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+<!DOCTYPE html>
+<html lang="en">
+<head>
+  <meta charset="UTF-8">
+  <title>COVID-19 UK</title>
+  <link rel="stylesheet"  href="output.css">
+</head>
+<body class="container mx-auto py-10">
+  <div>
+    <h1 class="text-center">COVID-19 in the UK</h1>
+    <p>
+      Up until recently, I used a couple of resources (i.e.
+      <a href="https://multimedia.scmp.com/infographics/news/china/article/3047038/wuhan-virus/index.html">one</a>, 
+      <a href="https://www.worldometers.info/coronavirus/">two</a>) for tracking
+      an updated number of confirmed covid-19 cases.
+    </p>
+    <p>
+      Given the high speed at which the virus is spreading, I was having a
+      difficult time intuiting the shape of this growth. For example if today
+      the total number of confirmed cases for covid-19 in the UK was 500, I
+      could not remember if yesterday it was 450, 400, or 200.
+    </p>
+    <p>
+      Thankfully someone is <a
+      href="https://github.com/pomber/covid19">publishing this data</a> as a
+      timeseries database. I am currently living in London, so I decided to
+      chart the <u>daily number of confirmed covid-19 cases in the UK</u> to
+      better understand what is happening.
+    </p>
+  </div>
+  <canvas id="myChart" class="py-12"></canvas>
+  <script src="./node_modules/chart.js/dist/Chart.bundle.min.js"></script>
+  <script>
+   var timeseries =
+     fetch('https://pomber.github.io/covid19/timeseries.json')
+       .then(res => res.json())
+       .then(createChart);
+
+   function createChart(data) {
+     var uk = data["United Kingdom"];
+     var data = uk.map(x => x["confirmed"]);
+     var labels = uk.map(x => x["date"]);
+
+     var ctx = document.getElementById('myChart').getContext('2d');
+     var myChart = new Chart(ctx, {
+       type: 'line',
+       data: {
+         labels: labels,
+         datasets: [{
+           label: 'Number of confirmed COVID-19 cases in the U.K.',
+           data: data,
+           backgroundColor: 'rgba(255, 0, 100, 0.2)',
+           borderWidth: 3
+         }]
+       },
+       options: {
+         scales: {
+           yAxes: [{
+             ticks: {
+               beginAtZero: true
+             }
+           }]
+         }
+       }
+     });
+   }
+  </script>
+  <div>
+    <h2 class="text-center">Back of the envelope predictions</h2>
+    <p>
+      From what I have read, a population where 60% of its constituents have
+      been infected with covid-19 and have recovered is said to have "herd
+      immunity". Once a population has herd immunity, the rate at which the
+      virus spreads decreases.
+    </p>
+    <p>
+      Roughly 60M people live in the UK; 60% of 60M is around 40M. Before a
+      population reaches "herd immunity", the total number of <em>true
+      covid-19 cases</em> <u>doubles every five days</u>. Therefore in <u>fifty
+      days</u> you might expect the number of true cases to be <u>1000x
+      larger</u> than what it is today.
+    </p>
+    <p>
+      So if you think the total number of <em>true covid-19 cases</em>
+      <u>today</u> is 40,000 then you might expect the rate of growth to slow
+      down in a little less than two months.
+    </p>
+    <p>
+      Thank you for reading.
+    </p>
+  </div>
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