{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "*This notebook contains material from [CBE40455-2020](https://jckantor.github.io/CBE40455-2020);\n", "content is available [on Github](https://github.com/jckantor/CBE40455-2020.git).*\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "< [2.2 Campus SEIR Modeling](https://jckantor.github.io/CBE40455-2020/02.02-Campus-SEIR-modeling.html) | [Contents](toc.html) | [2.4 Linear Analysis of Campus Reopening](https://jckantor.github.io/CBE40455-2020/02.04-Linear-Analysis-of-Campus-Reopening.html) >
"
]
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "eAbATGsb5fwf",
"nbpages": {
"level": 1,
"link": "[2.3 Campus Re-opening Model](https://jckantor.github.io/CBE40455-2020/02.03-Campus-reopening.html#2.3-Campus-Re-opening-Model)",
"section": "2.3 Campus Re-opening Model"
}
},
"source": [
"# 2.3 Campus Re-opening Model\n",
"\n",
"Following [Paltiel, et al. (2020)](https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2768923). \n",
"\n",
"\n",
"\n",
"(Figure e1 from Paltiel, et al., 2020)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "fmDN0ArmBQ5C",
"nbpages": {
"level": 3,
"link": "[2.3.1 Active transmission and testing pool. ](https://jckantor.github.io/CBE40455-2020/02.03-Campus-reopening.html#2.3.1-Active-transmission-and-testing-pool.)",
"section": "2.3.1 Active transmission and testing pool. "
}
},
"source": [
"\n",
"### 2.3.1 Active transmission and testing pool. \n",
"\n",
"This pool consists of individuals in the campus population subject to testing and the transmission of virus.\n",
"\n",
"* $U$ uninfected, susceptible individuals\n",
"* $E$ exposed, asymptomatic, non-infectious\n",
"* $A$ infected, asymptomatic\n",
"\n",
"\\begin{align*}\n",
"\\frac{dU}{dt} & = -\\beta U \\frac{A}{U + E + A} - \\tau (1-S_p) U + \\mu F_p - x(t) \\\\\n",
"\\frac{dE}{dt} & = \\beta U \\frac{A}{U + E + A} - \\theta E + x(t) \\\\\n",
"\\frac{dA}{dt} & = \\theta E - (\\sigma + \\rho + \\tau S_e)A\n",
"\\end{align*} \n"
]
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "H3sOz0YPBYOW",
"nbpages": {
"level": 3,
"link": "[2.3.2 Isolation pool](https://jckantor.github.io/CBE40455-2020/02.03-Campus-reopening.html#2.3.2-Isolation-pool)",
"section": "2.3.2 Isolation pool"
}
},
"source": [
"### 2.3.2 Isolation pool\n",
"\n",
"* $S$ infected, symptomatic with a true positive test result.\n",
"* $T_p$ infected, asymptomatic with a true positive test result\n",
"* $F_p$ uninfected with a false positive result.\n",
"\n",
"\\begin{align*}\n",
"\\frac{dF_p}{dt} & = -\\mu F_p + \\tau(1-S_p) U \\\\\n",
"\\frac{dT_p}{dt} & = -(\\sigma + \\rho) T_p + \\tau S_e A\\\\\n",
"\\frac{dS}{dt} & = -(\\rho + \\delta)S + \\sigma (T_p + A)\n",
"\\end{align*} "
]
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "D64CeE2hCIdC",
"nbpages": {
"level": 3,
"link": "[2.3.3 Removed pool](https://jckantor.github.io/CBE40455-2020/02.03-Campus-reopening.html#2.3.3-Removed-pool)",
"section": "2.3.3 Removed pool"
}
},
"source": [
"### 2.3.3 Removed pool\n",
"\n",
"* $R$ recovered. These individuals assumed to be immune for the remainder of the simulation, and not returned to the campus population.\n",
"* $D$ dead.\n",
"\n",
"\\begin{align*}\n",
"\\frac{dR}{dt} & = \\rho (T_p + A + S)\\\\\\\n",
"\\frac{dD}{dt} & = \\delta S\n",
"\\end{align*} "
]
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "Yso2VSWXrssr",
"nbpages": {
"level": 3,
"link": "[2.3.4 Parameter estimates](https://jckantor.github.io/CBE40455-2020/02.03-Campus-reopening.html#2.3.4-Parameter-estimates)",
"section": "2.3.4 Parameter estimates"
}
},
"source": [
"### 2.3.4 Parameter estimates\n",
"\n",
"Given:\n",
"\n",
"* $\\rho$ recovery rate \n",
"* $R_t$ basic reproductive number for asymptomatic transmission \n",
"* $p_{si}$ probability that an infected individual will become symptomatic.\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "6SpT6hhJ5lmU",
"nbpages": {
"level": 4,
