DataMining.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import covsirphy as cs\n",
    "from pprint import pprint"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cases Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Retrieving datasets from COVID-19 Data Hub https://covid19datahub.io/\n",
      "\tPlease set verbose=2 to see the detailed citation list.\n",
      "Retrieving COVID-19 dataset in Japan from https://github.com/lisphilar/covid19-sir/data/japan\n"
     ]
    }
   ],
   "source": [
    "data_loader = cs.DataLoader(\"input\")\n",
    "jhu_data_new = data_loader.jhu()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "print(type(jhu_data))"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "JHUdf = jhu_data.subset(country=\"United States\", end_date=\"22Mar2021\")\n",
    "JHUdf.to_csv(\"test.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_loader = cs.DataLoader(\"test\")\n",
    "jhu_data = data_loader.jhu(basename=\"test.csv\",local_file=\"test.csv\")"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "jhu_data.total()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Infected</th>\n",
       "      <th>Fatal</th>\n",
       "      <th>Recovered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-02-09</td>\n",
       "      <td>12</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-02-10</td>\n",
       "      <td>12</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-02-11</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-02-12</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>14</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>403</th>\n",
       "      <td>2021-03-18</td>\n",
       "      <td>29670983</td>\n",
       "      <td>22832433</td>\n",
       "      <td>540468</td>\n",
       "      <td>6298082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>2021-03-19</td>\n",
       "      <td>29732612</td>\n",
       "      <td>22892916</td>\n",
       "      <td>541614</td>\n",
       "      <td>6298082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405</th>\n",
       "      <td>2021-03-20</td>\n",
       "      <td>29787986</td>\n",
       "      <td>22947548</td>\n",
       "      <td>542356</td>\n",
       "      <td>6298082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>406</th>\n",
       "      <td>2021-03-21</td>\n",
       "      <td>29821754</td>\n",
       "      <td>22980877</td>\n",
       "      <td>542795</td>\n",
       "      <td>6298082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>2021-03-22</td>\n",
       "      <td>29873347</td>\n",
       "      <td>23031752</td>\n",
       "      <td>543513</td>\n",
       "      <td>6298082</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>408 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date  Confirmed  Infected   Fatal  Recovered\n",
       "0   2020-02-09         12         9       0          3\n",
       "1   2020-02-10         12         9       0          3\n",
       "2   2020-02-11         13        10       0          3\n",
       "3   2020-02-12         13        10       0          3\n",
       "4   2020-02-13         14        11       0          3\n",
       "..         ...        ...       ...     ...        ...\n",
       "403 2021-03-18   29670983  22832433  540468    6298082\n",
       "404 2021-03-19   29732612  22892916  541614    6298082\n",
       "405 2021-03-20   29787986  22947548  542356    6298082\n",
       "406 2021-03-21   29821754  22980877  542795    6298082\n",
       "407 2021-03-22   29873347  23031752  543513    6298082\n",
       "\n",
       "[408 rows x 5 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jhu_data.subset(\"USA\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df, complement = jhu_data.records(\"USA\")\n",
    "display(df.tail())\n",
    "# Show details of complement\n",
    "print(complement)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2021 = df.iloc[327:, ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df = jhu_data.cleaned()\n",
    "jhu_first_date, jhu_last_date = df[\"Date\"].min(), df[\"Date\"].max()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "print(jhu_first_date, jhu_last_date)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Population Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "326687501"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_data = data_loader.population()\n",
    "population_data.value(\"USA\", province=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_cols = [\"Infected\", \"Fatal\", \"Recovered\"]\n",
    "rate_cols = [\"Fatal per Confirmed\", \"Recovered per Confirmed\", \"Fatal per (Fatal or Recovered)\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_df = jhu_data.total()\n",
    "total_df = total_df.loc[total_df.index <= jhu_last_date, :]\n",
    "total_df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "population_data = loader.population()\n",
    "scenario = sir.Scenario(jhu_data, population_data, country=\"USA\")\n",
    "_ = scenario.records(variables=\"CFR\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "scenario.trend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Vaccine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "URL = \"https://github.com/owid/covid-19-data/blob/master/public/data/vaccinations/us_state_vaccinations.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [],
   "source": [
    "vaccine_data = pd.read_csv(\"us_state_vaccinations.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "vaccine_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SIR-F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "example_data = cs.ExampleData(tau=1440, start_date=\"01Jan2021\")\n",
    "# No records has been registered\n",
    "example_data.cleaned()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cs.SIRF.EXAMPLE[\"population\"]= 326687501\n",
    "cs.SIRF.EXAMPLE[\"y0_dict\"][\"Fatal\"] = 354232\n",
    "cs.SIRF.EXAMPLE[\"y0_dict\"][\"Infected\"] = 11581576\n",
    "cs.SIRF.EXAMPLE[\"y0_dict\"][\"Susceptible\"] = 312434510\n",
    "cs.SIRF.EXAMPLE[\"y0_dict\"][\"Recovered\"] = 8317183"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Model name\n",
    "print(cs.SIRF.NAME)\n",
    "# Example parameter values\n",
    "pprint(cs.SIRF.EXAMPLE, compact=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = cs.SIRF\n",
    "area = {\"country\": \"USA\", \"province\": model.NAME}\n",
    "# Add records with SIR model\n",
    "example_data.add(model, **area)\n",
    "# Records with model variables\n",
    "df = example_data.specialized(model, **area)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cs.line_plot(\n",
    "    df.set_index(\"Date\"),\n",
    "    title=f\"Example data of {model.NAME} model\",\n",
    "    y_integer=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scenario"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "326687501"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_data = data_loader.population()\n",
    "population_data.value(\"United States\", province=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "preset_dict = cs.SIRF.EXAMPLE[\"param_dict\"]\n",
    "preset_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = cs.SIRF\n",
    "area = {\"country\": \"USA\", \"province\": model.NAME}\n",
    "test_data = cs.ExampleData(tau=1440, start_date=\"01Jan2021\")\n",
    "# No records has been registered\n",
    "test_data.cleaned()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pprint(cs.SIRF.EXAMPLE, compact=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "_dict = {'param_dict': {'kappa': 0.005, 'rho': 0.2, 'sigma': 0.075, 'theta': 0.002},\n",
    " 'population': 326687501,\n",
    " 'step_n': 180,\n",
    " 'y0_dict': {'Fatal': 354232,\n",
    "             'Infected': 11581576,\n",
    "             'Recovered': 8317183,\n",
    "             'Susceptible': 312434510}}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_data.add(jhu_data.records(\"USA\"), step_n=110, **area)\n",
    "# Register population value\n",
    "population_data.update(value=population_data.value(\"United States\", province=None), **area)\n",
    "population_data.value(**area)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "df = test_data.specialized(model, **area)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "snl = cs.Scenario(tau=1440, **area)\n",
    "snl.register(test_data, population_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "record_df = snl.records()\n",
    "display(record_df.head())\n",
    "display(record_df.tail())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set 0th phase from 02Jan2020 to 31Jan2020 with preset parameter values\n",
    "snl.clear(include_past=True)\n",
    "snl.add(end_date=\"21Apr2021\", model=cs.SIRF, **preset_dict)\n",
    "# Show summary\n",
    "snl.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rho_vac = snl.get(\"rho\", phase=\"0th\") * 0.8\n",
    "kappa_vac = snl.get(\"kappa\", phase=\"0th\") * 0.6\n",
    "sigma_vac = snl.get(\"sigma\", phase=\"0th\") * 1.2\n",
    "snl.add(end_date=\"31Dec2021\",  rho=rho_vac, kappa=kappa_vac, sigma=sigma_vac)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = snl.history(target=\"Infected\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "snl.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TEST"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Infected</th>\n",
       "      <th>Fatal</th>\n",
       "      <th>Recovered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>403</th>\n",
       "      <td>2021-03-18</td>\n",
       "      <td>15044130</td>\n",
       "      <td>540468</td>\n",
       "      <td>14086385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>2021-03-19</td>\n",
       "      <td>15051341</td>\n",
       "      <td>541614</td>\n",
       "      <td>14139657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405</th>\n",
       "      <td>2021-03-20</td>\n",
       "      <td>15053300</td>\n",
       "      <td>542356</td>\n",
       "      <td>14192330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>406</th>\n",
       "      <td>2021-03-21</td>\n",
       "      <td>15034554</td>\n",
       "      <td>542795</td>\n",
       "      <td>14244405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>2021-03-22</td>\n",
       "      <td>15033952</td>\n",
       "      <td>543513</td>\n",
       "      <td>14295882</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date  Infected   Fatal  Recovered\n",
       "403 2021-03-18  15044130  540468   14086385\n",
       "404 2021-03-19  15051341  541614   14139657\n",
       "405 2021-03-20  15053300  542356   14192330\n",
       "406 2021-03-21  15034554  542795   14244405\n",
       "407 2021-03-22  15033952  543513   14295882"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_scenario = cs.Scenario(country=\"United States\")\n",
    "us_scenario.register(jhu_data, population_data)\n",
    "us_scenario.records().tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = us_scenario.trend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Type</th>\n",
       "      <th>Start</th>\n",
       "      <th>End</th>\n",
       "      <th>Population</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0th</th>\n",
       "      <td>Past</td>\n",
       "      <td>09Feb2020</td>\n",
       "      <td>16Mar2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1st</th>\n",
       "      <td>Past</td>\n",
       "      <td>17Mar2020</td>\n",
       "      <td>30Mar2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2nd</th>\n",
       "      <td>Past</td>\n",
       "      <td>31Mar2020</td>\n",
       "      <td>10Apr2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3rd</th>\n",
       "      <td>Past</td>\n",
       "      <td>11Apr2020</td>\n",
       "      <td>22Apr2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4th</th>\n",
       "      <td>Past</td>\n",
       "      <td>23Apr2020</td>\n",
       "      <td>03May2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5th</th>\n",
       "      <td>Past</td>\n",
       "      <td>04May2020</td>\n",
       "      <td>14May2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6th</th>\n",
       "      <td>Past</td>\n",
       "      <td>15May2020</td>\n",
       "      <td>22May2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7th</th>\n",
       "      <td>Past</td>\n",
       "      <td>23May2020</td>\n",
       "      <td>31May2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8th</th>\n",
       "      <td>Past</td>\n",
       "      <td>01Jun2020</td>\n",
       "      <td>08Jun2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9th</th>\n",
       "      <td>Past</td>\n",
       "      <td>09Jun2020</td>\n",
       "      <td>16Jun2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10th</th>\n",
       "      <td>Past</td>\n",
       "      <td>17Jun2020</td>\n",
       "      <td>28Jun2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11th</th>\n",
       "      <td>Past</td>\n",
       "      <td>29Jun2020</td>\n",
       "      <td>10Jul2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12th</th>\n",
       "      <td>Past</td>\n",
       "      <td>11Jul2020</td>\n",
       "      <td>18Jul2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13th</th>\n",
       "      <td>Past</td>\n",
       "      <td>19Jul2020</td>\n",
       "      <td>26Jul2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14th</th>\n",
       "      <td>Past</td>\n",
       "      <td>27Jul2020</td>\n",
       "      <td>10Aug2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15th</th>\n",
       "      <td>Past</td>\n",
       "      <td>11Aug2020</td>\n",
       "      <td>18Aug2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16th</th>\n",
       "      <td>Past</td>\n",
       "      <td>19Aug2020</td>\n",
       "      <td>26Aug2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17th</th>\n",
       "      <td>Past</td>\n",
       "      <td>27Aug2020</td>\n",
       "      <td>10Sep2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18th</th>\n",
       "      <td>Past</td>\n",
       "      <td>11Sep2020</td>\n",
       "      <td>25Sep2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19th</th>\n",
       "      <td>Past</td>\n",
       "      <td>26Sep2020</td>\n",
       "      <td>04Oct2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20th</th>\n",
       "      <td>Past</td>\n",
       "      <td>05Oct2020</td>\n",
       "      <td>12Oct2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21st</th>\n",
       "      <td>Past</td>\n",
       "      <td>13Oct2020</td>\n",
