coronavirus_model.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Initialization values\n",
    "The simulation will start using the parameter values defined below. Read on to see what this means.  To run the notebook, click \"Restart and run all\" from the kernel menu above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from corona_sim_aux import *\n",
    "N0=300e6 # initial population size\n",
    "I0=100 # initial number of infected\n",
    "contact_rate=20 # c: contacts per day\n",
    "transmission_probability=0.01 #p:  probability\n",
    "mortality_rate=0.03 # m: proportion of cases that end in death\n",
    "infection_duration=10 # d: number of days\n",
    "intervention_time=100 # t: time in days\n",
    "contact_rate_reduction_factor=0.4 # k: proportion, zero: no intervention, one: all interaction stops"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  Notebook Overview\n",
    "The plot below shows a simulation of a COVID-19 outbreak in the united states. \n",
    "\n",
    "Here is a guide to understanding the names of the relevant variables:\n",
    "* $S$ is the number of people who are **susceptible** to the coronavirus.\n",
    "* $I$ is the number of people who are  **infected** with the coronavirus.\n",
    "* $R$ is the number of people who have  **recovered** and are now immune to the coronavirus.\n",
    "* $D$ is the number of people who have **died** from the corona virus.\n",
    "\n",
    "and parameters:\n",
    "\n",
    " * $c$ is the **contact rate** (the number of face to face interactions that each person has per day) \n",
    " * $p$ is the **transmission probability** of the coronavirus during an interaction\n",
    " * $d$ is the **average infection duration** in days\n",
    " * $m$ is the **mortality rate** (the proportion of infections that end in death)\n",
    " * $t$ is the **intervention time** (the time when social distancing measures are adopted)\n",
    " * $k$ is the **contact rate reduction factor** (the amount we reduce the contact rate by social distancing)\n",
    "      \n",
    "If you are interested in reading about the details of the model, and understanding what each parameter means, scroll down to the bottom. \n",
    "\n",
    "Otherwise, try moving the sliders to change the parameters of the model to see how our decisions can affect the severity of an outbreak like COVID-19.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
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       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"799.9999826604674\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "719711a3b541426a9ec2cd7e797e3f87",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=20.0, description='c'), FloatSlider(value=0.01, description='p', max=0…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "(l1,l2,l3,l4,l5,l6,l7,l8,l9),params,update=make_interactive_plot(N0,\n",
    "                  I0,\n",
    "                  contact_rate,\n",
    "                  transmission_probability,\n",
    "                  mortality_rate,\n",
    "                  infection_duration,\n",
    "                  intervention_time,\n",
    "                  contact_rate_reduction_factor)\n",
    "interact(update)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note how early implementing (and following!) social distancing guidlines can have a dramatic effect on the time course of the disease!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# More details on how the model works\n",
    "\n",
    "\n",
    "Suppose that the US population can be divided into 4 categories:\n",
    "* S: Those who are **susceptible** to the coronavirus.\n",
    "* I: Those who are **infected** with the coronavirus.\n",
    "* R: Those who are **recovered** and immune to the coronavirus.\n",
    "* D: Those who have **died** from the corona virus.\n",
    "For simplicity we will let $N$ denote the entire living population.\n",
    "\n",
    "The number of people in each category can change due to the following events:\n",
    "\n",
    "1. Infection:  A susceptible person interacts with an infected person and the result is both people are infected.\n",
    "$$S+I\\rightarrow 2I$$\n",
    "The total number of infections in a given window of time is given by $\\Delta t cp SI/N$ where \n",
    "   * $\\Delta t$ is the window of time in days\n",
    "   * $c$ is the **contact rate**, i.e. the number of interactions that each person has per day \n",
    "   * $p$ is the **transmission probability** during an interaction\n",
    "   * $S$ is the number of susceptible people in the population\n",
    "   * $I/N$ is the probability that an interaction is with an infected person\n",
    "2. Recovery: An infected person can recover from the disease.\n",
    "$$I \\rightarrow R$$\n",
    "The total number of recoveries in a given window of time  is given by $\\Delta t r I$ \n",
    "  * $\\Delta t$ is the window of time in days\n",
    "  * $r$ is the **recovery rate* (i.e. the probability that person recovers on a given day)\n",
    "  * $I$ is the number of infected people (who could potentially recover).\n",
    "2. Death: An infected person can dies from the disease.\n",
    "$$I\\rightarrow D$$\n",
    "The total number of recoveries in a given window of time is given by $\\Delta t \\delta I$ \n",
    "  * $\\Delta t$ is the window of time in days\n",
    "  * $\\delta$ is the death rate (i.e. the probability that person dies on a given day)\n",
    "  * $I$ is the number of infected people (who could potentially recover).\n",
    "\n",
    "To simplify matters we will define variables $d$ for the **infection duration** and $m$ for the **mortality rate** so that the death rate is $\\delta=m/d$ and recovery rate is $r=(1-m)/d$. \n",
    "\n",
    "We can model the effect of social distancing by reducing the contact rate.  In other words, when social distancing measures are adopted at time $t$ (aka **intervention time**) we can replace $c$ with $(1-k)c$ where $k$ is the **contact rate reduction factor**.\n",
    "\n",
    "We can then simulate this probabilitic process with the help of a random number generator and see how different variables affect the outcome."
   ]
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