Epidemiology105.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"width: 100%; overflow: hidden;\">\n",
    "    <div style=\"width: 150px; float: left;\"> <img src=\"data/D4Sci_logo_ball.png\" alt=\"Data For Science, Inc\" align=\"left\" border=\"0\" width=160px> </div>\n",
    "    <div style=\"float: left; margin-left: 10px;\"> <h1>Epidemiology 105</h1>\n",
    "<h1>The Impact of Competing Strains</h1>\n",
    "        <p>Bruno Gonçalves<br/>\n",
    "        <a href=\"http://www.data4sci.com/\">www.data4sci.com</a><br/>\n",
    "            @bgoncalves, @data4sci</p></div>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import Counter\n",
    "from pprint import pprint\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt \n",
    "from mpl_toolkits.axes_grid1.inset_locator import inset_axes\n",
    "\n",
    "import cartopy\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "import tqdm as tq\n",
    "from tqdm.notebook import tqdm\n",
    "\n",
    "import epidemik\n",
    "from epidemik import EpiModel\n",
    "\n",
    "import watermark\n",
    "\n",
    "%load_ext watermark\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We start by print out the versions of the libraries we're using for future reference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Python implementation: CPython\n",
      "Python version       : 3.13.2\n",
      "IPython version      : 8.32.0\n",
      "\n",
      "Compiler    : Clang 16.0.0 (clang-1600.0.26.6)\n",
      "OS          : Darwin\n",
      "Release     : 24.3.0\n",
      "Machine     : arm64\n",
      "Processor   : arm\n",
      "CPU cores   : 16\n",
      "Architecture: 64bit\n",
      "\n",
      "Git hash: 6d9f1a6eb4084a40d0e306ad0ba8a2eaa55e5c85\n",
      "\n",
      "matplotlib: 3.10.0\n",
      "tqdm      : 4.67.1\n",
      "epidemik  : 0.1.2\n",
      "numpy     : 2.2.2\n",
      "watermark : 2.5.0\n",
      "cartopy   : 0.24.1\n",
      "pandas    : 2.2.3\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%watermark -n -v -m -g -iv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load default figure style"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.style.use('./d4sci.mplstyle')\n",
    "colors = plt.rcParams['axes.prop_cycle'].by_key()['color']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## CoVID19 Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We start by reintroducing the SEIIRD model as it contains enough features to be (somewhat) realistic while still being relatively simple to understand"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "mu = 0.1\n",
    "pD = 0.10\n",
    "rbeta = 0.75\n",
    "pa = 0.4\n",
    "epsilon = 0.4\n",
    "R0 = 2.0\n",
    "\n",
    "beta = R0*mu/(pa*rbeta+(1-pa))\n",
    "\n",
    "SEIIRD = EpiModel()\n",
    "SEIIRD.add_interaction('S', 'E', 'Ia', beta_a=rbeta*beta)\n",
    "SEIIRD.add_interaction('S', 'E', 'Is', beta_s=beta)\n",
    "SEIIRD.add_spontaneous('E', 'Ia', epsilon_a=epsilon*pa)\n",
    "SEIIRD.add_spontaneous('E', 'Is', epsilon_s=epsilon*(1-pa))\n",
    "SEIIRD.add_spontaneous('Ia', 'R', mu=mu)\n",
    "SEIIRD.add_spontaneous('Is', 'R', mu_ND=(1-pD)*mu)\n",
    "SEIIRD.add_spontaneous('Is', 'D', mu_D=pD*mu)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The model contains 7 different transitions across 6 compartments:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Epidemic Model with 6 compartments and 7 transitions:\n",
      "\n",
      "Parameters:\n",
      "  beta_a : 0.166667\n",
      "  beta_s : 0.222222\n",
      "  epsilon_a : 0.160000\n",
      "  epsilon_s : 0.240000\n",
      "  mu : 0.100000\n",
      "  mu_ND : 0.090000\n",
      "  mu_D : 0.010000\n",
      "\n",
      "\n",
      "Transitions:\n",
      "  - S + Ia = E beta_a\n",
      "  - S + Is = E beta_s\n",
      "  - E -> Ia mu_D\n",
      "  - E -> Is mu_D\n",
      "  - Ia -> R mu_D\n",
      "  - Is -> R mu_D\n",
      "  - Is -> D mu_D\n",
      "\n",
      "# R0=2.00\n"
     ]
    }
   ],
   "source": [
    "print(SEIIRD)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define our initial population"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "N = 100000\n",
    "I0 = 10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And integrate the model. This will be our baseline model. For the sake of simplicity we don't worry about seasonal effects as those would affect both strains equally"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "SEIIRD.integrate(365, S=N-I0, Ia=0, Is=I0, E=0, R=0, D=0)\n",
    "original = SEIIRD.values_.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we compute the timeline of the new strain with a value of $R_0$ higher by 0.7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "mu = 0.1\n",
    "pD = 0.10\n",
    "rbeta = 0.75\n",
    "pa = 0.4\n",
    "epsilon = 0.4\n",
    "R0 = 2.7\n",
    "\n",
    "beta = R0*mu/(pa*rbeta+(1-pa))\n",
    "\n",
    "SEIIRD2 = EpiModel()\n",
    "SEIIRD2.add_interaction('S', 'E', 'Ia', beta_a=rbeta*beta)\n",
    "SEIIRD2.add_interaction('S', 'E', 'Is', beta_s=beta)\n",
    "SEIIRD2.add_spontaneous('E', 'Ia', epsilon_a=epsilon*pa)\n",
    "SEIIRD2.add_spontaneous('E', 'Is', epsilon_s=epsilon*(1-pa))\n",
    "SEIIRD2.add_spontaneous('Ia', 'R', mu=mu)\n",
    "SEIIRD2.add_spontaneous('Is', 'R', mu_ND=(1-pD)*mu)\n",
    "SEIIRD2.add_spontaneous('Is', 'D', mu_D=pD*mu)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "SEIIRD2.integrate(365, S=N-I0, Ia=0, Is=I0, E=0, R=0, D=0)\n",