       "      <td>27Oct2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22nd</th>\n",
       "      <td>Past</td>\n",
       "      <td>28Oct2020</td>\n",
       "      <td>09Nov2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23rd</th>\n",
       "      <td>Past</td>\n",
       "      <td>10Nov2020</td>\n",
       "      <td>17Nov2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24th</th>\n",
       "      <td>Past</td>\n",
       "      <td>18Nov2020</td>\n",
       "      <td>25Nov2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25th</th>\n",
       "      <td>Past</td>\n",
       "      <td>26Nov2020</td>\n",
       "      <td>03Dec2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26th</th>\n",
       "      <td>Past</td>\n",
       "      <td>04Dec2020</td>\n",
       "      <td>12Dec2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27th</th>\n",
       "      <td>Past</td>\n",
       "      <td>13Dec2020</td>\n",
       "      <td>21Dec2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28th</th>\n",
       "      <td>Past</td>\n",
       "      <td>22Dec2020</td>\n",
       "      <td>31Dec2020</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29th</th>\n",
       "      <td>Past</td>\n",
       "      <td>01Jan2021</td>\n",
       "      <td>09Jan2021</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30th</th>\n",
       "      <td>Past</td>\n",
       "      <td>10Jan2021</td>\n",
       "      <td>18Jan2021</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31st</th>\n",
       "      <td>Past</td>\n",
       "      <td>19Jan2021</td>\n",
       "      <td>02Feb2021</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32nd</th>\n",
       "      <td>Past</td>\n",
       "      <td>03Feb2021</td>\n",
       "      <td>17Feb2021</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33rd</th>\n",
       "      <td>Past</td>\n",
       "      <td>18Feb2021</td>\n",
       "      <td>03Mar2021</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34th</th>\n",
       "      <td>Past</td>\n",
       "      <td>04Mar2021</td>\n",
       "      <td>11Mar2021</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35th</th>\n",
       "      <td>Past</td>\n",
       "      <td>12Mar2021</td>\n",
       "      <td>22Mar2021</td>\n",
       "      <td>326687501</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Type      Start        End  Population\n",
       "0th   Past  09Feb2020  16Mar2020   326687501\n",
       "1st   Past  17Mar2020  30Mar2020   326687501\n",
       "2nd   Past  31Mar2020  10Apr2020   326687501\n",
       "3rd   Past  11Apr2020  22Apr2020   326687501\n",
       "4th   Past  23Apr2020  03May2020   326687501\n",
       "5th   Past  04May2020  14May2020   326687501\n",
       "6th   Past  15May2020  22May2020   326687501\n",
       "7th   Past  23May2020  31May2020   326687501\n",
       "8th   Past  01Jun2020  08Jun2020   326687501\n",
       "9th   Past  09Jun2020  16Jun2020   326687501\n",
       "10th  Past  17Jun2020  28Jun2020   326687501\n",
       "11th  Past  29Jun2020  10Jul2020   326687501\n",
       "12th  Past  11Jul2020  18Jul2020   326687501\n",
       "13th  Past  19Jul2020  26Jul2020   326687501\n",
       "14th  Past  27Jul2020  10Aug2020   326687501\n",
       "15th  Past  11Aug2020  18Aug2020   326687501\n",
       "16th  Past  19Aug2020  26Aug2020   326687501\n",
       "17th  Past  27Aug2020  10Sep2020   326687501\n",
       "18th  Past  11Sep2020  25Sep2020   326687501\n",
       "19th  Past  26Sep2020  04Oct2020   326687501\n",
       "20th  Past  05Oct2020  12Oct2020   326687501\n",
       "21st  Past  13Oct2020  27Oct2020   326687501\n",
       "22nd  Past  28Oct2020  09Nov2020   326687501\n",
       "23rd  Past  10Nov2020  17Nov2020   326687501\n",
       "24th  Past  18Nov2020  25Nov2020   326687501\n",
       "25th  Past  26Nov2020  03Dec2020   326687501\n",
       "26th  Past  04Dec2020  12Dec2020   326687501\n",
       "27th  Past  13Dec2020  21Dec2020   326687501\n",
       "28th  Past  22Dec2020  31Dec2020   326687501\n",
       "29th  Past  01Jan2021  09Jan2021   326687501\n",
       "30th  Past  10Jan2021  18Jan2021   326687501\n",
       "31st  Past  19Jan2021  02Feb2021   326687501\n",
       "32nd  Past  03Feb2021  17Feb2021   326687501\n",
       "33rd  Past  18Feb2021  03Mar2021   326687501\n",
       "34th  Past  04Mar2021  11Mar2021   326687501\n",
       "35th  Past  12Mar2021  22Mar2021   326687501"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_scenario.summary()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "us_scenario.delete([\"37th\", \"38th\", \"39th\"])"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "us_scenario.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "<SIR-F model: parameter estimation>\n",
      "Running optimization with 8 CPUs...\n",
      "\t35th phase (12Mar2021 - 22Mar2021): finished  169 trials in 0 min  5 sec\n",
      "Completed optimization. Total: 2 min 12 sec\n"
     ]
    }
   ],
   "source": [
    "us_scenario.estimate(cs.SIRF, timeout=120)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Type</th>\n",
       "      <th>Start</th>\n",
       "      <th>End</th>\n",
       "      <th>Population</th>\n",
       "      <th>ODE</th>\n",
       "      <th>Rt</th>\n",
       "      <th>theta</th>\n",
       "      <th>kappa</th>\n",
       "      <th>rho</th>\n",
       "      <th>sigma</th>\n",
       "      <th>tau</th>\n",
       "      <th>alpha1 [-]</th>\n",
       "      <th>1/alpha2 [day]</th>\n",
       "      <th>1/gamma [day]</th>\n",
       "      <th>1/beta [day]</th>\n",
       "      <th>RMSLE</th>\n",
       "      <th>Trials</th>\n",
       "      <th>Runtime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0th</th>\n",
       "      <td>Past</td>\n",
       "      <td>09Feb2020</td>\n",
       "      <td>16Mar2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>20.91</td>\n",
       "      <td>0.000093</td>\n",
       "      <td>3.097596e-05</td>\n",
       "      <td>0.000943</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>224</td>\n",
       "      <td>491</td>\n",
       "      <td>7</td>\n",
       "      <td>0.798550</td>\n",
       "      <td>351</td>\n",
       "      <td>0 min 25 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1st</th>\n",
       "      <td>Past</td>\n",
       "      <td>17Mar2020</td>\n",
       "      <td>30Mar2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>42.06</td>\n",
       "      <td>0.003022</td>\n",
       "      <td>3.155022e-05</td>\n",
       "      <td>0.002037</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>10</td>\n",
       "      <td>0.003</td>\n",
       "      <td>220</td>\n",
       "      <td>414</td>\n",
       "      <td>3</td>\n",
       "      <td>0.244604</td>\n",
       "      <td>454</td>\n",
       "      <td>0 min 30 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2nd</th>\n",
       "      <td>Past</td>\n",
       "      <td>31Mar2020</td>\n",
       "      <td>10Apr2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>8.63</td>\n",
       "      <td>0.000717</td>\n",
       "      <td>4.277044e-05</td>\n",
       "      <td>0.000806</td>\n",
       "      <td>0.000051</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>162</td>\n",
       "      <td>137</td>\n",
       "      <td>8</td>\n",
       "      <td>0.061342</td>\n",
       "      <td>565</td>\n",
       "      <td>0 min 40 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3rd</th>\n",
       "      <td>Past</td>\n",
       "      <td>11Apr2020</td>\n",
       "      <td>22Apr2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>4.09</td>\n",
       "      <td>0.000231</td>\n",
       "      <td>2.650148e-05</td>\n",
       "      <td>0.000338</td>\n",
       "      <td>0.000056</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>262</td>\n",
       "      <td>123</td>\n",
       "      <td>20</td>\n",
       "      <td>0.035246</td>\n",
       "      <td>723</td>\n",
       "      <td>0 min 40 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4th</th>\n",
       "      <td>Past</td>\n",
       "      <td>23Apr2020</td>\n",
       "      <td>03May2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.52</td>\n",
       "      <td>0.000703</td>\n",
       "      <td>1.542423e-05</td>\n",
       "      <td>0.000239</td>\n",
       "      <td>0.000080</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>450</td>\n",
       "      <td>87</td>\n",
       "      <td>28</td>\n",
       "      <td>0.037127</td>\n",
       "      <td>759</td>\n",
       "      <td>0 min 55 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5th</th>\n",
       "      <td>Past</td>\n",
       "      <td>04May2020</td>\n",
       "      <td>14May2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>3.20</td>\n",
       "      <td>0.002534</td>\n",
       "      <td>1.144051e-05</td>\n",
       "      <td>0.000168</td>\n",
       "      <td>0.000041</td>\n",
       "      <td>10</td>\n",
       "      <td>0.003</td>\n",
       "      <td>607</td>\n",
       "      <td>170</td>\n",
       "      <td>41</td>\n",
       "      <td>0.019415</td>\n",
       "      <td>156</td>\n",
       "      <td>0 min 10 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6th</th>\n",
       "      <td>Past</td>\n",
       "      <td>15May2020</td>\n",
       "      <td>22May2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.05</td>\n",
       "      <td>0.003559</td>\n",
       "      <td>6.413542e-06</td>\n",
       "      <td>0.000144</td>\n",
       "      <td>0.000064</td>\n",
       "      <td>10</td>\n",
       "      <td>0.004</td>\n",
       "      <td>1082</td>\n",
       "      <td>109</td>\n",
       "      <td>48</td>\n",
       "      <td>0.021481</td>\n",
       "      <td>360</td>\n",
       "      <td>0 min 25 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7th</th>\n",
       "      <td>Past</td>\n",
       "      <td>23May2020</td>\n",
       "      <td>31May2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.000468</td>\n",
       "      <td>5.094119e-06</td>\n",
       "      <td>0.000119</td>\n",
       "      <td>0.000049</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1363</td>\n",
       "      <td>140</td>\n",
       "      <td>58</td>\n",
       "      <td>0.008624</td>\n",
       "      <td>1810</td>\n",
       "      <td>1 min 36 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8th</th>\n",
       "      <td>Past</td>\n",
       "      <td>01Jun2020</td>\n",
       "      <td>08Jun2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.22</td>\n",
       "      <td>0.001819</td>\n",
       "      <td>4.303535e-06</td>\n",
       "      <td>0.000111</td>\n",
       "      <td>0.000046</td>\n",
       "      <td>10</td>\n",
       "      <td>0.002</td>\n",
       "      <td>1613</td>\n",
       "      <td>152</td>\n",
       "      <td>62</td>\n",
       "      <td>0.003859</td>\n",
       "      <td>71</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9th</th>\n",
       "      <td>Past</td>\n",
       "      <td>09Jun2020</td>\n",
       "      <td>16Jun2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.50</td>\n",
       "      <td>0.000556</td>\n",
       "      <td>4.014641e-06</td>\n",
       "      <td>0.000108</td>\n",
       "      <td>0.000039</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>1729</td>\n",
       "      <td>177</td>\n",
       "      <td>64</td>\n",
       "      <td>0.003906</td>\n",
       "      <td>84</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10th</th>\n",
       "      <td>Past</td>\n",
       "      <td>17Jun2020</td>\n",
       "      <td>28Jun2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>3.80</td>\n",
       "      <td>0.001115</td>\n",
       "      <td>2.362704e-06</td>\n",
       "      <td>0.000151</td>\n",
       "      <td>0.000037</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>2939</td>\n",
       "      <td>185</td>\n",
       "      <td>45</td>\n",
       "      <td>0.005350</td>\n",
       "      <td>150</td>\n",
       "      <td>0 min 10 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11th</th>\n",
       "      <td>Past</td>\n",
       "      <td>29Jun2020</td>\n",
       "      <td>10Jul2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.84</td>\n",
       "      <td>0.000302</td>\n",
       "      <td>2.241752e-06</td>\n",
       "      <td>0.000196</td>\n",
       "      <td>0.000104</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3097</td>\n",
       "      <td>66</td>\n",
       "      <td>35</td>\n",
       "      <td>0.019334</td>\n",
       "      <td>375</td>\n",
       "      <td>0 min 25 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12th</th>\n",
       "      <td>Past</td>\n",
       "      <td>11Jul2020</td>\n",
       "      <td>18Jul2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>3.37</td>\n",
       "      <td>0.001115</td>\n",
       "      <td>2.107077e-06</td>\n",
       "      <td>0.000203</td>\n",
       "      <td>0.000058</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>3295</td>\n",
       "      <td>119</td>\n",
       "      <td>34</td>\n",
       "      <td>0.003058</td>\n",
       "      <td>150</td>\n",
       "      <td>0 min 10 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13th</th>\n",
       "      <td>Past</td>\n",
       "      <td>19Jul2020</td>\n",
       "      <td>26Jul2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.68</td>\n",
       "      <td>0.000544</td>\n",
       "      <td>2.266252e-06</td>\n",
       "      <td>0.000180</td>\n",
       "      <td>0.000065</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>3064</td>\n",
       "      <td>107</td>\n",
       "      <td>38</td>\n",
       "      <td>0.003309</td>\n",
       "      <td>85</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14th</th>\n",
       "      <td>Past</td>\n",
       "      <td>27Jul2020</td>\n",
       "      <td>10Aug2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.15</td>\n",
       "      <td>0.000060</td>\n",
       "      <td>2.621347e-06</td>\n",
       "      <td>0.000130</td>\n",
       "      <td>0.000058</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2649</td>\n",
       "      <td>119</td>\n",
       "      <td>53</td>\n",
       "      <td>0.008854</td>\n",
       "      <td>226</td>\n",
       "      <td>0 min 15 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15th</th>\n",
       "      <td>Past</td>\n",
       "      <td>11Aug2020</td>\n",
       "      <td>18Aug2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.05</td>\n",
