34:["$","title",null,{"children":"COVID-19, study weekly vs total, by population | Harald | Observable"}] 3c:T57a,countries = (trace) => { return [ trace('US', 'USA', 'blue'), trace('Sweden', 'SWE', 'green'), //trace('Italy', 'ITA', 'blue'), trace('France', 'FRA', 'cyan'), //trace('Spain', 'ESP', 'olive'), //trace('Portugal', 'PRT', 'plum'), trace('United Kingdom', 'GBR', 'darkblue'), trace('Netherlands', 'NLD', 'orange'), //trace('Denmark', 'DNK', 'gray'), //trace('Brazil', 'BRA', 'brown'), //trace('Belgium', 'BEL', 'gray'), //trace('Israel', 'ISR', 'black'), //trace('Chile', 'CHI', 'plum'), //trace('Peru', 'PER', 'orange'), // low numbers //trace('China', 'CHN', 'darkmagenta'), //trace('Korea South', 'KOR', 'darkgreen'), //trace('Mexico', 'MEX', 'darkorange'), //trace('Russia', 'RUS', 'red'), //trace('India', 'IND', 'pink'), //trace('Nigeria', 'NGA', 'olive'), //trace('Egypt', 'EGY', 'plum'), //trace('Japan', 'JPN', 'purple'), trace('Germany', 'DEU', 'magenta'), // later entries are drawn on top // if you want to add a country, you need // - the name from "progression" table // - the code from "country_data" table ]; } 3d:T6d1,html`

Background

(this fork and kind of chart)

These charts compare "increase per time" to "total", because these are proportional for exponential growth.

I think this kind of chart clearly shows, in which direction the current growth is heading.

Strict exponential growth would be a straight rising line. So, a raising line represents more or less exponential growth. Linear growth is indicated by a horizontal line (constant increase per time), and a declining line indicates growth coming to an end. Negative values for "increase per time" are not possible here, because total cases, deaths etc. are cumulative values. The epidemy stops, when new cases remain zero and all active cases come to an end, which is recovered or dead.

As a disadvantage of this kind of chart, time is less visible, dates only appear in tooltips.

A logarithmic scale would make the real progress more visible (long straight part, with the date points more evenly distributed), but the current situation (which happens in the high numbers) is better visible in linear scale.

The numbers are scaled by population to make the countries more comparable. Unfortunately, this also averages inhomogeneous regions like the US and China, because the numbers from hotspots (NY, Wuhan), which are late in the progress are combined with all the subregions that are much earlier in the progress. The latter may still have exponential growth (but don't count in the sum yet) while the former are on the declining path. However, they will take over later, so the curve may look exponential again. Other smaller Regions like the countries in Europe have a more evenly distribution and can be seen more like a unit.

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COVID-19, study weekly vs total, by population

\n\n\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":169,"value":"$3c","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":679,"value":"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":307,"value":"\"last date: \" + progression.Germany.times[progression.Germany.times.length-1]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":610,"value":"html`(see point data by mouse-over, zoom by dragging a frame, reset view by double click, use toolbar visible while hovering a chart)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":238,"value":"progressionPlot_cases = {\n let div = DOM.element('div');\n let title = 'cases';\n let period = 7;\n let trace = (country, code, color) => {\n let xx = progression[country];\n let pop = population[country];\n return {\n name: country,\n type: 'scatter',\n mode: 'lines+markers',\n line: { width: 1 },\n marker: {\n color: color,\n size: 3,\n line: { width: 0 }\n },\n x: xx.confirmed.map((x) => x/pop*1E6),\n y: xx.confirmed.map((x, i) => Math.max(0, x - xx.confirmed[i-period])).map((x) => x/pop*1E6),\n text: xx.times\n };\n\n debugger;\n };\n Plotly.newPlot(\n div,\n countries(trace),\n {\n xaxis: {\n title: title + ' / 1M',\n //type: 'log',\n //range: [0, 4]\n },\n yaxis: {\n title: 'new ' + title + ' in ' + period + ' days / 1M',\n //type: 'log',\n //range: [0, 4]\n },\n width:850,\n hovermode: 'closest',\n title:\n '' + title + ''\n }\n );\n\n return div;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":149,"value":"progressionPlot_deaths = {\n let div = DOM.element('div');\n let title = 'deaths';\n let period = 7;\n let trace = (country, code, color) => {\n let xx = progression[country];\n let pop = population[country];\n return {\n name: country,\n type: 'scatter',\n mode: 'lines+markers',\n line: { width: 1 },\n marker: {\n color: color,\n size: 3,\n line: { width: 0 }\n },\n x: xx.deaths.map((x) => x/pop*1E6),\n y: xx.deaths.map((x, i) => Math.max(0, x - xx.deaths[i-period])).map((x) => x/pop*1E6),\n text: xx.times\n };\n\n debugger;\n };\n Plotly.newPlot(\n div,\n countries(trace),\n {\n xaxis: {\n title: title + ' / 1M',\n //type: 'log',\n //range: [-1, 3]\n },\n yaxis: {\n title: 'new ' + title + ' in ' + period + ' days / 1M',\n //type: 'log',\n //range: [0, 300]\n },\n width:850,\n hovermode: 'closest',\n title:\n '' + title + ''\n }\n );\n\n return div;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":498,"value":"$3d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":17,"value":"md`\n

Data

Covid-19 data is collected by corona.js from JHU CSSE.
(see section \"Methods\" below at \"corona\")

Population data is from covid19-data on github
(see \"country_data\" below)

\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":87,"value":"progression = corona.progression()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":329,"value":"population = (() => { let obj = {}; let trace = (country, code, color) => { obj[country] = country_data.find(e => e.country_name == country || e.country_code == code).population; return obj;}; countries(trace); return obj; })()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":315,"value":"country_data = d3.json(\"https://raw.githubusercontent.com/covid19-data/covid19-data/master/output/cntry_stat_owid.json\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":66,"value":"md`\n

Methods

\nSupport javascript library maintained at github.com/episphere/corona.\n

\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":71,"value":"corona = require('https://episphere.github.io/corona/corona.js')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":73,"value":"Plotly = require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":317,"value":"d3 = require.alias({\n \"d3\": \"d3@5\",\n \"d3-regression\": \"d3-regression@1\",\n})(\"d3\", \"d3-regression\");","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W3e","stdlib":"1"}} 33:null