analysis/analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "from venn import venn\n",
    "from datetime import datetime, timedelta\n",
    "%matplotlib inline\n",
    "os.chdir('../')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('output/input_alternative.csv', parse_dates=[\"hospital_admission_any_cause_date\", \"ae_attendance_any_cause_date\", \"emergency_hospital_admission_date\", \"emergency_primary_covid_hospital_admission_date\", \"emergency_covid_hospital_admission_date\", \"ae_attendance_before_emergency_covid_hospital_admission_date\", \"ae_attendance_before_prim_emergency_covid_hospital_admission_date\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "num patients: 10000\n"
     ]
    }
   ],
   "source": [
    "num_patients=len(df[\"patient_id\"].unique())\n",
    "print(\"num patients:\", num_patients)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "num_patients_hospital_admission = len(df.loc[df[\"hospital_admission_any_cause\"]==1,\"patient_id\"])\n",
    "\n",
    "\n",
    "num_patients_emergency_hospital_admission = len(df.loc[df[\"emergency_hospital_admission_date\"].notnull(),\"patient_id\"])\n",
    "\n",
    "\n",
    "num_patients_emergency_covid_hospital_admission = len(df.loc[df[\"emergency_covid_hospital_admission_date\"].notnull(),\"patient_id\"])\n",
    "\n",
    "num_patients_emergency_primary_covid_hospital_admission = len(df.loc[df[\"emergency_primary_covid_hospital_admission_date\"].notnull(),\"patient_id\"])\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>hospital_admission</th>\n",
       "      <td>3000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>emergency_hospital_admission</th>\n",
       "      <td>3000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>emergency_admission_covid</th>\n",
       "      <td>3000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>emergency_admission_primary_covid</th>\n",
       "      <td>3000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      0\n",
       "hospital_admission                 3000\n",
       "emergency_hospital_admission       3000\n",
       "emergency_admission_covid          3000\n",
       "emergency_admission_primary_covid  3000"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hospitalisation_dict = {\n",
    "    \"hospital_admission\": num_patients_hospital_admission,\n",
    "    \"emergency_hospital_admission\": num_patients_emergency_hospital_admission,\n",
    "    \"emergency_admission_covid\": num_patients_emergency_covid_hospital_admission,\n",
    "    \"emergency_admission_primary_covid\": num_patients_emergency_primary_covid_hospital_admission\n",
    "}\n",
    "\n",
    "pd.DataFrame.from_dict(hospitalisation_dict, orient='index')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A&E before COVID emergency hospital admission:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_ae_before = len(df.loc[\n",
    "    (df[\"emergency_covid_hospital_admission_date\"].notnull()) &\n",
    "    (df[\"ae_attendance_before_emergency_covid_hospital_admission\"]==1)\n",
    "    ,\"patient_id\"])\n",
    "\n",
    "num_ae_with_discharge = len(df.loc[\n",
    "    (df[\"emergency_covid_hospital_admission_date\"].notnull()) &\n",
    "    (df[\"ae_attendance_before_emergency_covid_hospital_admission_any_cause_with_discharge\"]==1)\n",
    "    ,\"patient_id\"])\n",
    "\n",
    "num_ae_with_hospital_discharge = len(df.loc[\n",
    "    (df[\"emergency_covid_hospital_admission_date\"].notnull()) &\n",
    "    (df[\"ae_attendance_before_emergency_covid_hospital_admission_any_cause_hosp_discharge\"]==1)\n",
    "    ,\"patient_id\"])\n",
    "\n",
    "num_ae_with_hospital_discharge_covid = len(df.loc[\n",
    "    (df[\"emergency_covid_hospital_admission_date\"].notnull()) &\n",
    "    (df[\"ae_attendance_before_emergency_covid_hospital_admission_any_cause_hosp_discharge\"]==1) &\n",
    "    (df[\"ae_attendance_before_emergency_covid_hospital_covid_status\"]==1)\n",
    "    ,\"patient_id\"])\n",
    "\n",
    "num_ae_with_hospital_discharge_resp_plus_pos_test = len(df.loc[\n",
    "    (df[\"emergency_covid_hospital_admission_date\"].notnull()) &\n",
    "    (df[\"ae_attendance_before_emergency_covid_hospital_admission_any_cause_hosp_discharge\"]==1) &\n",
    "    ((df[\"ae_attendance_before_emergency_covid_hospital_respiratory_status\"]==1) & (df[\"positive_covid_test_before_ae_attendance_before_emergency_covid_hospital\"]==1))\n",