       "      <td>0.000079</td>\n",
       "      <td>1.860062e-06</td>\n",
       "      <td>0.000105</td>\n",
       "      <td>0.000049</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3733</td>\n",
       "      <td>140</td>\n",
       "      <td>66</td>\n",
       "      <td>0.005164</td>\n",
       "      <td>148</td>\n",
       "      <td>0 min 10 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16th</th>\n",
       "      <td>Past</td>\n",
       "      <td>19Aug2020</td>\n",
       "      <td>26Aug2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.92</td>\n",
       "      <td>0.001272</td>\n",
       "      <td>1.762781e-06</td>\n",
       "      <td>0.000080</td>\n",
       "      <td>0.000040</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>3939</td>\n",
       "      <td>173</td>\n",
       "      <td>86</td>\n",
       "      <td>0.003019</td>\n",
       "      <td>86</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17th</th>\n",
       "      <td>Past</td>\n",
       "      <td>27Aug2020</td>\n",
       "      <td>10Sep2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.81</td>\n",
       "      <td>0.001917</td>\n",
       "      <td>1.411886e-06</td>\n",
       "      <td>0.000075</td>\n",
       "      <td>0.000040</td>\n",
       "      <td>10</td>\n",
       "      <td>0.002</td>\n",
       "      <td>4918</td>\n",
       "      <td>173</td>\n",
       "      <td>92</td>\n",
       "      <td>0.003203</td>\n",
       "      <td>227</td>\n",
       "      <td>0 min 15 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18th</th>\n",
       "      <td>Past</td>\n",
       "      <td>11Sep2020</td>\n",
       "      <td>25Sep2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.83</td>\n",
       "      <td>0.002560</td>\n",
       "      <td>1.179216e-06</td>\n",
       "      <td>0.000069</td>\n",
       "      <td>0.000037</td>\n",
       "      <td>10</td>\n",
       "      <td>0.003</td>\n",
       "      <td>5889</td>\n",
       "      <td>190</td>\n",
       "      <td>100</td>\n",
       "      <td>0.003882</td>\n",
       "      <td>86</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19th</th>\n",
       "      <td>Past</td>\n",
       "      <td>26Sep2020</td>\n",
       "      <td>04Oct2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.26</td>\n",
       "      <td>0.000768</td>\n",
       "      <td>1.136250e-06</td>\n",
       "      <td>0.000068</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>6111</td>\n",
       "      <td>239</td>\n",
       "      <td>102</td>\n",
       "      <td>0.004049</td>\n",
       "      <td>69</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20th</th>\n",
       "      <td>Past</td>\n",
       "      <td>05Oct2020</td>\n",
       "      <td>12Oct2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.31</td>\n",
       "      <td>0.000307</td>\n",
       "      <td>1.370174e-06</td>\n",
       "      <td>0.000078</td>\n",
       "      <td>0.000032</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>5068</td>\n",
       "      <td>214</td>\n",
       "      <td>88</td>\n",
       "      <td>0.004355</td>\n",
       "      <td>85</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21st</th>\n",
       "      <td>Past</td>\n",
       "      <td>13Oct2020</td>\n",
       "      <td>27Oct2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.52</td>\n",
       "      <td>0.000543</td>\n",
       "      <td>1.282980e-06</td>\n",
       "      <td>0.000093</td>\n",
       "      <td>0.000035</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>5412</td>\n",
       "      <td>195</td>\n",
       "      <td>74</td>\n",
       "      <td>0.003968</td>\n",
       "      <td>87</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22nd</th>\n",
       "      <td>Past</td>\n",
       "      <td>28Oct2020</td>\n",
       "      <td>09Nov2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>3.35</td>\n",
       "      <td>0.000825</td>\n",
       "      <td>1.157219e-06</td>\n",
       "      <td>0.000135</td>\n",
       "      <td>0.000039</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>6000</td>\n",
       "      <td>177</td>\n",
       "      <td>51</td>\n",
       "      <td>0.003229</td>\n",
       "      <td>166</td>\n",
       "      <td>0 min 10 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23rd</th>\n",
       "      <td>Past</td>\n",
       "      <td>10Nov2020</td>\n",
       "      <td>17Nov2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>3.40</td>\n",
       "      <td>0.000463</td>\n",
       "      <td>1.455179e-06</td>\n",
       "      <td>0.000171</td>\n",
       "      <td>0.000049</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4772</td>\n",
       "      <td>142</td>\n",
       "      <td>40</td>\n",
       "      <td>0.003569</td>\n",
       "      <td>163</td>\n",
       "      <td>0 min 10 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24th</th>\n",
       "      <td>Past</td>\n",
       "      <td>18Nov2020</td>\n",
       "      <td>25Nov2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.93</td>\n",
       "      <td>0.000417</td>\n",
       "      <td>1.559167e-06</td>\n",
       "      <td>0.000176</td>\n",
       "      <td>0.000058</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4453</td>\n",
       "      <td>119</td>\n",
       "      <td>39</td>\n",
       "      <td>0.004040</td>\n",
       "      <td>613</td>\n",
       "      <td>0 min 40 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25th</th>\n",
       "      <td>Past</td>\n",
       "      <td>26Nov2020</td>\n",
       "      <td>03Dec2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.44</td>\n",
       "      <td>0.000071</td>\n",
       "      <td>1.340660e-06</td>\n",
       "      <td>0.000164</td>\n",
       "      <td>0.000066</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>5179</td>\n",
       "      <td>105</td>\n",
       "      <td>42</td>\n",
       "      <td>0.003718</td>\n",
       "      <td>300</td>\n",
       "      <td>0 min 10 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26th</th>\n",
       "      <td>Past</td>\n",
       "      <td>04Dec2020</td>\n",
       "      <td>12Dec2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.30</td>\n",
       "      <td>0.000867</td>\n",
       "      <td>1.634155e-06</td>\n",
       "      <td>0.000172</td>\n",
       "      <td>0.000073</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>4249</td>\n",
       "      <td>95</td>\n",
       "      <td>40</td>\n",
       "      <td>0.004366</td>\n",
       "      <td>163</td>\n",
       "      <td>0 min 10 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27th</th>\n",
       "      <td>Past</td>\n",
       "      <td>13Dec2020</td>\n",
       "      <td>21Dec2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.09</td>\n",
       "      <td>0.000165</td>\n",
       "      <td>1.843945e-06</td>\n",
       "      <td>0.000163</td>\n",
       "      <td>0.000076</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3766</td>\n",
       "      <td>91</td>\n",
       "      <td>42</td>\n",
       "      <td>0.002755</td>\n",
       "      <td>311</td>\n",
       "      <td>0 min 20 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28th</th>\n",
       "      <td>Past</td>\n",
       "      <td>22Dec2020</td>\n",
       "      <td>31Dec2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.87</td>\n",
       "      <td>0.000996</td>\n",
       "      <td>1.491989e-06</td>\n",
       "      <td>0.000124</td>\n",
       "      <td>0.000065</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>4654</td>\n",
       "      <td>106</td>\n",
       "      <td>55</td>\n",
       "      <td>0.002766</td>\n",
       "      <td>240</td>\n",
       "      <td>0 min 15 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29th</th>\n",
       "      <td>Past</td>\n",
       "      <td>01Jan2021</td>\n",
       "      <td>09Jan2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.62</td>\n",
       "      <td>0.000060</td>\n",
       "      <td>1.627618e-06</td>\n",
       "      <td>0.000146</td>\n",
       "      <td>0.000054</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4266</td>\n",
       "      <td>128</td>\n",
       "      <td>47</td>\n",
       "      <td>0.003278</td>\n",
       "      <td>235</td>\n",
       "      <td>0 min 15 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30th</th>\n",
       "      <td>Past</td>\n",
       "      <td>10Jan2021</td>\n",
       "      <td>18Jan2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.58</td>\n",
       "      <td>0.000159</td>\n",
       "      <td>1.790487e-06</td>\n",
       "      <td>0.000124</td>\n",
       "      <td>0.000046</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3878</td>\n",
       "      <td>149</td>\n",
       "      <td>55</td>\n",
       "      <td>0.002690</td>\n",
       "      <td>243</td>\n",
       "      <td>0 min 15 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31st</th>\n",
       "      <td>Past</td>\n",
       "      <td>19Jan2021</td>\n",
       "      <td>02Feb2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.98</td>\n",
       "      <td>0.000843</td>\n",
       "      <td>1.546285e-06</td>\n",
       "      <td>0.000087</td>\n",
       "      <td>0.000042</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>4491</td>\n",
       "      <td>163</td>\n",
       "      <td>79</td>\n",
       "      <td>0.003228</td>\n",
       "      <td>330</td>\n",
       "      <td>0 min 15 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32nd</th>\n",
       "      <td>Past</td>\n",
       "      <td>03Feb2021</td>\n",
       "      <td>17Feb2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.28</td>\n",
       "      <td>0.000309</td>\n",
       "      <td>1.176440e-06</td>\n",
       "      <td>0.000045</td>\n",
       "      <td>0.000034</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>5902</td>\n",
       "      <td>206</td>\n",
       "      <td>156</td>\n",
       "      <td>0.003685</td>\n",
       "      <td>85</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33rd</th>\n",
       "      <td>Past</td>\n",
       "      <td>18Feb2021</td>\n",
       "      <td>03Mar2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.06</td>\n",
       "      <td>0.000556</td>\n",
       "      <td>1.010582e-06</td>\n",
       "      <td>0.000033</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>6871</td>\n",
       "      <td>229</td>\n",
       "      <td>208</td>\n",
       "      <td>0.002401</td>\n",
       "      <td>77</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34th</th>\n",
       "      <td>Past</td>\n",
       "      <td>04Mar2021</td>\n",
       "      <td>11Mar2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.000543</td>\n",
       "      <td>6.448044e-07</td>\n",
       "      <td>0.000026</td>\n",
       "      <td>0.000027</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>10769</td>\n",
       "      <td>256</td>\n",
       "      <td>270</td>\n",
       "      <td>0.000807</td>\n",
       "      <td>124</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35th</th>\n",
       "      <td>Past</td>\n",
       "      <td>12Mar2021</td>\n",
       "      <td>22Mar2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.04</td>\n",
       "      <td>0.000863</td>\n",
       "      <td>4.283546e-07</td>\n",
       "      <td>0.000027</td>\n",
       "      <td>0.000026</td>\n",
       "      <td>10</td>\n",
       "      <td>0.001</td>\n",
       "      <td>16211</td>\n",
       "      <td>270</td>\n",
       "      <td>254</td>\n",
       "      <td>0.000632</td>\n",
       "      <td>169</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Type      Start        End  Population    ODE     Rt     theta  \\\n",
       "0th   Past  09Feb2020  16Mar2020   326687501  SIR-F  20.91  0.000093   \n",
       "1st   Past  17Mar2020  30Mar2020   326687501  SIR-F  42.06  0.003022   \n",
       "2nd   Past  31Mar2020  10Apr2020   326687501  SIR-F   8.63  0.000717   \n",
       "3rd   Past  11Apr2020  22Apr2020   326687501  SIR-F   4.09  0.000231   \n",
       "4th   Past  23Apr2020  03May2020   326687501  SIR-F   2.52  0.000703   \n",
       "5th   Past  04May2020  14May2020   326687501  SIR-F   3.20  0.002534   \n",
       "6th   Past  15May2020  22May2020   326687501  SIR-F   2.05  0.003559   \n",
       "7th   Past  23May2020  31May2020   326687501  SIR-F   2.18  0.000468   \n",
       "8th   Past  01Jun2020  08Jun2020   326687501  SIR-F   2.22  0.001819   \n",
       "9th   Past  09Jun2020  16Jun2020   326687501  SIR-F   2.50  0.000556   \n",
       "10th  Past  17Jun2020  28Jun2020   326687501  SIR-F   3.80  0.001115   \n",
       "11th  Past  29Jun2020  10Jul2020   326687501  SIR-F   1.84  0.000302   \n",
       "12th  Past  11Jul2020  18Jul2020   326687501  SIR-F   3.37  0.001115   \n",
       "13th  Past  19Jul2020  26Jul2020   326687501  SIR-F   2.68  0.000544   \n",
       "14th  Past  27Jul2020  10Aug2020   326687501  SIR-F   2.15  0.000060   \n",
       "15th  Past  11Aug2020  18Aug2020   326687501  SIR-F   2.05  0.000079   \n",
       "16th  Past  19Aug2020  26Aug2020   326687501  SIR-F   1.92  0.001272   \n",
       "17th  Past  27Aug2020  10Sep2020   326687501  SIR-F   1.81  0.001917   \n",
       "18th  Past  11Sep2020  25Sep2020   326687501  SIR-F   1.83  0.002560   \n",
       "19th  Past  26Sep2020  04Oct2020   326687501  SIR-F   2.26  0.000768   \n",
       "20th  Past  05Oct2020  12Oct2020   326687501  SIR-F   2.31  0.000307   \n",
       "21st  Past  13Oct2020  27Oct2020   326687501  SIR-F   2.52  0.000543   \n",
       "22nd  Past  28Oct2020  09Nov2020   326687501  SIR-F   3.35  0.000825   \n",
       "23rd  Past  10Nov2020  17Nov2020   326687501  SIR-F   3.40  0.000463   \n",
       "24th  Past  18Nov2020  25Nov2020   326687501  SIR-F   2.93  0.000417   \n",
       "25th  Past  26Nov2020  03Dec2020   326687501  SIR-F   2.44  0.000071   \n",
       "26th  Past  04Dec2020  12Dec2020   326687501  SIR-F   2.30  0.000867   \n",
       "27th  Past  13Dec2020  21Dec2020   326687501  SIR-F   2.09  0.000165   \n",
       "28th  Past  22Dec2020  31Dec2020   326687501  SIR-F   1.87  0.000996   \n",
       "29th  Past  01Jan2021  09Jan2021   326687501  SIR-F   2.62  0.000060   \n",
       "30th  Past  10Jan2021  18Jan2021   326687501  SIR-F   2.58  0.000159   \n",
       "31st  Past  19Jan2021  02Feb2021   326687501  SIR-F   1.98  0.000843   \n",