"link": "[2.3.4.1 Odds of becoming symptomatic if infected](https://jckantor.github.io/CBE40455-2020/02.03-Campus-reopening.html#2.3.4.1-Odds-of-becoming-symptomatic-if-infected)",
"section": "2.3.4.1 Odds of becoming symptomatic if infected"
}
},
"source": [
"#### 2.3.4.1 Odds of becoming symptomatic if infected\n",
"\n",
"Based on the compartmental relationships and rates, the probability of symptom development for infected individuals is given by\n",
"\n",
"$$p_{si} = \\frac{\\sigma}{\\sigma + \\rho}$$\n",
"\n",
"Inverting this relationship\n",
"\n",
"$$\\sigma = \\frac{p_{si}}{1 - p_{si}}\\rho$$\n",
"\n",
"where $\\frac{p_{si}}{1 - p_{si}}$ is the 'odds' that an infected individual becomes symptomatic.\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "-N4_RCNk5xPJ",
"nbpages": {
"level": 4,
"link": "[2.3.4.2 Effective reproductive number with isolation of symptomatic individuals](https://jckantor.github.io/CBE40455-2020/02.03-Campus-reopening.html#2.3.4.2-Effective-reproductive-number-with-isolation-of-symptomatic-individuals)",
"section": "2.3.4.2 Effective reproductive number with isolation of symptomatic individuals"
}
},
"source": [
"#### 2.3.4.2 Effective reproductive number with isolation of symptomatic individuals\n",
"\n",
"For an initially uninfected population with no testing regime, where transmission is solely due to non-isolated, asymptomatic individuals, the effective reproductive number is\n",
"\n",
"$$R_t = \\frac{\\beta}{\\sigma + \\rho}$$\n",
"\n",
"Expressed in terms of recovery rate and probability of becoming symptomatic\n",
"\n",
"$$R_t = \\frac{\\beta}{\\rho}(1 - p_{si})$$"
]
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "8e0Q1QYCAtcK",
"nbpages": {
"level": 4,
"link": "[2.3.4.3 Testing threshold](https://jckantor.github.io/CBE40455-2020/02.03-Campus-reopening.html#2.3.4.3-Testing-threshold)",
"section": "2.3.4.3 Testing threshold"
}
},
"source": [
"#### 2.3.4.3 Testing threshold\n",
"\n",
"With a testing regime, for effective herd immunity requires\n",
"\n",
"$$\\beta \\leq \\sigma + \\rho + \\tau S_e $$\n",
"\n",
"where $\\tau$ is the testing rate and $S_e$ is the test sensitivity. With some manipulation using the above relationships, the testing treshhold becomes\n",
"\n",
"$$\\tau S_e \\geq \\frac{(R_t - 1) \\rho}{1 - p_{si}}$$\n",
"\n",
"or \n",
"\n",
"$$\\frac{1}{\\tau} \\leq S_e \\left(\\frac{1 - p_{si}}{R_t - 1}\\right)\\frac{1}{\\rho} $$"
]
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "DM1O_lhAEPEN",
"nbpages": {
"level": 4,
"link": "[2.3.4.4 Parameter values](https://jckantor.github.io/CBE40455-2020/02.03-Campus-reopening.html#2.3.4.4-Parameter-values)",
"section": "2.3.4.4 Parameter values"
}
},
"source": [
"#### 2.3.4.4 Parameter values\n",
"\n",
"| parameter | value |\n",
"| :--: | :--: |\n",
"| $p_{si}$ | 0.3 |\n",
"| $R_t$ | [1.5, 2.5, 3.5] |\n",
"| $\\frac{1}{\\rho}$ | 14 d |\n",
"| $S_e$ | 0.7 |\n",
"\n",
"\n",
"t"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 283
},
"colab_type": "code",
"executionInfo": {
"elapsed": 594,
"status": "ok",
"timestamp": 1596387599982,
"user": {
"displayName": "Jeffrey Kantor",
"photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gg_n8V7bVINy02QRuRgOoMo11Ri7NKU3OUKdC1bkQ=s64",
"userId": "09038942003589296665"
},
"user_tz": 300
},
"id": "Nlvxm2wvE-hm",
"nbpages": {
"level": 4,
"link": "[2.3.4.4 Parameter values](https://jckantor.github.io/CBE40455-2020/02.03-Campus-reopening.html#2.3.4.4-Parameter-values)",
"section": "2.3.4.4 Parameter values"
},
"outputId": "cab1ce50-2134-4b13-f688-59a4ebaed9a1"
},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"
"
]
}
],
"metadata": {
"colab": {
"collapsed_sections": [],
"name": "Campus-reopening.ipynb",
"provenance": [
{
"file_id": "1ddb_0swsq9MRKyHrzflCzeF8Tqqmp24H",
"timestamp": 1596290235744
}
],
"toc_visible": true
},
"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": "3.7.4"
}
},
"nbformat": 4,
"nbformat_minor": 4
}