    "UK = SEIIRD2.values_.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When we plot them side by side, the difference is clear. The higher $R_0$ produces higher peaks that come earlier in the pandemic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Population')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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xSez0mWqM2r/+64u1V+Qx/8O1aFsh8ANAfY1sTuLNB1fjcydUY/bovnmGtqUj4qf3ZvG2SzriygVZ12ZeAAAAAAAAvUEXJAAAAP+/1ZdmseaSvNyiacTs91a7mtFhoCqKIq5/Mov3XtYRD6zqnSbQE3dM45PHVmPMUJ8tAGDwqQxLYsePVGP8ifX/Vde2hUU8+v6O2HBryWslAPgrdp2QxpdeUI1X71eJIZW+OYd12yK+fUcW7760I25Zknc99wAAAAAAAKinal2rAwAA0DBa5+Wx9IdZ6XWnnlmJUXvbZ4mBa8P2Ir57Zy1ue6p3mj6b0ojXH1CJE+emkSRCrgDA4JVUkpjx5koMnZnE0vOziDrmUPOtEU9+sdYVrJ12biUqNhsBoI6qaRKn71aJw2em8YO7anHnsr4Jmi7dFPGlm2qx87gkztm3EntP9owPAAAAAACoD0FXAAAAYsv8PJ78cq30xvCWA5KY9DINcAxcNy/J43t31qK1rXeON3lExPuPqMbccT5XAACdOjf+mPiip8OuT36lFtnm+h5v7ZV5bH4wj9nvrsbwndyTAVBfk0Yk8eGjqnHHsiL+Y14tVm7pm/OYv66IT1xTi70mJXHmXpXYY5JrIAAAAAAAUC6/fQAAABjkti3K44l/qUW+vdy6Q6ZHzHp3NZLUpCMGnk1tRXz15lp8+abeC7keNC2JL72gScgVAOCvGLVvGrt8sakr8FpvbcsiHvtwLVb8Josi65sJewAMrk0dDpmexjdObeoKmTZX+u5cHlhVxD//uRafuqYjHl1Tx1HqAAAAAADAoGOiKwAAwCDWtqyIBZ8qf+pRZVTEjh9tiupIIVcGnjuW5vHtO2qxoeRw+N/SmRU/a+9KnL57GmniMwUA8LcMmZLEzp+vxqJv1KL19joHULOIFT/PYtO8PGa9qxpDJrtPA6C+mitJnLFXJY6Zk8aP76nFLUv6brOFe1cWce/KWhwwNYkz967ETjblAgAAAAAAekjQFQAAYJBqX1PE45/siNqGcusm1Yg551W7msxhoE1xPf/uLK55svcmloweEvHew6ux92QNowAA3VEZlsScD1ZjxS+zWPnr+t+3bXmkiEff2xEz/qkSY49Ou6buAUA9TRqRxAeOaIr7VuTxg3m1eKq1785l3vIi5i2vxSHTk3jVXpWYM9bzCwAAAAAA4LkRdAUAABiEOjYUseCTHdGxpvzaM99WiZG7a2pj4CiKIm5cnMeP5mWxsa33jrvHxKQr5DpumLAEAMCzkaRJTP2Hagybncfib9Uir/M9XL4tYvE3s2i9q4gZb6xEdZT7NwDqb58paXz15Ka4dH4ev3wgi60dfXcuty8t4valtTh4ehIv3qnvzgMAAAAAAGhcgq4AAACDTG1zEQs+VYu2ZeXXnvzKNMYdXSm/MPSRVZuL+N5dta4JJb3p9N3SOGufSlRTIQkAgOdqzOFpDJlajSc+X4uO1fU/3oab8tj8QB4z3liNMYfZ/AeA+ut8bnDarpU4anYa/3l/Flc/kUfeu48w/oc7lhZxx9IkpqUHxT7VBTG5sr7vTgYAAAAAAGgogq4AAACDSLatiCc+U4vti8rveBtzZBpTzhRyZWDI8iIueSzvahJty3rvuGOGRrzzedXYb6pgBABAGYbNSWPXLzfF4m/Wuiau1lttY8STX6rF6MOSmPFP1WgaY+MSAOpvzNAk3nJwNU7dOY/z787i3pV9mHaNiGX5xFjWPjEmp+tin+rjUfTt6QAAAAAAAA1A0BUAAGCQyNuLWPj5Wmx9rPzOsuG7JDHr7ZVIEk3cNL4F6/L49h1ZPLG+d7swD5yWxNsOqXY1pwIAUJ7qqCTmfLgaq/6Qx/KfZRF5/Y+58ZYiNj/QETNeX4kxR6XWSgD0itlj0vj4MUncvbyI8++pxVOtfXs+K/NxcWX7IfHEdUWcsVfe9ewjdU0EAAAAAAD+CkFXAACAQSDvKOLJL9di8/3lB/eaJ0XMOa8aabMmNRrbto4ifvlAFn98LI+8FzOuTWnEa/arxCk7C0AAANRLkiYx+aWVGLFLEk9+tRa19fU/ZrYpYtHXs1h/Ux4z31SNpnHu9QCov85nCwdMS2LfKU1xxYK861lHa1vfntOC9Ul87oZazGxJ4iW7pXHU7DSaKq6LAAAAAADA/5X+xT8DAAAwAOVtRSz8XC1a7yw/uZcOj5jzkWo0jdGYRuMqiiJuXJTFO/7UERc92rsh15mjk/jiSdU4dRcTkQEAesPIPdPY9StNMXKf3rv3ar2jiIff2RFrr8667j0BoDdU0iRO2bkS//bCpjh9tzSq/aA7ZElrEf/n9ize8seOuPCRLLZ2uC4CAAAAAABPM9EVAABgAMu2FvHEZ2ux5aE6NI2lETu8rxrDZvWDLjl4jhZtyOMHd2Xx4Oreb6w8eae0a5LrkKqAKwBAb+rcqGfux6qx8jd5rPhVFtELt4L51ogl/5bF+uvzmPFP1Rg6wz0gAL1jRHMSr96vGifvXMQv7s/iuifz3rj0/V3rtkX85J4sfvNgFi/YKY0X7lKJccNcGwEAAAAAYDATdAUAABigapuKeOIztdg6vz6tazPfUomW/YVcaUxb2ov4xQNZXDq/dye4dhrVHPG251XjkOk+PwAAfSWpJDHlVZUYsWsSi75ei1pr7xx38/1FPPrejph0ehqTX16JdIhQDwC9Y9KIJN55aDVeslseP7svizuX9XXcNWJrR8TvH87j4kfzOHqHNE7bNY1Zoz0vAQAAAACAwUjQFQAAYADq2FDEgk/VYvui+jSsTX9dJcYfX6lLbainvCjimoV5XHBvFhvbev/4z5uRxJsOqsaYoQINAAD9waj90tjlK02x+Ju1rhBqbyhq0TVNdv0NT093bTlAoAeA3jN7TBofeX4aD6/O4yf3ZvHomr4PvNbyiKufyLt+9p2cxGm7VmK/qUmkiecnAAAAAAAwWAi6AgAADDDta4pY8MmOaFtWn/pTzqzExBcJudJ45q/N4wfzspi/tvcbOEc0RbzhwEo8f3YaiSZNAIB+pXl8EnM/UY3VF+ex/GdZVxC1N7SvjHjiM7UYfVgS019X7ToPAOgtu09M47PHJ3HHsqJrwuuSjX0feO1078oi7l1Zi+ktES/apdI16XVo1TUSAAAAAAAGOkFXAACAAaRtxdMh1/ZV9ak/8cVpTH6laUM0llWbi7jgvixuXJz3yfEPmJrEWw+pxrhhmjIBAPqrJE1i0ksqMWqfJBZ9PYvtS3ov7LPxliI23d0RU/6hEhNPTSOpuG8EoHd0bsZ1yPQkDpyaxPWL8vjVA1ms3BL9wtLWiO/emXWFcE+cm8YpO1ViwgjXSAAAAAAAGKgEXQEAAAaI7U89HXLtWFef+uNPTGPaayqmUdIwtrQX8duHsvjjY3nU+iDjOqwa8boDKnHcHFNcAQAaxbA5aezyxSSWXZDFmkt67yYy3x6x7D+yWHd1HtPPrcSofW0wBEDvqaRJHDunEkfNTuOahXn8+sEs1myNfmFze8TvH87jD4/kceiMNE7ZOY09JiaetQAAAAAAwAAj6AoAADAAbHk0jyc+V4ustT71xxyZxow3CrnSGGp5EZc//vQUkk3tfXMO+0xO4m2HVGOiSSMAAA0nHZLEjNdXo+WAPBZ/qxa1Db137O2Li1jwqVq0HJTE9NdWY8g095MA9J5qmsSJcytxzA5pXPVE3rWB2Lpt0S/kRcTNS/Kun5mjkzh5p7TrPIc1uVYCAAAAAMBAIOgKAADQ4NbfmMXib2VRdNSnfmeD9ex3ViKpaBqjfyuKIm5fWsRP7q3F8k19cw6dU1z/cd9KvGAnU1wBABpdy/5p7Pa1plj87Vq03l706rFb7yxi0z0dMeGUNCafUYmqDVQA6EVNlSRO2bkSx++YxhWP5/G7h7PYsD36jSUbi/j+XVlccG8Wx8xJ4+SdKl3hVwAAAAAAoHEJugIAADRwqG/Vb/NY/vOsbscYuVcSO7yvGklVoxj924Or8vjZfVk8sqZ3Awh/6ZDpSbzhwGpMGO7zAgAwUFRHJzHnQ9VYd3UeS8/PIt/ae8cuahGrL85j3XV5TP2HSow/IbUBEQC9qrmSxIt2rcSJc9O47PE8fv9wFq1t0W9sq0VcOj/v+tlrUueU10ocPD3pCuoCAAAAAACNRdAVAACgAeUdRTz13SzW/Tmv2zGG75zEnA9XIx2iMYz+a/7aPH5+Xxb3ruy7gOu4YdEVcD10Rtpn5wAAQP0kSRLjT6jEqP3SeOo7tWid17v3nllrdK3/1lyWx/TXPH0eANCbhlSTeMlulTh5pzSuXJDHhY9ksW5b9CsPrCrigVW1aBkScdycNE7YsRLTWjzXBAAAAACARiHoCgAA0GBqm4t48ou12PxA/Zqrh81NYsd/rkZlmGYw+qdFG/L4z/uzuH1p3wVcOz8dL9gpjbP3qcSIZp8VAICBrnlCEnM+Wo311+Wx9EdZZJt79/jbFxWx4NO1GLlPEtPOqcTwnQReAej9wGvnhNfO5yF/Xvj0hNdVW6Jf6Zw4e+EjnWHcPPacmHRNoz10Zto1nRYAAAAAAOi/BF0BAAAaSNuKIp74145oW1q/Y4zYPYkdP1KNygjNX/Q/yzcV8csHsrhhUR59F3GNmDk6ibccXIndJggXAAAMtumu446pxKh90njqe7XYeHvv35Vuvq+Ixz5Yi9GHJTH17GoMnWbtBkDvaqok8YKdKnH8jmlc/2Qev304i+Wbot95cHURD67OYuS8LI7eIe0Kvc4a7VkOAAAAAAD0R4KuAAAADWLLo3ks/Fwtaq31O8aofZPY4UPVqAzVKE3/smJzEb97KOuaFpL3YcK1KY145Z6VeMluaVdTJwAAg1PTuKfXThtuyuOpH2SR1XGd9rdsvKWIjbd1xPjj05h8RiWax7s/BaB3VdMkjtux0hUivWVJHr95KI/FG/tya7K/bnN7xCWP5V0/O41L4rg5aRw5O42Rza6dAAAAAADQXwi6AgAA9HNFUcS6q55uni466necloOT2OF91Ug1eNGPLG0t4rcPZXH9or4NuHY6aFoS5+5fjamjfEYAAHh6uuvYIysxau+0a73WGXrtdXnE2ivzWHddHhNfmMakl1aiOtL9KgC9q5ImceTsShwxK43bFrfHj29bFyvz8dEfPb6uiMfXZfEfd2dx8PQ0jtsxjX0nJ11/BgAAAAAAoO8IugIAAPRjeVsRS76Xxfpr6tswPebINGa/sxJJVUMX/cOiDU9PAbl5cR59PQdkysiI1x1QjYOmpX18JgAA9EfV0U9vGrTx6DyW/qAW7at6/xyK9ohVv89jzeV5THxRGqNP7P1zAIDOTSD2nxKxcsjtsTofHQ927BiL8smd/0v0Nx15xM1L8q6fccMijtkhjWPmVGJGS/87VwAAAAAAGAwEXQEAAPqptmVFLPxSLbYvqm/Mb9zxacx8cyWSiiYu+t6CdZ0B1yxue6qv460RzZWIV+xRiRfvlkazzwcAAM9g9EFpjNq7KVb8OovVF+VR1Hr/HPKtESt/lcfqiyNG77xzbNrjyciHdPT+iQAw6E1MN8YxQ+6O1nx4tE59fly/OOkKl/ZH67ZF/O7hvOtnp3FJPH92GkfOTmPMUM+DAAAAAACgtwi6AgAA9EMbbs1j8f+pdTUp19OEF6Yx/dxKJKmmLfpOURTx4KoiLnwki3nL+z7g2unwmWm8Zr9KTBzhswEAQPelQ5KYdk41xh1TxJLv1mLLg31zf5tvS2LMfTtFy8M7xKbdnozWPZ7sk/MAgJZ0a5yxf8TZ+zXFnx7L4rLH89jcHv3W4+uKeHxdFuffk8W+U54OvR4yPY1hTZ4RAQAAAABAPQm6AgAA9CNFrYhlFzw9/afeJr88jSlnVSJJNGnRN7K8iFufyuPCR/JYsK5/BFxntiTxhgMrsffktK9PBQCABjZ0RhI7fboa66/LY