       "32nd  Past  03Feb2021  17Feb2021   326687501  SIR-F   1.28  0.000309   \n",
       "33rd  Past  18Feb2021  03Mar2021   326687501  SIR-F   1.06  0.000556   \n",
       "34th  Past  04Mar2021  11Mar2021   326687501  SIR-F   0.92  0.000543   \n",
       "35th  Past  12Mar2021  22Mar2021   326687501  SIR-F   1.04  0.000863   \n",
       "\n",
       "             kappa       rho     sigma  tau  alpha1 [-]  1/alpha2 [day]  \\\n",
       "0th   3.097596e-05  0.000943  0.000014   10       0.000             224   \n",
       "1st   3.155022e-05  0.002037  0.000017   10       0.003             220   \n",
       "2nd   4.277044e-05  0.000806  0.000051   10       0.001             162   \n",
       "3rd   2.650148e-05  0.000338  0.000056   10       0.000             262   \n",
       "4th   1.542423e-05  0.000239  0.000080   10       0.001             450   \n",
       "5th   1.144051e-05  0.000168  0.000041   10       0.003             607   \n",
       "6th   6.413542e-06  0.000144  0.000064   10       0.004            1082   \n",
       "7th   5.094119e-06  0.000119  0.000049   10       0.000            1363   \n",
       "8th   4.303535e-06  0.000111  0.000046   10       0.002            1613   \n",
       "9th   4.014641e-06  0.000108  0.000039   10       0.001            1729   \n",
       "10th  2.362704e-06  0.000151  0.000037   10       0.001            2939   \n",
       "11th  2.241752e-06  0.000196  0.000104   10       0.000            3097   \n",
       "12th  2.107077e-06  0.000203  0.000058   10       0.001            3295   \n",
       "13th  2.266252e-06  0.000180  0.000065   10       0.001            3064   \n",
       "14th  2.621347e-06  0.000130  0.000058   10       0.000            2649   \n",
       "15th  1.860062e-06  0.000105  0.000049   10       0.000            3733   \n",
       "16th  1.762781e-06  0.000080  0.000040   10       0.001            3939   \n",
       "17th  1.411886e-06  0.000075  0.000040   10       0.002            4918   \n",
       "18th  1.179216e-06  0.000069  0.000037   10       0.003            5889   \n",
       "19th  1.136250e-06  0.000068  0.000029   10       0.001            6111   \n",
       "20th  1.370174e-06  0.000078  0.000032   10       0.000            5068   \n",
       "21st  1.282980e-06  0.000093  0.000035   10       0.001            5412   \n",
       "22nd  1.157219e-06  0.000135  0.000039   10       0.001            6000   \n",
       "23rd  1.455179e-06  0.000171  0.000049   10       0.000            4772   \n",
       "24th  1.559167e-06  0.000176  0.000058   10       0.000            4453   \n",
       "25th  1.340660e-06  0.000164  0.000066   10       0.000            5179   \n",
       "26th  1.634155e-06  0.000172  0.000073   10       0.001            4249   \n",
       "27th  1.843945e-06  0.000163  0.000076   10       0.000            3766   \n",
       "28th  1.491989e-06  0.000124  0.000065   10       0.001            4654   \n",
       "29th  1.627618e-06  0.000146  0.000054   10       0.000            4266   \n",
       "30th  1.790487e-06  0.000124  0.000046   10       0.000            3878   \n",
       "31st  1.546285e-06  0.000087  0.000042   10       0.001            4491   \n",
       "32nd  1.176440e-06  0.000045  0.000034   10       0.000            5902   \n",
       "33rd  1.010582e-06  0.000033  0.000030   10       0.001            6871   \n",
       "34th  6.448044e-07  0.000026  0.000027   10       0.001           10769   \n",
       "35th  4.283546e-07  0.000027  0.000026   10       0.001           16211   \n",
       "\n",
       "      1/gamma [day]  1/beta [day]     RMSLE  Trials       Runtime  \n",
       "0th             491             7  0.798550     351  0 min 25 sec  \n",
       "1st             414             3  0.244604     454  0 min 30 sec  \n",
       "2nd             137             8  0.061342     565  0 min 40 sec  \n",
       "3rd             123            20  0.035246     723  0 min 40 sec  \n",
       "4th              87            28  0.037127     759  0 min 55 sec  \n",
       "5th             170            41  0.019415     156  0 min 10 sec  \n",
       "6th             109            48  0.021481     360  0 min 25 sec  \n",
       "7th             140            58  0.008624    1810  1 min 36 sec  \n",
       "8th             152            62  0.003859      71  0 min  5 sec  \n",
       "9th             177            64  0.003906      84  0 min  5 sec  \n",
       "10th            185            45  0.005350     150  0 min 10 sec  \n",
       "11th             66            35  0.019334     375  0 min 25 sec  \n",
       "12th            119            34  0.003058     150  0 min 10 sec  \n",
       "13th            107            38  0.003309      85  0 min  5 sec  \n",
       "14th            119            53  0.008854     226  0 min 15 sec  \n",
       "15th            140            66  0.005164     148  0 min 10 sec  \n",
       "16th            173            86  0.003019      86  0 min  5 sec  \n",
       "17th            173            92  0.003203     227  0 min 15 sec  \n",
       "18th            190           100  0.003882      86  0 min  5 sec  \n",
       "19th            239           102  0.004049      69  0 min  5 sec  \n",
       "20th            214            88  0.004355      85  0 min  5 sec  \n",
       "21st            195            74  0.003968      87  0 min  5 sec  \n",
       "22nd            177            51  0.003229     166  0 min 10 sec  \n",
       "23rd            142            40  0.003569     163  0 min 10 sec  \n",
       "24th            119            39  0.004040     613  0 min 40 sec  \n",
       "25th            105            42  0.003718     300  0 min 10 sec  \n",
       "26th             95            40  0.004366     163  0 min 10 sec  \n",
       "27th             91            42  0.002755     311  0 min 20 sec  \n",
       "28th            106            55  0.002766     240  0 min 15 sec  \n",
       "29th            128            47  0.003278     235  0 min 15 sec  \n",
       "30th            149            55  0.002690     243  0 min 15 sec  \n",
       "31st            163            79  0.003228     330  0 min 15 sec  \n",
       "32nd            206           156  0.003685      85  0 min  5 sec  \n",
       "33rd            229           208  0.002401      77  0 min  5 sec  \n",
       "34th            256           270  0.000807     124  0 min  5 sec  \n",
       "35th            270           254  0.000632     169  0 min  5 sec  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_scenario.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "#T_d5c20_row0_col1,#T_d5c20_row0_col2,#T_d5c20_row0_col4,#T_d5c20_row6_col3{\n",
       "            background-color:  #fff7fb;\n",
       "            color:  #000000;\n",
       "        }#T_d5c20_row0_col3,#T_d5c20_row6_col1,#T_d5c20_row6_col2,#T_d5c20_row6_col4{\n",
       "            background-color:  #023858;\n",
       "            color:  #f1f1f1;\n",
       "        }#T_d5c20_row1_col1,#T_d5c20_row1_col2,#T_d5c20_row1_col4,#T_d5c20_row5_col3{\n",
       "            background-color:  #e3e0ee;\n",
       "            color:  #000000;\n",
       "        }#T_d5c20_row1_col3,#T_d5c20_row5_col1,#T_d5c20_row5_col2,#T_d5c20_row5_col4{\n",
       "            background-color:  #046198;\n",
       "            color:  #f1f1f1;\n",
       "        }#T_d5c20_row2_col1,#T_d5c20_row2_col2,#T_d5c20_row2_col4,#T_d5c20_row4_col3{\n",
       "            background-color:  #b4c4df;\n",
       "            color:  #000000;\n",
       "        }#T_d5c20_row2_col3{\n",
       "            background-color:  #2484ba;\n",
       "            color:  #000000;\n",
       "        }#T_d5c20_row3_col1,#T_d5c20_row3_col2,#T_d5c20_row3_col3,#T_d5c20_row3_col4{\n",
       "            background-color:  #73a9cf;\n",
       "            color:  #000000;\n",
       "        }#T_d5c20_row4_col1,#T_d5c20_row4_col2,#T_d5c20_row4_col4{\n",
       "            background-color:  #2685bb;\n",
       "            color:  #000000;\n",
       "        }</style><table id=\"T_d5c20_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Date</th>        <th class=\"col_heading level0 col1\" >Confirmed</th>        <th class=\"col_heading level0 col2\" >Fatal</th>        <th class=\"col_heading level0 col3\" >Infected</th>        <th class=\"col_heading level0 col4\" >Recovered</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_d5c20_level0_row0\" class=\"row_heading level0 row0\" >462</th>\n",
       "                        <td id=\"T_d5c20_row0_col0\" class=\"data row0 col0\" >2021-05-16 00:00:00</td>\n",
       "                        <td id=\"T_d5c20_row0_col1\" class=\"data row0 col1\" >32807610</td>\n",
       "                        <td id=\"T_d5c20_row0_col2\" class=\"data row0 col2\" >597058</td>\n",
       "                        <td id=\"T_d5c20_row0_col3\" class=\"data row0 col3\" >14860886</td>\n",
       "                        <td id=\"T_d5c20_row0_col4\" class=\"data row0 col4\" >17349666</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_d5c20_level0_row1\" class=\"row_heading level0 row1\" >463</th>\n",
       "                        <td id=\"T_d5c20_row1_col0\" class=\"data row1 col0\" >2021-05-17 00:00:00</td>\n",
       "                        <td id=\"T_d5c20_row1_col1\" class=\"data row1 col1\" >32860125</td>\n",
       "                        <td id=\"T_d5c20_row1_col2\" class=\"data row1 col2\" >598020</td>\n",
       "                        <td id=\"T_d5c20_row1_col3\" class=\"data row1 col3\" >14857512</td>\n",
       "                        <td id=\"T_d5c20_row1_col4\" class=\"data row1 col4\" >17404593</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_d5c20_level0_row2\" class=\"row_heading level0 row2\" >464</th>\n",
       "                        <td id=\"T_d5c20_row2_col0\" class=\"data row2 col0\" >2021-05-18 00:00:00</td>\n",
       "                        <td id=\"T_d5c20_row2_col1\" class=\"data row2 col1\" >32912619</td>\n",
       "                        <td id=\"T_d5c20_row2_col2\" class=\"data row2 col2\" >598982</td>\n",
       "                        <td id=\"T_d5c20_row2_col3\" class=\"data row2 col3\" >14854130</td>\n",
       "                        <td id=\"T_d5c20_row2_col4\" class=\"data row2 col4\" >17459507</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_d5c20_level0_row3\" class=\"row_heading level0 row3\" >465</th>\n",
       "                        <td id=\"T_d5c20_row3_col0\" class=\"data row3 col0\" >2021-05-19 00:00:00</td>\n",
       "                        <td id=\"T_d5c20_row3_col1\" class=\"data row3 col1\" >32965091</td>\n",
       "                        <td id=\"T_d5c20_row3_col2\" class=\"data row3 col2\" >599943</td>\n",
       "                        <td id=\"T_d5c20_row3_col3\" class=\"data row3 col3\" >14850739</td>\n",
       "                        <td id=\"T_d5c20_row3_col4\" class=\"data row3 col4\" >17514409</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_d5c20_level0_row4\" class=\"row_heading level0 row4\" >466</th>\n",
       "                        <td id=\"T_d5c20_row4_col0\" class=\"data row4 col0\" >2021-05-20 00:00:00</td>\n",
       "                        <td id=\"T_d5c20_row4_col1\" class=\"data row4 col1\" >33017541</td>\n",
       "                        <td id=\"T_d5c20_row4_col2\" class=\"data row4 col2\" >600904</td>\n",
       "                        <td id=\"T_d5c20_row4_col3\" class=\"data row4 col3\" >14847339</td>\n",
       "                        <td id=\"T_d5c20_row4_col4\" class=\"data row4 col4\" >17569298</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_d5c20_level0_row5\" class=\"row_heading level0 row5\" >467</th>\n",
       "                        <td id=\"T_d5c20_row5_col0\" class=\"data row5 col0\" >2021-05-21 00:00:00</td>\n",
       "                        <td id=\"T_d5c20_row5_col1\" class=\"data row5 col1\" >33069970</td>\n",
       "                        <td id=\"T_d5c20_row5_col2\" class=\"data row5 col2\" >601865</td>\n",
       "                        <td id=\"T_d5c20_row5_col3\" class=\"data row5 col3\" >14843931</td>\n",
       "                        <td id=\"T_d5c20_row5_col4\" class=\"data row5 col4\" >17624174</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_d5c20_level0_row6\" class=\"row_heading level0 row6\" >468</th>\n",
       "                        <td id=\"T_d5c20_row6_col0\" class=\"data row6 col0\" >2021-05-22 00:00:00</td>\n",
       "                        <td id=\"T_d5c20_row6_col1\" class=\"data row6 col1\" >33122378</td>\n",
       "                        <td id=\"T_d5c20_row6_col2\" class=\"data row6 col2\" >602826</td>\n",
       "                        <td id=\"T_d5c20_row6_col3\" class=\"data row6 col3\" >14840514</td>\n",
       "                        <td id=\"T_d5c20_row6_col4\" class=\"data row6 col4\" >17679038</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fe427259670>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_scenario.clear()\n",
    "us_scenario.add(days=60)\n",
    "us_scenario.simulate().tail(28).style.background_gradient(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Infected</th>\n",
       "      <th>Fatal</th>\n",
       "      <th>Recovered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>2021-04-21</td>\n",
       "      <td>14438403</td>\n",
       "      <td>569491</td>\n",
       "      <td>16854200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>2021-04-22</td>\n",
       "      <td>14451901</td>\n",
       "      <td>570434</td>\n",
       "      <td>16907016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>2021-04-23</td>\n",
       "      <td>14461167</td>\n",
       "      <td>571197</td>\n",
       "      <td>16959386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>2021-04-24</td>\n",
       "      <td>14461883</td>\n",
       "      <td>571921</td>\n",
       "      <td>17011309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>441</th>\n",
       "      <td>2021-04-25</td>\n",
       "      <td>14442192</td>\n",
       "      <td>572200</td>\n",
       "      <td>17062786</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date  Infected   Fatal  Recovered\n",
       "437 2021-04-21  14438403  569491   16854200\n",
       "438 2021-04-22  14451901  570434   16907016\n",
       "439 2021-04-23  14461167  571197   16959386\n",
       "440 2021-04-24  14461883  571921   17011309\n",
       "441 2021-04-25  14442192  572200   17062786"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_scenario_new = cs.Scenario(country=\"United States\")\n",
    "us_scenario_new.register(jhu_data_new, population_data)\n",
