=> !thresholdFunction(d)); //let x = d=>(d["BA.2 half date"] - d["BA.1+BA.4+BA.5 half date"])/(1000*60*60*24); //let y = d=>d["BA.2 3day"]/d["BA.1+BA.4+BA.5 3day"]; //let x = d=>d[v2]/d[`${v1} peak`]; //let y = d=>d[`${v2} peak`]/d[`${v1} peak`]; let x = d=>d[v2]/denom(d); let y = d=>d[`${v2} peak`]/denom(d); return Plot.plot({ height: 400, width: 1000, marginLeft: 75, marginRight: 25, marginTop: 25, marginBottom: 45, style: { fontSize: 15, }, color: { //legend: "swatches", //columns: "11em", //range: colorRange }, //x: {type: "label"}, x: { label: `Level of ${v2} at 50% (samples per million)`, labelAnchor: "center", nice:true, //type: "band", //domain: d3.sort(data, d=> d.numcrew + d.numpax).map(d=>d["Ship Name"]) }, y: { labelAnchor: "center", label: "BA.2 peak (samples per million)", tickPadding: 1, tickSize: 3, nice:true, }, grid: true, marks: [ Plot.ruleY([0]), Plot.circle(data, { x, y, r: d=>Math.sqrt(d["BA.2 3day"]), title: d=>d.State , fill: d=>!thresholdFunction(d), stroke: d=>!thresholdFunction(d), }), Plot.text(data, { x, y, dx: 7, dy: 0, fill: d=>d.State, fontSize: d=>Math.sqrt(d["BA.2 3day"]) + 2, text: d=>d.State, textAnchor: "start", }), Plot.linearRegressionY(data1, { x, y, stroke: "steelblue", ci: 0.95}), Plot.linearRegressionY(data2, { x, y, stroke: "rgb(255, 155, 57)", ci: 0.95}), ] }) }3a:T4f0,{ if (!showGrowthAdvantage) { return md`Check box above to show chart.`; } await visibility(); let data = [...dataForLogRatio]; let startDate = (new Date(logRatioStartDate)).valueOf(); let endDate = d3.max(data,d=>d.Date) ; let startPoints = data.filter(d=>d.Date === startDate && d.Variants in {'BA.2':1,'BA.4+BA.5':1}); console.log(startPoints); let projectionDays = 60; let msPerDay = 1000 * 24*60*60; let projectionMs = projectionDays * msPerDay; startPoints.forEach(s => { let endPoint = data.slice().reverse().find(d => d.State === s.State && d.Date === endDate && d.Variants === s.Variants) console.log(endPoint); if (!endPoint) { return ; } let projectionDate = projectionMs + endPoint.Date; let projectionRatio = (endPoint.LogRatio - s.LogRatio)/ (endPoint.Date - s.Date) * projectionMs + endPoint.LogRatio ; let Variants = s.Variants + " trend"; data.push({ ...s, Variants, }); data.push({ ...endPoint, Variants, }); data.push({ Date: projectionDate, LogRatio: projectionRatio, State: s.State, Variants, }); }); return plotVariants(data,"LogRatio",[firstPlotDate, Date.now() + projectionMs],1.2,[-12,12]); }3b:T882,function checkForNewColumns() { const newKeys = Object.keys(allData1.filter(d=>d.State==="California").slice(-1)[0]); const oldKeys = [ "State", "Date", "7day_mov_avg", "7day_top1", "7day_top1rate", "7day_top2", "7day_top2rate", "7day_top3", "7day_top3rate", "7day_top4", "7day_top4rate", "7day_top5", "7day_top5rate", "7day_mov_avgOmi", "7day_mov_avgPreOmi", "7day_mvOmi_nmrtr", "7day_mvOmi_dnmntr", "7day_mvPreOmi_nmrtr", "7day_mvPreOmi_dnmntr", "test_number_pos", "test_number_pos_rolling", "test_number_ALL_rolling", "test_number_lineage", "total", "Omicro_period", "Presume_period", "update_dt", "1weekago_view_positive", "1weekago_view_ALL", "3weekago_view_positive", "3weekago_view_ALL", "7day_mov_Pre", "Place", "Longitude", "Latitude", "Current_rel_change", "3day_mov_avgOmiOther", "3day_PreOmiBA2Nation", "3day_PreOmiBA11Nation", "3day_mov_avgOmiBA1Nation", "3day_mov_avgOmiBA2", "3day_mov_avgOmiBA1", "3day_mov_avgOmiBA2Nation", "3day_mov_avgOmiOtherNation", "3day_mvOmiBA2_nmrtr", "3day_mvPreOther_nmrtr", "3day_mvPreOmiBA2_nmrtr", "3day_mvPreOmiBA11_nmrtr", "3day_mov_avgPreOmiBA2", "3day_mov_avgPreOmiBA11", "3day_mov_avgPreOther", "3day_PreOtherNation", "3day_mvOmiBA1_nmrtr", "3day_mvOmiBA4_nmrtr", "3day_mov_avgOmiBA4", "3day_mov_avgOmiBA4Nation", "3day_mvOmiBA5_nmrtr", "3day_mov_avgOmiBA5", "3day_mov_avgOmiBA5Nation", "3day_mvOmiOther_nmrtr", "3day_mvOmiOtherOmi_nmrtr", "3day_mov_avgOmiOtherOmi", "Region", "BA2_nation_new", "BA4_nation_new", "BA5_nation_new", "OmiOth_new", "BA2_state_new", "BA4_state_new", "BA5_state_new", "OmiOth_state_new", "OthAll_new", "OthAll_state_new", "Range2", "lineage_end_date", "Other 1day", "BA.1+BA.4+BA.5 1day", "BA.2 1day", "i", "BA.1 1day", "BA.4+BA.5 1day" ]; const diffs = []; newKeys.forEach((k,i)=>{ if (k !== oldKeys[i]) { diffs.push(k); } }); return diffs; }3c:T4b9,statePopulation = { return {"undefined":null,"California":39029342,"Texas":30029572,"Florida":22244823,"New York":19677151,"Pennsylvania":12972008,"Illinois":12582032,"Ohio":11756058,"Georgia":10912876,"North Carolina":10698973,"Michigan":10034113,"New Jersey":9261699,"Virginia":8683619,"Washington":7785786,"Arizona":7359197,"Tennessee":7051339,"Massachusetts":6981974,"Indiana":6833037,"Missouri":6177957,"Maryland":6164660,"Wisconsin":5892539,"Colorado":5839926,"Minnesota":5717184,"South Carolina":5282634,"Alabama":5074296,"Louisiana":4590241,"Kentucky":4512310,"Oregon":4240137,"Oklahoma":4019800,"Connecticut":3626205,"Utah":3380800,"Puerto Rico":3221789,"Iowa":3200517,"Nevada":3177772,"Arkansas":3045637,"Mississippi":2940057,"Kansas":2937150,"New Mexico":2113344,"Nebraska":1967923,"Idaho":1939033,"West Virginia":1775156,"Hawaii":1440196,"New Hampshire":1395231,"Maine":1385340,"Montana":1122867,"Rhode Island":1093734,"Delaware":1018396,"South Dakota":909824,"North Dakota":779261,"Alaska":733583,"District of Columbia":671803,"Vermont":647064,"Wyoming":581381,"Guam":null,"U.S. Virgin Islands":null,"American Samoa":null,"Northern Mariana Islands":null,"Contiguous United States":331113778}; }3d:T46b,statePopulationFromWikipedia = { return statePopulation; // I used this to fetch population data from wikipedia. let response = await fetch(`https://en.wikipedia.org/w/api.php?format=json&origin=*&action=parse&prop=text&page=List_of_U.S._states_and_territories_by_population§ion=5`).then(response => response.json()); const parser = new DOMParser(); const external = parser.parseFromString(response.parse.text["*"], "text/html"); console.log(response.parse.text["*"]); const table = document.adoptNode(external.querySelector("table")); table.style = ` display: block; position: relative; max-width: none; max-height: 600px; overflow-y: auto; -webkit-overflow-scrolling: touch; `; let rows = table.querySelectorAll("tr:not(:first-child)"); let states = Array.from(rows, r=>r.querySelector(":nth-child(3) a")?.innerHTML); let pop = Array.from(rows, r=>parseInt(r.querySelector(":nth-child(4)")?.innerHTML.replace(/\D/g,""))); let o = {}; states.forEach((s,i)=>o[s] = pop[i]); console.log("Fetched state population table from wikipedia",o, JSON.stringify(o)); return o; }3e:T4b6,stateAbbreviations = ({ "Alabama": "AL", "Alaska": "AK", "American Samoa": "AS", "Arizona": "AZ", "Arkansas": "AR", "California": "CA", "Colorado": "CO", "Connecticut": "CT", "Delaware": "DE", "District of Columbia": "DC", "Florida": "FL", "Georgia": "GA", "Guam": "GU", "Hawaii": "HI", "Idaho": "ID", "Illinois": "IL", "Indiana": "IN", "Iowa": "IA", "Kansas": "KS", "Kentucky": "KY", "Louisiana": "LA", "Maine": "ME", "Maryland": "MD", "Massachusetts": "MA", "Michigan": "MI", "Minnesota": "MN", "Mississippi": "MS", "Missouri": "MO", "Montana": "MT", "Nebraska": "NE", "Nevada": "NV", "New Hampshire": "NH", "New Jersey": "NJ", "New Mexico": "NM", "New York": "NY", "North Carolina": "NC", "North Dakota": "ND", "Northern Mariana Islands": "MP", "Ohio": "OH", "Oklahoma": "OK", "Oregon": "OR", "Pennsylvania": "PA", "Puerto Rico": "PR", "Rhode Island": "RI", "South Carolina": "SC", "South Dakota": "SD", "Tennessee": "TN", "Texas": "TX", "Utah": "UT", "Vermont": "VT", "Virgin Islands": "VI", "Virginia": "VA", "Washington": "WA", "West Virginia": "WV", "Wisconsin": "WI", "Wyoming": "WY" })3f:T8d2,getVariants = function(data, keys = ["Other","BA.1","BA.2","BA.4+BA.5"] ) { //const keys = ["Other","BA.1","BA.2","BA.4+BA.5","BA.1+BA.4+BA.5"]; //const keys = ["Other","BA.1+BA.4+BA.5","BA.2"]; let byStateDate = {}; let v = data.flatMap((r,i) => { let a = []; let peak = variantPeaks[r.State]["BA.4+BA.5 Cases"]; keys.forEach(k => { let p = r[k + " Proportion"]; let p7 = r[k + " Proportion 7day"]; let p9 = r[k + " Proportion 9day"]; let cases = casesByDateAndState[r.State][r.Date]; let logRatio = Math.log2(p)-Math.log2(1-p); let d = { Date:r.Date, State:r.State, Variants: k, Samples: r[k], Samples3day: r[k +" 3day"], Samples7day: r[k +" 7day"], Samples9day: r[k +" 9day"], Proportion: p, Proportion7day: p7, Proportion9day: p9, LogRatio: logRatio, Cases: r[k + " Cases"], "Cases scaled": r[k + " Cases"]/peak, Days: r.Days, }; a.push(d); byStateDate[k] = byStateDate[k] || {}; byStateDate[k][r.State] = byStateDate[k][r.State] || {}; byStateDate[k][r.State][r.Date] = d; let period = 7; let lastWeek = byStateDate[k][r.State][r.Date - period*24*60*60*1000]; if (lastWeek && p && p < 1) { let lastP = lastWeek.Proportion; if (lastP && lastP < 1){ let relativeGrowth = Math.pow(p/(1-p) / (lastP/(1-lastP)),1/period) - 1; d.RelativeGrowth = relativeGrowth; } let twoWeeksAgo = byStateDate[k][r.State][r.Date - 2*period*24*60*60*1000]; if (twoWeeksAgo) { let lastP2 = twoWeeksAgo.Proportion; if (lastP2 && lastP2 < 1){ let relativeGrowth2weeks = Math.pow(p/(1-p) / (lastP2/(1-lastP2)),1/2/period) - 1; d.RelativeGrowth2weeks = relativeGrowth2weeks; let relativeGrowth2 = Math.pow(lastP/(1-lastP) / (lastP2/(1-lastP2)),1/period) - 1; d.RelativeGrowthChange = (d.RelativeGrowth - relativeGrowth2)/period; } } } }); a.push({ Date:r.Date, State:r.State, Variants: "All", Cases: r.Positives, }); return a; }); return v; }40:Ta49,getVariantsMult = function(data) { let a = []; let m = {}; data.forEach((r,i) => { const keys = ["Other","BA.1","BA.2","BA.4+BA.5"]; //const keys = ["BA.4+BA.5","BA.1","BA.2","Other"]; //const keys = ["BA.1+BA.4+BA.5","BA.2","Other"]; let peak = variantPeaks[r.State]["BA.1 Cases"]; keys.forEach(k => { let p = r[k + " Proportion"]; let cases = casesByDateAndState[r.State][r.Date]; if (!m[r.Date]) { m[r.Date] = { }; } if (!m[r.Date][k]) { m[r.Date][k] = { Date:r.Date, State:r.State, Variants: k, Samples: r[k] || 0, TotalSamples: p ? Math.round(r[k]/p) : 0, Samples3day: r[k +" 3day"] || 0, Samples9day: r[k +" 9day"] || 0, Samples7day: r[k +" 7day"] || 0, Samples1day: r[k +" 1day"] || 0, Proportion: p, Cases: r[k + " Cases"] || 0, "Cases scaled": (r[k + " Cases"]||0)/peak, Days: r.Days, StateCount: 1, } } else { let o = m[r.Date][k]; o.State += ", " + r.State; o.Samples += r[k] || 0; o.TotalSamples += p ? Math.round(r[k]/p) : 0; o.Samples3day += r[k +" 3day"] || 0; o.Samples7day += r[k +" 7day"] || 0; o.Samples9day += r[k +" 9day"] || 0; o.Samples1day += r[k +" 1day"] || 0; o.Proportion = o.Samples/o.TotalSamples; o.Cases += r[k + " Cases"] || 0; o["Cases scaled"] = o.Cases/peak; o.Days += r.Days; o.StateCount++; } if (r.Date == 1687305600000-5*1000*24*60*60) { //console.log("debug ",m[r.Date][k],r); } }); if (r.Date < firstPlotDate) { return ; } if (!m[r.Date].All) { m[r.Date].All = { Date:r.Date, State:r.State, Variants: "All", Cases: r.Positives } } else { m[r.Date].All.Cases += r.Positives; } let keysToTotal = { "Samples":"", "Samples1day":" 1day", "Samples3day":" 3day", "Samples7day":" 7day", "Samples9day":" 9day", }; keys.forEach(k => { Object.entries(keysToTotal).forEach( entry => { let ko = entry[0]; let ki = entry[1]; m[r.Date].All[ko] = (m[r.Date].All[ko] || 0) + (r[k + ki]||0); }); }); if (r.State == "Alaska" && r.Date == lastDate-1*1000*24*60*60) { //debugger; } }); Object.values(m).forEach(mm => { Object.values(mm).forEach(r => { a.push(r); }); }); console.log("getVariantsMult returning",a); return a; }41:T1b07,allBA4 = { let ko = "3day_mvPreOther_nmrtr"; let k1 = "3day_mvPreOmiBA11_nmrtr"; let k2 = "3day_mvPreOmiBA2_nmrtr"; let kp = "test_number_pos_rolling"; let kall = "test_number_ALL_rolling"; let ba1zeroDate = (new Date("May 1, 2022")).valueOf(); //console.log(ba1zeroDate); let a = []; let lastDays = { other: [], ba1: [], ba2: [], }; function sigmoid(x) { return 1 / (1 + Math.exp(-x)); } let previous = { other: 0, ba1: 0, ba2: 0, }; let cumulativeCases = {} let keys3Day = [ko,k1,k2]; let keys1Day = ["Other 1day","BA.1+BA.4+BA.5 1day","BA.2 1day"]; let keys7Day = ["Other 7day","BA.1+BA.4+BA.5 7day","BA.2 7day"]; let keys9Day = ["Other 9day","BA.1+BA.4+BA.5 9day","BA.2 9day"]; function ba45sigmoid(x, date) { return Math.round(x * sigmoid((date - ba1zeroDate)/(5*1000*24*60*60))); } statesList.forEach(s => { let sd = allData.filter(r => r.State === s); // Infer the daily samples of each variant sd.forEach((r,i)=> { if (i) { let prevDate = sd[i-1].Date; let daysElapsed = (r.Date - prevDate)/24/60/60/1000; if (daysElapsed !