9n5WdRa++Y80o5qjL5/pxj18A6xanvE1JcWUW2xBgSg93VORz1rn2q8bI8irnsyjz8+lsXSPro+dkdeRNy9vIi7l2cxpJLF82akXaHXfaYkUbVpIAAAAAAAlE7QFQAAoJ/oWFfEk1+pxZaH6x/4m3pOJSa/rFL348Bfs71WxNVP5PHHR7NYuSX6hZYhEa/aqxInzk01KwIAUIrOTYXGHVOJlgPTWP6zLNZemUf00f4uaa0aa/8Qsf7yjhh/QhoTT6tE80T3vQD0vqHVJF6w09PPYO5ZUXQ9H+r8z/6sLYu4flHe9TOqOeLQmWkcOSuNPSYmUfEcCQAAAAAASiHoCgAA0A9svDOPJf9Wi9rG+h4naYqY9Y5KjD1SyJXet2F7EX96LIvLHs9jc3v0C01pxGm7pvHS3SsxolljIgAA5auOSmLmm6sx7rg8lv4wi63z+y7Mk2+PWP3HPFZfmsfYI9OYdHoaw2anfXY+AAxeaZLEAVM7f9JYvDGPSx7Luya9tmfRr21qj7hyQd71M2ZoxGH/FXrddULS9WcCAAAAAACeG0FXAACAPpRtK2Lpf2Sx7qq87seqtETseF41RuymiZnetWBdHn96LI8bF+fRUf+/6t32/NlpnLVPJSaN0IQIAED9jdgljZ0/l8T6G/JY/tMsOtb14clkEeuvy7t+Wg5MYtLplRixR9I1hRYAetus0Wm85eA0zt6n6AqQXv54Fmu2Rr+3YXvEpfPzrp/xwyIOn5XG4TPT2Hm80CsAAAAAADxbgq4AAAB9ZPPDeSz+Zi3aV9b/WEOmR+z40aYYMkWDFb2jlhdx65I8Lpmfx6Nr+m5i1V+zx8QkXrt/JXYaJ/QNAEDvStIkxh1didHPS2PVhVmsujCPor1vz6n1riJa76rF8F2eDryOPjiJpGLtCEDvaxmSxMv3qMTpu6Vx57IiLpufxb0r+9dzpb9l7baIix/Nu37GDYt43ow0DpuRxu4Tk6ikrqsAAAAAAPBMBF0BAAB6Wd5RxIpfPN3QHL3QpzVyryR2+GA1qiM1VFF/G7YXccXjeVyxIIt126JfmT4q4h/3rcbB002qAgCgb1WGJjH1zGqMP76IZRdkseH/Y+8+wCSryryBv1UdJuc8DDlKUJKighJERDAiKirm1TUruq6ou+q3Kuqaw5r2U1HXhBkDriCIiH6oZFGQMMRhBibnTnW/59zqnumJfWc6VFXX7/c8l1t161SdWzVFvX2q7v+eqyq13qVY/48s7v7P7mifEzHzqS0x/UnlaJ3g72YARl4Khh63IC3leGB1ls/wevnCSqzvioaQvhPrm+l18piI4/Yox3F7luOI2aVoczIJAAAAAADYLkFXAACAEbTh7krc8+me2HjPyMxEMP3kcix4TUuU2xxAxfDJsiz+sSyLX91RiavvrUR37Y/R38Ks8RHPO7wlTtqnbAYNAADqSvusUuxzXmuse2olHvhqT6y/o/az1nUuiVh0YU9+gqbpJ5Vj5hktMXaBv6MBqI09JpfiFUe3xgsfmcVV91TDo3evrH29LGp1R8Sld1XyZUJbxLHzy/HoBeU4am4pxvnOFgAAAAAANhF0BQAAGAFZTxYPXVyJxd/piax7ZPqc98KWmP2cspkrGTZrO7O48u5KXHpnJe5dVX8HGE4dG3H2oS3x5P3LZssAAKCuTTikHAd+uBQrrqrkAdMUNq21ysaIpb+q5MukI0sx62kt+brk5DEA1MDY1lI8ef+WOHW/cn7CtcvurMTv761ER080jHVdEVfeU8mX1nLEEXNK8Zg9ynn4dcZ49RUAAAAAgOYm6AoAADDM1t1eifu/2BMbFo5MELDUFrHXG1ti2gktI9IfzTd7661Lszzc+of7KtFZhwcTTmyPeNYjWuKMA8v5QZAAANAIUoB0+oktMfXx5Vh2aSWWfL8nuldFXVhzQxZrbuiOMfMjZpzWEtNPLkfrJH9rAzDy0kn9Dp6ZlnK8/OjqLK+/vrMSC1fU30nYdqa7EnH9g1lc/2BPfCl6Yv/ppXh0mu11j1LsM7Xk5IUAAAAAADQdQVcAAIBh0rMuiwe/3ZPPfhMjdJxV26yIfd/eGuMPKI9MhzSNNR1Z/K73wMH76nD21mRsa8QzDi7H0w9uiQntDgYEAKAxldtKMeuMapj04Z9V4qGf9OSzq9aDjkURiy7siQe/1RNTH1eOGaeVY8IjhHEAqI3xbaV4ygEt+XLn8kp+Yrb0/dXG7mg4dy7P4s7lPfHdv0bMGBdx9PxyHDO/HI+cU3IiNwAAAAAAmoKgKwAAwDDMeLnyD5V44Ks90b1i5PqdfHQp9npzq1l1GDLdlSxueDCLyxf2xF8WZflME/UacE2zt6aA65Sx3v8AAIwOLeNKMfd5LTHzKeVY8sPqSZSyOgnuZF0RK35XyZexe5ZixpPLMe2kcrRO9Pc4ALWx//Ryvrz0yCyuvrcSVyysxN+X1ufJ2gaybEPkod20tJYjDp9dykOvx8wrx1zf/QIAAAAAMEoJugIAAAyhjsVZ3P/f3bHm+hE8iKoUMfcFLTHnrHKUyg50YvDuXlk9GPB3d1diVUfUrQltEWceVI4zD2qJSWO89wEAGJ1ap5Rij1e0xsynZbH4uz15uDTq6CQ0G+/L8hM9Lfqfnpj6+HLMONUsrwDUzri2Upy6f0u+LFqTxW8X9uTfc6XwaCNKJ567YXEWNyzuia9ET8yfFHHUvHIcNbcch80uxRizvQIAAAAAMEoIugIAAAyBSlcWD19cicXf74msc+T6bZ0csfd5rTHpUeWR65RRadXGLH5/byUuX1iJhSvqe7aLSe2Rz9761APLMaHdwXwAADSHMbNLsfebWmPO2Vks+X5PrLiqvgKvaSy84reVfGmfGzH9pJaYflI52mf7mx2A2pg/qRQvfGRrPP/wLG5+KIsr7qrENQ9UorMnGtaiNWmpxC/+UYm2csQjZpXiyHnlOHJuKfae4kQTAAAAAAA0LkFXAACAQciyLFZeXYkH/6cnOh8a2b7HH1yKfd7WGu0zHbzE7lnflcU191fygOuNi7Oo1He+NaaOjXjmIS1x2v7lfHYOAABoRmPnl2LvN7fG3OdmsfiHPbHiyvoKvCadiyOffTYtE48oxfSTyzHlseVoGevveABGXku5lAdBj5xbjnWd1ZO9XXl3JW5dWudfhg2gqxJx05IsblrSE9+IiGljI3+Oj5xbiiPmlGP6OHUXAAAAAIDGIegKAACwm9b+vRKLLuyJ9beP/AFRM88sx/yXtERZ2I9d1NmTxXWLsrjq3p64dlHWEDNYzJ5QncH11P3KMabVex4AAJIxKfD6xtaYm2Z4/UFPLK/DwGuy9uYs1t7cE+Uv98TU48sx7cRyTDy0FKWyv+0BGHkT2kvxlANa8mXx2iyuuqcSv7u7Jx5YEw1vxcaIK+6uxBV3p2s9scfkiMNnl/PQ6+GzSzF5jNoLAAAAAED9EnQFAADYRR2Ls1j0je5Y9f9GPuBaHh+x52tbYtrxLSPeN42ru5LFzUuqs1WkGVzXd0VD2H96KZ51SDkeu6Ccz7wBAABsa8y8Uuz1xtaY89zewOtv6zPwWtkYsfw3lXxpmx7V0OsTyzFuv1KUSv7eB2DkzZ1Yiuce1hJnH1qOu1Zk+Syv6fuzlRtjVHhgdVoq8b93VP8w2HtqKY6YXYrD55TjsFmlPPQLAAAAAAD1QtAVAACgoO41WSz5fk8s/VUlsu6R73/i4aXY6w2t0T7bAUgMrKsnixuXZPHH+yrx5wcqsbYzGsbR81LAtSUOm+2AdwAAKGrM3OqYcc7zslj8485Ydlklyj31eZKkruURD/+ski9j5kVMfUI5pp3QEmMX+PsfgJGXvn9KJ1zbf3o5Xnpk9YRxV95TiT/dX4kNNfgeeLjcszLLl5//oxLpnHL7TSvlM72mGV8fMasUY1vVYQAAAAAAakfQFQAAYAA967N4+BeVePjinuhZN/L9l9oi5p3bErPOLEfJrJbsREd3FjcsroZb/7KocWZuTVrLEU/cuxzPOKQce00p13p3AACgYY2ZXYq5L4u4aeoVMenWvfOlpaM96lXHgxFLLqrky7h9SzH1hHJMfVw5D+4CwEhrKZfiyHlpKUdnTxbXP5jF1fdWv2vbOIpCr5Us4o7lWb785NZK/t3cAdNT6DWFX8tx0IxSjBF8BQAAAABgBAm6AgAA7EDPuiwe/mWaYaYnetbWZh/G7VeKvd/cGmP3dFAR27e2M4vrFlXiTw9kcd2DjXfA3eQxEaftX47TD2yJ6eO8zwEAYKhUxnbFqiPviNWHLYyJd+wRcxYeGl0P1/ff3BsWZrFhYU88+M2ePPQ65bHV0KuZXgGohfaWUhy3IC3l/ARz1y7K4vf39sR1D2bR2ROjSncl4talWb58/5ZKtJQi9p1WikNmluIRs8r5eprv7gAAAAAAGEaCrgAAANsLuP6iN+Bagxlcc+WIOWeVY85zW6Lc5gAitrR4bRZ/fqCSL397OMtnYGg0+08rxRkHleP4vcr5QYMAAMDwyNp6Ys0j7o3Hv+nQ2HBtSzz0k0oeKK13faHXxd/piTELIqb2hV73KUWpZAwBwMhKs5s+fq+0lGNDV/W7uT/eX8lnfB1todekp9+Mrz//RyXfNmdCxCGzyvGImaU4ZFYpFkwuRVlNBgAAAABgiAi6AgAA1FPANR00NS9irze1xoSDy7XbCepKT6V6UFkebl2UxX2r6v+g9O1JedbH71nOA64HzXBwOgAAjKRSS8S0J7TE1BPKsfavafzbE6v/nEU0wPCi4/6IJT+o5Ev7nIgpjy7H5EeXY+IjSlFqNa4AYGSNayvFE/dpyZeN3Vkedv1/91XiL4sqsaE7Rq0l69JSiSvvrl6f2B5xcAq9zqzO+HrA9FIeCAYAAAAAgN0h6AoAADS9ruVZPPzLnlj2v5WaBlyTmU8tx7wXt0TLWAcENbtVG7O4YXElrnswixserMSazmhYU8dGnLZ/OU47oCWmj/PeBgCAWkonnJl0RFrK0bE4i6WX9MSy31Sisj4aQueSiId/XsmXlgkRk44ux5RHl2LSUeVonWC8AcDIGttaisftmZZydPZkcdPiLJ/pNZ2wbm0Df59XRHp+1y7K4tpF1SltW8sR+01LwddSHDyznAdfZ46v/u0BAAAAAAADEXQFAACa1oaFlXjoZ5VY+ftKZDU+0/7YvUux52tazOLa5LO23rkii+sWVcOtdy7PGmFipZ161JxSPPmAlnj0/FK0pelcAQCAujJmbin2eHlrzD0ni+W/rcTSX/REx6JoGOlkVSuvqsTKqyKipScmHlqKyceWY/Ix5RgzT7AGgJHV3lKKY/dISzm6K1nc8lCWB17/9EAlljbICSUGo7sS8Y9lWb7EbZV825QxEQfOSLO9VoOvB8woxeQx6jMAAAAAANsSdAUAAJpKlmWx5vosHrq4J9beVPsYYXlMxNznt8Ssp5Wj1OoAn2bz0Lo0y0MlblxSXTfyrK39Z289Zd9ynLpfS8yd5D0NAACNoGVcKWY9tSVmPqUca27I4uFf9uRj54Y6+05PxNqbs1h7c08s+lpPtM+JmHRkOSYfVY6JR5Ty5wgAI6W1XIpHzU1LOV55dBZ3r0yh1ywPvd61opEK7OCs6oj4y6Is/tI762syZ0LE/tPLvQHYUj4L7Lg2dRoAAAAAoNkJugIAAE2h0pHFiqsq8fDPKrHxvvo4kGjysaVY8E+t0T7bQTzNYm1nFjenUOuSSh5sfXBtjBpHzi3Fk/dviUfvUcoP5AMAABpPqVyKyUenpRwdD2Wx/LKeWHZZJbpXRsPpXBKx7H8r+VJqjZhwSPV5TTqqFGP3KpntFYARk2rOvtPSEvG8w1ti6bos/ryoks/2+teHsnwm1GayZF1aKvGH+6rX01eJCyZXQ69pSQHYvaaUoq