    "us_scenario_new.records().tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = us_scenario_new.trend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "<SIR-F model: parameter estimation>\n",
      "Running optimization with 8 CPUs...\n",
      "\t39th phase (14Apr2021 - 25Apr2021): finished  178 trials in 0 min  5 sec\n",
      "Completed optimization. Total: 2 min 42 sec\n"
     ]
    }
   ],
   "source": [
    "us_scenario_new.estimate(cs.SIRF, timeout=120)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Type</th>\n",
       "      <th>Start</th>\n",
       "      <th>End</th>\n",
       "      <th>Population</th>\n",
       "      <th>ODE</th>\n",
       "      <th>Rt</th>\n",
       "      <th>theta</th>\n",
       "      <th>kappa</th>\n",
       "      <th>rho</th>\n",
       "      <th>sigma</th>\n",
       "      <th>tau</th>\n",
       "      <th>1/alpha2 [day]</th>\n",
       "      <th>alpha1 [-]</th>\n",
       "      <th>1/gamma [day]</th>\n",
       "      <th>1/beta [day]</th>\n",
       "      <th>RMSLE</th>\n",
       "      <th>Trials</th>\n",
       "      <th>Runtime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0th</th>\n",
       "      <td>Past</td>\n",
       "      <td>09Feb2020</td>\n",
       "      <td>16Mar2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>20.91</td>\n",
       "      <td>0.000093</td>\n",
       "      <td>1.548798e-05</td>\n",
       "      <td>0.000471</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>5</td>\n",
       "      <td>224</td>\n",
       "      <td>0.000</td>\n",
       "      <td>491</td>\n",
       "      <td>7</td>\n",
       "      <td>0.798572</td>\n",
       "      <td>377</td>\n",
       "      <td>0 min 25 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1st</th>\n",
       "      <td>Past</td>\n",
       "      <td>17Mar2020</td>\n",
       "      <td>30Mar2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>42.05</td>\n",
       "      <td>0.003022</td>\n",
       "      <td>1.578128e-05</td>\n",
       "      <td>0.001018</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>5</td>\n",
       "      <td>220</td>\n",
       "      <td>0.003</td>\n",
       "      <td>414</td>\n",
       "      <td>3</td>\n",
       "      <td>0.244587</td>\n",
       "      <td>512</td>\n",
       "      <td>0 min 35 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2nd</th>\n",
       "      <td>Past</td>\n",
       "      <td>31Mar2020</td>\n",
       "      <td>10Apr2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>8.62</td>\n",
       "      <td>0.000740</td>\n",
       "      <td>2.127978e-05</td>\n",
       "      <td>0.000403</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>5</td>\n",
       "      <td>163</td>\n",
       "      <td>0.001</td>\n",
       "      <td>136</td>\n",
       "      <td>8</td>\n",
       "      <td>0.061326</td>\n",
       "      <td>523</td>\n",
       "      <td>0 min 35 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3rd</th>\n",
       "      <td>Past</td>\n",
       "      <td>11Apr2020</td>\n",
       "      <td>22Apr2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>4.09</td>\n",
       "      <td>0.000231</td>\n",
       "      <td>1.325074e-05</td>\n",
       "      <td>0.000169</td>\n",
       "      <td>0.000028</td>\n",
       "      <td>5</td>\n",
       "      <td>262</td>\n",
       "      <td>0.000</td>\n",
       "      <td>123</td>\n",
       "      <td>20</td>\n",
       "      <td>0.035246</td>\n",
       "      <td>579</td>\n",
       "      <td>0 min 40 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4th</th>\n",
       "      <td>Past</td>\n",
       "      <td>23Apr2020</td>\n",
       "      <td>03May2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.52</td>\n",
       "      <td>0.000703</td>\n",
       "      <td>7.712115e-06</td>\n",
       "      <td>0.000120</td>\n",
       "      <td>0.000040</td>\n",
       "      <td>5</td>\n",
       "      <td>450</td>\n",
       "      <td>0.001</td>\n",
       "      <td>87</td>\n",
       "      <td>28</td>\n",
       "      <td>0.037127</td>\n",
       "      <td>770</td>\n",
       "      <td>0 min 55 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5th</th>\n",
       "      <td>Past</td>\n",
       "      <td>04May2020</td>\n",
       "      <td>14May2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>3.20</td>\n",
       "      <td>0.002534</td>\n",
       "      <td>5.720253e-06</td>\n",
       "      <td>0.000084</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>5</td>\n",
       "      <td>607</td>\n",
       "      <td>0.003</td>\n",
       "      <td>170</td>\n",
       "      <td>41</td>\n",
       "      <td>0.019415</td>\n",
       "      <td>167</td>\n",
       "      <td>0 min 10 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6th</th>\n",
       "      <td>Past</td>\n",
       "      <td>15May2020</td>\n",
       "      <td>22May2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.83</td>\n",
       "      <td>0.000117</td>\n",
       "      <td>3.813866e-06</td>\n",
       "      <td>0.000066</td>\n",
       "      <td>0.000032</td>\n",
       "      <td>5</td>\n",
       "      <td>910</td>\n",
       "      <td>0.000</td>\n",
       "      <td>106</td>\n",
       "      <td>52</td>\n",
       "      <td>0.021118</td>\n",
       "      <td>903</td>\n",
       "      <td>1 min  6 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7th</th>\n",
       "      <td>Past</td>\n",
       "      <td>23May2020</td>\n",
       "      <td>31May2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.000468</td>\n",
       "      <td>2.547060e-06</td>\n",
       "      <td>0.000059</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>5</td>\n",
       "      <td>1363</td>\n",
       "      <td>0.000</td>\n",
       "      <td>140</td>\n",
       "      <td>58</td>\n",
       "      <td>0.008624</td>\n",
       "      <td>1833</td>\n",
       "      <td>1 min 25 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8th</th>\n",
       "      <td>Past</td>\n",
       "      <td>01Jun2020</td>\n",
       "      <td>08Jun2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.22</td>\n",
       "      <td>0.001819</td>\n",
       "      <td>2.151768e-06</td>\n",
       "      <td>0.000055</td>\n",
       "      <td>0.000023</td>\n",
       "      <td>5</td>\n",
       "      <td>1613</td>\n",
       "      <td>0.002</td>\n",
       "      <td>152</td>\n",
       "      <td>62</td>\n",
       "      <td>0.003859</td>\n",
       "      <td>89</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9th</th>\n",
       "      <td>Past</td>\n",
       "      <td>09Jun2020</td>\n",
       "      <td>16Jun2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.50</td>\n",
       "      <td>0.000556</td>\n",
       "      <td>2.007320e-06</td>\n",
       "      <td>0.000054</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>5</td>\n",
       "      <td>1729</td>\n",
       "      <td>0.001</td>\n",
       "      <td>177</td>\n",
       "      <td>64</td>\n",
       "      <td>0.003906</td>\n",
       "      <td>85</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10th</th>\n",
       "      <td>Past</td>\n",
       "      <td>17Jun2020</td>\n",
       "      <td>28Jun2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>3.80</td>\n",
       "      <td>0.001115</td>\n",
       "      <td>1.181352e-06</td>\n",
       "      <td>0.000076</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>5</td>\n",
       "      <td>2939</td>\n",
       "      <td>0.001</td>\n",
       "      <td>185</td>\n",
       "      <td>45</td>\n",
       "      <td>0.005350</td>\n",
       "      <td>167</td>\n",
       "      <td>0 min 10 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11th</th>\n",
       "      <td>Past</td>\n",
       "      <td>29Jun2020</td>\n",
       "      <td>10Jul2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.84</td>\n",
       "      <td>0.000302</td>\n",
       "      <td>1.120876e-06</td>\n",
       "      <td>0.000098</td>\n",
       "      <td>0.000052</td>\n",
       "      <td>5</td>\n",
       "      <td>3097</td>\n",
       "      <td>0.000</td>\n",
       "      <td>66</td>\n",
       "      <td>35</td>\n",
       "      <td>0.019334</td>\n",
       "      <td>389</td>\n",
       "      <td>0 min 25 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12th</th>\n",
       "      <td>Past</td>\n",
       "      <td>11Jul2020</td>\n",
       "      <td>19Jul2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>3.68</td>\n",
       "      <td>0.000557</td>\n",
       "      <td>9.660092e-07</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>0.000026</td>\n",
       "      <td>5</td>\n",
       "      <td>3594</td>\n",
       "      <td>0.001</td>\n",
       "      <td>132</td>\n",
       "      <td>34</td>\n",
       "      <td>0.004730</td>\n",
       "      <td>88</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13th</th>\n",
       "      <td>Past</td>\n",
       "      <td>20Jul2020</td>\n",
       "      <td>27Jul2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.60</td>\n",
       "      <td>0.000154</td>\n",
       "      <td>1.368472e-06</td>\n",
       "      <td>0.000084</td>\n",
       "      <td>0.000031</td>\n",
       "      <td>5</td>\n",
       "      <td>2537</td>\n",
       "      <td>0.000</td>\n",
       "      <td>113</td>\n",
       "      <td>41</td>\n",
       "      <td>0.003915</td>\n",
       "      <td>315</td>\n",
       "      <td>0 min 20 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14th</th>\n",
       "      <td>Past</td>\n",
       "      <td>28Jul2020</td>\n",
       "      <td>04Aug2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.36</td>\n",
       "      <td>0.002051</td>\n",
       "      <td>9.132656e-07</td>\n",
       "      <td>0.000073</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>5</td>\n",
       "      <td>3801</td>\n",
       "      <td>0.002</td>\n",
       "      <td>116</td>\n",
       "      <td>47</td>\n",
       "      <td>0.005298</td>\n",
       "      <td>166</td>\n",
       "      <td>0 min 10 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15th</th>\n",
       "      <td>Past</td>\n",
       "      <td>05Aug2020</td>\n",
       "      <td>12Aug2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.33</td>\n",
       "      <td>0.000237</td>\n",
       "      <td>1.075982e-06</td>\n",
       "      <td>0.000061</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>5</td>\n",
       "      <td>3227</td>\n",
       "      <td>0.000</td>\n",
       "      <td>139</td>\n",
       "      <td>57</td>\n",
       "      <td>0.004492</td>\n",
       "      <td>243</td>\n",
       "      <td>0 min 15 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16th</th>\n",
       "      <td>Past</td>\n",
       "      <td>13Aug2020</td>\n",
       "      <td>20Aug2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.85</td>\n",
       "      <td>0.000785</td>\n",
       "      <td>1.040092e-06</td>\n",
       "      <td>0.000048</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>5</td>\n",
       "      <td>3338</td>\n",
       "      <td>0.001</td>\n",
       "      <td>140</td>\n",
       "      <td>72</td>\n",
       "      <td>0.003587</td>\n",
       "      <td>83</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17th</th>\n",
       "      <td>Past</td>\n",
       "      <td>21Aug2020</td>\n",
       "      <td>30Aug2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.06</td>\n",
       "      <td>0.000542</td>\n",
       "      <td>8.621427e-07</td>\n",
       "      <td>0.000043</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>5</td>\n",
       "      <td>4027</td>\n",
       "      <td>0.001</td>\n",
       "      <td>174</td>\n",
       "      <td>81</td>\n",
       "      <td>0.004303</td>\n",
       "      <td>88</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18th</th>\n",
       "      <td>Past</td>\n",
       "      <td>31Aug2020</td>\n",
       "      <td>08Sep2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.78</td>\n",
       "      <td>0.000159</td>\n",
       "      <td>8.757387e-07</td>\n",
       "      <td>0.000039</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>5</td>\n",
       "      <td>3964</td>\n",
       "      <td>0.000</td>\n",
       "      <td>167</td>\n",
       "      <td>89</td>\n",
       "      <td>0.003032</td>\n",
       "      <td>243</td>\n",
       "      <td>0 min 15 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19th</th>\n",
       "      <td>Past</td>\n",
       "      <td>09Sep2020</td>\n",
       "      <td>16Sep2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.14</td>\n",
       "      <td>0.000556</td>\n",
       "      <td>7.916625e-07</td>\n",
       "      <td>0.000035</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>5</td>\n",
       "      <td>4385</td>\n",
       "      <td>0.001</td>\n",
       "      <td>220</td>\n",
       "      <td>98</td>\n",
       "      <td>0.002367</td>\n",
       "      <td>80</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20th</th>\n",
       "      <td>Past</td>\n",
       "      <td>17Sep2020</td>\n",
       "      <td>01Oct2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.84</td>\n",
       "      <td>0.001068</td>\n",
       "      <td>6.361833e-07</td>\n",
       "      <td>0.000040</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>5</td>\n",
       "      <td>5457</td>\n",
       "      <td>0.001</td>\n",
       "      <td>165</td>\n",
       "      <td>87</td>\n",
       "      <td>0.004099</td>\n",
       "      <td>233</td>\n",
       "      <td>0 min 15 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21st</th>\n",
       "      <td>Past</td>\n",
       "      <td>02Oct2020</td>\n",
       "      <td>09Oct2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.03</td>\n",
       "      <td>0.000690</td>\n",
       "      <td>4.453144e-07</td>\n",
       "      <td>0.000037</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>5</td>\n",
       "      <td>7797</td>\n",
       "      <td>0.001</td>\n",
       "      <td>197</td>\n",
       "      <td>94</td>\n",
       "      <td>0.002548</td>\n",
       "      <td>88</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22nd</th>\n",
       "      <td>Past</td>\n",
       "      <td>10Oct2020</td>\n",
       "      <td>18Oct2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.75</td>\n",
       "      <td>0.000690</td>\n",