== 1) { //console.warn("Day skipped?",sd[i-1],r); } } keys3Day.forEach((k, ki) => { let k2 = keys1Day[ki]; let prev = sd[i-1] && sd[i-1][k2]; let prev2 = sd[i-2] && sd[i-2][k2]; if (r[k]===null) { r[k2] = null; } else if (prev === null) { r[k2] = 1/3 * r[k]; } else if (prev2 === null) { r[k2] = 1/6 * r[k] + 1/6 * sd[i-1][k] ; } else { // Clamp to 0 because there are some data anomalies r[k2] = Math.max(0,(r[k] || 0) - prev - prev2); } }); r.i = i ; let ba145 = r["BA.1+BA.4+BA.5 1day"]; let ba45 = ba45sigmoid(ba145,24*1000*60*60 + r.Date) ; let ba1 = ba145 - ba45; r["BA.1 1day"] = ba1 ; r["BA.4+BA.5 1day"] = ba45 ; }); let smap = sd.map((r,i) => { let other = r[ko] || 0; let ba1 = r[k1] || 0; let ba2 = r[k2] || 0; let tot = ba1+ba2+other ; let ii = i - 3 while (tot < 100 && ii > i - 14) { if (sd[ii]) { other += sd[ii][keys1Day[0]]; ba1 += sd[ii][keys1Day[1]]; ba2 += sd[ii][keys1Day[2]]; tot = ba1+ba2+other ; } //console.log(r.State,{tot,other,ba1,ba2}); ii -= 1; } if (!tot && r.State === "North Dakota") { //console.log(r.State,r.Date,{tot,other,ba1,ba2}); } let days = i - ii; let ba145 = ba1; let ba45 = ba45sigmoid(ba145,r.Date) ; ba1 = ba145 - ba45; let ba145_3day = r[k1]; let ba45_3day = ba45sigmoid(ba145_3day,r.Date) ; let ba1_3day = ba145_3day - ba45_3day; let pos = r[kp]; let tests = r[kall]; let po = other / tot; let p1 = ba1 / tot; let p145 = tot > 0 ? ba145 / tot : 0; if (tot < 1 && s === "California") { //console.warn("tot zero",tot,new Date(r.Date),r); } let p45 = ba45 / tot; let p2 = ba2 / tot; let d7 = {}; keys7Day.forEach((k7,ki)=>{ d7[k7] = r[keys3Day[ki]] + (sd[i-3] && sd[i-3][keys3Day[ki]]|| 0) + (sd[i-6] && sd[i-6][keys1Day[ki]]|| 0); }); let d9 = {}; keys9Day.forEach((k9,ki)=>{ d9[k9] = r[keys3Day[ki]] + (sd[i-3] && sd[i-3][keys3Day[ki]]|| 0) + (sd[i-6] && sd[i-6][keys3Day[ki]]|| 0); }); let ba145_7day = d7["BA.1+BA.4+BA.5 7day"]; let ba45_7day = ba45sigmoid(ba145_7day,r.Date-2*24*60*60*1000) ; let ba1_7day = ba145_7day - ba45_7day; d7["BA.4+BA.5 7day"] = ba45_7day ; let ba145_9day = d9["BA.1+BA.4+BA.5 9day"]; let ba45_9day = ba45sigmoid(ba145_9day,r.Date-2*24*60*60*1000) ; let ba1_9day = ba145_9day - ba45_9day; d7["BA.1 7day"] = ba1_7day ; let ba2_7day = d7["BA.2 7day"]; let other_7day = d7["Other 7day"]; let tot_7day = other_7day + ba2_7day + ba145_7day ; d7["All Samples 7day"] = tot_7day ; d9["BA.1 9day"] = ba1_9day ; let ba2_9day = d9["BA.2 9day"]; let other_9day = d9["Other 9day"]; let tot_9day = other_9day + ba2_9day + ba145_9day ; d9["All Samples 9day"] = tot_9day ; if (0 && r.State === "California") { console.log({ Date:(new Date(r.Date).toString()).slice(0,20) , po, p1, p145, p45, p2, //ba145_1day:r[keys1Day[1]], //ba145_3day, //ba145_7day, //ba1_7day, //d7 }); } let po_7day = other_7day / tot_7day; let p1_7day = ba1_7day / tot_7day; let p145_7day = ba145_7day / tot_7day; let p45_7day = ba45_7day / tot_7day; let p2_7day = ba2_7day / tot_7day; let po_9day = other_9day / tot_9day; let p1_9day = ba1_9day / tot_9day; let p145_9day = ba145_9day / tot_9day; let p45_9day = ba45_9day / tot_9day; let p2_9day = ba2_9day / tot_9day; if (r.State === "Nevada") { //console.log({ba145_7day,ba1_7day,r, d7,tot_7day,po_7day,p1_7day,p145_7day,p45_7day,p2_7day}); } return { Date: r.Date, State: r.State, "BA.4+BA.5 Proportion": p45, "BA.2 Proportion": p2, "BA.4+BA.5": ba45, "BA.2": ba2, Days: days, "BA.4+BA.5 3day": ba45_3day, "BA.2 3day": r[k2], "BA.4+BA.5 Cases": p45_9day * pos, "BA.2 Cases": p2_9day * pos, "Positives": pos, ...d9, ...d7, "Other 1day": r["Other 1day"], "BA.1 1day": r["BA.1 1day"], "BA.2 1day": r["BA.2 1day"], "BA.1+BA.4+BA.5 1day": r["BA.1+BA.4+BA.5 1day"], "BA.4+BA.5 1day": r["BA.4+BA.5 1day"], "Other Proportion": po, "BA.1 Proportion": p1, "BA.1+BA.4+BA.5 Proportion": p145, "BA.4+BA.5 Proportion 9day": p45_9day, "BA.2 Proportion 9day": p2_9day, "Other Proportion 9day": po_9day, "BA.1 Proportion 9day": p1_9day, "BA.4+BA.5 Proportion 7day": p45_7day, "BA.2 Proportion 7day": p2_7day, "Other Proportion 7day": po_7day, "BA.1 Proportion 7day": p1_7day, "Other Cases": po_9day * pos, "BA.1 Cases": p1_9day * pos, "BA.1+BA.4+BA.5 Cases": p145_9day * pos, "Other": other, "BA.1": ba1, "BA.1+BA.4+BA.5": ba145, Tests: tests, Positivity: pos/tests, "Other 3day": r[ko], "BA.1 3day": ba1_3day, "BA.1+BA.4+BA.5 3day": ba145_3day, "All Samples": tot, }; }); a.push(smap); }); //console.log(a); return [].concat(...a); } 42:T52a, variantPeaks = { const peaks = {}; const transitionDates = {}; allBA4.forEach(d=>{ if (!peaks[d.State]) { peaks[d.State] = { State: d.State }; } for (const [k, v] of Object.entries(d)) { if (isNaN(v) || v===null) { continue ; } if (k in peaks[d.State]) { if (v >= peaks[d.State][k]) { peaks[d.State][k] = v; peaks[d.State][k + " date"] = d.Date; peaks[d.State][k+ " half"] = null; peaks[d.State][k + " half date"] = null; } if (v <= 0.5*peaks[d.State][k] && !peaks[d.State][k + " half date"]) { peaks[d.State][k+ " half"] = v; peaks[d.State][k + " half date"] = d.Date; } } else { peaks[d.State][k] = v; peaks[d.State][k + " date"] = d.Date; } } if (!transitionDates[d.State]) { if (d["BA.4+BA.5 3day"] > d["BA.2 3day"]) { transitionDates[d.State] = d.Date ; } } }); Object.values(peaks).forEach(d=> { d["BA.4+BA.5 peak to BA.2 peak"] = d["BA.4+BA.5"]/d["BA.2"]; d["BA.4+BA.5 peak to BA.1 peak"] = d["BA.4+BA.5"]/d["BA.1"]; }); return peaks; let a = []; for (const [k, v] of Object.entries(peaks)) { a.push({State:k,...v}); } return a; }43:T41b,currentBA4growth = { const k = "BA.1+BA.4+BA.5 Proportion"; const ka = "All Samples"; currentBA4.forEach((r,i) => { // BA4 (SGTF) fraction growth if (!prevBA4[i]) { return ; } r.Growth = r[k] / prevBA4[i][k] - 1; // BA2 (non-SGTF) fraction growth r.Growth2 = (1-r[k]) / (1- prevBA4[i][k]) - 1; r.PositivityChange = r.Positivity - prevBA4[i].Positivity; r.PositivityGrowth = r.Positivity/prevBA4[i].Positivity - 1; r.Change = r[k] - prevBA4[i][k]; const vars = ["BA.2","BA.4+BA.5",ka,"Positives","Tests"]; r[ka + " Projected"] = 0; vars.forEach(v => { const k2 = {Positives:1,Tests:1}[v] ? v : (v + " 7day"); r[v + " Growth"] = r[k2] / prevBA4[i][k2] - 1; r[v + " Change"] = r[k2] - prevBA4[i][k2]; if (v !== ka) { r[v + " Projected"] = r[k2] + r[k2] * r[v + " Growth"]; r[ka + " Projected"] += r[v + " Projected"]; } }); r[ka + " Projected Growth"] = r[ka + " Projected"] / r[ka + " 7day"] - 1; }); return currentBA4; }44:T120d, function stateTable(stateName,dataTotals,variantsData) { let lastDay = mapDay - numberOfDays - 1; let lagDays = 1; let kr = "7day_mov_avg"; let kpos = "test_number_pos_rolling"; let kall = "test_number_ALL_rolling"; let empty = { [kr]:0, [kpos]:0, [kall]:0, }; let current = dataTotals.slice(lastDay-lagDays)[0]; let prior = dataTotals.slice(lastDay-7-lagDays)[0]; console.log(current); let prior2 = dataTotals.slice(lastDay-14-lagDays)[0]; console.log(kr,{current:current[kr], prior:prior[kr]}); console.log(kpos,{current:current[kpos], prior:prior[kpos]}); console.log(kall,{current:current[kall], prior:prior[kall]}); let currentRate = current[kpos] / current[kall] ; let priorRate = prior[kpos] / prior[kall] ; let prior2Rate = prior2[kpos] / prior2[kall] ; console.log({lastDay, mapDay, numberOfDays}); let ba45 = variantsData.filter(d=>d.Variants=="BA.4+BA.5"); let ba2 = variantsData.filter(d=>d.Variants=="BA.2"); console.log("ba45",ba45); console.log("ba2",ba2); let ba45_last_n_days = ba45.slice(-14-lagDays); let ba2_last_n_days = ba2.slice(-14-lagDays); let sgtf_samples9_last_week = ba45_last_n_days[0].Samples3day + ba45_last_n_days[3].Samples3day + ba45_last_n_days[6].Samples3day; let sgtf_samples9 = ba45_last_n_days[7].Samples3day + ba45_last_n_days[10].Samples3day + ba45_last_n_days[13].Samples3day; let non_sgtf_samples9_last_week = ba2_last_n_days[0].Samples3day + ba2_last_n_days[3].Samples3day + ba2_last_n_days[6].Samples3day; let non_sgtf_samples9 = ba2_last_n_days[7].Samples3day + ba2_last_n_days[10].Samples3day + ba2_last_n_days[13].Samples3day; console.log({lastDay,mapDay,ba45length:ba45.length, sgtf_samples9, sgtf_samples9_last_week, non_sgtf_samples9, non_sgtf_samples9_last_week}); let currentBA45 = ba45.slice(lastDay)[0].Proportion; let currentBA45lag = ba45.slice(lastDay-lagDays)[0].Proportion; let currentBA45p = (currentBA45*100).toFixed(1)+"%"; let currentBA45Cases = (current[kpos]* currentBA45lag).toFixed(0); let currentBA2Cases = current[kpos] - currentBA45Cases; let priorBA45 = ba45.slice(lastDay-7)[0].Proportion; console.log("priorBA45",priorBA45); let priorBA45lag = ba45.slice(lastDay-7-lagDays)[0].Proportion; let priorBA45p = (priorBA45lag*100).toFixed(1)+"%"; let priorBA45Cases = (prior[kpos]* priorBA45lag).toFixed(0); let priorBA2Cases = prior[kpos] - priorBA45Cases; let prior2BA45 = ba45.slice(lastDay-14)[0].Proportion; let prior2BA45lag = ba45.slice(lastDay-14-lagDays)[0].Proportion; let prior2BA45p = (prior2BA45lag*100).toFixed(1)+"%"; let prior2BA45Cases = (prior2[kpos]* prior2BA45lag).toFixed(0); let prior2BA2Cases = prior2[kpos] - prior2BA45Cases; function toPercent(x,d=1) { return (x * 100).toFixed(d); } return md`| ${stateName} Walgreens | Positivity Rate | Positive Tests | Total Tests | SGTF % | SGTF Pos Tests, 9 days | non-SGTF Pos Tests, 9 days | ------ | -------- | ---------- | ------- | Current week | ${toPercent(currentRate)}% | ${current[kpos]?.toLocaleString()} | ${current[kall].toLocaleString()} | ${currentBA45p} | ${sgtf_samples9.toLocaleString()} | ${non_sgtf_samples9.toLocaleString()} | Prior week | ${toPercent(priorRate)}% | ${prior[kpos]?.toLocaleString()} | ${prior[kall].toLocaleString()} | ${priorBA45p} | ${priorBA45Cases.toLocaleString()} | ${priorBA2Cases.toLocaleString()} | 2 weeks prior | ${toPercent(prior2Rate)}% | ${prior2[kpos]?.toLocaleString()} | ${prior2[kall].toLocaleString()} | ${prior2BA45p} | ${prior2BA45Cases?.toLocaleString()} | ${prior2BA2Cases.toLocaleString()} | *1-week Change* | *${toPercent(currentRate-priorRate)}%* | *${toPercent((current[kpos]-prior[kpos])/prior[kpos])}%* | *${toPercent((current[kall]-prior[kall])/prior[kall])}%* | *${toPercent(currentBA45lag-priorBA45lag)}%* | *${toPercent((currentBA45Cases-priorBA45Cases)/priorBA45Cases)}%* | *${toPercent((currentBA2Cases-priorBA2Cases)/priorBA2Cases)}%* | *2-week Change* | *${toPercent(currentRate-prior2Rate)}%* | *${toPercent((current[kpos]-prior2[kpos])/prior2[kpos])}%* | *${toPercent((current[kall]-prior2[kall])/prior2[kall])}%* | *${toPercent(currentBA45lag-prior2BA45lag)}%* | *${toPercent((currentBA45Cases-prior2BA45Cases)/prior2BA45Cases)}%* | *${toPercent((currentBA2Cases-prior2BA2Cases)/prior2BA2Cases)}%* "Est. SGTF (or non-SGTF) Pos Tests" is the product of the 7-day rolling positive tests times the estimate of the proportion of SGTF (or non-SGTF) cases, ${lagDays} days back (to reduce the effect of reporting lag). `; }45:T156d,function plotTestsPositivity(datain,domain,showAllTests = true, regionSelected="", stateSelected) { domain = domain || [new Date(2021, 4, 0), Date.now()]; let data = { tests: datain.tests.sort((a,b)=>a.Date - b.Date).filter(d=>d.Date >= domain[0] && d.Date <= domain[1] && (d.Tests !