    "    ,\"patient_id\"])\n",
    "\n",
    "\n",
    "num_ae_classified = len(df.loc[\n",
    "    (df[\"ae_attendance_before_emergency_covid_hospital_admission_any_cause_hosp_discharge\"]==1) &\n",
    "    (\n",
    "        (df[\"ae_attendance_before_emergency_covid_hospital_covid_status\"]==1) |\n",
    "        (\n",
    "            (df[\"ae_attendance_before_emergency_covid_hospital_respiratory_status\"]==1) &\n",
    "            (df[\"positive_covid_test_before_ae_attendance_before_emergency_covid_hospital\"]==1)\n",
    "        )\n",
    "    )\n",
    "    ,\"patient_id\"])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ae before</th>\n",
       "      <td>1509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ae before with discharge</th>\n",
       "      <td>1189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ae before with hospital discharge</th>\n",
       "      <td>1178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ae with covid and hospital discharge</th>\n",
       "      <td>1057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ae with resp/test and hospital discharge</th>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>classified</th>\n",
       "      <td>1111</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                                             0\n",
       "ae before                                 1509\n",
       "ae before with discharge                  1189\n",
       "ae before with hospital discharge         1178\n",
       "ae with covid and hospital discharge      1057\n",
       "ae with resp/test and hospital discharge   511\n",
       "classified                                1111"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ae_before_hospitalisation_dict = {\n",
    "    \"ae before\": num_ae_before,\n",
    "    \"ae before with discharge\": num_ae_with_discharge,\n",
    "    \"ae before with hospital discharge\": num_ae_with_hospital_discharge,\n",
    "    \"ae with covid and hospital discharge\": num_ae_with_hospital_discharge_covid,\n",
    "    \"ae with resp/test and hospital discharge\": num_ae_with_hospital_discharge_resp_plus_pos_test,\n",
    "    \"classified\": num_ae_classified\n",
    "}\n",
    "\n",
    "pd.DataFrame.from_dict(ae_before_hospitalisation_dict, orient='index')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A&E before primary COVID emergency hospital admission:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_ae_before_prim = len(df.loc[\n",
    "    (df[\"emergency_primary_covid_hospital_admission_date\"].notnull()) &\n",
    "    (df[\"ae_attendance_before_prim_emergency_covid_hospital_admission\"]==1)\n",
    "    ,\"patient_id\"])\n",
    "\n",
    "num_ae_with_discharge_prim = len(df.loc[\n",
    "    (df[\"emergency_primary_covid_hospital_admission_date\"].notnull()) &\n",
    "    (df[\"ae_attendance_before_prim_emergency_covid_hospital_admission_any_cause_with_discharge\"]==1)\n",
    "    ,\"patient_id\"])\n",
    "\n",
    "num_ae_with_hospital_discharge_prim = len(df.loc[\n",
    "    (df[\"emergency_primary_covid_hospital_admission_date\"].notnull()) &\n",
    "    (df[\"ae_attendance_before_prim_emergency_covid_hospital_admission_any_cause_hosp_discharge\"]==1)\n",
    "    ,\"patient_id\"])\n",
    "\n",
    "num_ae_with_hospital_discharge_covid_prim = len(df.loc[\n",
    "    (df[\"emergency_primary_covid_hospital_admission_date\"].notnull()) &\n",
    "    (df[\"ae_attendance_before_prim_emergency_covid_hospital_admission_any_cause_hosp_discharge\"]==1) &\n",
    "    (df[\"ae_attendance_before_prim_emergency_covid_hospital_covid_status\"]==1)\n",
    "    ,\"patient_id\"])\n",
    "\n",
    "num_ae_with_hospital_discharge_resp_plus_pos_test_prim = len(df.loc[\n",
    "    (df[\"emergency_primary_covid_hospital_admission_date\"].notnull()) &\n",
    "    (df[\"ae_attendance_before_prim_emergency_covid_hospital_admission_any_cause_hosp_discharge\"]==1) &\n",
    "    ((df[\"ae_attendance_before_prim_emergency_covid_hospital_respiratory_status\"]==1) & (df[\"positive_covid_test_before_ae_attendance_before_prim_emergency_covid_hospital\"]==1))\n",
    "    ,\"patient_id\"])\n",
    "\n",
    "\n",
    "num_ae_classified_prim = len(df.loc[\n",
    "    (\n",
    "        (df[\"ae_attendance_before_prim_emergency_covid_hospital_covid_status\"]==1) |\n",
    "        (\n",