       "      <td>5.515393e-07</td>\n",
       "      <td>0.000045</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>5</td>\n",
       "      <td>6295</td>\n",
       "      <td>0.001</td>\n",
       "      <td>220</td>\n",
       "      <td>77</td>\n",
       "      <td>0.003690</td>\n",
       "      <td>86</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23rd</th>\n",
       "      <td>Past</td>\n",
       "      <td>19Oct2020</td>\n",
       "      <td>01Nov2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.71</td>\n",
       "      <td>0.000041</td>\n",
       "      <td>6.332029e-07</td>\n",
       "      <td>0.000054</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>5</td>\n",
       "      <td>5483</td>\n",
       "      <td>0.000</td>\n",
       "      <td>178</td>\n",
       "      <td>63</td>\n",
       "      <td>0.002438</td>\n",
       "      <td>307</td>\n",
       "      <td>0 min 20 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24th</th>\n",
       "      <td>Past</td>\n",
       "      <td>02Nov2020</td>\n",
       "      <td>16Nov2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>3.63</td>\n",
       "      <td>0.001383</td>\n",
       "      <td>4.963693e-07</td>\n",
       "      <td>0.000080</td>\n",
       "      <td>0.000022</td>\n",
       "      <td>5</td>\n",
       "      <td>6995</td>\n",
       "      <td>0.001</td>\n",
       "      <td>161</td>\n",
       "      <td>43</td>\n",
       "      <td>0.003908</td>\n",
       "      <td>453</td>\n",
       "      <td>0 min 30 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25th</th>\n",
       "      <td>Past</td>\n",
       "      <td>17Nov2020</td>\n",
       "      <td>24Nov2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>3.27</td>\n",
       "      <td>0.000827</td>\n",
       "      <td>7.149806e-07</td>\n",
       "      <td>0.000082</td>\n",
       "      <td>0.000024</td>\n",
       "      <td>5</td>\n",
       "      <td>4856</td>\n",
       "      <td>0.001</td>\n",
       "      <td>142</td>\n",
       "      <td>42</td>\n",
       "      <td>0.004770</td>\n",
       "      <td>161</td>\n",
       "      <td>0 min 10 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26th</th>\n",
       "      <td>Past</td>\n",
       "      <td>25Nov2020</td>\n",
       "      <td>02Dec2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.52</td>\n",
       "      <td>0.001158</td>\n",
       "      <td>5.698483e-07</td>\n",
       "      <td>0.000072</td>\n",
       "      <td>0.000028</td>\n",
       "      <td>5</td>\n",
       "      <td>6093</td>\n",
       "      <td>0.001</td>\n",
       "      <td>124</td>\n",
       "      <td>48</td>\n",
       "      <td>0.002641</td>\n",
       "      <td>391</td>\n",
       "      <td>0 min 25 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27th</th>\n",
       "      <td>Past</td>\n",
       "      <td>03Dec2020</td>\n",
       "      <td>16Dec2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.45</td>\n",
       "      <td>0.000453</td>\n",
       "      <td>8.977712e-07</td>\n",
       "      <td>0.000085</td>\n",
       "      <td>0.000034</td>\n",
       "      <td>5</td>\n",
       "      <td>3867</td>\n",
       "      <td>0.000</td>\n",
       "      <td>103</td>\n",
       "      <td>41</td>\n",
       "      <td>0.004451</td>\n",
       "      <td>459</td>\n",
       "      <td>0 min 20 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28th</th>\n",
       "      <td>Past</td>\n",
       "      <td>17Dec2020</td>\n",
       "      <td>27Dec2020</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.88</td>\n",
       "      <td>0.000542</td>\n",
       "      <td>7.270137e-07</td>\n",
       "      <td>0.000064</td>\n",
       "      <td>0.000033</td>\n",
       "      <td>5</td>\n",
       "      <td>4776</td>\n",
       "      <td>0.001</td>\n",
       "      <td>104</td>\n",
       "      <td>54</td>\n",
       "      <td>0.005252</td>\n",
       "      <td>164</td>\n",
       "      <td>0 min 10 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29th</th>\n",
       "      <td>Past</td>\n",
       "      <td>28Dec2020</td>\n",
       "      <td>05Jan2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.22</td>\n",
       "      <td>0.000692</td>\n",
       "      <td>8.853294e-07</td>\n",
       "      <td>0.000069</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>5</td>\n",
       "      <td>3921</td>\n",
       "      <td>0.001</td>\n",
       "      <td>115</td>\n",
       "      <td>50</td>\n",
       "      <td>0.002829</td>\n",
       "      <td>88</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30th</th>\n",
       "      <td>Past</td>\n",
       "      <td>06Jan2021</td>\n",
       "      <td>13Jan2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.55</td>\n",
       "      <td>0.000557</td>\n",
       "      <td>9.795121e-07</td>\n",
       "      <td>0.000068</td>\n",
       "      <td>0.000026</td>\n",
       "      <td>5</td>\n",
       "      <td>3544</td>\n",
       "      <td>0.001</td>\n",
       "      <td>134</td>\n",
       "      <td>50</td>\n",
       "      <td>0.004606</td>\n",
       "      <td>82</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31st</th>\n",
       "      <td>Past</td>\n",
       "      <td>14Jan2021</td>\n",
       "      <td>24Jan2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>2.08</td>\n",
       "      <td>0.000463</td>\n",
       "      <td>7.911269e-07</td>\n",
       "      <td>0.000049</td>\n",
       "      <td>0.000023</td>\n",
       "      <td>5</td>\n",
       "      <td>4388</td>\n",
       "      <td>0.000</td>\n",
       "      <td>152</td>\n",
       "      <td>70</td>\n",
       "      <td>0.002907</td>\n",
       "      <td>169</td>\n",
       "      <td>0 min 10 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32nd</th>\n",
       "      <td>Past</td>\n",
       "      <td>25Jan2021</td>\n",
       "      <td>04Feb2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.64</td>\n",
       "      <td>0.000543</td>\n",
       "      <td>7.723977e-07</td>\n",
       "      <td>0.000035</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>5</td>\n",
       "      <td>4495</td>\n",
       "      <td>0.001</td>\n",
       "      <td>167</td>\n",
       "      <td>98</td>\n",
       "      <td>0.002696</td>\n",
       "      <td>87</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33rd</th>\n",
       "      <td>Past</td>\n",
       "      <td>05Feb2021</td>\n",
       "      <td>16Feb2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.20</td>\n",
       "      <td>0.000867</td>\n",
       "      <td>4.843029e-07</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>5</td>\n",
       "      <td>7169</td>\n",
       "      <td>0.001</td>\n",
       "      <td>173</td>\n",
       "      <td>140</td>\n",
       "      <td>0.002506</td>\n",
       "      <td>160</td>\n",
       "      <td>0 min 10 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34th</th>\n",
       "      <td>Past</td>\n",
       "      <td>17Feb2021</td>\n",
       "      <td>27Feb2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.001580</td>\n",
       "      <td>5.257516e-07</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>5</td>\n",
       "      <td>6604</td>\n",
       "      <td>0.002</td>\n",
       "      <td>187</td>\n",
       "      <td>205</td>\n",
       "      <td>0.001844</td>\n",
       "      <td>88</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35th</th>\n",
       "      <td>Past</td>\n",
       "      <td>28Feb2021</td>\n",
       "      <td>10Mar2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>0.87</td>\n",
       "      <td>0.001579</td>\n",
       "      <td>3.779337e-07</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>5</td>\n",
       "      <td>9187</td>\n",
       "      <td>0.002</td>\n",
       "      <td>198</td>\n",
       "      <td>223</td>\n",
       "      <td>0.001032</td>\n",
       "      <td>83</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36th</th>\n",
       "      <td>Past</td>\n",
       "      <td>11Mar2021</td>\n",
       "      <td>22Mar2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>0.84</td>\n",
       "      <td>0.001579</td>\n",
       "      <td>2.991591e-07</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>5</td>\n",
       "      <td>11606</td>\n",
       "      <td>0.002</td>\n",
       "      <td>210</td>\n",
       "      <td>245</td>\n",
       "      <td>0.001917</td>\n",
       "      <td>83</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37th</th>\n",
       "      <td>Past</td>\n",
       "      <td>23Mar2021</td>\n",
       "      <td>03Apr2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.17</td>\n",
       "      <td>0.000184</td>\n",
       "      <td>3.067557e-07</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>5</td>\n",
       "      <td>11319</td>\n",
       "      <td>0.000</td>\n",
       "      <td>229</td>\n",
       "      <td>191</td>\n",
       "      <td>0.001901</td>\n",
       "      <td>82</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38th</th>\n",
       "      <td>Past</td>\n",
       "      <td>04Apr2021</td>\n",
       "      <td>13Apr2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.27</td>\n",
       "      <td>0.000786</td>\n",
       "      <td>2.956837e-07</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>5</td>\n",
       "      <td>11743</td>\n",
       "      <td>0.001</td>\n",
       "      <td>238</td>\n",
       "      <td>183</td>\n",
       "      <td>0.001783</td>\n",
       "      <td>82</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39th</th>\n",
       "      <td>Past</td>\n",
       "      <td>14Apr2021</td>\n",
       "      <td>25Apr2021</td>\n",
       "      <td>326687501</td>\n",
       "      <td>SIR-F</td>\n",
       "      <td>1.25</td>\n",
       "      <td>0.003307</td>\n",
       "      <td>1.110903e-07</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>0.000013</td>\n",
       "      <td>5</td>\n",
       "      <td>31255</td>\n",
       "      <td>0.003</td>\n",
       "      <td>263</td>\n",
       "      <td>208</td>\n",
       "      <td>0.000633</td>\n",
       "      <td>178</td>\n",
       "      <td>0 min  5 sec</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Type      Start        End  Population    ODE     Rt     theta  \\\n",
       "0th   Past  09Feb2020  16Mar2020   326687501  SIR-F  20.91  0.000093   \n",
       "1st   Past  17Mar2020  30Mar2020   326687501  SIR-F  42.05  0.003022   \n",
       "2nd   Past  31Mar2020  10Apr2020   326687501  SIR-F   8.62  0.000740   \n",
       "3rd   Past  11Apr2020  22Apr2020   326687501  SIR-F   4.09  0.000231   \n",
       "4th   Past  23Apr2020  03May2020   326687501  SIR-F   2.52  0.000703   \n",
       "5th   Past  04May2020  14May2020   326687501  SIR-F   3.20  0.002534   \n",
       "6th   Past  15May2020  22May2020   326687501  SIR-F   1.83  0.000117   \n",
       "7th   Past  23May2020  31May2020   326687501  SIR-F   2.18  0.000468   \n",
       "8th   Past  01Jun2020  08Jun2020   326687501  SIR-F   2.22  0.001819   \n",
       "9th   Past  09Jun2020  16Jun2020   326687501  SIR-F   2.50  0.000556   \n",
       "10th  Past  17Jun2020  28Jun2020   326687501  SIR-F   3.80  0.001115   \n",
       "11th  Past  29Jun2020  10Jul2020   326687501  SIR-F   1.84  0.000302   \n",
       "12th  Past  11Jul2020  19Jul2020   326687501  SIR-F   3.68  0.000557   \n",
       "13th  Past  20Jul2020  27Jul2020   326687501  SIR-F   2.60  0.000154   \n",
       "14th  Past  28Jul2020  04Aug2020   326687501  SIR-F   2.36  0.002051   \n",
       "15th  Past  05Aug2020  12Aug2020   326687501  SIR-F   2.33  0.000237   \n",
       "16th  Past  13Aug2020  20Aug2020   326687501  SIR-F   1.85  0.000785   \n",
       "17th  Past  21Aug2020  30Aug2020   326687501  SIR-F   2.06  0.000542   \n",
       "18th  Past  31Aug2020  08Sep2020   326687501  SIR-F   1.78  0.000159   \n",
       "19th  Past  09Sep2020  16Sep2020   326687501  SIR-F   2.14  0.000556   \n",
       "20th  Past  17Sep2020  01Oct2020   326687501  SIR-F   1.84  0.001068   \n",
       "21st  Past  02Oct2020  09Oct2020   326687501  SIR-F   2.03  0.000690   \n",
       "22nd  Past  10Oct2020  18Oct2020   326687501  SIR-F   2.75  0.000690   \n",
       "23rd  Past  19Oct2020  01Nov2020   326687501  SIR-F   2.71  0.000041   \n",
       "24th  Past  02Nov2020  16Nov2020   326687501  SIR-F   3.63  0.001383   \n",
       "25th  Past  17Nov2020  24Nov2020   326687501  SIR-F   3.27  0.000827   \n",
       "26th  Past  25Nov2020  02Dec2020   326687501  SIR-F   2.52  0.001158   \n",
       "27th  Past  03Dec2020  16Dec2020   326687501  SIR-F   2.45  0.000453   \n",
       "28th  Past  17Dec2020  27Dec2020   326687501  SIR-F   1.88  0.000542   \n",
       "29th  Past  28Dec2020  05Jan2021   326687501  SIR-F   2.22  0.000692   \n",
       "30th  Past  06Jan2021  13Jan2021   326687501  SIR-F   2.55  0.000557   \n",
       "31st  Past  14Jan2021  24Jan2021   326687501  SIR-F   2.08  0.000463   \n",
       "32nd  Past  25Jan2021  04Feb2021   326687501  SIR-F   1.64  0.000543   \n",
       "33rd  Past  05Feb2021  16Feb2021   326687501  SIR-F   1.20  0.000867   \n",
       "34th  Past  17Feb2021  27Feb2021   326687501  SIR-F   0.88  0.001580   \n",
       "35th  Past  28Feb2021  10Mar2021   326687501  SIR-F   0.87  0.001579   \n",
       "36th  Past  11Mar2021  22Mar2021   326687501  SIR-F   0.84  0.001579   \n",
       "37th  Past  23Mar2021  03Apr2021   326687501  SIR-F   1.17  0.000184   \n",
       "38th  Past  04Apr2021  13Apr2021   326687501  SIR-F   1.27  0.000786   \n",
       "39th  Past  14Apr2021  25Apr2021   326687501  SIR-F   1.25  0.003307   \n",
       "\n",
       "             kappa       rho     sigma  tau  1/alpha2 [day]  alpha1 [-]  \\\n",
       "0th   1.548798e-05  0.000471  0.000007    5             224       0.000   \n",
       "1st   1.578128e-05  0.001018  0.000008    5             220       0.003   \n",
       "2nd   2.127978e-05  0.000403  0.000025    5             163       0.001   \n",
       "3rd   1.325074e-05  0.000169  0.000028    5             262       0.000   \n",
       "4th   7.712115e-06  0.000120  0.000040    5             450       0.001   \n",
       "5th   5.720253e-06  0.000084  0.000020    5             607       0.003   \n",
       "6th   3.813866e-06  0.000066  0.000032    5             910       0.000   \n",
       "7th   2.547060e-06  0.000059  0.000025    5            1363       0.000   \n",
       "8th   2.151768e-06  0.000055  0.000023    5            1613       0.002   \n",