== "All Tests" || showAllTests)), positivity: datain.positivity.sort((a,b)=>a.Date - b.Date).filter(d=>d.Date >= domain[0] && d.Date <= domain[1] ), }; let wastewaterPlot = null; let wastewaterLabel = null; console.log("regionSelected",regionSelected); let wastewaterRegion = regionSelected; console.log("wastewaterRegion",wastewaterRegion); if (regionSelected == "National" && !stateSelected ) { stateSelected = "Alabama"; } let statesInRegion = usCensusRegions[regionSelected]; if (statesInRegion && !stateSelected ) { stateSelected = statesInRegion[0]; } if (wastewaterRegion) { let regionWastewaterData = newCdcWasteWaterData.filter(d=>d.date >= domain[0] && d.date <= domain[1] && d.state === stateSelected && d.date_period === "All Results"); console.log("regionWastewaterData",regionWastewaterData); let key = "wastewater" ; if (regionSelected == "National") { key = "national_wastewater"; } else if (usCensusRegions[regionSelected]) { key = "regional_wastewater"; } if (regionWastewaterData.length) { let recentWastewaterMean = d3.mean(regionWastewaterData.slice(-14,-1),d=>d[key]); let lastWastewaterDate = regionWastewaterData.slice(-2)[0].date.valueOf(); let recentTests = data.tests.filter(d=>d.Tests === "Positive Tests" && d.Date <= lastWastewaterDate && d.Date > lastWastewaterDate-13*7*24*60*60*1000); //console.log("recentTests",recentTests); let recentPositivesMean = d3.mean(recentTests,d=>d.WeeklyTests); //console.log(lastWastewaterDate); //console.log("recentWastewaterMean",recentWastewaterMean); //console.log("recentPositivesMean",recentPositivesMean); let wastewaterScale = recentPositivesMean / recentWastewaterMean; wastewaterScale = 1; wastewaterPlot = Plot.lineY(regionWastewaterData, { x: d=>d.date.valueOf(), y: d=>d[key] * wastewaterScale, stroke: d=>"Wastewater", tip: true }); wastewaterLabel = Plot.text(regionWastewaterData, Plot.selectLast({ x: d=>d.date.valueOf(), y: d=>d[key] * wastewaterScale, fill: d=>"Wastewater", text: ()=>"CDC Wastewater " + wastewaterRegion, textAnchor: "end", fontSize: chartFontSize, dx: -5, dy: -5 })); //console.log("wastewaterPlot",wastewaterPlot); } } let maxY = d3.max(data.tests,d=>d.WeeklyTests); let positiveTests = data.tests.filter(d=>d.Tests==="Positive Tests"); let maxPos = d3.max(data.tests.filter(d=>d.Tests==="Positive Tests"),d=>d.WeeklyTests); let posScale = maxY/maxPos; let positiveTestsScaled = positiveTests.map(d=> { return { ...d, Tests: "Positives scaled", WeeklyTests: d.WeeklyTests*posScale, }; }); //data.tests = data.tests.concat(positiveTestsScaled); let dayMS = 24*60*60*1000 ; let daysShaded = [-7,0].map(d=>{ return { Date: lastTimestamp + d*dayMS, WeeklyTests: maxY, }; }); let domainDays = (domain[1].valueOf() - domain[0].valueOf())/dayMS; console.log("domainDays is ",domainDays); let yearLine = null; if (domainDays > 372) { console.log("Going to put a 1-year-ago line, domainDays is ",domainDays); yearLine = [ Plot.ruleX([{date:new Date(domain[1].valueOf()-365*dayMS)}],{x:d=>d.date.valueOf(),y1:d=>0,y2:d=>maxY, stroke:"#888",opacity:0.9}), Plot.text([{date:new Date(domain[1].valueOf()-365*dayMS)}],{x:d=>d.date.valueOf(),y:d=>0, text:d=>"One year ago", opacity:0.9, textAnchor:"start",lineAnchor:"bottom", fill:d=>"#888", dx: 5, fontSize: width/75}), ]; } console.log("year line",yearLine); let plot = multiLayerX( { ...chartConfig, style: "overflow: visible;", x: { type: "utc", domain: domain, grid: true, tickRotate: -30 }, y: { axis: "left", types: [null,"%"], grid: true, zero: true, label: "Weekly Tests" }, }, Plot.line(data.tests,{ y: "WeeklyTests", x: "Date", stroke:d=>d.Tests === "Positive Tests" ? "#E6B442" : "#4865C2", tip: true, }), Plot.line(data.positivity,{ y: "Positivity", x: "Date", stroke:"#cccccc", tip: true, }), Plot.areaY(daysShaded, { y: "WeeklyTests", x: "Date", fill: "#ccc", opacity: 0.5, }), Plot.text(data.tests, Plot.selectMaxY({ x: d => d.Tests === "All Tests" ? d.Date : d.Date, y: d => d.Tests === "All Tests" ? d.WeeklyTests : d.WeeklyTests/6, fill:d=>d.Tests === "Positive Tests" ? "#E6B442" : "#4865C2", text: "Tests", textAnchor: "end", fontSize: chartFontSize, dy: 0, dx: -10 })), Plot.text(data.positivity, Plot.selectLast({ x: "Date", y: "Positivity", fill: "#888888", text: ()=>"Positivity", textAnchor: "end", fontSize: chartFontSize, dx: -20, dy: -5 })), yearLine, wastewaterPlot, wastewaterLabel, ); plot.setAttribute("font-size",chartFontSize); return scaleToFit(plot); } 46:T16e7,plotVariants = function(datain,column = "Proportion", domain = [firstPlotDate, Date.now()],aspectRatio = 1.2, ydomain=false) { if (column === "Proportion") { console.log(datain); } let curve = {Samples1day:1,Samples3day:1,Samples7day:1}[column] ? "step" : "linear"; const variantsOrder = { "Other":1, "BA.1":2, "BA.2":3, "BA.4+BA.5":4, "All":5, "BA.2 trend":6, "BA.4+BA.5 trend":7, }; function variantsFill(v) { const cmap = { "Other":"a", "BA.1":"b", "BA.2":"c", "BA.4+BA.5":"d", "All":"e", "BA.2 trend":"c", "BA.4+BA.5 trend":"d", }; if (! v in cmap) { console.log("Unexpected variant",v); } return cmap[v] || "a"; } let colorRange = [d3.schemeTableau10[0],d3.schemeTableau10[1],d3.schemeTableau10[3],d3.schemeTableau10[2],"#888888"]; //console.log(colorRange,d3.schemeTableau10); let data = datain.filter(d=>d.Date >= domain[0]); ydomain = ydomain || [Math.min(0,d3.min(data,d=>d[column])),d3.max(data,d=>d[column])]; // TODO: figure out how to order drawing of variants without messing up sorting data = [...data].sort( (a,b)=> (variantsOrder[a.Variants] - variantsOrder[b.Variants]) || a.State.localeCompare(b.State) || (a.Date - b.Date)); let maxY = ydomain ? ydomain[1] : d3.max(data,d=>d[column]); let dayMS = 24*60*60*1000 ; let daysShaded = [-7,0].map(d=>{ return { Date: lastTimestamp*dayMS, [column]: maxY, }; }); //console.log(data); //console.log(datain); let plot = Plot.plot({ style: "overflow: visible;", ...chartConfig, x: { type: "utc", domain, grid: true, tickRotate: -30 }, y: { grid: true, domain: ydomain, nice: true, label: column }, opacity: { type: "linear", domain: [0,1], }, strokeOpacity: { type: "linear", domain: [0,1], range: [0,1], }, fillOpacity: { type: "linear", domain: [0,1], range: [0,1], }, r: { type: "linear", domain: [0,1], }, color: { type: "categorical", reverse:false, range: colorRange }, marks: [ Plot.areaY(daysShaded, { y: column, x: "Date", fill: "#ccc", opacity: 0.5, }), Plot.line(data,{ y: column, x: "Date", curve, z: d=>d.State + " " + d.Variants, //stroke: d=> d.Variants === "All" ? "ZZZZ" : d.Variants, stroke: d=> variantsFill(d.Variants), opacity: (d,i)=> { if (data.length > 365 * 20) { return Math.min(0.9,Math.sqrt(365*10/data.length)); } if (d.Variants === "All") { return 0.5; } if (d.Variants in {"BA.2 trend":1,"BA.4+BA.5 trend":1}) { return 0.2; } return 0.9; }, //strokeOpacity: (d,i)=> column === "Proportion" ? 0.1 : (d.Variants === "All" ? 0.5 : 0.9) , //fillOpacity: (d,i)=> column === "Proportion" ? 0.1 : (d.Variants === "All" ? 0.5 : 0.9) , //fillOpacity: (d,i)=> d.State === data[i-1] && data[i-1].State ? (d.Variants === "All" ? 0.5 : 0.9) : 0, //strokeOpacity: (d,i)=> d.State === data[i-1] && data[i-1].State ? (d.Variants === "All" ? 0.5 : 0.9) : 0, clip: true }), Plot.dot(data,{ y: column, x: "Date", r: ()=>0.5, //z: column, stroke: d=> variantsFill(d.Variants), //stroke: d=> d.Variants === "All" ? "ZZZZ" : d.Variants, opacity: d=>d && 0.1 || 0, //title: (d) => `${(new Date(d.Date)).toLocaleDateString()} ${d.State}\n${column} ${d.Variants} ${d[column]}`, //strokeOpacity: (d,i)=> column === "Proportion" ? 0.0 : (d.Variants === "All" ? 0.5 : 0.9) , //fillOpacity: (d,i)=> column === "Proportion" ? 0.0 : (d.Variants === "All" ? 0.5 : 0.9) , //fillOpacity: (d,i)=> d.State === data[i-1] && data[i-1].State ? (d.Variants === "All" ? 0.5 : 0.9) : 0, //strokeOpacity: (d,i)=> d.State === data[i-1] && data[i-1].State ? (d.Variants === "All" ? 0.5 : 0.9) : 0, clip: true }), /* TODO: try area for all Plot.area(data,{ y: column, x: "Date", stroke: d=> d.Variants === "All" ? "ZZZZ" : d.Variants, opacity: d=> d.Variants === "All" ? 0.5 : 0.9, }),*/ Plot.text(data, Plot.selectMaxY({ x: d=>Math.min(d.Date , lastTimestamp - 7*24*1000*60*60), y: column, fill: d=> variantsFill(d.Variants), text: d=> { if (d.Variants === "All") return ""; if (d.Variants === "BA.2" && d.Date >= new Date("2022-11-01").valueOf()) return "non-SGTF (XBB)"; if (d.Variants === "BA.4+BA.5" && d.Date >= new Date("2022-11-01").valueOf()) return "SGTF (BA.4+BA.5)"; return d.Variants; }, textAnchor: column === "Proportion" ? "start" : "middle", //title: (f, d) => `${d.State}\n${column} ${d[column]}`, dx: column === "Proportion" ? 22 : 10, dy: -chartFontSize*0.5, })), Plot.text(data.filter(d => d.Variants === "BA.2"), Plot.selectMaxX({ x: d => new Date("2022-11-01").valueOf() , y: 0.35, fill: d=> variantsFill(d.Variants), text: d=> column === "Proportion" ? "non-SGTF (XBB)" : "", textAnchor: "start" , //title: (f, d) => `${d.State}\n${column} ${d[column]}`, dx: 0, dy: 0,}) ), Plot.text(data, Plot.selectMinY({ x: "Date", y: d=> d[column] || null, fill: d=> variantsFill(d.Variants), opacity: 0.5, text: d=> d.Variants === "All" ? d.Variants : "", textAnchor: column === "Proportion" ? "start" : "middle", title: (f, d) => `${d.State}\n${column} ${d[column]}`, dx: column === "Proportion" ? 