    "            (df[\"ae_attendance_before_prim_emergency_covid_hospital_respiratory_status\"]==1) &\n",
    "            (df[\"positive_covid_test_before_ae_attendance_before_prim_emergency_covid_hospital\"]==1)\n",
    "        )\n",
    "    )\n",
    "    ,\"patient_id\"])\n",
    "\n",
    "df[\"num_ae_classified_prim\"] = df.loc[\n",
    "    (\n",
    "        (df[\"ae_attendance_before_prim_emergency_covid_hospital_covid_status\"]==1) |\n",
    "        (\n",
    "            (df[\"ae_attendance_before_prim_emergency_covid_hospital_respiratory_status\"]==1) &\n",
    "            (df[\"positive_covid_test_before_ae_attendance_before_prim_emergency_covid_hospital\"]==1)\n",
    "        )\n",
    "    )\n",
    "    ,\"patient_id\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ae before</th>\n",
       "      <td>1498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ae before with discharge</th>\n",
       "      <td>1217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ae before with hospital discharge</th>\n",
       "      <td>1154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ae with covid and hospital discharge</th>\n",
       "      <td>1036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ae with resp/test and hospital discharge</th>\n",
       "      <td>509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>classified</th>\n",
       "      <td>3783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ae no hospital</th>\n",
       "      <td>3135</td>\n",
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      ],
      "text/plain": [
       "                                             0\n",
       "ae before                                 1498\n",
       "ae before with discharge                  1217\n",
       "ae before with hospital discharge         1154\n",
       "ae with covid and hospital discharge      1036\n",
       "ae with resp/test and hospital discharge   509\n",
       "classified                                3783\n",
       "ae no hospital                            3135"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ae_before_hospitalisation_prim_dict = {\n",
    "    \"ae before\": num_ae_before_prim,\n",
    "    \"ae before with discharge\": num_ae_with_discharge_prim,\n",
    "    \"ae before with hospital discharge\": num_ae_with_hospital_discharge_prim,\n",
    "    \"ae with covid and hospital discharge\": num_ae_with_hospital_discharge_covid_prim,\n",
    "    \"ae with resp/test and hospital discharge\": num_ae_with_hospital_discharge_resp_plus_pos_test_prim,\n",
    "    \"classified\": num_ae_classified_prim\n",
    "}\n",
    "\n",
    "pd.DataFrame.from_dict(ae_before_hospitalisation_prim_dict, orient='index')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A&E admissions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_patients_ae = len(df.loc[df[\"ae_attendance_any_cause\"]==1,\"patient_id\"])\n",
    "\n",
    "num_patients_ae_with_discharge = len(df.loc[df[\"ae_attendance_any_cause_with_discharge\"]==1,\"patient_id\"])\n",
    "\n",
    "\n",
    "num_patients_ae_hosp_discharge = len(df.loc[df[\"ae_attendance_any_cause_hosp_discharge\"]==1,\"patient_id\"])\n",
    "\n",
    "\n",
    "num_patients_ae_covid = len(df.loc[df[\"ae_attendance_covid_status\"]==1,\"patient_id\"])\n",
    "\n",
    "\n",
    "num_patients_ae_resp = len(df.loc[df[\"ae_attendance_respiratory_status\"]==1,\"patient_id\"])\n",
    "\n",
    "\n",
    "num_patients_ae_covid_test = len(df.loc[df[\"positive_covid_test_before_ae_attendance\"]==1,\"patient_id\"])\n",
    "\n",
    "num_patients_classified_at_ae = len(df.loc[\n",
    "    (df[\"ae_attendance_any_cause_hosp_discharge\"]==1) &\n",
    "    (\n",
    "        (df[\"ae_attendance_covid_status\"]==1) |\n",
    "        ((df[\"ae_attendance_respiratory_status\"]==1) & (df[\"positive_covid_test_before_ae_attendance\"]==1))\n",
    "    )\n",
    "    ,\"patient_id\"])\n",
    "\n",
    "df[\"classified_at_ae\"] = df.loc[\n",
    "    (df[\"ae_attendance_any_cause_hosp_discharge\"]==1) &\n",
    "    (\n",
    "        (df[\"ae_attendance_covid_status\"]==1) |\n",
    "        ((df[\"ae_attendance_respiratory_status\"]==1) & (df[\"positive_covid_test_before_ae_attendance\"]==1))\n",
    "    )\n",
    "    ,\"patient_id\"]\n",
    "\n",
    "\n",
    "\n",
    "num_admitted_after_primary = len(df.loc[\n",