1FrQYAAAAAaCaCrgAAwKi24d5KLPt1JVZcWYmedVEX2qZH7PFPrTHlOAfWjnYburL4+9Isbnmokgdc71yeNdSESAOZOT7i5H3LcfK+LTF3ovcyAACMJmNml2LeC1tj7vOyWPWXLJb9uifW3Nhgs7z2yroj1v41i7V/7Yn4RkTr1IhJR5Rj4iNL+doJqAAYSTMnlOKpB7bkS/r+MH1veO2iSlz7YCWWb4imU8ki7l2V5cvlC6vbWsuRh133nVqKfaZtXo838ysAAAAAwKgl6AoAAIzK2VtX/qEacF13Wx0dgVuOmHVGOea+oCVaxjkgZ9QGWx/O4paHq7MxpGBrOlBrNBnTEvG4PVO4tRyHzS5FWVgbAABGtVJrKaY+Ni3l6FiSxbJLe2L55Y05y2uftO8rrqrEiqvStZ5on1sNvk56VDkmHl6K1snGOQCMjHFtpXjMgrSUI8uyuHtlCr1meej19mWj77vFotIst3etyPIlesOvyZwJkc+Ou8/UcuyX1tNKMWNcddZcAAAAAAAam6ArAAAwamy8L4ulv+6pzt66NurKpEeVYv5LW2LcPuVa7wpDaHVHFrc+nMWtSytxSwq2rhi9B58dNquUh1tTyDUdgAcAADSfMXNKMf/c1pj7/CzWXJ/Fsst7YvW1WcqKNrTOxRHLFldi2aWV/PrYvUsx8dBSTDysHBMOLUXbVGMgAIZfCmumEOe+0yLOPqwl1nRkccPiStzwYBbXL67Eyo213sPaW7IuLVn8v/s3//Exqb0v/FratN5jcilay+o3AAAAAEAjEXSl6Tz00EPxt7/9LV+WLFkSa9asyZe2traYNGlSTJ48Ofbdd9849NBD4+CDD45x48bVepdHhQ0bNsStt96av+533313rF69On/du7q68tc9LXPnzo1HPOIR+Ws/e/bsGE287wBg+HStzGLl1ZVY8btKrL+9/hKGY/esBlwnHVVyVvkGl2ZUeHBtxN8frsStS1PAtRIPrIlRbY9JESfs3RIn7VOOORO9fwEAgKpyWymmPCYt5XxcnmZHTbO8bryn/sbluyM9j7QsvaQafB2zR+Sh14mHlWLCoeVon2F8BMDwmzSmFE/YuyWesHf1u8l7VmV56DWFX//2cJbPekrEms6Im5Zk+dKnrRyxYEop9ppcij3Tekp1PWtCRNn39AAAAAAAdUnQlVEv/eBz+eWXx8UXXxy//OUv44477ih83xRCPOGEE+KMM86Is88+O/bZZ59h3dfRZuHChfGDH/wgf92vvvrqPNRa1IEHHpi/7s94xjPi5JNPbrhQiPcdAAyvSkcWq/5UyWduXX1DFlGHB/S0To2Ye05LzHhSOUotjfW3DFUbu7O4c3kW/1iWlko+c+uqjhj1ZoxL4dZynLBXOfabJqANAADsXJrtdPbTW/Jl/cJq4DUFX3tWx6jR8UBaKrHs1+laT7TPiZhwSDkmHFKKCQeX8pNcGfsDMJzSd3RpptJ9pkY86xEt0dGdxS0PVWd6vXlJFveuGh0nmxgqXZWIhSuyfOlvbGvks732BWD7QrAzx1dfYwAAAAAAakfQlVGro6MjvvKVr8RnPvOZuO2223brMVIw84orrsiXd7zjHfHMZz4z3vrWt+YhRHbsqquuik984hN5yLNS2b3Uye233x6f/vSn8+WQQw6JN73pTfGKV7wixowZE/XM+w4Ahk/Wk8Xav2ax/HeVWPXHSlQ2Rl0qtUfMfkY5Zj+7JVrGOTCmUVSyLBatjjzQmoKtty+rzpBQaZLjwya1Rzx+r2q49RGzSmY1AAAAdsv4fcsx/pXlmP+SLFZfl8XKqyqx6i+VyDpjVOlckpZ0Aq7q9fL4iAkHpdBrOQ++jj+oFC3jjasAGD5jWktx9Py0lPPrKzem4Gs19HrzQ5V4cE2t97A+beyO/OSGaelvXOuWM8D2LemkgAKwAAAAAAAjQ9CVUemSSy6JN77xjXHnnXcO2WOmwOaPf/zjfHn+85+fBznnz58/ZI8/GjzwwANx3nnnxfe///0hfdxbb701Xve61+Wv+ec+97l4ylOeEvXI+w4Ahl6lK4u1N2ex8v9V8hlc63o2mFLEtJPKMe8FLdE+04Ev9SzLIj/Q677FPXHXiizuSgc2rchifVc0lQltEY/eoxzH71WOR80tRWvZ+xYAABga5bZSTD0uLeXo2ZDlY/o0y+uaG7KI3Ts/Zl2rrI/8ua25oae6oRQxdkEpxh/YuxxQinF7l6LUatwFwPCYOrYUx+/VEsfvVb2+dH0Wf11SiZsfyuLmJZVYur7We1jfNnRHfvLDtGw9A+z8SaXYY1Ip5k9O64h56fKkUoxrU9cBAAAAAIaSoCujSppN87WvfW187WtfG9Z+vve978Uvf/nLuPDCC+Oss84a1r4axQ9/+MN4+ctfHmvWDN+pYe+44444/fTT85ldP//5z9fN7K7edwAwtCodWay+PotV11Ri1Z8r+cGida0UMfX4csx9bkuM3dOBLfWmp5LFfasj7uyeH8sqU2JZNjmWVybHNy5L/1a9ByA3kTRz63ELyvG4Pctx+OxStLV4zwIAAMOrZVwppp/Yki/dq7NY+cdq6HXd37YMkowqWcTG+7J8WX55dVOpPWLcvtXQ64QDSzFu/3KMmRdRctIhAIbBzPGlOGnfljhp33TivyyWrIs88PrX3uDryo213sPGmQE2P1niim3/bpk+LvoFYDevZ46PaFHfAQAAAAB2maAro8aiRYvi2c9+dvzpT38akf5SoPPss8+Od7/73fEf//EfUSo15w8V6Uex97znPfHBD34wvzwSvvrVr8Ytt9ySz3I6b968qCXvOwAYGt2rUri1OmvrmuuzqHRE/UsB1xPKMfdsAdd60dWTxf2rqwcd3bm8ur57ZRadPenf51HRrKaOrYZbH79nOQ6dVXKQFQAAUDOtk0sx8ykt+dK5tBp6XfXHSqy7dRSHXntlnRHrb8vyZWm+pSfKYyPG7VeK8fuV8nVaxu5RipKTEgEwhNJvynMnRsyd2BJP3r/6G/8DqyNufqiyKfy6trPWe9l4lm9IS5bPmttfWzlibj4LbHU22DkT0+tfXWaMjyj7jR8AAAAAYLsEXRkVFi9eHCeddFLcfvvtI9pv+gHoAx/4QB4+/NSnPhXN6M1vfnN89rOfHfF+r7nmmvzf/He/+13MmTMnasH7DgB2X1bJYsOdWay+Li2VWH9Hls920hD6Aq5pBtcFDkiphfT3UJpx4L5VWdzbuyxckcU9q7LortR67+rDvEkRj9mjHI+eX46DZwq3AgAA9ad9ZilmP70lX7qWZ7HymmrodW2a6bVJxnaVjZHPbNt/dtu+mV/H7VOKcXuVYuze1aV1gnEdAEMXfF0wJWLBlJZ46oEtUekNvt66tBK3PpzF35dWYvHaWu9l4+qqVL+7vm9VurblDx+t5Yg5EyIPv86bVA2/9gVh0/Y2J7sAAAAAAJqYoCsNb/ny5XHqqaeOeNiwv09/+tMxYcKEfFbTZvKud72rJiHXPv/4xz/yf/srr7wypk+fPqJ9e98BwK7rXpPFmhsrebh1zXWV6F4djaUUMe2EcswRcB1RazrSAUHVMOt9q7O4d2X18hozDGwhvSNToPXRKdy6RzkWTPYeBQAAGkfb9FLMempLvnSvymLVnyr5bK9rbs7SxKdNpf/Mr/21zYxNwddxveHXMfNLUW4z/gNgcNIMo3tOidhzSnXG12TFhixuW1oNvabw610rsuhplJNV1rF0osYH1qQli3hwyxc0VfQ042v/8GuaiXf2hFK+TB5TDSkDAAAAAIxWgq40/ExO5557btxyyy2F71Mul/NZOM8666x49KMfHfvss09MmzYtOjo6YtmyZXHzzTfH1VdfHd/+9rfj3nvvLfy4F1xwQTzqUY+K5z3vedEMvvvd78aHPvShXbrPvvvuGy94wQvi+OOPj8MPPzxmzJgRbW1tsXLlyli4cGH86U9/ih/96Ed5cDX92xbx17/+NV7ykpfEz372sxH7Ucf7DgCK6dmQxbq/Z7HmpkqsvTmLDXc30Kyt/ZTaIqafVI5ZTxdwHU4burK4PwVZ+2ZpXVkNti7fUOs9q19jWyMeOaeUz9x69PxyTB3r/QkAADS+1imlmPHklnzpXpfFmusrserPWay+thKV9dG0upamJctPILZJS8TYPfqFX/eqrlMoVhAGgMGYNq4Uj90zLeX8ekd3Fncsz+LvD2fVmV+XZrG+q9Z7ObqkCr90fVqy+OtD2/6YMqYlYtaEavB1Vu8ye0LErPHVIOzUseo/AAAAANDYBF1paB/+8IfjkksuKdw+hQzTfQ488MBtbkuBy4kTJ8bee+8dT3va0/IA4fe+97181tIUwizin/7pn+Koo47a7uOPJmkm1Ve/+tWF2++3337563722Wdv94eV2bNn58txxx0Xb3zjG+PWW2+Nd77znfGTn/yk0OP/4he/iP/8z/+Md7zjHTESvO8AYPsqnVms+0cWa2+uxNqbslh3R2PPutIyOWLm6eWYeXpLtE11cMhQqGRZLFtfPVv9g2uyWNS7PLA6i4fW1XrvGsOCyRFHzSvH0fPKceisUrS1eG8CAACjV+uEUkw7oSWmnRCRdWex9u9ZrP5zJVb9pRKdi2u9d3WgJ2LjvVm+rLxq8+by+Orsr2NSCHaP6syv6fKYORGlVuNIAHbdmNZSHDY7LelaS/5d732rUug1y2d8TeHXJb7jHVYdPRH3r05LCsFuG4Rtb4mYOb5fEDYPwKZwbClmji/FtHERrWV/BwAAAAAA9UvQlYaVZvJ8z3veU6jt+PHj44tf/GK8+MUvLvz4KZB5zjnn5OHDV7ziFfH9739/wPusWbMmXvrSl+Yzc47WM2Wm2Uxf9rKX5c+1iDSD63//93/HhAkTCvdxyCGHxI9//OO48MIL43Wve11s2DDwNF7/9m//lv9bHXbYYTGcvO8AYLPu1VmsuzUtlXy9/s4sslFwBvcxe0TMfkZLTHtiOcpj1NbdsbqjN8S6enOY9cE1EQ+uzaKzgcPPtZq19Yg5pTzYmgKu6SAlAACAZpQCmpOOSEs55r88i477I1b9uRKrr6t+LxGVWu9h/Ugz31a/s9kqBNMSMWZu5MHXPADbG4JNl1snG28CUFy5VIq9p6Yl4ikHbP5e+I5l1Zlfb19eyS+v6qj1njaP9N37ojVp2X4QNlX6NOtrCr3OGB8xI1+nEGzEjHHCsAAAAABA7Qm60rDSzJ/d3d2FwoZp9s0nPvGJu9VPmm3zoosuin/+53+OL3/5ywO2/+Mf/xjf+MY38uDhaPT1r389f45FvOENb4jPfvazu91XCtTutddeceaZZ8bGjRt32ja9F9J74vLLL4/h5H0HQLNKJ7voeDAdJFmJdX+vhls7HohRZeLhpZj1jJaYfHQpSg7kGPD9sKYzYsnaNBNrNcTaF2hNy9rOWu9h40rvvP2ml+JRc0rxyDnleIRZWwEAALaRTvo4ds+IsXu2xJyzWqJnXRZrbs5izfXV4GvXslrvYZ3qifz7nI4H0sy4WwZgWibGFuHXfD0vYsyckhOBAVDI5DGlOHp+WtK1lvx75KXrI25fngKwlTwAe+fyLDYM/HM7wyBV/hUb05KCyH1bioVhZ4yLmD4uBWFLMW1sxLg2fxsAAAAAAENP0JWGlGa5/O1vf1uo7Xe+853dDhv2l2bmXLJkSfz0pz8dsO073vGOeM5znpOHFUeTtWvXxvnnn1+obXr+n/nMZwbd5ymnnBLf+ta38scbyBVXXBE/+MEP4uyzz47h4H0HQLNIB5+kA0LX35HF+jsq+XrDnVn0rItRpzw+YvoTyzHjtHKM26dc692pKxu7s94ga+Rh1sW9odaH1kYsWZfFRgcjDZm5EyMPtT5qbjkOn12KSQ4gBgAA2CUtE0ox9bFpKVdP1nV/5IHX1ddXYt3fssiMYQfUszZi3W1ZvmytdWo18No+txTtc3ovzynFmLml/DYnDANgRyemmDUhYtaEUjx+z+r375Usi0WrU/i1GnxNs74uXJlFt5nZGyYMm4xrTcHXqAZfx5Wql8eWttk2ttXfCAAAAABAcYKuNKT3v//9hdq95S1viWc84xlD9iPM1772tXjUox4V9913307bpmDif//3f8d5550Xo8mXvvSl/LkNZJ999omvfOUr+Ws2FM4666x8dtjPfe5zA7b9wAc+MGxBV+87AEZzqHXD3VlsWNgbbL09i+6VMaqNP6CUh1unnlCOlrHNeaBFR3cWy9ZHPLy+GmBNodYlKdSar7NY3VHrPRy90hnvD59djsN7Z22dM7E534MAAADDPdvr7Ge2RKUji7V/z2LtTZVYc1P1+48dZDbYgfQ9UffK7YdgS+0R7bM3h1/zAGy+jvxys37vAsD2lUulWDAlYsGUljh53+q2rp4s7llVDb3evbIafL1nZRadPbXeW3Ykzcr7wJq0pL8NdvyH1fi26vfhKfg6dWwppoxNM8amyxFTetdTx1S3t7X4mwEAAAAAmp2gKw3nl7/8Zdx8880DtluwYEF88IMfHNK+p02bFp/85CcLBSlTuxTObGtri9Ggq6srf05FfPrTn44pU6YMaf8f+tCH4oc//GE8+OCDO2134403xq9+9as4/fTTh7R/7zsARoNKV5rRJKuGWvuWhVk+Y0czKKcziafZW59cjvH7je7ZW9OBQcs2RCxbn8XSfIl8na4v6728prPWe9lkwdY51dlaD5tdjnkTqwdeAwAAMPzKY0ox+ci0VL8L6F6Txdqbs1hzcyUPv3bs/GcHBpB1Rj6DbvrOaXtBl5aJEe2zStE2o29divZZEW0zS9E+sxRt0yNKgi0ATS0FHA+YnpbN23oqWTy4JmLhykosXFENwN61wgkaG836ruoyUCA2mdAW/QKwvSHYfuHYtJ6c/q4bU51R1nfsAAAAADD6CLrScD7xiU8UanfBBRfE+PHjh7z/5zznOfGEJzwhrrrqqp22S7NvXnTRRfGiF70oRoPvfe978cADDwzY7pRTThmy2Uz7mzhxYj5b6ytf+coB23784x8f8qCr9x0AjSTrzqJjccTGe7PYeH+2ad2xKIusO5rO+INLMeOU3tlbxzX+gQ8burJYsSFixca03hxizYOsveHWlRtrvZfNbdb4iENmCbYCAADUo9ZJpZj6+LRUg6+dD2ex9q+VWPu3LNb+rRKdgq9DKp1gbcPadLK12H7ApRzRNjWibVYp2meUom1WVAOweRA28mBs6+SIUtm4GqCZtJQ3z/z6hL2r27IsixUbI+5eUZ31tRqAreSBWJO1N751XdWlSCi2tRwxqT1i8thSTG6PmNQ7K2y+rTcMm9aTxmy+bsZYAAAAAKh/gq40lBTiu/zyywdst9dee8ULXvCCYduPd7zjHQMGDpNvfOMboyZweOGFFxZ+bYbLi1/84vj3f//3WLRo0U7bpfdICuXuscceQ9Kv9x0A9ap7XRadi7LYuCiLjgfTbK0RG++rXm7GQGt/Y+ZFTDuxJZ/Bdczc+j94IR2gkw7gSAHW5RuqAdZ0wM4W697LG5v837bepONs955aikNmluIRs9K6HDPH1/97DgAAgKo0y+j0k1ti+snV653Lslj390qsvSWLtbdU8u9bGEaViK7lacli/Y5CLS0RbVMi2qaXonVadd02LS0RrWk9PfLreSBWiAVg1EonE5w+LmL6uFIcPX/Lk0Pes6ov+JrFfauqS/rOndGpu5JOBlo9IWjVwFHnNAvs1gHYtJ7S/3p7xITe4GyaYXZMq78rAAAAAGAkCbrSUL797W/nIYCBvP71r4/W1uF7e59xxhlx0EEHxT/+8Y+dtvvNb34Tixcvjrlz50YjS8HSK664YsB2hx56aJx22mnDth9tbW35v+273/3unbarVCr5e+Xtb3/7kPTrfQdALfWsy6JjSRadS6IaZk1LCrYuyqJ7Va33rr6kgxnTrK3TTizH+ANKNZ9Bs5JlsbYzYtXGtGSxqiOrXu63XrlpZtaIrkpNd5eCxrdFHDi9FAfPLOWzth40oxTj2xzsAgAAMFqkWUXbT2iJaSdUr3etzGLdrWmp5OsNdznB2Ijr2RyGrdrBbza9s8Pm4dd+gdjWtG1KKVqnbF63jK8GpgBofOPaqiciPGTm5m19s7/e2xt6TUvf5Q3qeFNK/+5pWbKueDi2rRwxsT0tpTwAu+XlUu/1FI7tu1xdp5CsGWQBAAAAYNcJutJQvvOd7wzYplwuD/tslumH73PPPTfe85737LRdT09PXHTRRfGmN70pGll6Dik8OpD0mgy31Me//du/DRg8Te+VoQq6et8BMJwqHVl0Lo3oWppF50O9odbF0RtuzaJnba33sL6Vx0ZMfnQ5pj+xHJMeVYrSMJ5du6eSxZrOiLUdEWs6s1jTsWVodXOgtbpObSsDHydBnc/WuteUUh5mPXBGKQ6eUY75k9N2B6gAAAA0i7appZj62LSU8+uVzizW35nF+ts2h1+7V9d6L9l6dtgN+YYdfzFTak2h120DsG1bXc/X6buAdt8FADTq7K9H9js/dDrOYNn6iHtXbw7A5svqLDYKwLKVrm1mjk2K/fAzpmXHIdl08sx0Us3qsv3L7S1OygEAAABA8xF0paFmFb3xxhsHbHfCCSfEHnvsMez784IXvGDAwGFyySWXNHzgMD2HIs4555xh35e99torHv/4x8fVV1+903bXX3/9kMxq6n0HwGBUurLoWhbRuTSts+hauvlyX7hVkHXXtUyMmPKYckx5bDkmPbK0ywcapgNZOnoiD6r2BVY3rXsv94VZV+fbqqHV9V3D9pSoE/MmRuw7rRz7pRlbZ5Riv2mlfDYAAAAA6JO+h5j4iLSkay359wydD0asu70S62/P8mXDQrO+1rv075O+t0vf0/Vu2Wn78piIlkkRrZNKm9atk3a0rboumzUWoO6kz+WZEyJmTijF0fM2b69kWSxdVw3A3r86i0VpWZPFA6urJ7eEXZV+h+rYELFsw66HZJPWcsS41t4AbHspxqfLOwjJphlkx221fWxr2pYex98iAAAAADQOQVcaxmWXXVao3Zlnnhkj4YADDogDDzwwbr/99p22+93vfhednZ3R3t4ejaijoyOuuuqqAds94hGPiH333XdE9umMM84YMOja954Z7Cyz3ncAbE/Wk0X3mojulVl0r4zoWpVF94reEGuamTUdJLc0i+5Vtd7T0aN1asSU48ox9XHlmHhoKSrlavD0oY6ItWsrsTYFUdNsq51ZrOuKWNe7Ttvzy+m2ruo63a974MnqGdWy2GNSxP7TW2L/6dVA6z5T05nUHfABAADArgdmxsyPGDO/JaafuPnkZxvvzmLdHdXg6/rbK9HxQK33lMGodFSX9J1f4aBKS0TrxN4w7MRStExIJ3DrXfddHr95W2u/28vjhGQBRlK5VIrZEyNmTyzFsfO3vC39xtAXes3Xa1IQNuLBtVl09tRqjxnt0u9Y6SSsaYl1uxeW7R+YrQZfewOw6XoKx7amk3323ta6ORy77fXN7dJMtf5GAQAAAGC4CLrSMIoGDk899dRh35f+fQ0UOFy/fn0eyjz55JOjEaV937BhQ9297u9+97sHbHfppZeOWNDV+w6g8WXdWXSvjujqDa92r8qiK63T9VW921f1Xl+Tjm6r9R6PfutmRDy0T8R9+0TcPzNiQ3cl1t9ViQ3/iNhoVhQKSicrXzApi7Z1D8SM8qqYUVod08pr4umnPjnGjDEkBgAAYOiV04xaB6YlIp5a3dazLosNd2ex/q4sNtyZ1r3h113LKtBIetJ3jNWlY9M/dMF/8HL0hmBTKLY3HJuujyvlM8W2jEth2N6gbLo8vtS7rrbpu5zeiwAMTjpB4oEz0rLl9r5ZYPPg65otw7BL19dqb2Engdlt/g7Jdus3l77Aa/qJZUxrKb+ctrXn61K/21K7Ur7e0e1jW0rR3nt72p7aCNICAAAANC9H9dIwiszgOWXKlDjqqKNipJx00knxhS98YcB2jRw4LPK6970WI+XYY4+NiRMnxtq1a4dk3wf7GN53APUly7LoWR/RsyaiZ201lLp5HdG9JsvXPWuy6O5b995GbXW2RCycE3HH3Ig75kWsmtDvxhU13DEaRjoIYsGUUuw3tRT79c7UuvfUUmTdnfGrX91c690DAACgiaWw4sTD0rJ5W8+GLDbek8X6PPhanQV24/1ZZF213FPqQqX6fWX1O8vdn8Wt1NoXfk1B2VI+U2z/YGwKyvYFZstje5cxpXzdkl8vRXlM3/aIUpvwCcD2ZoE9at6Wt3V0Z/HQuojFa7NNy5LeddqewofQiCpZxPqu6lI1+PDs1jYFYXcWpu29nLa3pbBsX0i2EnFX97xoKVWiJXqiJSpx+/KICWMr0d5Sirbedn1LS8nfNgAAAAD1RNCVhrBq1apYuHDhgO1S2HAkv4BMgcsirr/++mhU1113XaF2xxxzTIyUcrmc/1tfddVVO2131113xerVq2Py5Mm71Y/3HUBtVLqyqKSgar70hlbXR1T6X96QRc+6dDBgb5t1/YKr6eAvBwg0jGUTI26fVw223jMroqel1ntEI2gtR+wxuRR7TSnFnmk9tXp59oTqwUVb6zADMAAAAHUozbw54ZC0bN6W9WTR8WDEhnsqeQh2wz1ZbLw3i84ltdxTGlXWHdGzuroMJjC7SXlz6LUvFNuSLo/r29YbjN20rRqaTddbem8rtUeUe5dSur3vct86TRUH0OBSMG/PKRF7Ttn2M62nksWyDbEp+Lp5qW7bHCCE5tTRU10225Uwbfp/7sgttvz6yvTf7f9QlP7sSIHXtvLm8Gv/4Gz1elqXoj21ae3fthqcTdfTOv12Vb1cytet/bfn7TZvb93qftv7bQsAAACgGQm60jBhyzQ720COPvroGEn77bdfTJs2LVasWNHUQdcZM2bE3nvvHSMpBWsHCrqm98wNN9wQT3ziE3erD+87gJ1Ln5FZZ0QlLRsiKh0RPRuzqGyM6tKR5dt78stpW7/b8iWr3raxOntFpTe4asaK0W3N2OqsrQtnR9w9e6tZW2E7BxjMmxTVMOuUFGgt5+t5EyNaHPQIAADAKFRqKcXYBRFjF7REHL/V7K/39gZfUwD23uq6OuMnjJBKOiFhdRmuWdzSLLSbwrApMNte2hyCbesLyZailN/WLzTb3i8029bbtq1UfbxN13sfv++23uv59r7bfOcEDLP03XY6aePsCaU4Ys62v72t6azOBPvQuursrw+vy/IlXX943dYBQGCwM9Ru7I7YOODfM4P/G2dn8vBrXzh2UzA2BWL7hWa3CM5uG6ZNS5qhtrVc2ny9vNVtqW2ptO1t27l//9s332YGXAAAAGB4CbrSEFJYsYjDDz88Rtqhhx4aV1999U7bpFlB0+ygU6ZMiUaSgpT33nvvgO0OO+ywEdmf3elzMEFX7zug7kOm3dUz8qdgaFpXuvouZ/m60u/2Sr/tm9r33dbZG1hNYdTO6A2vZtUAa9/1/LZ+wdbe7TCQ9e3VQGtaUrh12aTekylDP+mH8bkTU6i1OkNrOst9CrSmWVvTGbEBAACg2eWzvx6cli2/I+xaHnngdVMI9v4sOhZVT0AHjajve+8dh2l3tG1o5GHXTWHYfgHYttIW1zddTtu3F6ZtLUWppd/jpctbXC9teds2623vn47uKPddTrcJmsCok/6/njwmYvKYUhw0Y9vbU+1f3RHV0Ov63vWmIGz1egrtAY2lu1Jdiv/NM7zB251JP9vtKASbQrKbQrO94dz+7dO6pVTKt5X73ZbOM9L3GPnl3nabL2/ZbuvLedu+dv1v793W/zE332fLfdiynb+zAAAAoFYEXWkId9xxR6F2BxxwQIy0Aw88cMDAYXLnnXeO+Myfo/11H8rnMJj7et/B0Fq1rBJ/v6onP2t6+u2glM4Kmp8ZtLou9y4pKJfWfbeXU/ve2/LfHLLNS5ZOxbrpcm9H6Xqld1tf23635e36tdl0//6Xe3oPuqlUL0e63pNVt6frW2zvd73Sf1tWvVyJKPW2zW/vbRPpx+ieiFJad1fbpMt5W6hDK8dH3Dcz4r4Z1fWSqYKtbDZzfMT8SaUtl8mlmDXeDK0AAACwq9LB1+0zItpnlGLy0VuGYLpXRGx8oBp67Xgg23S586GaHhcPDRO0TVO79dR50CSFXVPwNbYOym4K1lZ/N9kUjE1L+n2ld9um6/m6GqytXt76ts3tq/ctbXNb/8spqDPhzvmRlbOIUhZZuRJrro3oGFvZfL+tHj99h7xpnadL+u1r+tqwvO31vm1b37/axneNjE7pvT1lbMSUsaU4cAdB2LWdEQ+vrwZfl63PepeIpWm9IYvlG3YUqAMYWE86vKEnorNnd/8uaozBSPrZckfB2r7b8j87Nl2vBnM3Lf0eY4sl/Z2yzW294d88YLuD+/Xe1teu/33LBe67/aW03ftt2pe87mx+7L793vpyOXqP7el93n23b9q29WPt4HH6Lve9/v6eAwAAaE6CrjSENDPlUIYfh1LRPtNzaLTA4Wh53Zv9+Tfa+w6WLMxi7Df60qTb1/fbayP8Btv31buv4BmNKqWIJVN6g629y+rxtd4ram1S++Yw67zeIOv8SRHzJpZiTKtPQwAAABhu6YDgtukRbdNLMemILW+rdGbR8WAKv0Zs7A3BpgBsCsJunkETaAg9EZWeoQqSDGXopBQz41FbbLn/ivTfEZxmsrSDkOzWodr+27do35fU2E6YdmcB3H5L/+t5UKOvfdq/dJ/e9Zbttn95m9v63T9/uuXt9LWzx+x/vwH2Y7uPsen+fWmUrR6vr31vqGXTtq1v63+9/1fHpR3cr+/xtmqbt99O2x32tUU/pe3eb0ftd9bXFnmcre67xWtasK9t8j1bP/52pPtMbImYOKkU+07efsNKZLFqYzX4unzj5jDs0vURyzb0bt9QDbMBNKt0vvK05H+9FDoJ+WA+NH3g7sj2QrI7u7zDQG3/EG4K+PYP4m4vnLudx+7bn6T/nw8Db6te6Xusvtrf/0+2Qtv6/U2z9bZNj731c9lmW2nH7bazD9s8713ctqP93vT3T35x85Ut/hza+k+0Im0K3q//31j997H/42yxrd9j9r9t622dnRHLKvkfYJvcvTKivb2y0/v1/avs7HkO+vUp+Jy3+fN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      "text/plain": [
       "<Figure size 3840x2640 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1)\n",
    "(original.Is/N).plot(color=colors[0], label='Original Strain $R_0=2.0$', ax=ax)\n",
    "(UK.Is/N).plot(color=colors[1], label='UK Strain $R_0=2.7$', ax=ax)\n",
    "\n",
    "ax.legend()\n",
    "ax.set_xlabel('Days')\n",
    "ax.set_ylabel('Population')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Competition"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But what happens if the two strains are spreading on the same population? For this we need to modify our model by adding parallel compartments for both strains"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "mu = 0.1\n",
    "pD = 0.10\n",
    "rbeta = 0.75\n",
    "pa = 0.4\n",
    "epsilon = 0.4\n",
    "R0 = 2.0\n",
    "\n",
    "betao = R0*mu/(pa*rbeta+(1-pa))\n",
    "betan = (R0+0.7)*mu/(pa*rbeta+(1-pa))\n",
    "\n",
    "SEIIRDStrain = EpiModel()\n",
    "SEIIRDStrain.add_interaction('S', 'Eo', 'Iao', beta_rao=rbeta*betao)\n",
    "SEIIRDStrain.add_interaction('S', 'Eo', 'Iso', betao=betao)\n",
    "SEIIRDStrain.add_spontaneous('Eo', 'Iao', epsilon_ao=epsilon*pa)\n",
    "SEIIRDStrain.add_spontaneous('Eo', 'Iso', epsilon_so=epsilon*(1-pa))\n",
    "SEIIRDStrain.add_spontaneous('Iao', 'R', mu=mu)\n",
    "SEIIRDStrain.add_spontaneous('Iso', 'R', mu_ND=(1-pD)*mu)\n",
    "SEIIRDStrain.add_spontaneous('Iso', 'D', mu_D=pD*mu)\n",
    "\n",
    "SEIIRDStrain.add_interaction('S', 'En', 'Ian', beta_rn=rbeta*betan)\n",
    "SEIIRDStrain.add_interaction('S', 'En', 'Isn', beta_n=betan)\n",
    "SEIIRDStrain.add_spontaneous('En', 'Ian', epsilon_an=epsilon*pa)\n",
    "SEIIRDStrain.add_spontaneous('En', 'Isn', epsilon_sn=epsilon*(1-pa))\n",
    "SEIIRDStrain.add_spontaneous('Ian', 'R', mu=mu)\n",
    "SEIIRDStrain.add_spontaneous('Isn', 'R', mu_ND=(1-pD)*mu)\n",
    "SEIIRDStrain.add_spontaneous('Isn', 'D', mu_D=pD*mu)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So we now have 9 compartments and 14 transitions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Epidemic Model with 9 compartments and 14 transitions:\n",
      "\n",
      "Parameters:\n",
      "  beta_rao : 0.166667\n",
      "  betao : 0.222222\n",
      "  epsilon_ao : 0.160000\n",
      "  epsilon_so : 0.240000\n",
      "  mu : 0.100000\n",
      "  mu_ND : 0.090000\n",
      "  mu_D : 0.010000\n",
      "  beta_rn : 0.225000\n",
      "  beta_n : 0.300000\n",
      "  epsilon_an : 0.160000\n",
      "  epsilon_sn : 0.240000\n",
      "\n",
      "\n",
      "Transitions:\n",
      "  - S + Iao = Eo beta_rao\n",
      "  - S + Iso = Eo betao\n",
      "  - S + Ian = En beta_rn\n",
      "  - S + Isn = En beta_n\n",
      "  - Eo -> Iao epsilon_sn\n",
      "  - Eo -> Iso epsilon_sn\n",
      "  - Iao -> R epsilon_sn\n",
      "  - Iso -> R epsilon_sn\n",
      "  - Iso -> D epsilon_sn\n",
      "  - En -> Ian epsilon_sn\n",
      "  - En -> Isn epsilon_sn\n",
      "  - Ian -> R epsilon_sn\n",
      "  - Isn -> R epsilon_sn\n",
      "  - Isn -> D epsilon_sn\n",
      "\n",
      "# R0=2.70\n"
     ]
    }
   ],
   "source": [
    "print(SEIIRDStrain)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And integrating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "N = 100000\n",
    "I0o = 10\n",
    "I0n = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "SEIIRDStrain.integrate(365, S=N-I0o-I0n, Iao=0, Iso=I0o, Eo=0, R=0, D=0, Ian=0, Isn=I0n, En=0)\n",
    "compete = SEIIRDStrain.values_.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We find that the strain with the higher $R_0$ \"chokes out\" the original strain by reducing the pool of susceptibles "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Competing Strains')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3840x2640 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = (compete.Iso/N).plot(label='Original Strain $R_0=2.0$')\n",
    "(compete.Isn/N).plot(ax=ax, label='UK Strain $R_0=2.7$')\n",
    "ax.legend()\n",
    "ax.set_xlabel('Days')\n",
    "ax.set_ylabel('Population')\n",
    "ax.set_title('Competing Strains')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What if the new strain arrives when the epidemic is already on it's way so that the original strain has a head start?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "[S, Ia, Is, E, R, D] = original.loc[50].values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We initialize our population with the compartments at time 50 from the original epidemic and just add 10 new infectious"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "SEIIRDStrain.integrate(315, S=S-I0n, Iao=Ia, Iso=Is, Eo=E, R=R, D=D,\n",