22 : 0, dy: -chartFontSize, })), ] }); plot.setAttribute("font-size",chartFontSize); return scaleToFit(plot,aspectRatio);}47:Td99,plotVariantFacets = function(datain,variant="BA.2",column = "Samples3day", domain = [Date.now()-61*24*60*60*1000, Date.now()],aspectRatio = 4, ydomain=false) { let curve = {Samples1day:1,Samples3day:1,Samples7day:1}[column] ? "step" : "linear"; //let y = d=>d[column]/statePopulation[d.State]*1000000; let data = datain.filter(d=>d.Date >= domain[0] && d.Variants === variant); let maxByState = {}; let minByState = {}; let recentMaxByState = {}; let recentMaxByStateNormalized = {}; let recentAvgByState = {}; let recentAvgByStateNormalized = {}; let recentMaxDivMinByState = {}; let dayMS = 24*60*60*1000 ; let recentDate = lastTimestamp-6*dayMS ; statesList.forEach(state => { maxByState[state] = d3.max(data,d=>d.State === state ? d[column] : 0); minByState[state] = d3.min(data,d=>d.State === state && d[column] ? d[column] : 9999999); recentMaxByState[state] = d3.max(data,d=>d.State === state && d.Date > recentDate ? d[column] : 0); recentAvgByState[state] = d3.sum(data,d=>d.State === state && d.Date > recentDate ? d[column] : 0); recentMaxByStateNormalized[state] = recentMaxByState[state]/maxByState[state] ; recentMaxDivMinByState[state] = recentMaxByState[state]/minByState[state] ; recentAvgByStateNormalized[state] = recentAvgByState[state]/maxByState[state] ; }); let y = d=>d[column]/maxByState[d.State]; //data = data.filter(d=>maxByState[d.State]>5); data = data.filter(d=>minByState[d.State]>1); let items = Object.entries(recentMaxDivMinByState); items.sort((a,b)=>(recentMaxByStateNormalized[b[0]] - recentMaxByStateNormalized[a[0]])*50 + b[1]-a[1]); let stateSort = {}; items.forEach((item,i)=>stateSort[item[0]] = i); console.log("sorted states",items); //data.sort((a,b)=>recentAvgByStateNormalized[a.State] - recentAvgByStateNormalized[b.State]) ydomain = [0,1.1]; console.log(maxByState); let daysShaded = [-7,0].map(d=>{ return { Date: lastTimestamp+d*dayMS, [column]: 1, }; }); let plot = Plot.plot({ style: "overflow: visible;", ...chartConfig, height: 3000, x: { type: "utc", domain, axis: "top", grid: true, }, y: { grid: true, domain: ydomain, nice: true, //label: column }, opacity: { type: "linear", domain: [0,1], }, strokeOpacity: { type: "linear", domain: [0,1], range: [0,1], }, fillOpacity: { type: "linear", domain: [0,1], range: [0,1], }, r: { type: "linear", domain: [0,1], }, color: { //type: "categorical", //reverse:false, //range: colorRange }, facet: { data: data, y: "State", //x: d=>d.State.length % 2, size: chartFontSize * 1.5, marginRight: 90 }, marks: [ Plot.areaY(daysShaded, { y: d=>d[column], x: "Date", fill: "#ccc", opacity: 0.5, }), Plot.line(data,{ y, x: "Date", curve, z: d=>-stateSort[d.State], stroke: y, sort: { fy: {value: "z", reverse: true} }, }), /* Plot.line(data,{ // all lines as background on all facets y, x: "Date", curve, opacity: d=>0.05, stroke: y, facet: "exclude", z: d=>recentAvgByStateNormalized[d.State], sort: { fy: {value: "z", reverse: true} }, }),*/ ] }); plot.setAttribute("font-size",chartFontSize*1); return scaleToFit(plot,aspectRatio);} 48:T5c6,variantsUS = { let us = getVariantsMult(allBA4); let usAllByDay = {}; us.forEach(d=> { if (!usAllByDay[d.Variants]) { usAllByDay[d.Variants] = {}; } usAllByDay[d.Variants][d.Date] = d; }); console.log(usAllByDay); us.forEach(d=> { d.State = "US"; if (!usAllByDay["All"][d.Date]) { //console.log("No usAllByDay for "+d.Date); return ; } let p = d.Samples3day / (usAllByDay["All"][d.Date].Samples3day || 1); d.Proportion = p; let logRatio = Math.log2(p)-Math.log2(1-p) ; d.LogRatio = isFinite(logRatio) ? logRatio : null; let period = 7; let lastWeek = usAllByDay[d.Variants][d.Date - period*24*60*60*1000]; if (lastWeek && p && p < 1) { let lastP = lastWeek.Proportion; if (lastP && lastP < 1){ let relativeGrowth = Math.pow(p/(1-p) / (lastP/(1-lastP)),1/period) - 1; d.RelativeGrowth = relativeGrowth; } let twoWeeksAgo = usAllByDay[d.Variants][d.Date - 2*period*24*60*60*1000]; if (twoWeeksAgo) { let lastP2 = twoWeeksAgo.Proportion; if (lastP2 && lastP2 < 1){ let relativeGrowth2weeks = Math.pow(p/(1-p) / (lastP2/(1-lastP2)),1/2/period) - 1; d.RelativeGrowth2weeks = relativeGrowth2weeks; let relativeGrowth2 = Math.pow(lastP/(1-lastP) / (lastP2/(1-lastP2)),1/period) - 1; d.RelativeGrowthChange = (d.RelativeGrowth - relativeGrowth2)/period; } } } }); return us; }49:T13d3,mapChart = { let domain = [0,1]; let data = currentBA4growth; let type = "diverging"; let pivot = 0.5; let thresholds = [0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9]; if ({"BA.4+BA.5 peak to BA.2 peak":1,"BA.4+BA.5 peak to BA.1 peak":1}[mapMode]) { data = Object.values(variantPeaks); } if (mapByRegion) { let regionData = []; } let values = { Proportion: d => d["BA.2 Proportion"], "3day": d => { let tot = d["BA.1+BA.4+BA.5 3day"] + d["BA.2 3day"] + d["Other 3day"]; return (tot < 2) ? null : d["BA.2 3day"]/tot ; }, "9day": d => { let tot = d["BA.1+BA.4+BA.5 9day"] + d["BA.2 9day"] + d["Other 9day"]; return (tot < 2) ? null : d["BA.2 9day"]/tot ; }, "BA.2 Growth": d => { let tot = d["BA.2 3day"]; return (tot < 6) ? null : d["BA.2 Growth"]; }, "BA.4+BA.5 Growth": d => { let tot = d["BA.1+BA.4+BA.5 3day"]; return (tot < 6) ? null : d["BA.4+BA.5 Growth"]; }, // Change was calculated for BA1/4/5 Change: d =>-d.Change, growthAdvantage: d=>(1+d["BA.2 Growth"])/(1+d["BA.4+BA.5 Growth"]) - 1, } let value = values[mapMode] || (d => d[mapMode]); let maxValue = d3.max(data.map(d=>value(d) < 1 ? value(d) : null)); console.log("maxValue",maxValue, data.map(d=>value(d) < 1 ? value(d) : null)); let minValue = d3.min(data.map(d=>value(d) < 1 ? value(d) : null)); let stateLabel = null ; if (mapMode === "Proportion" || mapMode === "3day" || mapMode === "9day") { //let m = Math.ceil(mValue*10)/10 ; //thresholds = thresholds.map(x => (x*m).toFixed(2)); thresholds = thresholds.map(v=>0.5+0.5*v); } if (mapMode === "3day") { stateLabel = (f, d) => { //console.log({f,d}); return d ? `${d.State} ${(value(d)*100).toFixed(2)}% ${d["BA.2 3day"]}/${d["BA.1+BA.4+BA.5 3day"]+d["BA.2 3day"]+d["Other 3day"]}` : f.properties.name; } } if (mapMode === "9day") { stateLabel = (f, d) => { //console.log({f,d}); return d ? `${d.State} ${(value(d)*100).toFixed(2)}% ${d["BA.2 9day"]}/${d["BA.1+BA.4+BA.5 9day"]+d["BA.2 9day"]+d["Other 9day"]}` : f.properties.name; } } if (mapMode === "Change") { thresholds = thresholds.map(x => ((x-0.5)/2).toFixed(2)); } else if ({"BA.4+BA.5 peak to BA.2 peak":1,"BA.4+BA.5 peak to BA.1 peak":0}[mapMode]) { thresholds = [ 0.4,0.5,0.6,0.7,0.8,0.9,1.0,1.1,1.2]; } else if (mapMode === "Growth" || mapMode === "Growth2" ) { thresholds = thresholds.map(x => (x > 0.5 ? 2 : 1)*(x/0.5-1).toFixed(1)); } else if (mapMode === "BA.4+BA.5 Growth") { // thresholds = [0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9]; thresholds = [-0.8,-0.6,-0.4,-0.2,0.0,0.2,0.4,0.6,0.8,1]; } else if (mapMode === "BA.2 Growth") { thresholds = [-0.8,-0.6,-0.4,-0.2,0.0,0.2,0.4,0.6,0.8,1]; } else if (mapMode === "Positivity") { thresholds = thresholds.map(x => (0.05 + x/2).toFixed(2)); } else if (mapMode === "PositivityChange") { thresholds = [-0.08,-0.06,-0.04,-0.02,0.0,0.02,0.04,0.06,0.08,.1]; } else if (mapMode === "Positives Growth") { //thresholds = [-0.16,-0.12,-0.08,-0.04,0.0,0.04,0.08,0.12,0.16,.2]; thresholds = [-0.5,-0.3,-0.2,-0.1,0.0,0.1,0.2,0.3,0.4,.5]; } else if (mapMode === "growthAdvantage") { thresholds = [-0.8,-0.6,-0.4,-0.2,0.0,0.2,0.4,0.6,0.8,1]; thresholds = [-0.8,-0.6,-0.4,-0.2,0.0,0.25,0.5,1,1.5,2]; } //let colorSchemeName = "scheme"+colorSchemeID.charAt(0).toUpperCase() + colorSchemeID.slice(1); let colorScheme; if (colorSchemeID === "schemeCustom") { colorScheme = [...myScheme]; } else { colorScheme = [...(d3[colorSchemeID][10] || d3[colorSchemeID][9] || d3[colorSchemeID][0])] ; } if (!reverseMapColors) { colorScheme.reverse(); } let map = Choropleth( data, { id: d => namemap.get(d.State), value, scale: d3.scaleThreshold, domain: thresholds, range: colorScheme, strokeWidth: d=>(d && d["BA.2 3day"] || 0)*10+1, // stroke color for borders stroke: "#ffffff", // stroke color for borders fill: "#dddddd", // fill color for outline title: stateLabel || ((f, d) => { //console.log({f,d}); return d ? `${d.State}\n${(value(d)*100).toFixed(2)}%` : f.properties.name; }), features: states, borders: statemesh, width: 1000, height: 620, }); function scrollToSelectedState() { document.getElementById("charts-for-selected-state-puerto-rico-or-dc").scrollIntoView(); } window.scrollToSelectedState = scrollToSelectedState; function handleClick(e) { console.log("Map clicked:",e); //console.log("Source element:",e.srcElement); let stateClicked = e.srcElement.textContent.split("\n")[0]; console.log("State clicked: ", stateClicked); (viewof stateSelected).value = stateClicked; (viewof stateSelected).dispatchEvent(new Event("input", {bubbles: true})); scrollToSelectedState(); } console.log({map}); map.addEventListener("click", handleClick); return map; }4a:[] 2f:{"title":"Andy's Walgreens COVID-19 Tracker Tracker","cells":[{"id":952,"value":"# ***Andy's Walgreens COVID-19 Tracker Tracker***","pinned":false,"hidden":false,"mode":"md"},{"id":5486,"value":"## Walgreens Dashboard has been removed\n\nIf anyone has found that it has moved, please let me know here or via X or email. (andy dot bloch @ gmail dot com)\n\nI will keep this page as it is indefinitely.","pinned":false,"hidden":false,"mode":"md"},{"id":4512,"value":"#### NOTE: ***I've added CDC wastewater plots to the national and regional charts.***\n
Also see: https://observablehq.com/@labvegas/cdc-covid-emergency-department-visits-by-age\n\nWalgreens is now updating weekly, on Monday or Tuesday afternoons. \n\nWalgreens stopped reporting SGTF data in April, 2023, but their data is still useful for tracking COVID-19 trends (along with wastewater, emergency, and hospital data).\n\nSome SGTF plots are now hidden by default, but can be shown by checking the appropriate boxes.\n\nIf you notice that this page hasn't updated in a while or have any questions, please feel free to message me on 𝕏itter at Andy_Bloch or Facebook, Threads, here, gmail (andy.bloch) etc.","pinned":false,"hidden":false,"mode":"md"},{"id":3824,"value":"{\n let loadingMessage = md`### Data being fetched for all 50 states, DC & PR (over 13MB)... `;\n return html`${loadingMessage}`;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3408,"value":"viewof showInfo = Inputs.toggle({label: \"Show more information\", value: false})","pinned":false,"hidden":false,"mode":"ojs"},{"id":455,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":449,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":1125,"value":"mapAndLegend = {\n if (!allData) {\n return md`### Fetching data, please be patient`;\n }\n let w = Math.min(width,1.2*window.outerHeight);\n let titles = {\n Positivity: \"Positivity\",\n PositivityChange: \"Change in Positivity rate\",\n \"Positives Growth\":\"Case growth\", \n Change: \"non-SGTF fraction change, 1 week\",\n Growth: \"SGTF proportion growth\",\n Growth2: \"non-SGTF proportion growth\",\n Proportion: \"Fraction non-SGTF (likely XBB), last 100 samples or 14 days\",\n '3day': \"Fraction non-SGTF, last 3 days\",\n '9day': \"Fraction non-SGTF, last 9 days\",\n \"BA.4+BA.5 peak to BA.2 peak\": \"Ratio, BA.4+BA.5 peak to BA.2 peak\",\n \"BA.4+BA.5 peak to BA.1 peak\": \"Ratio, BA.4+BA.5 peak to BA.1 peak\",\n \"SGTF Growth\": \"SGTF 7-day growth rate\",\n \"non-SGTF Growth\": \"non-SGTF 7-day growth rate\",\n \n }\n let title = titles[mapMode] || \"\";\n \n return html`

${Legend(mapChart.scales.color, {title})}\n${mapChart}

`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":763,"value":"Testing dates through ${dateThrough}","pinned":false,"hidden":false,"mode":"md"},{"id":1018,"value":"viewof mapMode = Inputs.radio(\n [\n \"Positivity\",\n \"PositivityChange\",\n \"Positives Growth\",\n \"Proportion\",\n \"9day\",\n \"3day\",\n \"Change\", \n \"Growth2\",\n \"Growth\",\n \"BA.4+BA.5 peak to BA.2 peak\",\n \"BA.4+BA.5 peak to BA.1 peak\",\n \"BA.4+BA.5 Growth\",\n \"BA.2 Growth\",\n \"growthAdvantage\"\n ], \n {\n label: \"Map display mode:\",\n value: \"Positivity\",\n format: (k,i)=>[\n html`Positivity`,\n `Positivity Change`,\n html`Case growth`,\n \"Percentage non-SGTF, >= 100 samples or last 14 days\",\n \"Percentage non-SGTF, last 9 days\",\n \"Percentage non-SGTF, last 3 days\",\n \"Weekly change of non-SGTF prop.\",\n \"Weekly growth of non-SGTF prop.\",\n \"Weekly growth of SGTF prop.\",\n \"BA.4+BA.5 peak to BA.2 peak\",\n \"BA.4+BA.5 peak to BA.1 peak\",\n \"SGTF 7-day Growth\",\n \"non-SGTF 7-day Growth\",\n \"Non-SGTF 7-day growth advantage\"\n ][i]})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1754,"value":"html`