    "    (df[\"emergency_primary_covid_hospital_admission_after_ae\"]==1) &\n",
    "    (df[\"ae_attendance_any_cause_hosp_discharge\"]==1) &\n",
    "    (\n",
    "        (df[\"ae_attendance_covid_status\"]==1) |\n",
    "        ((df[\"ae_attendance_respiratory_status\"]==1) & (df[\"positive_covid_test_before_ae_attendance\"]==1))\n",
    "    )\n",
    "    ,\"patient_id\"])\n",
    "\n",
    "df[\"admitted_after_primary\"] = df.loc[\n",
    "    (df[\"emergency_primary_covid_hospital_admission_after_ae\"]==1) &\n",
    "    (df[\"ae_attendance_any_cause_hosp_discharge\"]==1) &\n",
    "    (\n",
    "        (df[\"ae_attendance_covid_status\"]==1) |\n",
    "        ((df[\"ae_attendance_respiratory_status\"]==1) & (df[\"positive_covid_test_before_ae_attendance\"]==1))\n",
    "    )\n",
    "    ,\"patient_id\"]\n",
    "\n",
    "num_admitted_after = len(df.loc[\n",
    "    (df[\"emergency_covid_hospital_admission_after_ae\"]==1) &\n",
    "    (df[\"ae_attendance_any_cause_hosp_discharge\"]==1) &\n",
    "    (\n",
    "        (df[\"ae_attendance_covid_status\"]==1) |\n",
    "        ((df[\"ae_attendance_respiratory_status\"]==1) & (df[\"positive_covid_test_before_ae_attendance\"]==1))\n",
    "    )\n",
    "    ,\"patient_id\"])\n",
    "\n",
    "df[\"num_admitted_after\"] = df.loc[\n",
    "    (df[\"emergency_covid_hospital_admission_after_ae\"]==1) &\n",
    "    (df[\"ae_attendance_any_cause_hosp_discharge\"]==1) &\n",
    "    (\n",
    "        (df[\"ae_attendance_covid_status\"]==1) |\n",
    "        ((df[\"ae_attendance_respiratory_status\"]==1) & (df[\"positive_covid_test_before_ae_attendance\"]==1))\n",
    "    )\n",
    "    ,\"patient_id\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
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       "      <th>0</th>\n",
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       "    <tr>\n",
       "      <th>ae</th>\n",
       "      <td>4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ae with discharge</th>\n",
       "      <td>4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ae with hospital discharge</th>\n",
       "      <td>4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ae with covid</th>\n",
       "      <td>9001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ae with resp</th>\n",
       "      <td>9001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>covid test +ve</th>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               0\n",
       "ae                          4000\n",
       "ae with discharge           4000\n",
       "ae with hospital discharge  4000\n",
       "ae with covid               9001\n",
       "ae with resp                9001\n",
       "covid test +ve              5000"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ae_dict = {\n",
    "    \"ae\": num_patients_ae,\n",
    "    \"ae with discharge\": num_patients_ae_with_discharge,\n",
    "    \"ae with hospital discharge\": num_patients_ae_hosp_discharge,\n",
    "    \"ae with covid\": num_patients_ae_covid,\n",
    "    \"ae with resp\": num_patients_ae_resp,\n",
    "    \"covid test +ve\": num_patients_ae_covid_test\n",
    "}\n",
    "\n",
    "pd.DataFrame.from_dict(ae_dict, orient='index')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hospitalisation after A&E"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>num classified at ae</th>\n",
       "      <td>3766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hospital after ae</th>\n",
       "      <td>1118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>primary hospital after ae</th>\n",
       "      <td>1119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hospital admission no ae</th>\n",
       "      <td>2369</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              0\n",
       "num classified at ae       3766\n",
       "hospital after ae          1118\n",
       "primary hospital after ae  1119\n",
       "hospital admission no ae   2369"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hospital_after_ae_dict = {\n",
    "    \"num classified at ae\": num_patients_classified_at_ae,\n",
    "    \"hospital after ae\": num_admitted_after,\n",
    "    \"primary hospital after ae\": num_admitted_after_primary}\n",
    "\n",
    "pd.DataFrame.from_dict(hospital_after_ae_dict, orient='index')"
   ]
  }
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