       "9th   2.007320e-06  0.000054  0.000020    5            1729       0.001   \n",
       "10th  1.181352e-06  0.000076  0.000019    5            2939       0.001   \n",
       "11th  1.120876e-06  0.000098  0.000052    5            3097       0.000   \n",
       "12th  9.660092e-07  0.000100  0.000026    5            3594       0.001   \n",
       "13th  1.368472e-06  0.000084  0.000031    5            2537       0.000   \n",
       "14th  9.132656e-07  0.000073  0.000030    5            3801       0.002   \n",
       "15th  1.075982e-06  0.000061  0.000025    5            3227       0.000   \n",
       "16th  1.040092e-06  0.000048  0.000025    5            3338       0.001   \n",
       "17th  8.621427e-07  0.000043  0.000020    5            4027       0.001   \n",
       "18th  8.757387e-07  0.000039  0.000021    5            3964       0.000   \n",
       "19th  7.916625e-07  0.000035  0.000016    5            4385       0.001   \n",
       "20th  6.361833e-07  0.000040  0.000021    5            5457       0.001   \n",
       "21st  4.453144e-07  0.000037  0.000018    5            7797       0.001   \n",
       "22nd  5.515393e-07  0.000045  0.000016    5            6295       0.001   \n",
       "23rd  6.332029e-07  0.000054  0.000019    5            5483       0.000   \n",
       "24th  4.963693e-07  0.000080  0.000022    5            6995       0.001   \n",
       "25th  7.149806e-07  0.000082  0.000024    5            4856       0.001   \n",
       "26th  5.698483e-07  0.000072  0.000028    5            6093       0.001   \n",
       "27th  8.977712e-07  0.000085  0.000034    5            3867       0.000   \n",
       "28th  7.270137e-07  0.000064  0.000033    5            4776       0.001   \n",
       "29th  8.853294e-07  0.000069  0.000030    5            3921       0.001   \n",
       "30th  9.795121e-07  0.000068  0.000026    5            3544       0.001   \n",
       "31st  7.911269e-07  0.000049  0.000023    5            4388       0.000   \n",
       "32nd  7.723977e-07  0.000035  0.000021    5            4495       0.001   \n",
       "33rd  4.843029e-07  0.000025  0.000020    5            7169       0.001   \n",
       "34th  5.257516e-07  0.000017  0.000019    5            6604       0.002   \n",
       "35th  3.779337e-07  0.000016  0.000018    5            9187       0.002   \n",
       "36th  2.991591e-07  0.000014  0.000016    5           11606       0.002   \n",
       "37th  3.067557e-07  0.000018  0.000015    5           11319       0.000   \n",
       "38th  2.956837e-07  0.000019  0.000015    5           11743       0.001   \n",
       "39th  1.110903e-07  0.000017  0.000013    5           31255       0.003   \n",
       "\n",
       "      1/gamma [day]  1/beta [day]     RMSLE  Trials       Runtime  \n",
       "0th             491             7  0.798572     377  0 min 25 sec  \n",
       "1st             414             3  0.244587     512  0 min 35 sec  \n",
       "2nd             136             8  0.061326     523  0 min 35 sec  \n",
       "3rd             123            20  0.035246     579  0 min 40 sec  \n",
       "4th              87            28  0.037127     770  0 min 55 sec  \n",
       "5th             170            41  0.019415     167  0 min 10 sec  \n",
       "6th             106            52  0.021118     903  1 min  6 sec  \n",
       "7th             140            58  0.008624    1833  1 min 25 sec  \n",
       "8th             152            62  0.003859      89  0 min  5 sec  \n",
       "9th             177            64  0.003906      85  0 min  5 sec  \n",
       "10th            185            45  0.005350     167  0 min 10 sec  \n",
       "11th             66            35  0.019334     389  0 min 25 sec  \n",
       "12th            132            34  0.004730      88  0 min  5 sec  \n",
       "13th            113            41  0.003915     315  0 min 20 sec  \n",
       "14th            116            47  0.005298     166  0 min 10 sec  \n",
       "15th            139            57  0.004492     243  0 min 15 sec  \n",
       "16th            140            72  0.003587      83  0 min  5 sec  \n",
       "17th            174            81  0.004303      88  0 min  5 sec  \n",
       "18th            167            89  0.003032     243  0 min 15 sec  \n",
       "19th            220            98  0.002367      80  0 min  5 sec  \n",
       "20th            165            87  0.004099     233  0 min 15 sec  \n",
       "21st            197            94  0.002548      88  0 min  5 sec  \n",
       "22nd            220            77  0.003690      86  0 min  5 sec  \n",
       "23rd            178            63  0.002438     307  0 min 20 sec  \n",
       "24th            161            43  0.003908     453  0 min 30 sec  \n",
       "25th            142            42  0.004770     161  0 min 10 sec  \n",
       "26th            124            48  0.002641     391  0 min 25 sec  \n",
       "27th            103            41  0.004451     459  0 min 20 sec  \n",
       "28th            104            54  0.005252     164  0 min 10 sec  \n",
       "29th            115            50  0.002829      88  0 min  5 sec  \n",
       "30th            134            50  0.004606      82  0 min  5 sec  \n",
       "31st            152            70  0.002907     169  0 min 10 sec  \n",
       "32nd            167            98  0.002696      87  0 min  5 sec  \n",
       "33rd            173           140  0.002506     160  0 min 10 sec  \n",
       "34th            187           205  0.001844      88  0 min  5 sec  \n",
       "35th            198           223  0.001032      83  0 min  5 sec  \n",
       "36th            210           245  0.001917      83  0 min  5 sec  \n",
       "37th            229           191  0.001901      82  0 min  5 sec  \n",
       "38th            238           183  0.001783      82  0 min  5 sec  \n",
       "39th            263           208  0.000633     178  0 min  5 sec  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_scenario_new.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 648x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
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       "            background-color:  #0872b1;\n",
       "            color:  #f1f1f1;\n",
       "        }#T_5a82d_row20_col3{\n",
       "            background-color:  #0771b1;\n",
       "            color:  #f1f1f1;\n",
       "        }#T_5a82d_row21_col1,#T_5a82d_row21_col2,#T_5a82d_row21_col4{\n",
       "            background-color:  #056ba9;\n",
       "            color:  #f1f1f1;\n",
       "        }#T_5a82d_row21_col3{\n",
       "            background-color:  #056aa6;\n",
       "            color:  #f1f1f1;\n",
       "        }#T_5a82d_row22_col1,#T_5a82d_row22_col2,#T_5a82d_row22_col4{\n",
       "            background-color:  #04649e;\n",
       "            color:  #f1f1f1;\n",
       "        }#T_5a82d_row22_col3{\n",
       "            background-color:  #04649d;\n",
       "            color:  #f1f1f1;\n",
       "        }#T_5a82d_row23_col1,#T_5a82d_row23_col2,#T_5a82d_row23_col4{\n",
       "            background-color:  #045e94;\n",
       "            color:  #f1f1f1;\n",
       "        }#T_5a82d_row23_col3{\n",
       "            background-color:  #045e93;\n",
       "            color:  #f1f1f1;\n",
       "        }#T_5a82d_row24_col1,#T_5a82d_row24_col2,#T_5a82d_row24_col4{\n",
       "            background-color:  #045687;\n",
       "            color:  #f1f1f1;\n",
       "        }#T_5a82d_row24_col3{\n",
       "            background-color:  #045585;\n",
       "            color:  #f1f1f1;\n",
       "        }#T_5a82d_row25_col1,#T_5a82d_row25_col2,#T_5a82d_row25_col4{\n",
       "            background-color:  #034c78;\n",
       "            color:  #f1f1f1;\n",
       "        }#T_5a82d_row25_col3{\n",
       "            background-color:  #034b76;\n",
       "            color:  #f1f1f1;\n",
       "        }#T_5a82d_row26_col1,#T_5a82d_row26_col2,#T_5a82d_row26_col3,#T_5a82d_row26_col4{\n",
       "            background-color:  #034267;\n",
       "            color:  #f1f1f1;\n",
       "        }#T_5a82d_row27_col1,#T_5a82d_row27_col2,#T_5a82d_row27_col3,#T_5a82d_row27_col4{\n",
       "            background-color:  #023858;\n",
       "            color:  #f1f1f1;\n",
       "        }</style><table id=\"T_5a82d_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Date</th>        <th class=\"col_heading level0 col1\" >Confirmed</th>        <th class=\"col_heading level0 col2\" >Fatal</th>        <th class=\"col_heading level0 col3\" >Infected</th>        <th class=\"col_heading level0 col4\" >Recovered</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_5a82d_level0_row0\" class=\"row_heading level0 row0\" >450</th>\n",
       "                        <td id=\"T_5a82d_row0_col0\" class=\"data row0 col0\" >2021-05-04 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row0_col1\" class=\"data row0 col1\" >32674949</td>\n",
       "                        <td id=\"T_5a82d_row0_col2\" class=\"data row0 col2\" >577987</td>\n",
       "                        <td id=\"T_5a82d_row0_col3\" class=\"data row0 col3\" >14527901</td>\n",
       "                        <td id=\"T_5a82d_row0_col4\" class=\"data row0 col4\" >17569061</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row1\" class=\"row_heading level0 row1\" >451</th>\n",
       "                        <td id=\"T_5a82d_row1_col0\" class=\"data row1 col0\" >2021-05-05 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row1_col1\" class=\"data row1 col1\" >32737812</td>\n",
       "                        <td id=\"T_5a82d_row1_col2\" class=\"data row1 col2\" >578660</td>\n",
       "                        <td id=\"T_5a82d_row1_col3\" class=\"data row1 col3\" >14534954</td>\n",
       "                        <td id=\"T_5a82d_row1_col4\" class=\"data row1 col4\" >17624198</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row2\" class=\"row_heading level0 row2\" >452</th>\n",
       "                        <td id=\"T_5a82d_row2_col0\" class=\"data row2 col0\" >2021-05-06 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row2_col1\" class=\"data row2 col1\" >32800693</td>\n",
       "                        <td id=\"T_5a82d_row2_col2\" class=\"data row2 col2\" >579333</td>\n",
       "                        <td id=\"T_5a82d_row2_col3\" class=\"data row2 col3\" >14541997</td>\n",
       "                        <td id=\"T_5a82d_row2_col4\" class=\"data row2 col4\" >17679363</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row3\" class=\"row_heading level0 row3\" >453</th>\n",
       "                        <td id=\"T_5a82d_row3_col0\" class=\"data row3 col0\" >2021-05-07 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row3_col1\" class=\"data row3 col1\" >32863588</td>\n",
       "                        <td id=\"T_5a82d_row3_col2\" class=\"data row3 col2\" >580006</td>\n",
       "                        <td id=\"T_5a82d_row3_col3\" class=\"data row3 col3\" >14549029</td>\n",
       "                        <td id=\"T_5a82d_row3_col4\" class=\"data row3 col4\" >17734553</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row4\" class=\"row_heading level0 row4\" >454</th>\n",
       "                        <td id=\"T_5a82d_row4_col0\" class=\"data row4 col0\" >2021-05-08 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row4_col1\" class=\"data row4 col1\" >32926503</td>\n",
       "                        <td id=\"T_5a82d_row4_col2\" class=\"data row4 col2\" >580680</td>\n",
       "                        <td id=\"T_5a82d_row4_col3\" class=\"data row4 col3\" >14556052</td>\n",
       "                        <td id=\"T_5a82d_row4_col4\" class=\"data row4 col4\" >17789771</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row5\" class=\"row_heading level0 row5\" >455</th>\n",
       "                        <td id=\"T_5a82d_row5_col0\" class=\"data row5 col0\" >2021-05-09 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row5_col1\" class=\"data row5 col1\" >32989434</td>\n",
       "                        <td id=\"T_5a82d_row5_col2\" class=\"data row5 col2\" >581354</td>\n",
       "                        <td id=\"T_5a82d_row5_col3\" class=\"data row5 col3\" >14563065</td>\n",
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       "                        <th id=\"T_5a82d_level0_row6\" class=\"row_heading level0 row6\" >456</th>\n",
       "                        <td id=\"T_5a82d_row6_col0\" class=\"data row6 col0\" >2021-05-10 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row6_col1\" class=\"data row6 col1\" >33052381</td>\n",
       "                        <td id=\"T_5a82d_row6_col2\" class=\"data row6 col2\" >582028</td>\n",
       "                        <td id=\"T_5a82d_row6_col3\" class=\"data row6 col3\" >14570068</td>\n",
       "                        <td id=\"T_5a82d_row6_col4\" class=\"data row6 col4\" >17900285</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row7\" class=\"row_heading level0 row7\" >457</th>\n",
       "                        <td id=\"T_5a82d_row7_col0\" class=\"data row7 col0\" >2021-05-11 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row7_col1\" class=\"data row7 col1\" >33115345</td>\n",
       "                        <td id=\"T_5a82d_row7_col2\" class=\"data row7 col2\" >582702</td>\n",
       "                        <td id=\"T_5a82d_row7_col3\" class=\"data row7 col3\" >14577060</td>\n",
       "                        <td id=\"T_5a82d_row7_col4\" class=\"data row7 col4\" >17955583</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row8\" class=\"row_heading level0 row8\" >458</th>\n",
       "                        <td id=\"T_5a82d_row8_col0\" class=\"data row8 col0\" >2021-05-12 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row8_col1\" class=\"data row8 col1\" >33178326</td>\n",
       "                        <td id=\"T_5a82d_row8_col2\" class=\"data row8 col2\" >583377</td>\n",
       "                        <td id=\"T_5a82d_row8_col3\" class=\"data row8 col3\" >14584043</td>\n",
       "                        <td id=\"T_5a82d_row8_col4\" class=\"data row8 col4\" >18010906</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row9\" class=\"row_heading level0 row9\" >459</th>\n",
       "                        <td id=\"T_5a82d_row9_col0\" class=\"data row9 col0\" >2021-05-13 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row9_col1\" class=\"data row9 col1\" >33241323</td>\n",
       "                        <td id=\"T_5a82d_row9_col2\" class=\"data row9 col2\" >584052</td>\n",