${viewof colorSchemeID}

${viewof reverseMapColors}

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":729,"value":"{\n return htl.html`\n

\nChange day: ${\nmapDaySlider\n} ${viewof animateButton}\n

\n\n`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1528,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":5466,"value":"{\n let x = d=>stateAbbreviations[d.State];\n let y = d=>d.Tests;\n let data = d3.sort(currentBA4growth, d=>-y(d));\n let fill = d=>d.PositivityChange;\n \n let xDomain = data.map(x);\n return Plot.plot({\n width,\n x: { grid: true, domain: xDomain, label: \"State\"},\n y: { grid: true, label: \"Tests\" },\n title: \"Weekly tests by state\",\n color: { legend: true, label: \"Positivity change\" },\n subtitle: \"Colored by positivity change\",\n marks: [\n Plot.barY(data, {\n x,\n y,\n fill,\n tip: true\n }),\n Plot.ruleY([0])\n ]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3502,"value":"### Walgreens tests, positive tests, and positivity nationwide\nRaw totals","pinned":false,"hidden":false,"mode":"md"},{"id":3498,"value":"nationalPlot = {\n await visibility(md`Drawing chart...`);\n let startDate = new Date(usStartDate1).valueOf();\n return plotTestsPositivity({tests:testsUS,positivity:positivityUS},[startDate, Date.now()],showAllTests,\"National\");\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":4472,"value":"html`
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":5058,"value":"viewof showAllTests = Inputs.toggle({label: \"Show all tests (including negative)\", value: false})","pinned":false,"hidden":false,"mode":"ojs"},{"id":4461,"value":"Inputs.button([\n [\"Since 5/1/2021\",()=>setInput(viewof usStartDate1,\"2021-05-01\")],\n [\"Since 11/21/2021\",()=>setInput(viewof usStartDate1,\"2021-11-21\")],\n //[\"Since 6/1/2023\",()=>setInput(viewof usStartDate1,\"2023-06-01\")],\n [\"Last 15 months\",()=>setInput(viewof usStartDate1,new Date(Date.now()-460*24*60*60*1000))],\n [\"Last 4 months\",()=>setInput(viewof usStartDate1,new Date(Date.now()-120*24*60*60*1000))],\n]);","pinned":false,"hidden":false,"mode":"ojs"},{"id":4459,"value":"viewof usStartDate1 = Inputs.date({label: \"Start date\", value: new Date(Date.now()-460*24*60*60*1000)})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2224,"value":"stateTable(\"All US\", allDataTotals, variantsUS)","pinned":false,"hidden":false,"mode":"ojs"},{"id":4895,"value":"variantsUS.slice(-20)","pinned":true,"hidden":false,"mode":"ojs"},{"id":883,"value":"{\n //return md``;\n if (width < 400) {\n return html`Rotate or make window wider to view table data`;\n }\n return md`Current data by state: \n${Inputs.table(currentBA4growth,{\n columns: [\n \"State\",\n \"Positives\",\n \"Tests\",\n \"Positivity\",\n \"Days\",\n //\"BA.2 7day\",\n //\"BA.4+BA.5 7day\",\n \"BA.2 Proportion\",\n \"BA.2 9day\",\n \"BA.1+BA.4+BA.5 9day\",\n \"BA.2 3day\",\n \"BA.4+BA.5 3day\",\n \"PositivityChange\",\n \"PositivityGrowth\",\n //\"Positives Change\",\n //\"Tests Change\",\n ],//*/\n })}`;\n}\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":1267,"value":"## Proportions of SGTF/non-SGTF variants for US states & PR.\n","pinned":false,"hidden":false,"mode":"md"},{"id":3102,"value":"### Fraction of SGTF and non-SGTF tests, total of all US Walgreens","pinned":false,"hidden":false,"mode":"md"},{"id":3099,"value":"{\n if (0 && !showAllSGTF) {\n return md`Check box above to show chart.`;\n }\n return plotVariants(variantsUS,\"Proportion\",[usStartDate2, Date.now()]);\n}\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":4825,"value":"Inputs.button([\n [\"Since 11/21/2021\",()=>setInput(viewof usStartDate2,\"2021-11-21\")],\n [\"Since 8/15/2023\",()=>setInput(viewof usStartDate2,\"2023-08-15\")],\n [\"Last 120 days\",()=>setInput(viewof usStartDate2,new Date(Date.now()-120*24*60*60*1000))],\n]);","pinned":false,"hidden":false,"mode":"ojs"},{"id":4823,"value":"viewof usStartDate2 = Inputs.date({label: \"Start date\", value: \"2021-11-21\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3907,"value":"---\n### Fraction of SGTF and non-SGTF tests, by state, for all US Walgreens","pinned":false,"hidden":false,"mode":"md"},{"id":4156,"value":"Estimates based on Walgreens SGTF + rSGTP data.","pinned":false,"hidden":false,"mode":"md"},{"id":4709,"value":"viewof showAllSGTF = Inputs.toggle({label: \"Show plots\", value: false})","pinned":false,"hidden":false,"mode":"ojs"},{"id":293,"value":"{\n if (!showAllSGTF) {\n return md`Check box above to show chart. Warning: high memory usage may crash this page.`;\n }\n return md`This chart is under (re)construction.`;\n await visibility(md`Drawing chart...`);\n return plotVariants(variantsAllStatesFiltered.map(d=>({...d,Date: d.Date - 12*1000*60*60*(d.Days-3)})),\"Proportion\")\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3085,"value":"----","pinned":false,"hidden":false,"mode":"md"},{"id":1852,"value":"----\n### Positive tests by SGTF (as a proxy for certain variants) for all US Walgreens\n\n${variantDescription[variantColumnUS]}, through ${dateThrough}","pinned":false,"hidden":false,"mode":"md"},{"id":1838,"value":"{\n if (0 && !showStateSGTF) {\n return md`Check box above to show chart.`;\n }\n await visibility(md`Drawing chart...`);\n let startDate = new Date(usStartDate).valueOf();\n return plotVariants(variantsUS.filter(d=>d.Date >= startDate),variantColumnUS, [startDate, Date.now()]);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":4180,"value":"Inputs.button([\n [\"Since 11/21/2021\",()=>setInput(viewof usStartDate,\"2021-11-21\")],\n [\"Since 6/1/2023\",()=>setInput(viewof usStartDate,\"2023-06-01\")],\n [\"Last 120 days\",()=>setInput(viewof usStartDate,new Date(Date.now()-120*24*60*60*1000))],\n]);","pinned":false,"hidden":false,"mode":"ojs"},{"id":3939,"value":"viewof usStartDate = Inputs.date({label: \"Start date\", value: \"2021-11-21\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1842,"value":"viewof variantColumnUS = Inputs.radio([\"Cases\", \"Samples3day\",\"Samples7day\",\"Samples1day\"], {label: \"Select data to plot:\", value: \"Cases\", format: (x,i)=>[\"Estimated positive tests\",\"Samples detected last 3 days\",\"Samples detected last 7 days\",\"Samples detected last day\"][i]})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2031,"value":"Note: The ”Estimated positive tests” selection shows the total positive tests multiplied by the percentage of SGTF/rSGTP. Walgreens reports more tests than presumed variants detected. (Either they are not TAQ-PATH PCR tests, or SGTF is not conclusive.) I also include options to chart the count of the samples, by day, week, or 3-day period.","pinned":false,"hidden":false,"mode":"md"},{"id":626,"value":"---","pinned":false,"hidden":false,"mode":"md"},{"id":4451,"value":"### All positive tests by state at a glance. \nLast 2 months, scaled to maximum over that period, sorted by relative recent maximum","pinned":false,"hidden":false,"mode":"md"},{"id":4448,"value":"{\n await visibility(md`Drawing charts...`);\n return html`

${plotVariantFacets(variantsAllStates,\"All\",\"Cases\")}

\n\n`;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":691,"value":"selected_state = md`## Charts for a region or an individual state (incl. Puerto Rico & DC)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":500,"value":"### Tests, Positive tests, and Positivity\n${stateSelected === \"None\" && regionSelected==\"0\" ? \"Please select a state above\" :\n (variants[0].State + \" Walgreens COVID-19 7-day rolling totals by date of test, through \" + dateThrough )\n }","pinned":false,"hidden":false,"mode":"md"},{"id":2214,"value":"stateSelected === \"None\" && !regionSelected ? md`` : stateTable(regionOrStateSelected, stateDataTotals, variants)","pinned":false,"hidden":false,"mode":"ojs"},{"id":480,"value":"viewof stateSelected = Inputs.select([...statesList,\"None\"], {value:new URLSearchParams(window.location.search).get(\"state\") || \"California\", width:\"12em\", label: \"Select a state, PR, or DC:\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3529,"value":"Or, select a HHS region (matching CDC's variant tracker), or CDC wastewater regions, or a Biobot region:","pinned":false,"hidden":false,"mode":"md"},{"id":1642,"value":"viewof regionSelected = Inputs.select([...Object.keys(regionToStates)], {label: \"Region\", value: 0, format: (x,i)=> i ? \"Region \" + x : \"Single state\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2222,"value":"regionOrStateSelected === \"None\" ? md`` : md`----\n\n**${regionOrStateSelected}** Walgreens tests through ${dateThrough}`","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"{\n await visibility(md`Drawing chart...`);\n let startDate = new Date(stateStartDate1).valueOf();\n return plotTestsPositivity({tests,positivity},[startDate, Date.now()],showAllTests1, regionSelected == \"0\" ? stateSelected : regionSelected, regionSelected == \"0\" && stateSelected);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":5062,"value":"viewof showAllTests1 = Inputs.toggle({label: \"Show all tests (including negative)\", value: false})","pinned":false,"hidden":false,"mode":"ojs"},{"id":4192,"value":"----","pinned":false,"hidden":false,"mode":"md"},{"id":4594,"value":"Inputs.button([\n [\"Since 5/1/2021\",()=>setInput(viewof stateStartDate1,\"2021-05-01\")],\n [\"Since 11/21/2021\",()=>setInput(viewof stateStartDate1,\"2021-11-21\")],\n [\"Since 6/1/2023\",()=>setInput(viewof stateStartDate1,\"2023-06-01\")],\n [\"Last 15 months\",()=>setInput(viewof stateStartDate1,new Date(Date.now()-460*24*60*60*1000))],\n [\"Last 4 months\",()=>setInput(viewof stateStartDate1,new Date(Date.now()-120*24*60*60*1000))],\n]);","pinned":false,"hidden":false,"mode":"ojs"},{"id":4597,"value":"viewof stateStartDate1 = Inputs.date({label: \"Start date\", value: new Date(Date.now()-460*24*60*60*1000)})","pinned":false,"hidden":false,"mode":"ojs"},{"id":4188,"value":"Inputs.bind(Inputs.select([...statesList,\"None\"], {value:new URLSearchParams(window.location.search).get(\"state\") || \"California\", width:\"12em\", label: \"Select a state, PR, or DC:\"}), viewof stateSelected)","pinned":false,"hidden":false,"mode":"ojs"},{"id":4195,"value":"Inputs.bind(Inputs.select([...Object.keys(regionToStates)], {label: \"Or region\", value: 0, format: (x,i)=> i ? \"Region \" + x : \"Single state\"}), viewof regionSelected)","pinned":false,"hidden":false,"mode":"ojs"},{"id":332,"value":"(regionOrStateSelected === \"None\") ? md`` : md`\n### Positive tests by SGTF (as a proxy for variant sometimes)\n\n\n${variants[0].State} Walgreens ${variantDescription[variantColumn]}, through ${dateThrough}`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4705,"value":"viewof showStateSGTF = Inputs.toggle({label: \"Show plots\", value: false})","pinned":false,"hidden":false,"mode":"ojs"},{"id":329,"value":"{\n if (!showStateSGTF) {\n return md`Check box above to show chart.`;\n }\n \n await visibility();\n return regionOrStateSelected === \"None\" ? md`` : plotVariants(variants,variantColumn,[new Date(stateStartDate).valueOf(),Date.now()]);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2975,"value":"