    "                       Ian=0, Isn=I0n, En=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "introduction = original.iloc[:49].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "SEIIRDStrain.values_.index += 49"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Rename the compartments so that they match"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "introduction.rename(columns={'Ia':'Iao', 'Is': 'Iso', 'E':'Eo'}, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And combine the two results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "introduction = pd.concat([introduction, SEIIRDStrain.values_]).fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x10fcc5bd0>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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c41pne8T9m/cvg9p6I7ZYvDrxdfMlEXOXRLT3RVMoRDFmLN4mW3b659Grk19nPZIlvT41kPy6cG5Kfu2sd3MZQVffynhy5cPZMpIJLZMHEmL7k19XJccOJMhOaZsRU9tnxJS2mTGpdWoUC+N3VmgAAAAAaHYSXRlTUhLfFVdcMWK57bbbLl75yldWrR0f/vCHR0w4TL7//e+Pm4TD8847L/dnUy2vec1r4mMf+1g8+uijGyyXviMpKXfrrbeuSL2+dwAwNi3t6ohHli2K+SsWxFMdC2Nh58JY0rUwVvQsis6+hdFdWhilSEmsi6NQWM+dU5JY66JUmhWTW/aO7abtEwdssU8csOXO0day4e7rltMK8bEjJ8bHrnh7LOjdMWZP//r6k5PXo1xujaUrXhZLlp8a5ZgY204vxFuf0RJPm+vGGRpzdtbexRFd88vR9Vg5uh/rT2bteiSyx804Q+uGTN69P7l15rOK0TbTiR0AAAAaQaFQiK2mRWw1rSWO3rF/X3dfOe5fXI67FvQnvt69sBSPLk1Jj+NbT2vEw3P6l1XKEbNW9Ce9Dl02WxZRLDdJ8uuibbNlpzuPyfaVCn2xdOYjsWCLf8aCuXdn64Vz7jPz6xjW1dcRXSs74qmVIw+8XoxiTE6Jr1ny68yY0jY9pral9cxsX39S7OB2//OtxbaaHAcAAAAAMHoSXRlTfvSjH2U3847kHe94R7S2Vu/rfcIJJ8Ruu+0W//znPzdY7vLLL4/58+fHlltuGWNZSiy98sorRyy35557xnOf+9yqtaOtrS37t/3oRz+6wXKlUin7rnzwgx+sSL2+dwDQGFKMX97TGfOXL4knOhbFUx2LY2HngljctSiW9yyMlb0peXVR9JUXRTkWRbE4wo0txez/qbNyuRiF8s4xa8KesfOMPeOgrfaKXWdtGcXixv/r7DirGB85vDU+efXz4/GF28bcmZ+KlpYluV67smv/WLj07dHbt220t0S8fK+WeNHuxWhrkRBH/ZR7y9H9VET3k+XoTgmtA0mtXfMje1wyecWIya0zDynGjEOLMWFL/y0DAADAWNDeUojdNkvL6n0dPeW4Z2E57kqJrwtKWQLsUx0x/hUiFk3tX+4cMsZzS1/EnGUDia8Ds79uvjRiRhN8JsVyS8xctF227HzHcatmfl0+/YlYNOe+WLTZvf3rOffF0pmPRqxvkEvGpFL6t+5J14QWReT8vqcZYye3TovJbdNicuv0Vesp2Trtn77O59ta2qt9OAAAAADAGiS6Mqb8+Mc/HrFMuiG+2rNZppFlTzvttPi3f/u3DZbr6+uLCy+8MN797nfHWJaOISWWjCR9JtWW6vjXf/3XERNP03elUomuvncAUB29pb5Y0LEsnuhYGk91LIoFnUticefiWNa9JFb0Lo7O3iXRVVoSvaUlUYolUSikpXvDb1pIMTNb0cCztU4s7h7zpu4Ve222Vxwyb/eYNmFSxd5/z82L8f5ntcbnr9k7Hn3q2zFz2nkxddIl6521t6d3m1i8/DXR0XlE9gXab8tCvOXA1myGWKi2Ulc5ehZGdC8oR09KZn0iovuJcnQ9UY7ux/ufi5G7YgwqRkzduxAzDy3GjIOL0Tbbf8cAAAAwHkxuK8Q+W6QlPWrJ9i3uTEmv/TO+9s/8Wo6lXdEU+loiHp/Zv8T2q/dP6F496+vcpf1Lmv11+srxP/PrtKVbZst29z5z1f6e1s5YMvuBVYmvaVk4597onri8ru2lDjPG9nXEoq7HN+p1bcUJ60iEXTMhtv/5Sa1TY2LLlJjUOiUmtk4xiywAAAAAbCKJroypWUVvueWWEcsddthhsfXWQ4YzrZJXvvKVIyYcJhdffPGYTzhMx5DHqaeeWvW2bLfddvGsZz0rrr322g2Wu+mmmyoyq6nvHQDkS1hd3NkRT61cGgtXLo1FnctiadfSWNq9LFb0LIuVvUujs3dZdJeWRW95WfSVl0U5lkahkJYcGVxmXh2zSqXJ0VbYLeZO2j12nrFHHLDFHrHDzLmbNFvrxnjG1sV476Et8dXrZ8TCpe+JZR0nxaT2v8SE9n9ES/Gp6CvNiL7SZtHReVR0dj89uxVqxoSINxzQEodtV8wGGIHRSAPzlDoGElgXRvSk9YLBdTm6B7b73FM3aoX2iGn79c/cOv2gYrRKUgcAAICmMHNiIQ7aOi3FVb/HpFle719cHlhK2Xr+sjTjZ3Poao94aG7/MlR7T8Scpf2zwA6uN1saMXt5RMs4/nDaeifGnCd2z5ZB5ShHx9SnYtFmq5Nf+2d/fSRKLb11bS+NpafUFUu60/LURr+2rdieJb6mpNcsCTZbT4mJLVNXJcNm+zZQpqXolj4AAAAAmo9fxRgzLrvsslzlTjzxxKiFXXbZJXbddde46667NljuD3/4Q3R3d0d7e3uMRV1dXfHHP/5xxHJPe9rTYscdd6xJm0444YQRE10HvzOjnWXW9w6AZpBmbl/R0xULO1fE4s7lsbhreSztXh7Lu5bH8p4V0dG7PDqzZUV0l1ZET2l59JaWRymWRjmWRaGwPF/CamLG1XGd1Npa2DlmTdg5dpi+ezx986fF0+ZsHa3F/hkWau2w7Vti7pRC/N9remNR5w7R07tDRMfa5YqFiGN3KsZrnt4SU9t9M9mwcqk/ObVncTl6l0T0LhlYLy5H96qE1v6k1lJnvVs7frVvHjH9wGJMP6CYzeBanOC/XQAAAGh2afC6uVMi+03wGdn4xP2/S67sKceDSwaTX/uXBxaXo7OJchq72yIe3ax/GapYipi1fEgC7GAS7LKIiT0xLhWiEFOWz82WbR44eNX+UrE3lk1/LJbMfiiWzH4wFs/qXy+Z9XD0to/zKXGpuJ5Sd7Ys61m0ye+RZpQdmgyblgktkwaWydl6YuvkaE/rgceD+ye0Djzf0v98Srw1wCcAAAAAY4FEV8aMvAmHxx13XNXbMrSukRIOOzo6sqTMo48+Osai1PaVK1c23Of+0Y9+dMRyl156ac0SXX3vAKiH7r7eWNq1MpZ2dsTS7o5Y1tMRy7o7oqO7I1b0dsTK3o7o7F0ZXX0d0dW3Mnr6OqK33BE9pRXRV+6IciyPcqyIQiEtG3lXT7E/WdVl8eZUKm0eE4s7xdxJu8QOM3aJfebuErvO2rLqM7VurN3nFOMbL2iLax4sxf/e1Rv3L+qNnmiLQpRiWmFlPGunyXHS09pji6m+yc0qzfRR7o5VSas9Q5NX03pxRM/Qx0vTfwD1bnUTaomYumchS2xNCa4Ttu6/eRUAAABgJJPaCrH7nLSs3lcql+OJ5TFs5te0PLEimkqpGLFgev9yZ5YcPKAcMbWzP+l11rL+mV+HLm19Me4US60xY/G22RL3PmutGWAXZ0mvA8mvKRl21oPROXlJXdvM+J9Rtqe7K5bFwlG/VzGKA8mvgwmx/UmxE1snDUmUTUmxE/uX4sRc263FNr/TAgAAAFBREl0ZM/LM4DljxozYf//9o1aOOuqoOPfcc0csN5YTDvN87oOfRa0cdNBBMXXq1Fi+fHlF2j7a9/C9AyDPjKkdPd2xoqczlnV3xorerujo7oyOns5Y2dcZnT2d0dnXGSt7O7OE1M7elJjaEd0pObXcEb2llVliaqm8Mt1SEeVYGYVCWro2rUEDGaoSVRlJudwShfJ2MbV159hySkpm3SWevvnOscXUGTFWTGgtxLE7tcRhW/fGxRdfFt3RGm3RF8VCOY7f9/iYYCbI8TPTakdks632LS9H78C6b1ms3l6etvvX2fay/u1yE83eMZZM2Cpi6r7FmPb0YkzbtxAtk/23CgAAAFRGsVCILadFbDmtEIduu3rwvhXd/bO/Pry0f3lkaTkeWlKOJzuiuRQilk/qX+7ffI3nyhHTVvYnvKbZYDcbWA8mwbb3jt8ZYLd+8MBhz3VOXLIq6XXx7Idi2cxHY+mMR2L5jPlRahlnHwRjWilKsbJ3ebZUUiGKQxJfJ2RJs6sTYicMbA/sS48HEmVbi+3ZLLNp1tq2lgkD2wOPs3392/3l+p+XUAsAAADQHCS6MiYsWbIk7rvvvhHLpWTDWv64mRIu87jppptirLrxxhtzlTvwwOEXdaopzRSW/q3/+Mc/brDcvffeG0uXLo3p06dvUj2+dwDjP/m0q683VvZ2Z0tKRO3Mtruis7crunq7o7PUna27+7qiq687uvo6s+3utC51Rm8aTbmvM/rKXdFb7ozS4BJdUY7OiOiKKHRGIbqiUCiPrsGSU6myUmlGtBa2j1kTdoptpu4cT9tsl9h38x1iUtuEGC/Sn2wTwg1GjTijat/KyBJVSx3l4dspeXXl6v2l9HhomZXl6FsR2ZJusmPsap0VMW3fYkzdp5Ct2+eIdgAAAEBtTWkvxNPmpmX4/s7e/qTXhwcSXweTYB9bnmaHjeZSiFg2uX95YB1JsGkm2FVJsGlG2BURMweWKZs4dmejmtg5IyY+OiO2eHTvYftLhb5YMe3JWDrzkVg249FYOvNRSbCMS+V0RbSvf/DeahtMhF1Xkmza176BJNlUrlBqicfa7oxitEax3BrFaIm7l9wckyZMidZCWzY77aql0D7scbHQUvXjAwAAAKCfRFfGTLJlugF6JAcccEDU0k477RSzZs2KRYsWNXWi62abbRbbb7991FJKrB0p0TV9Z26++eY44ogjNqkO3zuA6iSWdvX2RFdfT3QObHf39T9O6+5Sb/QMrLt7e6K31BM9pfQ4bfeuetyXtsv9z/eVe6JUTs91Z0up3B195bTuilKkdU+UU8JpdEc5egaST7ujED1RKJQqe5CSURkDSqXNor2wXcyYsH1sMXn72HHG9rHnnO1j3rRZ9W4aDajcV45ST2TJqKXuwXW5f7snotQVUepM63L0da7e7l8PPO4sDynX/zgrO7AvKnwqZmxomR4x9WmFmLpPmrG1GBO2TsnooicAAADQeCa2FmLn2WkZvr+nLyW7luPhJdGfBDuQDPvYsnJ090XzGTIT7INrJAsnbb2rk17XtUxKl3DGgWK5JaYt3TJbIoYPGC4JFjZNT6k7W0Zl8vCHt/3917leVkzpsVlCbVu0ZImwg0mwAwmx60iUbRn2eEjZIeVTmZZCa/9STOuWaCmk/a1r7G+N1mJrFNM6e75lre1iYfXs5AAAAABjmURXxoSUrJjH3nsPHymzFvbcc8+49tprN1gmzQqaZgedMWNGjCUpkfLBBx8csdxee+1Vk/ZsSp2jSXT1vYP66C31xcqe7mgttkRrsRgthWI2k/N4TPrsK5eit1SKUpSjr9QXpVI5esulbLuvnPal50rR11fK9mfbpf7tcvb6VK4U3X29/e/V1xe9WcJnX/YeKTE0lRlcZ/sG1v2v7Y1S9rh34L37H2dLpPWQx+W+1MpsX3lwO1Zvl9P+SAml6S6E/u0Y2E5LoZCSSmt8cX4wV2Yg8XToLmgGpdIWMaG4fcxs3y62mrp97Dxz+9hrzvax2eRp0dRKhSiUClEuliPHmCZVkQ2mUooopwTPtO5bx3Zap6U3otRbztarlpR4uupxOUpDnxu29L8uS1Rd13MpUbVnHQmsaXsguTWVhUpo3yJiytOKWXJrWktsBQAAAMa6tpZCbDcjLcP3l8rlWNgRWRJsSnqdv7wcj2bryLabMgk2XTVqjXhyRv+yLhO6B5JeOyJmLh9Yr4iYkZaVEZNGmeM2FpJgV05ZGMunPx7Lp8+PZdPnr9pO646pT0W5aNRAqLV0Hb271JktjSol42ZJsmskyK7aHnxc3HACbf97tESxOLBvYDtbD1nW/TiVK26w3OC+VPe69q/rsesIAAAA0FwkujIm3H333bnK7bLLLlFru+6664gJh8k999xT85k/x/vnXsljGM1rfe+gsm5/8qE47x9vGLavXG7JLs+UoyUi2+5/3L/u3y4MbPevhybGDs1iWn9GU3m95db3mrS/PyupnK1XP157KQ/MHLp6KRTqlF1VaWtkkEoohdoqlSZFMbaOSS3zYsaErWPrqdv1J7TO3S6mT1hjaOomnY20455yLLulHEtvjdj6/qOipWNiFMr9Z6k7LkghozsKrRFpsOvBdRZGRnMiS6f48hoJrGusYVxriZi0fSGm7J6SWvsTW9s389cBAAAA0ByKhULMmRIxZ0oh9tliHUmwKyNLgJUEO1xXe8TjaZm17ufbevoTXqd3RMzoWMd6ZURb39hOgp2yfG62bPHo2oNtl4q9sWLqk8MSYVdMfzyWDTxeOXVhXdoN1F82ZHa5K3rKXf07xvC5cE2FcpbGu/6lMLid7hlJibb99470r/sfZ89l5dJ6YF+2v2XY4/7tliGPh24Xo6U4fF8asD0rXxz6fNrfsvr54tB612jXYB1rPC6k/8va178urHOdvUu2LmxgXdzA8/3HP3R///sCAABAPUl0ZUxIM1NWMvmxkvLWmY5hrCUcjpfPvdmPf6x97yDNRrqmQiHt64tCmiG0Sr+rj+Zt/dQPVFOpNDmKMS8mtWwdMyfMiy0mbx3bzdgmdp21dcybOmtczno9Gl3zU2JrKVuW31aOvhWDzxSiNSat/YLSwMylNW4njCftm0dM3rUYk3ct9C87FaI4wV9IAAAAAOtMgp0cMWfyhpNgn1hRjseXl+PJFZFtpyU918y/Y/a0RTyVlunrKVDun/V1aPLr4HZKgp2akmRXRrSO0YEIi6XWmLZ0q2xZl76W7lg+7YnomPpkrJj2ZJYUm60HtjumPRU97R01bzfAaJQLpeiLtPTkfMEaazZOeSDhtTyQUFvuHx141eNh28WB8qsfp8GGV22vWbY/9XZ4+XWuV79Hkrb678opZH9HZXVmCbn9pVaXWPs1gwm8g3uiMNimWPs9srKDr+4vM/Q9smfX2B4svTpJePX26vJD3nNVe/rrz9qbisXadaT/T5/XsPfIEp1jdX2FtY9xsMzQ5wYTmFcnMqd9A1sD7zP8+f6/WQcat+r9Vh3vsPKr9w9srGr/6s934F9wdaXrL7+qnqHvOVjf4DNDvhcDL11nmwbLD9axjrYMP/5Vn84ar1vdzsK62rJmnev4rHp6eqK3ryvKQz7jFSuXR2+pe92f6xqXWYcloa/xWQ37/IccxxovWGfZdT5fyP9ayfEAAFSDRFfGhDwJh+3t7bHFFmtcCaqBbbbZJle5e++9N8aavIme2267bdTalltuGa2trdHb21u1z933Duqj+6EN/3cNMB61dk+JKcvnxdTl82L6inkxs2NezOrYOmZ3bh1Te2es42JDRLod5e5sSOZxNCzzKPUuLUf34/VuBYxvrbMiS2SdtGMhJu9WjMm7FKJtpouYAAAAAJVMgl2Xnr5yLOjoT3x9fEVKgk0JsKsTYRc1eSJs+hl95YT+Zf56ZoVNH9DE7ohpncOTX4eu03NTO9MMqzGmtPS1x4zF22TL+nS3rxhIgH1iWALsqqTYqU9GqTVnMhkA40+hHNn/FcboqBCNQsI16zJ7+MNrbz43xr3ykATcIdsjlR0xIXeN/7bWKjtCXRsuv2Y7NtzOtcoPa9uGy659zGu3NHfZkdq1gc9vxGToEcpvvNHfWzDi9ylPVaM+R1fiHonGuM8i9+e5/ncYfSNG04ZC5eLuuu7P27TGjEIVj6NcHv7mN/7+og2+y6iM+ntVGYVxchwbMql7Xnz4lR+vdzOgoiS6MiY88MADI5bZfPPN6zJCUEq4rNQxNJq8bc77GVRSmrls7ty58dhjj1Xtc/e9g/ro7ZSwBYw/E1ZOjynLNo+pS7foX5ZtHlNWbW8R7d1T1vvaldn/ugoG1F77FhGTdirE5B2L2TotkloBAAAA6qOtpRBbTovYctr6E2Gf6ohVSbBPdfQnxmbrlf3bnc0+3mwhonNC//LkjA0UK0VM6VojCbYzYspAEuzQ7bE0Q2y6FtG+cErMWrjDOp9PyU1dk5ZEx+SFsXLqwuiYsiBbVk4Zsj11YaycvDDKxTF04AAA1N6QrM/y8AzQEblDBgDyKS0yYBnjj0RXGt6KFSti5cr+2/sbLdlyY+p98sknY6zJ2+Z6fvYjJboOfn8mTZq0Ue/tewf101uW6AqMPRM7ZvQnrg4msy7bYkgi6+bR1jO53k0EWK+WKRETtytky6S03r5/aZ0iqRUAAABgLCXCbjUtYqtp65+5o6NnMPE1YkGWCNufAJsSYdP+lCjb9Mmw6bMqRiyf1L9suGDExJ7hCbBrJsKuWnc1/iyxaaaTiStnZkss2Gm95UqFvv6E2FVJsP2JsCtTMuzUBbFy8qJs6Zy8OEotvlAAAAAAQD4SXWl4CxYsyFVuzpw5UQ9pVtFKHkcjGU+f/TbbbNO0xw5jTals9F+gcRRKxZjYMSumLJ8Tk7Nls5iyfG5MXrHZwOP+fa19E+rdVIARFSdFTNymEBO2HkhoHVjaNosoFCS1AgAAAIxn6fefKe0RU9oLsf3M9Zfr6Fk9G+yileVY1Dm4Lseilav3dRu7tn+G2Pb+ZcH0EYqWBpJiuyImD1mmbGC7pUEvmxbLLTGpY3a2xAbG3k4zxHZPWD6Q9Nqf/Lpy8uIh2/3JsJJiAQAAAIBEoisNb+HChbnKTZs2reptGU29eY+jkYynz35jE13H07HDWNMXrooDtdHWPTkmrZiV3YgxedmcLHl1dUJr/+NJK2ZnN2wAjCVtcyImbt2f0Jqtt+lft86S0AoAAADAhk1uK8R2M9Ky/jKDs8OmhNfFQ5NghyXD9m+v6Kll6xt7ltiVE/qXfC+IaO9dnfyarTvXSIjtHp4Ym8o32gyxE7qmZUss2m6DZddMiu2ctGTV0jVp6ertiav3l1tcVwYAAACA8USiKw0vb6Le9OkjDI9ZJVOnTo1isRilUmncJRzmaXNLS0tMnjw56iHvv/mmfPa+d1A/feW+bPRjgE1R7GuNSR2zYmKWwNqfxNqfzDqwrEgjjM/KZmlt651Y7+YCbJpCZLOwTtiqEBO2LGTr9mwd2ePiBH9MAQAAAFCL2WEjtpm+4d+ievrKsaw7YklnOZZ0RizpGr5eOuTxYjPFrlaI6G7rXxZNzfeS1t6ISd39S5o9NtvuWse+tN09fP9YSoodTIztae8YSHpdPCwZdjAhtmvisuieuCy6Ji6Prgn922aNBQAAAIDGJdGVhtfR0ZE78a9eUt1Lly6tyHE0kjxtrufnnndW00357H3vNl1Kvu3q6qp5vTS27u7uXPuS3r4ef6EAw0xYOS0mrJwREweWCZ2rt9MymLya1u1dU7ObIQDGupap5WibG6uXzSPah2wX21Op8lqvy+5J8+c4jOk+EQBUmjgEQL2JRUwpRkyZHDEvxxjanb0p+bV/WTKwTomyy7uHr5d19W8v74kolV0XSHpbI5alZSPHKi+UhifBrisZdugyYSA5dkJPRHudEpPTtaD27inZMn3JvFyvScmxva1dA8mv/Uv3hPVtL1+dKDthWfS2d1b9mAAAAAA2lrwNKmGkCfhqSRoJDa+nJ9/QkW1tbVVvy2jqHosX6vJ89o3+uW/qZ+97t+kWLVoUN998c83rZey54oor1rn/4TRU8/Y1bw5QI23dk6O9c2pM6JzWvwwmrHbOGJ7MunJ6TFw5MytTLLfUu9kAFVVq7Y2+KZ3RO7kz+gaW3ilp3RW9U1ZG79SVUW5fY2aB9FvS4wMLMK77RABQC+IQAPUmFrEx0phvsweWYVoiysWI7miNrnJ7dEVb/7rcFp3Rvx7c311OS2t0D25Ha5SjWJ8DajDpM1w5oX/ZWMVSf8LrYOLr4DrbHpIQu64yg+u2vtolx7b1Toy25RNjyvK5G/XavpbuVcmvKfF1MAm2e8KK6G5fET2r1h3ZOpVNM84OPl9qbYBpcwEAAIDxpRxxySWX1LsVjAP77bdfzJw5MxqBRFcaXt5EvXomHLa2tlYscXKsffaN/rlv6mfvewf1U0pDBgMNrVAqZgmrKQm1PSWrdk1bvb2ex/3lpkaxpAsCjG99E7r7E1cHk1indK2V0Fpu6013VQEAAAAAo1QoREy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      "text/plain": [
       "<Figure size 3840x2640 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = (introduction.Iso/N).plot(label='Original Strain')\n",
    "((introduction.Isn)/N).plot(ax=ax, label='UK Strain')\n",
    "((introduction.Iso+introduction.Isn)/N).plot(ax=ax, label='Total (Original + UK)')\n",
    "ax.legend()\n",
    "ax.set_xlabel('Days')\n",
    "ax.set_ylabel('Population')\n",
    "ax.set_title('New Strain Introduced')\n",
    "ax.axvline(x=50, linestyle=':', color=colors[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center>\n",
    "     <img src=\"data/D4Sci_logo_full.png\" alt=\"Data For Science, Inc\" align=\"center\" border=\"0\" width=300px> \n",
    "</center>"
   ]
  }
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