       "                        <td id=\"T_5a82d_row9_col3\" class=\"data row9 col3\" >14591015</td>\n",
       "                        <td id=\"T_5a82d_row9_col4\" class=\"data row9 col4\" >18066256</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row10\" class=\"row_heading level0 row10\" >460</th>\n",
       "                        <td id=\"T_5a82d_row10_col0\" class=\"data row10 col0\" >2021-05-14 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row10_col1\" class=\"data row10 col1\" >33304338</td>\n",
       "                        <td id=\"T_5a82d_row10_col2\" class=\"data row10 col2\" >584727</td>\n",
       "                        <td id=\"T_5a82d_row10_col3\" class=\"data row10 col3\" >14597978</td>\n",
       "                        <td id=\"T_5a82d_row10_col4\" class=\"data row10 col4\" >18121633</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row11\" class=\"row_heading level0 row11\" >461</th>\n",
       "                        <td id=\"T_5a82d_row11_col0\" class=\"data row11 col0\" >2021-05-15 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row11_col1\" class=\"data row11 col1\" >33367369</td>\n",
       "                        <td id=\"T_5a82d_row11_col2\" class=\"data row11 col2\" >585403</td>\n",
       "                        <td id=\"T_5a82d_row11_col3\" class=\"data row11 col3\" >14604930</td>\n",
       "                        <td id=\"T_5a82d_row11_col4\" class=\"data row11 col4\" >18177036</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row12\" class=\"row_heading level0 row12\" >462</th>\n",
       "                        <td id=\"T_5a82d_row12_col0\" class=\"data row12 col0\" >2021-05-16 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row12_col1\" class=\"data row12 col1\" >33430416</td>\n",
       "                        <td id=\"T_5a82d_row12_col2\" class=\"data row12 col2\" >586079</td>\n",
       "                        <td id=\"T_5a82d_row12_col3\" class=\"data row12 col3\" >14611872</td>\n",
       "                        <td id=\"T_5a82d_row12_col4\" class=\"data row12 col4\" >18232465</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row13\" class=\"row_heading level0 row13\" >463</th>\n",
       "                        <td id=\"T_5a82d_row13_col0\" class=\"data row13 col0\" >2021-05-17 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row13_col1\" class=\"data row13 col1\" >33493479</td>\n",
       "                        <td id=\"T_5a82d_row13_col2\" class=\"data row13 col2\" >586755</td>\n",
       "                        <td id=\"T_5a82d_row13_col3\" class=\"data row13 col3\" >14618803</td>\n",
       "                        <td id=\"T_5a82d_row13_col4\" class=\"data row13 col4\" >18287921</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row14\" class=\"row_heading level0 row14\" >464</th>\n",
       "                        <td id=\"T_5a82d_row14_col0\" class=\"data row14 col0\" >2021-05-18 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row14_col1\" class=\"data row14 col1\" >33556559</td>\n",
       "                        <td id=\"T_5a82d_row14_col2\" class=\"data row14 col2\" >587431</td>\n",
       "                        <td id=\"T_5a82d_row14_col3\" class=\"data row14 col3\" >14625725</td>\n",
       "                        <td id=\"T_5a82d_row14_col4\" class=\"data row14 col4\" >18343403</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row15\" class=\"row_heading level0 row15\" >465</th>\n",
       "                        <td id=\"T_5a82d_row15_col0\" class=\"data row15 col0\" >2021-05-19 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row15_col1\" class=\"data row15 col1\" >33619655</td>\n",
       "                        <td id=\"T_5a82d_row15_col2\" class=\"data row15 col2\" >588108</td>\n",
       "                        <td id=\"T_5a82d_row15_col3\" class=\"data row15 col3\" >14632636</td>\n",
       "                        <td id=\"T_5a82d_row15_col4\" class=\"data row15 col4\" >18398911</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row16\" class=\"row_heading level0 row16\" >466</th>\n",
       "                        <td id=\"T_5a82d_row16_col0\" class=\"data row16 col0\" >2021-05-20 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row16_col1\" class=\"data row16 col1\" >33682768</td>\n",
       "                        <td id=\"T_5a82d_row16_col2\" class=\"data row16 col2\" >588785</td>\n",
       "                        <td id=\"T_5a82d_row16_col3\" class=\"data row16 col3\" >14639537</td>\n",
       "                        <td id=\"T_5a82d_row16_col4\" class=\"data row16 col4\" >18454446</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row17\" class=\"row_heading level0 row17\" >467</th>\n",
       "                        <td id=\"T_5a82d_row17_col0\" class=\"data row17 col0\" >2021-05-21 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row17_col1\" class=\"data row17 col1\" >33745895</td>\n",
       "                        <td id=\"T_5a82d_row17_col2\" class=\"data row17 col2\" >589462</td>\n",
       "                        <td id=\"T_5a82d_row17_col3\" class=\"data row17 col3\" >14646427</td>\n",
       "                        <td id=\"T_5a82d_row17_col4\" class=\"data row17 col4\" >18510006</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row18\" class=\"row_heading level0 row18\" >468</th>\n",
       "                        <td id=\"T_5a82d_row18_col0\" class=\"data row18 col0\" >2021-05-22 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row18_col1\" class=\"data row18 col1\" >33809040</td>\n",
       "                        <td id=\"T_5a82d_row18_col2\" class=\"data row18 col2\" >590140</td>\n",
       "                        <td id=\"T_5a82d_row18_col3\" class=\"data row18 col3\" >14653307</td>\n",
       "                        <td id=\"T_5a82d_row18_col4\" class=\"data row18 col4\" >18565593</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row19\" class=\"row_heading level0 row19\" >469</th>\n",
       "                        <td id=\"T_5a82d_row19_col0\" class=\"data row19 col0\" >2021-05-23 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row19_col1\" class=\"data row19 col1\" >33872201</td>\n",
       "                        <td id=\"T_5a82d_row19_col2\" class=\"data row19 col2\" >590818</td>\n",
       "                        <td id=\"T_5a82d_row19_col3\" class=\"data row19 col3\" >14660177</td>\n",
       "                        <td id=\"T_5a82d_row19_col4\" class=\"data row19 col4\" >18621206</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row20\" class=\"row_heading level0 row20\" >470</th>\n",
       "                        <td id=\"T_5a82d_row20_col0\" class=\"data row20 col0\" >2021-05-24 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row20_col1\" class=\"data row20 col1\" >33935378</td>\n",
       "                        <td id=\"T_5a82d_row20_col2\" class=\"data row20 col2\" >591496</td>\n",
       "                        <td id=\"T_5a82d_row20_col3\" class=\"data row20 col3\" >14667037</td>\n",
       "                        <td id=\"T_5a82d_row20_col4\" class=\"data row20 col4\" >18676845</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row21\" class=\"row_heading level0 row21\" >471</th>\n",
       "                        <td id=\"T_5a82d_row21_col0\" class=\"data row21 col0\" >2021-05-25 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row21_col1\" class=\"data row21 col1\" >33998569</td>\n",
       "                        <td id=\"T_5a82d_row21_col2\" class=\"data row21 col2\" >592174</td>\n",
       "                        <td id=\"T_5a82d_row21_col3\" class=\"data row21 col3\" >14673886</td>\n",
       "                        <td id=\"T_5a82d_row21_col4\" class=\"data row21 col4\" >18732509</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row22\" class=\"row_heading level0 row22\" >472</th>\n",
       "                        <td id=\"T_5a82d_row22_col0\" class=\"data row22 col0\" >2021-05-26 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row22_col1\" class=\"data row22 col1\" >34061777</td>\n",
       "                        <td id=\"T_5a82d_row22_col2\" class=\"data row22 col2\" >592853</td>\n",
       "                        <td id=\"T_5a82d_row22_col3\" class=\"data row22 col3\" >14680724</td>\n",
       "                        <td id=\"T_5a82d_row22_col4\" class=\"data row22 col4\" >18788200</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row23\" class=\"row_heading level0 row23\" >473</th>\n",
       "                        <td id=\"T_5a82d_row23_col0\" class=\"data row23 col0\" >2021-05-27 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row23_col1\" class=\"data row23 col1\" >34125001</td>\n",
       "                        <td id=\"T_5a82d_row23_col2\" class=\"data row23 col2\" >593531</td>\n",
       "                        <td id=\"T_5a82d_row23_col3\" class=\"data row23 col3\" >14687553</td>\n",
       "                        <td id=\"T_5a82d_row23_col4\" class=\"data row23 col4\" >18843917</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row24\" class=\"row_heading level0 row24\" >474</th>\n",
       "                        <td id=\"T_5a82d_row24_col0\" class=\"data row24 col0\" >2021-05-28 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row24_col1\" class=\"data row24 col1\" >34188242</td>\n",
       "                        <td id=\"T_5a82d_row24_col2\" class=\"data row24 col2\" >594211</td>\n",
       "                        <td id=\"T_5a82d_row24_col3\" class=\"data row24 col3\" >14694371</td>\n",
       "                        <td id=\"T_5a82d_row24_col4\" class=\"data row24 col4\" >18899660</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row25\" class=\"row_heading level0 row25\" >475</th>\n",
       "                        <td id=\"T_5a82d_row25_col0\" class=\"data row25 col0\" >2021-05-29 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row25_col1\" class=\"data row25 col1\" >34251496</td>\n",
       "                        <td id=\"T_5a82d_row25_col2\" class=\"data row25 col2\" >594890</td>\n",
       "                        <td id=\"T_5a82d_row25_col3\" class=\"data row25 col3\" >14701178</td>\n",
       "                        <td id=\"T_5a82d_row25_col4\" class=\"data row25 col4\" >18955428</td>\n",
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       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row26\" class=\"row_heading level0 row26\" >476</th>\n",
       "                        <td id=\"T_5a82d_row26_col0\" class=\"data row26 col0\" >2021-05-30 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row26_col1\" class=\"data row26 col1\" >34314767</td>\n",
       "                        <td id=\"T_5a82d_row26_col2\" class=\"data row26 col2\" >595570</td>\n",
       "                        <td id=\"T_5a82d_row26_col3\" class=\"data row26 col3\" >14707975</td>\n",
       "                        <td id=\"T_5a82d_row26_col4\" class=\"data row26 col4\" >19011222</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_5a82d_level0_row27\" class=\"row_heading level0 row27\" >477</th>\n",
       "                        <td id=\"T_5a82d_row27_col0\" class=\"data row27 col0\" >2021-05-31 00:00:00</td>\n",
       "                        <td id=\"T_5a82d_row27_col1\" class=\"data row27 col1\" >34378053</td>\n",
       "                        <td id=\"T_5a82d_row27_col2\" class=\"data row27 col2\" >596250</td>\n",
       "                        <td id=\"T_5a82d_row27_col3\" class=\"data row27 col3\" >14714761</td>\n",
       "                        <td id=\"T_5a82d_row27_col4\" class=\"data row27 col4\" >19067042</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fe3df64a550>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_scenario_new.clear()\n",
    "us_scenario_new.add(days=35)\n",
    "us_scenario_new.simulate().tail(28).style.background_gradient(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "test = us_scenario_new.simulate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Fatal</th>\n",
       "      <th>Infected</th>\n",
       "      <th>Recovered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-02-09</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-02-10</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-02-11</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-02-12</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>2021-05-27</td>\n",
       "      <td>34125001</td>\n",
       "      <td>593531</td>\n",
       "      <td>14687553</td>\n",
       "      <td>18843917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>474</th>\n",
       "      <td>2021-05-28</td>\n",
       "      <td>34188242</td>\n",
       "      <td>594211</td>\n",
       "      <td>14694371</td>\n",
       "      <td>18899660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>475</th>\n",
       "      <td>2021-05-29</td>\n",
       "      <td>34251496</td>\n",
       "      <td>594890</td>\n",
       "      <td>14701178</td>\n",
       "      <td>18955428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>476</th>\n",
       "      <td>2021-05-30</td>\n",
       "      <td>34314767</td>\n",
       "      <td>595570</td>\n",
       "      <td>14707975</td>\n",
       "      <td>19011222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477</th>\n",
       "      <td>2021-05-31</td>\n",
       "      <td>34378053</td>\n",
       "      <td>596250</td>\n",
       "      <td>14714761</td>\n",
       "      <td>19067042</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>478 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date  Confirmed   Fatal  Infected  Recovered\n",
       "0   2020-02-09         12       0         9          3\n",
       "1   2020-02-10         13       0        10          3\n",
       "2   2020-02-11         15       0        12          3\n",
       "3   2020-02-12         16       0        13          3\n",
       "4   2020-02-13         18       0        15          3\n",
       "..         ...        ...     ...       ...        ...\n",
       "473 2021-05-27   34125001  593531  14687553   18843917\n",
       "474 2021-05-28   34188242  594211  14694371   18899660\n",
       "475 2021-05-29   34251496  594890  14701178   18955428\n",
       "476 2021-05-30   34314767  595570  14707975   19011222\n",
       "477 2021-05-31   34378053  596250  14714761   19067042\n",
       "\n",
       "[478 rows x 5 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fe3e60a1310>]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.plot(test[\"Date\"], test[\"Confirmed\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}