\n\n","pinned":false,"hidden":false,"mode":"md"},{"id":4167,"value":"Inputs.button([\n [\"Since 11/21/2021\",()=>setInput(viewof stateStartDate,\"2021-11-21\")],\n [\"Last 120 days\",()=>setInput(viewof stateStartDate,new Date(Date.now()-120*24*60*60*1000))],\n]);","pinned":false,"hidden":false,"mode":"ojs"},{"id":3951,"value":"viewof stateStartDate = Inputs.date({label: \"Start date\", value: \"2021-11-21\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1103,"value":"viewof variantColumn = Inputs.radio([\"Cases\", \"Samples3day\",\"Samples7day\",\"Samples1day\"], {label: \"Select data to plot:\", value: \"Samples3day\", format: (x,i)=>[\"Estimated positive tests, last 7 days\",\"Samples detected last 3 days\",\"Samples detected last 7 days\",\"Samples detected last day\"][i]})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2969,"value":"{\n return md``;\n let lastDay = Date.now()-3*24*60*60*1000;\n let last30Days = lastDay - 30*24*60*60*1000;\n return plotVariants(variants.filter(d => d.Date > last30Days && d.Variants === \"BA.2\"),variantColumn,[last30Days,lastDay]);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":334,"value":"(regionOrStateSelected === \"None\") ? md`` : md`### Variant proportions\n${variants[0].State} Walgreens COVID-19 variant estimates based on SGTF + rSGTP, through ${dateThrough}`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1236,"value":"{\n if (!showStateSGTF) {\n return md`Check box above to show chart.`;\n }\n await visibility();\n return (regionOrStateSelected === \"None\") ? md`` : plotVariants(variants,\"Proportion\",[new Date(stateStartDate).valueOf(),Date.now()]);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":4360,"value":"----","pinned":false,"hidden":false,"mode":"md"},{"id":1465,"value":"{\n await visibility();\n if (stateSelected === \"None\") return md``;\n if (width < 600) {\n return html`Rotate or make window wider to view table data`;\n }\n return md`\n----\n### Data for ${stateSelected}:\\n${Inputs.table(allBA4.filter(r=>r.State === stateSelected).reverse().map(d=>{\n return {\n ...d,\n Date: timeStampToDateString(d.Date).slice(5), \n }\n })\n ,{\n columns: [\n \"Date\",\n \"Days\",\n \"Positives\",\n \"Tests\",\n \"Positivity\",\n \"BA.2 9day\",\n \"BA.1+BA.4+BA.5 9day\",\n \"BA.2 7day\",\n \"BA.1+BA.4+BA.5 7day\",\n \"BA.2 3day\",\n \"BA.1+BA.4+BA.5 3day\",\n \"PositivityChange\",\n \"PositivityGrowth\",\n //\"Positives Change\",\n //\"Tests Change\",\n ],\n })}`;\n}\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":469,"value":"(regionOrStateSelected === \"None\") ? md`` : md`----\n### Positive tests and positivity versus tests\n${variants[0].State} Walgreens, since May 2021`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4657,"value":"viewof showPvT = Inputs.toggle({label: \"Show plots\", value: false})","pinned":false,"hidden":false,"mode":"ojs"},{"id":208,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":2206,"value":"----","pinned":false,"hidden":false,"mode":"md"},{"id":527,"value":"{\nif (regionOrStateSelected === \"None\") return md`\n### Positive tests and positivity versus tests\nSelect state above.\n`;\nreturn md`\n### Positive tests and positivity versus tests\n${variants[0].State} Walgreens, select range of days`\n}\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":234,"value":"viewof lastDay = Inputs.range([1, stateDataTotals.length], {label: \"Last day\", step: 1, value: stateDataTotals.length})","pinned":false,"hidden":false,"mode":"ojs"},{"id":231,"value":"viewof days = Inputs.range([1, stateDataTotals.length], {label: \"Days\", step: 1, value: 91})","pinned":false,"hidden":false,"mode":"ojs"},{"id":975,"value":"$${days} days through ${(new Date(firstTimestamp + lastDay*1000*24*60*60)).toLocaleDateString()}","pinned":false,"hidden":false,"mode":"md"},{"id":4664,"value":"viewof showPvTrange = Inputs.toggle({label: \"Show plots\", value: false})","pinned":false,"hidden":false,"mode":"ojs"},{"id":223,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":534,"value":"----","pinned":false,"hidden":false,"mode":"md"},{"id":2547,"value":"Experiments = md`## Experiments`\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":2793,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":4668,"value":"viewof showPeakvBA2 = Inputs.toggle({label: \"Show plots\", value: false})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2739,"value":"$37","pinned":false,"hidden":false,"mode":"ojs"},{"id":2809,"value":"The number of days between peaks also was correlated with the ratio of the peaks, but less so, probably because there's a lot of uncertainty in the dates of the peaks because of flat peaks, holiday interruptions, and randomness.","pinned":false,"hidden":false,"mode":"md"},{"id":2796,"value":"$38","pinned":false,"hidden":false,"mode":"ojs"},{"id":4008,"value":"Relationship between BA.2 peaks and amount of BA.2 when BA.2 became dominant (>50%)","pinned":false,"hidden":false,"mode":"md"},{"id":4032,"value":"$39","pinned":false,"hidden":false,"mode":"ojs"},{"id":2790,"value":"---","pinned":false,"hidden":false,"mode":"md"},{"id":2932,"value":"### Growth advantage of SGTF versus non-SGTF","pinned":false,"hidden":false,"mode":"md"},{"id":4678,"value":"viewof showGrowthAdvantage = Inputs.toggle({label: \"Show plots\", value: false})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2785,"value":"$${statesForGrowthComparison.join(\", \")} relative daily growth advantage of SGTF versus SGTF-negative variants, averaged over 2 weeks.","pinned":false,"hidden":false,"mode":"md"},{"id":2413,"value":"{\n if (!showGrowthAdvantage) {\n return md`Check box above to show chart.`;\n }\n \n await visibility();\n return plotVariants(variantsAllStates.filter(d=>!statesForGrowthComparison.length || statesForGrowthComparison.includes(d.State)).map(d=>({...d, RelativeGrowth2weeks: Math.max(-0.5,Math.min(d.RelativeGrowth2weeks,0.5))})),\"RelativeGrowth2weeks\");\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3141,"value":"----\nAll US Walgreens, relative daily growth advantage of SGTF versus SGTF-negative variants, averaged over 2 weeks.","pinned":false,"hidden":false,"mode":"md"},{"id":3131,"value":"{\n if (!showGrowthAdvantage) {\n return md`Check box above to show chart.`;\n }\n await visibility();\n return plotVariants(variantsUS.map(d=>({...d, RelativeGrowth2weeks: Math.max(-0.5,Math.min(d.RelativeGrowth2weeks,0.5))})),\"RelativeGrowth2weeks\");\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2561,"value":"---","pinned":false,"hidden":false,"mode":"md"},{"id":2577,"value":"viewof statesForGrowthComparison = Inputs.checkbox(statesList, {label: \"Select states\", value: [\"California\"/*,\"Florida\",\"Illinois\",\"Texas\"*/], format:x=>html`${x}`})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2468,"value":"Walgreens SGTF data from ${statesForGrowthComparison.join(\", \")}\n
+/- Log₂(SGTF / SGTF-negative)\n","pinned":false,"hidden":false,"mode":"md"},{"id":2455,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs"},{"id":3144,"value":"viewof logRatioStartDate = Inputs.date({label: \"Date for start of projection\", value: \"2023-01-02\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3117,"value":"---\nAll US states\n
+/- Log₂(SGTF / SGTF-negative)\n","pinned":false,"hidden":false,"mode":"md"},{"id":3104,"value":"{\n if (!showGrowthAdvantage) {\n return md`Check box above to show chart.`;\n }\n await visibility();\n return plotVariants(variantsUS,\"LogRatio\");\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3031,"value":"
","pinned":false,"hidden":false,"mode":"md"},{"id":3002,"value":"dataForLogRatio = getVariants(allBA4).filter(d=>isFinite(d.LogRatio) && (!statesForGrowthComparison.length || statesForGrowthComparison.includes(d.State)))","pinned":false,"hidden":false,"mode":"ojs"},{"id":2553,"value":"---","pinned":false,"hidden":false,"mode":"md"},{"id":2480,"value":"viewof tableRelativeGrowth = Inputs.table(filterByCurrentSamples(allBA4,200))","pinned":false,"hidden":false,"mode":"ojs"},{"id":4312,"value":"### Non-SGTF (XBB.1.5 etc.) by state at a glance. \nLast 2 months, scaled to maximum over that period, sorted by relative recent maximum ","pinned":false,"hidden":false,"mode":"md"},{"id":4272,"value":"{\n return md``;\n await visibility(md`Drawing charts...`);\n return html`

${plotVariantFacets(variantsAllStates)}

\n\n`;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":531,"value":"## Code Appendix. Not Much to see below here.","pinned":false,"hidden":false,"mode":"md"},{"id":3239,"value":"import {Plot} from \"@mkfreeman/plot-tooltip\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":345,"value":"import {us, states, statemesh, Choropleth, Legend} from \"@d3/choropleth\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":4165,"value":"function setInput(input, value) {\n // https://observablehq.com/@observablehq/synchronized-inputs?collection=@observablehq/inputs\n input.value = value;\n input.dispatchEvent(new Event(\"input\", {bubbles: true}));\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3605,"value":"dataURL = \"https://labvegas.com/data/covid19/walgreens/dashboard-Tracker_Aggregation.csv\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":5128,"value":"cdcWastewaterURL = \"https://www.cdc.gov/wcms/vizdata/NCEZID_DIDRI/NWSSRegionalLevel.json\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":5362,"value":"newCdcWastewaterURL = \"https://www.cdc.gov/wcms/vizdata/NCEZID_DIDRI/SC2/nwsssc2stateactivitylevelDL.csv\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":5148,"value":"CDC Wastewater page:\nhttps://www.cdc.gov/nwss/rv/COVID19-nationaltrend.html","pinned":false,"hidden":false,"mode":"md"},{"id":5235,"value":"Plot.plot({\n width,\n color: { legend: true },\n x: { grid: true },\n y: { grid: true },\n title: \"COVID-19 Wastewater Viral Activity Level\",\n caption: \"Source: https://www.cdc.gov/nwss/rv/COVID19-nationaltrend.html\",\n marks: [\n Plot.lineY(newCdcWasteWaterData.filter(d=>d.date_period===\"All Results\"), {\n x: \"date\",\n y: \"regional_wastewater\",\n stroke: d=>stateToCensusRegion[d.state],\n tip: true\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":5376,"value":"\nPlot.plot({\n width,\n color: { legend: true },\n x: { grid: true },\n y: { grid: true },\n title: \"COVID-19 Wastewater Viral Activity Level - National\",\n caption: \"Source: https://www.cdc.gov/nwss/rv/COVID19-nationaltrend.html\",\n marks: [\n// Note: the national wastewater level is reported along with every state's data, so just need to pick one state\n Plot.lineY(newCdcWasteWaterData.filter(d=>d.date_period===\"All Results\" && d.state == \"Alabama\"), {\n x: \"date\",\n y: \"national_wastewater\",\n stroke: d=>\"National\",\n tip: true\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":5364,"value":"newCdcWasteWaterDataRaw = d3.csv(newCdcWastewaterURL, d3.autoType)","pinned":true,"hidden":false,"mode":"ojs"},{"id":5132,"value":"//cdcWasteWaterDataRaw = d3.json(cdcWastewaterURL)","pinned":true,"hidden":false,"mode":"ojs"},{"id":5136,"value":"newCdcWasteWaterData = d3.sort(newCdcWasteWaterDataRaw.map(d=>{\n let date = new Date(d.Week_Ending_Date);\n let date_period = d.Data_Collection_Period;\n let state = d[\"State/Territory\"];\n let regional_wastewater = d.Regional_WVAL;\n let national_wastewater = d.National_WVAL;\n let wastewater = d[\"State/Territory_WVAL\"];\n let coverage = d.Coverage;\n return {\n date,\n state,\n date_period,\n wastewater,\n regional_wastewater,\n national_wastewater,\n coverage,\n };\n}).filter(d=>d.date_period===\"All Results\"), d=>d.date, d=>d.state, d=>d.date_period)","pinned":true,"hidden":false,"mode":"ojs"},{"id":5367,"value":"cdcWasteWaterData = [] /* cdcWasteWaterDataRaw.flatMap(d=>{\n let date = new Date(d.Week_Ending_Date);\n let date_period = d.Data_Collection_Period;\n let keys = [\"Midwest\",\"National\",\"Northeast\",\"South\",\"West\",];\n return keys.map(region=>({\n date,\n region,\n date_period,\n wastewater:Number(d[region+\"_WVAL\"]),\n }));\n}).filter(d=>d.date_period===\"All Results\")*/","pinned":true,"hidden":false,"mode":"ojs"},{"id":5032,"value":"allData.filter(d=>d.State === \"Texas\").slice(-10)\n","pinned":true,"hidden":false,"mode":"ojs"},{"id":353,"value":"allData = {\n return allData1 || lastDataAllStates;\n}\n \n ","pinned":false,"hidden":false,"mode":"ojs"},{"id":5042,"value":"checkForNewColumns()","pinned":true,"hidden":false,"mode":"ojs"},{"id":5034,"value":"$3b","pinned":false,"hidden":false,"mode":"ojs"},{"id":4123,"value":"allData1 = {\n let all = await d3.csv(dataURL, d3.autoType);\n return all.filter(d=>d.State);\n}\n \n ","pinned":false,"hidden":false,"mode":"ojs"},{"id":4128,"value":"$3c","pinned":false,"hidden":false,"mode":"ojs"},{"id":4038,"value":"$3d","pinned":false,"hidden":false,"mode":"ojs"},{"id":4108,"value":"statePopulationFraction = {\n let total = 0; \n statesList.forEach(state => {\n let population = statePopulation[state];\n if (!population) {\n console.error(\"State population not found for state \"+state);\n }\n else {\n total += population;\n }\n });\n let o ={};\n statesList.forEach(state => o[state] = statePopulation[state] / total);\n return o;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3914,"value":"lastDataCalifornia = {\n // https://grep.lvab.workers.dev/?u=https://labvegas.com/data/covid19/walgreens/dashboard-Tracker_Aggregation.csv&s=,1673395200000,&h=1\n let all = d3.csv(\"https://grep.lvab.workers.dev/?u=\"+dataURL+\"&s=California&h=1&f=-7\", d3.autoType);\n return all;\n}\n \n ","pinned":false,"hidden":false,"mode":"ojs"},{"id":4137,"value":"lastDataCaliforniaYesterday = {\n // https://grep.lvab.workers.dev/?u=https://labvegas.com/data/covid19/walgreens/dashboard-Tracker_Aggregation.csv&s=,1673395200000,&h=1\n let url2 = encodeURIComponent(dataURL + \"?date=\" + new Date(Date.now()-24*60*60*1000));\n let all = d3.csv(\"https://grep.lvab.workers.dev/?u=\"+url2+\"&s=California&h=1&f=-7\", d3.autoType);\n return all;\n}\n \n ","pinned":false,"hidden":false,"mode":"ojs"},{"id":3917,"value":"lastDataAllStates = {\n // https://grep.lvab.workers.dev/?u=https://labvegas.com/data/covid19/walgreens/dashboard-Tracker_Aggregation.csv&s=,1673395200000,&h=1\n let url = \"https://grep.lvab.workers.dev/?u=\"+dataURL+\"&s=,\"+lastDataCalifornia[0].Date+\",&h=1\";\n console.log(url);\n let all = d3.csv(url, d3.autoType);\n return all;\n}\n \n ","pinned":false,"hidden":false,"mode":"ojs"},{"id":3814,"value":"dataBeingFetched = {\n yield \"started\";\n while (!allData) {\n yield Promises.delay(100,\"fetching\");\n }\n document.getElementById(\"loadingMessage\").innerHTML = md`### Data last updated on ${lastUpdateDate} with tests taken through ${lastDataDate}.`.outerHTML;\n yield false;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":740,"value":"firstTimestamp = allData[0].Date","pinned":false,"hidden":false,"mode":"ojs"},{"id":5111,"value":"firstDate = new Date(firstTimestamp)","pinned":false,"hidden":false,"mode":"ojs"},{"id":744,"value":"lastTimestamp = allData.slice().reverse().find(d=>d.State === \"Florida\" && (d[\"test_number_pos\"])).Date\n\n","pinned":true,"hidden":false,"mode":"ojs"},{"id":3836,"value":"lastRecord = allData.filter(d=>d.State === \"California\" && d[\"3day_mvPreOmiBA11_nmrtr\"]).slice(-1)[0]","pinned":false,"hidden":false,"mode":"ojs"},{"id":2392,"value":"dateThrough =(new Date(firstTimestamp + mapDay*1000*24*60*60)).toGMTString().slice(0,16)\n// Note: this will change if the date slider changes","pinned":false,"hidden":false,"mode":"ojs"},{"id":3893,"value":"lastDataDate =(new Date(lastTimestamp)).toGMTString().slice(0,16)","pinned":false,"hidden":false,"mode":"ojs"},{"id":3895,"value":"lastUpdateDate =(new Date(lastRecord.update_dt)).toGMTString().slice(0,16)","pinned":false,"hidden":false,"mode":"ojs"},{"id":3833,"value":"lastDate = new Date(lastTimestamp)","pinned":true,"hidden":false,"mode":"ojs"},{"id":749,"value":"numberOfDays = (lastTimestamp - firstTimestamp)/(1000*24*60*60)","pinned":false,"hidden":false,"mode":"ojs"},{"id":543,"value":"chartConfig = {\n let w = width;\n \n return {\n marginLeft: 10,\n marginRight: 10,\n marginBottom: 10,\n width: w,\n height: w*0.5,\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":16,"value":"//stateData = d3.csv(\"https://grep.lvab.workers.dev/?h=1&u=https://labvegas.com/data/covid19/walgreens/dashboard-Tracker_Aggregation.csv&s=\"+(stateSelected ? \"^\" + stateSelected : \"\"), d3.autoType)","pinned":false,"hidden":false,"mode":"ojs"},{"id":2949,"value":"stateData.slice(-10)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1192,"value":"stateData = allData.filter(r => multiStatesSelected ? multiStatesSelected[r.State] : r.State === stateSelected)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1673,"value":"Array.from(d3.group(stateData,d=>d.Date)).slice(-20)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1657,"value":"stateDataTotals = getStateDataTotals(stateData)","pinned":true,"hidden":false,"mode":"ojs"},{"id":2701,"value":"stateDataTotals.slice(-20)","pinned":true,"hidden":false,"mode":"ojs"},{"id":2705,"value":"viewof stateDataTable = Inputs.table(stateDataTotals)","pinned":true,"hidden":false,"mode":"ojs"},{"id":2227,"value":"function getStateDataTotals(data) {\n return Array.from(d3.group(data,d=>d.Date)).map(dd => {\n let Date = dd[0];\n let rows = dd[1];\n let r = {};\n for (let i = 0 ; i < rows.length ; i++) {\n let d = rows[i];\n Object.entries(d).forEach(kv => {\n let k = kv[0];\n let v = kv[1];\n if (v) {\n if (typeof v === \"number\") {\n r[k] = (r[k] || 0) + v ;\n }\n else {\n let s = v.toString();\n if (r[k] !== s) {\n if (r[k]) {\n r[k] = r[k] + \",\" + s; \n }\n else {\n r[k] = s;\n }\n }\n }\n }\n else if (v === null || v === \"null\") {\n r[k] = (r[k] || 0);\n }\n\n });\n }\n r.Date = Date ;\n return r;\n }).sort((a,b)=>a.Date-b.Date);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3481,"value":"allDataTotals = getStateDataTotals(allData)","pinned":true,"hidden":false,"mode":"ojs"},{"id":3988,"value":"regionTotals = {\n if (!mapByRegion) {\n return [];\n }\n let t = [];\n for (let r = 1 ; r <= 10 ; r++) {\n t[r] = getStateDataTotals(allData.filter(d=>stateToRegion[d.State] === r ));\n }\n return t;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":228,"value":"data2 = stateDataTotals.slice(Math.max(0,lastDay - days),lastDay);","pinned":false,"hidden":false,"mode":"ojs"},{"id":416,"value":"lastVariantDate = Math.min(lastTimestamp, allBA4.reduce((o,r)=>{o = Math.max(o,r.Date); return o},0))","pinned":true,"hidden":false,"mode":"ojs"},{"id":154,"value":"statesList= Object.keys(allData.reduce((s,r)=>({...s,[r.State]:1}),{}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":5379,"value":"stateToCensusRegion = {\n let o = {};\n Object.entries(usCensusRegions).forEach(kv=>{\n kv[1].forEach(state=> {\n o[state] = kv[0];\n });\n });\n return o;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":5124,"value":"usCensusRegions = ({\n // https://www.cdc.gov/nwss/rv/COVID19-nationaltrend.html\n West: [\"Alaska\", \"Arizona\", \"California\", \"Colorado\", \"Guam\", \"Hawaii\", \"Idaho\", \"Montana\", \"Nevada\", \"New Mexico\", \"Oregon\", \"Utah\", \"Washington\", \"Wyoming\"],\n Midwest: [\"Illinois\", \"Indiana\", \"Iowa\", \"Kansas\", \"Michigan\", \"Minnesota\", \"Missouri\", \"Nebraska\", \"North Dakota\", \"Ohio\", \"South Dakota\", \"Wisconsin\"],\n Northeast: [\"Connecticut\", \"Maine\", \"Massachusetts\", \"New Hampshire\", \"New Jersey\", \"New York\", \"Pennsylvania\", \"Puerto Rico\", \"Rhode Island\", \"Vermont\"],\n South: [\"Arkansas\", \"Alabama\", \"Delaware\", \"District of Columbia\", \"Florida\", \"Georgia\", \"Kentucky\", \"Louisiana\", \"Maryland\", \"Mississippi\", \"North Carolina\", \"Oklahoma\", \"South Carolina\", \"Tennessee\", \"Texas\", \"Virginia\", \"West Virginia\"]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":5469,"value":"$3e","pinned":true,"hidden":false,"mode":"ojs"},{"id":1636,"value":"stateToRegion = ({\nAlabama: 4,\nAlaska: 10,\nArizona: 9,\nArkansas: 6,\nCalifornia: 9,\nColorado: 8,\nConnecticut: 1,\nDelaware: 3,\n\"District of Columbia\": 3,\nFlorida: 4,\nGeorgia: 4,\nHawaii: 9,\nIdaho: 10,\nIllinois: 5,\nIndiana: 5,\nIowa: 7,\nKansas: 7,\nKentucky: 4,\nLouisiana: 6,\nMaine: 1,\nMaryland: 3,\nMassachusetts: 1,\nMichigan: 5,\nMinnesota: 5,\nMississippi: 4,\nMissouri: 7,\nMontana: 8,\nNebraska: 7,\nNevada: 9,\n\"New Hampshire\": 1,\n\"New Jersey\": 2,\n\"New Mexico\": 6,\n\"New York\": 2,\n\"North Carolina\": 4,\n\"North Dakota\": 8,\nOhio: 5,\nOklahoma: 6,\nOregon: 10,\nPennsylvania: 3,\n\"Puerto Rico\": 2,\n\"Rhode Island\": 1,\n\"South Carolina\": 4,\n\"South Dakota\": 8,\nTennessee: 4,\nTexas: 6,\nUtah: 8,\nVermont: 1,\nVirginia: 3,\nWashington: 10,\n\"West Virginia\": 3,\nWisconsin: 5,\nWyoming: 8,\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":4740,"value":"stateToBiobotRegion = ({\nConnecticut: 1,\nMaine: 1,\nMassachusetts: 1,\n\"New Hampshire\": 1,\n\"Rhode Island\": 1,\nVermont: 1,\n\"New Jersey\": 1,\n\"New York\": 1,\n\"Puerto Rico\": 0,\nDelaware: 1,\nMaryland: 1,\nPennsylvania: 1,\n \n\"District of Columbia\": 2,\n\"West Virginia\": 2,\nVirginia: 2,\nAlabama: 2,\nFlorida: 2,\nGeorgia: 2,\nKentucky: 2,\nMississippi: 2,\n\"North Carolina\": 2,\n\"South Carolina\": 2,\nTennessee: 2,\nArkansas: 2,\nLouisiana: 2,\nOklahoma: 2,\nTexas: 2,\n\nIllinois: 3,\nIndiana: 3,\nMichigan: 3,\nMinnesota: 3,\nOhio: 3,\nWisconsin: 3,\nIowa: 3,\nKansas: 3,\nMissouri: 3,\nNebraska: 3,\n\"North Dakota\": 3,\n\"South Dakota\": 3,\n \nAlaska: 4,\nArizona: 4,\nCalifornia: 4,\nColorado: 4,\nHawaii: 4,\nIdaho: 4,\nMontana: 4,\nNevada: 4,\n\"New Mexico\": 4,\nOregon: 4,\nUtah: 4,\nWashington: 4,\nWyoming: 4,\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1645,"value":"regionToStates = {\n let s = {0:{}};\n Object.entries(usCensusRegions).forEach(rs => {\n let region = rs[0];\n let states = rs[1];\n s[region] = {}\n states.forEach(st => s[region][st] = region);\n });\n \n Object.entries(stateToRegion).forEach(sr => {\n let region = sr[1];\n let state = sr[0];\n s[region] = s[region] || {};\n s[region][state] = region;\n //s[11] = s[11] || {};\n //s[11][state] = 11;\n });\n Object.entries(stateToBiobotRegion).forEach(sr => {\n let biobotRegions = [0,\"Biobot Northeast\",\"Biobot South\",\"Biobot Midwest\",\"Biobot West\"];\n let region = biobotRegions[sr[1]];\n if (!region) {\n return ;\n }\n let state = sr[0];\n s[region] = s[region] || {};\n s[region][state] = region;\n //s[11] = s[11] || {};\n //s[11][state] = 11;\n });\n return s;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3549,"value":"regionOrStateSelected = regionSelected !