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@ChrisAichinger
Created January 16, 2022 17:16
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Covid Variant Model: showing how a more infectious variant out-competes others
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{
"cells": [
{
"cell_type": "markdown",
"id": "f109f499",
"metadata": {},
"source": [
"# How do new Covid variants replace older strains?\n",
"\n",
"Simple simulation with just three rules:\n",
"\n",
"* At the beginning only the base variant exists, until on day 200 the Omicron variant is introduced.\n",
"* Each base variant infection causes 1.25 follow-up infections. Each Omicron infection causes 1.40 follow-up infections.\n",
"* If the number of sick people rises above 20000, a lockdown is started. This results in a reduction of new infections by 36%. The lockdown ends when the number of sick people has fallen below 6000 again.\n",
"\n",
"See the [accompanying blog post](https://www.caichinger.com/blog/2022/01/16/covid-variant-competiton/) for more explanation.\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "de6ef09b",
"metadata": {},
"outputs": [],
"source": [
"from dataclasses import dataclass\n",
"from typing import Dict\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"from matplotlib.patches import Rectangle\n",
"\n",
"plt.rcParams.update({'font.size': 14, 'figure.figsize': (10, 7)})"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "72288d12",
"metadata": {},
"outputs": [],
"source": [
"INITIALLY_SICK = 140\n",
"SICKNESS_DURATION = 14\n",
"INFECTIOUS_START = 2\n",
"INFECTIOUS_END = 12\n",
"\n",
"R_BASE_V1 = 1.25\n",
"R_BASE_V2 = 1.40\n",
"\n",
"NUM_SICK_FOR_LOCKDOWN_START = 20000\n",
"NUM_SICK_FOR_LOCKDOWN_END = 6000\n",
"R_LOCKDOWN_FACTOR = 0.80 / 1.25\n",
"\n",
"SIMULATION_DAYS = 700\n",
"V2_START_DAY = 200"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "e7f44574",
"metadata": {},
"outputs": [],
"source": [
"Day = int\n",
"InfectedCount = int\n",
"\n",
"# Mapping D -> N, representing the number N of people currently on day D of their infection.\n",
"# Day 0 is all the people who got infected today. Everyone on day 14 will be healthy again tomorrow.\n",
"# Total number of infected is `sum(sick_by_infection_day.values())`.\n",
"SickByInfectionDay = Dict[Day, InfectedCount]\n",
"\n",
"\n",
"@dataclass\n",
"class VirusState:\n",
" \"\"\"Captures the full state of the virus simulation at a given timepoint\"\"\"\n",
" sick_by_day_variant1: SickByInfectionDay \n",
" sick_by_day_variant2: SickByInfectionDay\n",
" in_lockdown: bool = False"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "1b4fe5ef",
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 720x504 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"def propagate_disease(sick_by_day, in_lockdown, r_base):\n",
" \"\"\"Move everyone forward one day in their infection progress, and add newly infected\"\"\"\n",
" sick_by_day = {day: sick_by_day.get(day - 1, 0) for day in range(1, SICKNESS_DURATION)}\n",
" \n",
" num_infectious = sum(\n",
" sick_by_day[day] for day in range(INFECTIOUS_START, INFECTIOUS_END)\n",
" )\n",
" adjusted_r = r_base * (R_LOCKDOWN_FACTOR if in_lockdown else 1)\n",
" new_infections = int(num_infectious * adjusted_r / (INFECTIOUS_END - INFECTIOUS_START))\n",
" sick_by_day[0] = new_infections \n",
" return sick_by_day\n",
"\n",
"\n",
"def get_new_lockdown_state(state):\n",
" \"\"\"Calculate the new lockdown state given yesterday's state\"\"\"\n",
" in_lockdown = state.in_lockdown\n",
" num_sick = sum(state.sick_by_day_variant1.values()) + sum(state.sick_by_day_variant2.values())\n",
" if num_sick >= NUM_SICK_FOR_LOCKDOWN_START:\n",
" in_lockdown = True\n",
" elif num_sick <= NUM_SICK_FOR_LOCKDOWN_END:\n",
" in_lockdown = False\n",
" return in_lockdown\n",
" \n",
" \n",
"def step_time(t, state):\n",
" \"\"\"Calculate the new virus state based on the yesterday's state\"\"\"\n",
" sick_v1 = propagate_disease(state.sick_by_day_variant1, state.in_lockdown, R_BASE_V1)\n",
" sick_v2 = propagate_disease(state.sick_by_day_variant2, state.in_lockdown, R_BASE_V2)\n",
" in_lockdown = get_new_lockdown_state(state)\n",
" \n",
" # Introduce variant 2 by infecting a few people.\n",
" if t == V2_START_DAY:\n",
" sick_v2 = {day: INITIALLY_SICK//SICKNESS_DURATION for day in range(SICKNESS_DURATION)}\n",
" \n",
" return VirusState(\n",
" sick_by_day_variant1=sick_v1,\n",
" sick_by_day_variant2=sick_v2,\n",
" in_lockdown=in_lockdown)\n",
"\n",
"\n",
"# Initial state\n",
"###############\n",
"\n",
"state = VirusState(\n",
" sick_by_day_variant1={day: INITIALLY_SICK//SICKNESS_DURATION for day in range(SICKNESS_DURATION)},\n",
" sick_by_day_variant2={day: 0 for day in range(SICKNESS_DURATION)},\n",
" in_lockdown=False,\n",
")\n",
"\n",
"\n",
"# Running the simulation\n",
"########################\n",
"\n",
"timeseries_v1 = []\n",
"timeseries_v2 = []\n",
"lockdown_timepoints = []\n",
"for t in range(SIMULATION_DAYS):\n",
" old_lockdown_state = state.in_lockdown\n",
" state = step_time(t, state)\n",
" timeseries_v1.append(sum(state.sick_by_day_variant1.values()))\n",
" timeseries_v2.append(sum(state.sick_by_day_variant2.values()))\n",
" if old_lockdown_state != state.in_lockdown:\n",
" lockdown_timepoints.append(t)\n",
" \n",
" \n",
"# Plotting the results\n",
"######################\n",
"\n",
"df = pd.DataFrame({'Base Variant': timeseries_v1, 'Omicron': timeseries_v2})\n",
"plot_ax = df.plot(\n",
" xlabel='Days',\n",
" ylabel='Number of people currently infected',\n",
" title='Covid variant competition',\n",
" ylim=(0, df.max().max() * 1.2)\n",
")\n",
"plt.legend(loc='upper left')\n",
"plot_ax.annotate(\n",
" \"Omicron emerges\",\n",
" xy=(V2_START_DAY, 500),\n",
" xytext=(V2_START_DAY, 3500),\n",
" horizontalalignment='center',\n",
" arrowprops=dict(arrowstyle=\"->\"),\n",
");\n",
"for i in range(0, len(lockdown_timepoints), 2):\n",
" x_start = lockdown_timepoints[i]\n",
" x_end = lockdown_timepoints[i+1] if i+1 < len(lockdown_timepoints) else SIMULATION_DAYS\n",
" plot_ax.add_patch(Rectangle((x_start, 0), x_end - x_start, df.max().max()*2,\n",
" alpha=0.12, facecolor='k', label='Lockdowns'))\n",
"plot_ax.legend(handles=plot_ax.legend().get_lines() + [plot_ax.patches[-1]]);"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.9.7"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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