== \"0\" ? \"Region \" + regionSelected : stateSelected;","pinned":false,"hidden":false,"mode":"ojs"},{"id":49,"value":"tests = stateDataTotals.flatMap(r => [{Date:r.Date, State:r.State, Tests:\"All Tests\", WeeklyTests: r.test_number_ALL_rolling},{Date:r.Date, State:r.State, Tests:\"Positive Tests\", WeeklyTests: r.test_number_pos_rolling}])","pinned":false,"hidden":false,"mode":"ojs"},{"id":3495,"value":"testsUS = allDataTotals.flatMap(r => [{Date:r.Date, State:\"All US\", Tests:\"All Tests\", WeeklyTests: r.test_number_ALL_rolling},{Date:r.Date, State:\"All US\", Tests:\"Positive Tests\", WeeklyTests: r.test_number_pos_rolling}])","pinned":false,"hidden":false,"mode":"ojs"},{"id":2695,"value":"tests.slice(-20)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1649,"value":"multiStatesSelected = regionSelected !== \"0\" ? regionToStates[regionSelected] : false","pinned":true,"hidden":false,"mode":"ojs"},{"id":287,"value":"variants = getVariantsMult(allBA4.filter(r => multiStatesSelected ? multiStatesSelected[r.State] : r.State === stateSelected))","pinned":true,"hidden":false,"mode":"ojs"},{"id":1800,"value":"variants.slice(-20)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1813,"value":"//plotVariants(variantsAllStates.filter(d=>d.Date>new Date(2022, 2, 22)),\"Cases scaled\",[new Date(2022, 2, 22), Date.now()])","pinned":false,"hidden":false,"mode":"ojs"},{"id":1219,"value":"$3f","pinned":true,"hidden":false,"mode":"ojs"},{"id":4950,"value":"testBA4filtered = allBA4.filter(d=>testStates[d.State])","pinned":true,"hidden":false,"mode":"ojs"},{"id":4939,"value":"testVariants = getVariantsMult(testBA4filtered)\n","pinned":true,"hidden":false,"mode":"ojs"},{"id":4943,"value":"testVariants.slice(-20)","pinned":true,"hidden":false,"mode":"ojs"},{"id":4998,"value":"testDataTotals.slice(-5)[0]","pinned":true,"hidden":false,"mode":"ojs"},{"id":4956,"value":"testDataTotals = getStateDataTotals(testBA4filtered)","pinned":true,"hidden":false,"mode":"ojs"},{"id":4960,"value":"testStates = ({California:0,Texas:1,Utah:0,\"North Carolina\":0,Alaska:1,})","pinned":true,"hidden":false,"mode":"ojs"},{"id":4972,"value":"Plot.plot({\n marks: [\n Plot.auto(null, {})\n ]\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":4948,"value":"stateTable(\"Test\",testAllDataTotals,testVariants)","pinned":true,"hidden":false,"mode":"ojs"},{"id":4992,"value":"testAllData.slice(-20)","pinned":true,"hidden":false,"mode":"ojs"},{"id":4990,"value":"testAllData = allData.filter(d=>testStates[d.State])","pinned":true,"hidden":false,"mode":"ojs"},{"id":5000,"value":"{\n let o = testAllDataTotals.slice(-1)[0];\n let o2 = {};\n let keys = [\"State\",\"3day_mvPreOmiBA2_nmrtr\",\"3day_mvPreOmiBA11_nmrtr\"];\n keys.forEach(k=>o2[k] = o[k]);\n return o2;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":4994,"value":"testAllDataTotals = getStateDataTotals(testAllData)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1695,"value":"$40","pinned":true,"hidden":false,"mode":"ojs"},{"id":4101,"value":"allBA4.filter(d=>d.State === \"Texas\").slice(-10)","pinned":false,"hidden":false,"mode":"ojs"},{"id":357,"value":"$41","pinned":false,"hidden":false,"mode":"ojs"},{"id":1911,"value":"totalPositive = d3.sum(allBA4, d=>d.Positives)/7","pinned":true,"hidden":false,"mode":"ojs"},{"id":1782,"value":"$42","pinned":false,"hidden":false,"mode":"ojs"},{"id":2726,"value":"\ntransitions = {\n let v1 = \"BA.2\";\n let v2 = \"BA.4+BA.5\";\n const transitions = {};\n \n allBA4.forEach(d=>{\n if (!transitions[d.State]) {\n if (d[v2 + \" 3day\"] > d[v1+\" 3day\"]) {\n let peaks = variantPeaks[d.State] ;\n transitions[d.State] = {\n [`${v1} peak`]:peaks[v1],\n [`${v2} peak`]:peaks[v2],\n [`${v1} to ${v1} peak`]:d[v1]/peaks[v1],\n [`${v2} peak to ${v1} peak`]:peaks[v2]/peaks[v1],\n ...d,\n };\n }\n }\n });\n return Object.values(transitions);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":4017,"value":"transitionsBA2toBA4 = getTransitions(\"BA.2\",\"BA.4+BA.5\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":4015,"value":"\nfunction getTransitions(v1,v2) {\n const transitions = {};\n \n allBA4.forEach(d=>{\n if (!transitions[d.State]) {\n if (d[v2 + \" 3day\"] > d[v1+\" 3day\"]) {\n let peaks = variantPeaks[d.State] ;\n transitions[d.State] = {\n [`${v1} peak`]:peaks[v1],\n [`${v2} peak`]:peaks[v2],\n [`${v1} to ${v1} peak`]:d[v1]/peaks[v1],\n [`${v2} peak to ${v1} peak`]:peaks[v2]/peaks[v1],\n ...d,\n };\n }\n }\n });\n return Object.values(transitions);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1470,"value":"function timeStampToDateString(d) {\n return (new Date(d)).toGMTString().slice(0,16);\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":4856,"value":"lastVariantDate","pinned":true,"hidden":false,"mode":"ojs"},{"id":4862,"value":"lastTimestamp","pinned":true,"hidden":false,"mode":"ojs"},{"id":886,"value":"currentBA4 = allBA4.filter(d => Math.abs(parseInt(d.Date) - (lastVariantDate - 1000*60*60*24*(numberOfDays-mapDay))) < 1000*60*60*1).map(d => ({...d,Date: timeStampToDateString(d.Date)}))","pinned":true,"hidden":false,"mode":"ojs"},{"id":2243,"value":"currentBA = allBA4.filter(d => Math.abs(parseInt(d.Date) - (lastVariantDate - 1000*60*60*24*(numberOfDays-mapDay))) < 1000*60*60*13).map(d => ({...d,Date: timeStampToDateString(d.Date)}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":980,"value":"prevBA4 = allBA4.filter(d => Math.abs(parseInt(d.Date) - (lastVariantDate - 1000*60*60*24*(numberOfDays+7-mapDay))) < 1000*60*60*13).map(d => ({...d,Date: (new Date(d.Date)).toLocaleDateString()}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":984,"value":"$43","pinned":false,"hidden":false,"mode":"ojs"},{"id":262,"value":"$44","pinned":true,"hidden":false,"mode":"ojs"},{"id":324,"value":"casesByDate = stateDataTotals.reduce((o,r)=>{o[r.Date] = r.test_number_pos_rolling; return o},{})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1257,"value":"casesByDateAndState = allData.reduce((o,r)=>{\n o[r.State] = o[r.State] || {};\n o[r.State][r.Date] = r.test_number_pos_rolling;\n return o},{})","pinned":false,"hidden":false,"mode":"ojs"},{"id":69,"value":"positivity = stateDataTotals.map(r => ({Date:r.Date, Positivity: 100*r.test_number_pos_rolling / r.test_number_ALL_rolling, State:r.State}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":3493,"value":"positivityUS = allDataTotals.map(r => ({Date:r.Date, Positivity: 100*r.test_number_pos_rolling / r.test_number_ALL_rolling, State:\"All US\"}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":343,"value":"namemap = new Map(states.features.map(d => [d.properties.name, d.id]))","pinned":false,"hidden":false,"mode":"ojs"},{"id":4804,"value":"testsUS.slice(0,10)","pinned":true,"hidden":false,"mode":"ojs"},{"id":3484,"value":"$45","pinned":true,"hidden":false,"mode":"ojs"},{"id":2676,"value":"Style","pinned":false,"hidden":false,"mode":"md"},{"id":504,"value":" html``","pinned":false,"hidden":false,"mode":"ojs"},{"id":84,"value":"function multiLayerX(config, base, ...layers) {\n const A = Plot.plot({\n ...config,\n marks: [base]\n });\n const x = A.scale(\"x\");\n\n return Plot.plot({\n ...config,\n marks: [\n base,\n ...layers.map((l,i) => () =>\n Plot.plot({\n ...config,\n\n marks: [l],\n x: { ...x, axis: null },\n y: {\n zero: config.y.zero,\n axis: i ? null : \"right\",\n line: false,\n nice: true ,\n dx: 100,\n labelAnchor: \"center\",\n }\n })\n )\n ]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1285,"value":"scaleToFit = function(el,aspectRatio = 1.2) {\n let w = Math.min(width*0.9,window.outerHeight*aspectRatio);\n return html`

${el}

`\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":1380,"value":"chartFontSize = Math.min(chartConfig.width/35,12);\n","pinned":true,"hidden":false,"mode":"ojs"},{"id":1872,"value":"firstPlotDate = new Date(2021, 10, 22);","pinned":true,"hidden":false,"mode":"ojs"},{"id":1887,"value":"d3.schemeTableau10","pinned":true,"hidden":false,"mode":"ojs"},{"id":2005,"value":"variantDescription = ({\n \"Cases\":\"Estimated positive tests, last 7 days\",\n \"Samples3day\":\"Samples detected last 3 days\",\n \"Samples7day\":\"Samples detected last 7 days\",\n \"Samples1day\":\"Samples detected last day\"\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":1216,"value":"$46","pinned":false,"hidden":false,"mode":"ojs"},{"id":4264,"value":"$47","pinned":true,"hidden":false,"mode":"ojs"},{"id":1244,"value":"variantsAllStates = getVariants(allBA4)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1991,"value":"variantsAllStatesFiltered = {\n return getVariants(allBA4);\n // Now, no states have samples\n // Only states with 100 samples\n let statesFilt = currentBA4.filter(d=>d[\"All Samples\"] >= 100);\n let statesMap = {};\n statesFilt.forEach(d=>statesMap[d.State] = 1);\n return getVariants(allBA4.filter(d=>statesMap[d.State]));\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2432,"value":"function filterByCurrentSamples(data,minSamples) {\n // Only states with 100 samples\n let statesFilt = currentBA4.filter(d=>d[\"All Samples\"] >= minSamples);\n let statesMap = {};\n statesFilt.forEach(d=>statesMap[d.State] = 1);\n return getVariants(data.filter(d=>statesMap[d.State]));\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":4819,"value":"variantsUS.slice(-50)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1835,"value":"$48","pinned":false,"hidden":false,"mode":"ojs"},{"id":3092,"value":"variantsUS.slice(-10)","pinned":true,"hidden":false,"mode":"ojs"},{"id":800,"value":"viewof mapDay = mapDaySlider","pinned":false,"hidden":false,"mode":"ojs"},{"id":2646,"value":"---","pinned":false,"hidden":false,"mode":"md"},{"id":3984,"value":"mapByRegion = 0\n","pinned":true,"hidden":false,"mode":"ojs"},{"id":1169,"value":"mapChart below","pinned":false,"hidden":false,"mode":"md"},{"id":341,"value":"$49","pinned":true,"hidden":false,"mode":"ojs"},{"id":2648,"value":"---","pinned":false,"hidden":false,"mode":"md"},{"id":793,"value":"mapDaySlider = Inputs.range(\n [1, numberOfDays-1],\n {\n step: 1,\n width: width*0.9,\n value: numberOfDays\n }\n )","pinned":true,"hidden":false,"mode":"ojs"},{"id":1411,"value":"animationDay = animateSlider(animateButton, mapDaySlider)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1444,"value":"animateSlider = {\n let lastButton = 0;\n return function* (button,slider, alwaysAnimatePeriod = 0) {\n let day = button>lastButton ? slider[0].min : slider[0].max - alwaysAnimatePeriod;\n lastButton = button\n while (day <= slider[0].max) {\n slider.value = day;\n slider.dispatchEvent(new Event(\"input\", {bubbles: true}));\n yield day++;\n }\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1420,"value":"viewof animateButton = Inputs.button(\"Animate\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":1037,"value":"viewof colorSchemeID = Inputs.select([\"schemeCustom\",...Object.keys(d3).filter(k => k.startsWith(\"scheme\") && (d3[k][10] || d3[k][9]) && !d3[k][0])], {label: \"Color scheme\", value: \"schemeSpectral\", format: k => k.slice(6), width: 90})","pinned":true,"hidden":false,"mode":"ojs"},{"id":1775,"value":"viewof reverseMapColors = Inputs.toggle({label: \"Reverse Colors\", value: false})","pinned":true,"hidden":false,"mode":"ojs"},{"id":2051,"value":"myScheme = ['#6aaa80',\n'#5cac7c','#8ecda2','#c1e1c1','#f1f1d1','#f3b6a6','#ffaabc','#f09fa2','#ec838a','#e66572','#de425b']\n//['#fff5f0','#fee0d2','#fcbba1','#fc9272','#fb6a4a','#ef3b2c','#cb181d','#a50f15','#67000d']//['#7f3b08','#b35806','#e08214','#fdb863','#fee0b6','#d8daeb','#b2abd2','#8073ac','#542788','#2d004b']\n//[\"#aa0000\",\"#aa1111\",\"#bb2222\",\"#cc3333\",\"#770055\",\"#550077\",\"#330099\",\"#1100bb\",\"#0000dd\",\"#0000ff\"];\n","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W4a","stdlib":"1","titling":"auto"}