A novel COVID-19 epidemiological model with explicit susceptible and asymptomatic isolation compartments reveals unexpected consequences of timing social distancing
•A novel mathematical model of COVID-19 explicitly includes social-distancing.•Short delay of distancing mandates has no appreciable effects on flattening the curve.•Effect of periodic relaxation of distancing is highly sensitive to timing.•Rate of gradual relaxation determines presence of a second...
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Veröffentlicht in: | Journal of theoretical biology 2021-02, Vol.510, p.110539-110539, Article 110539 |
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creator | Gevertz, Jana L. Greene, James M. Sanchez-Tapia, Cynthia H. Sontag, Eduardo D. |
description | •A novel mathematical model of COVID-19 explicitly includes social-distancing.•Short delay of distancing mandates has no appreciable effects on flattening the curve.•Effect of periodic relaxation of distancing is highly sensitive to timing.•Rate of gradual relaxation determines presence of a second wave, and its severity.
Motivated by the current COVID-19 epidemic, this work introduces an epidemiological model in which separate compartments are used for susceptible and asymptomatic “socially distant” populations. Distancing directives are represented by rates of flow into these compartments, as well as by a reduction in contacts that lessens disease transmission. The dynamical behavior of this system is analyzed, under various different rate control strategies, and the sensitivity of the basic reproduction number to various parameters is studied. One of the striking features of this model is the existence of a critical implementation delay (CID) in issuing distancing mandates: while a delay of about two weeks does not have an appreciable effect on the peak number of infections, issuing mandates even slightly after this critical time results in a far greater incidence of infection. Thus, there is a nontrivial but tight “window of opportunity” for commencing social distancing in order to meet the capacity of healthcare resources. However, if one wants to also delay the timing of peak infections – so as to take advantage of potential new therapies and vaccines – action must be taken much faster than the CID. Different relaxation strategies are also simulated, with surprising results. Periodic relaxation policies suggest a schedule which may significantly inhibit peak infective load, but that this schedule is very sensitive to parameter values and the schedule’s frequency. Furthermore, we considered the impact of steadily reducing social distancing measures over time. We find that a too-sudden reopening of society may negate the progress achieved under initial distancing guidelines, but the negative effects can be mitigated if the relaxation strategy is carefully designed. |
doi_str_mv | 10.1016/j.jtbi.2020.110539 |
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Motivated by the current COVID-19 epidemic, this work introduces an epidemiological model in which separate compartments are used for susceptible and asymptomatic “socially distant” populations. Distancing directives are represented by rates of flow into these compartments, as well as by a reduction in contacts that lessens disease transmission. The dynamical behavior of this system is analyzed, under various different rate control strategies, and the sensitivity of the basic reproduction number to various parameters is studied. One of the striking features of this model is the existence of a critical implementation delay (CID) in issuing distancing mandates: while a delay of about two weeks does not have an appreciable effect on the peak number of infections, issuing mandates even slightly after this critical time results in a far greater incidence of infection. Thus, there is a nontrivial but tight “window of opportunity” for commencing social distancing in order to meet the capacity of healthcare resources. However, if one wants to also delay the timing of peak infections – so as to take advantage of potential new therapies and vaccines – action must be taken much faster than the CID. Different relaxation strategies are also simulated, with surprising results. Periodic relaxation policies suggest a schedule which may significantly inhibit peak infective load, but that this schedule is very sensitive to parameter values and the schedule’s frequency. Furthermore, we considered the impact of steadily reducing social distancing measures over time. We find that a too-sudden reopening of society may negate the progress achieved under initial distancing guidelines, but the negative effects can be mitigated if the relaxation strategy is carefully designed.</description><identifier>ISSN: 0022-5193</identifier><identifier>ISSN: 1095-8541</identifier><identifier>EISSN: 1095-8541</identifier><identifier>DOI: 10.1016/j.jtbi.2020.110539</identifier><identifier>PMID: 33242489</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Asymptomatic Infections - epidemiology ; Basic Reproduction Number - statistics & numerical data ; COVID-19 ; COVID-19 - epidemiology ; COVID-19 - prevention & control ; COVID-19 - transmission ; Disease Susceptibility - epidemiology ; Epidemic modeling ; Humans ; Mathematical Concepts ; Models, Biological ; Pandemics - prevention & control ; Pandemics - statistics & numerical data ; Physical Distancing ; SARS-CoV-2 ; Social distancing ; Systems Biology ; Time Factors</subject><ispartof>Journal of theoretical biology, 2021-02, Vol.510, p.110539-110539, Article 110539</ispartof><rights>2020 Elsevier Ltd</rights><rights>Copyright © 2020 Elsevier Ltd. All rights reserved.</rights><rights>2020 Elsevier Ltd. All rights reserved. 2020 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c455t-ab1da22404d609dad899890153e0c49ef6fca625ddea0974e53488c3a0d7ff3e3</citedby><cites>FETCH-LOGICAL-c455t-ab1da22404d609dad899890153e0c49ef6fca625ddea0974e53488c3a0d7ff3e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jtbi.2020.110539$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,780,784,885,3548,27923,27924,45994</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33242489$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gevertz, Jana L.</creatorcontrib><creatorcontrib>Greene, James M.</creatorcontrib><creatorcontrib>Sanchez-Tapia, Cynthia H.</creatorcontrib><creatorcontrib>Sontag, Eduardo D.</creatorcontrib><title>A novel COVID-19 epidemiological model with explicit susceptible and asymptomatic isolation compartments reveals unexpected consequences of timing social distancing</title><title>Journal of theoretical biology</title><addtitle>J Theor Biol</addtitle><description>•A novel mathematical model of COVID-19 explicitly includes social-distancing.•Short delay of distancing mandates has no appreciable effects on flattening the curve.•Effect of periodic relaxation of distancing is highly sensitive to timing.•Rate of gradual relaxation determines presence of a second wave, and its severity.
Motivated by the current COVID-19 epidemic, this work introduces an epidemiological model in which separate compartments are used for susceptible and asymptomatic “socially distant” populations. Distancing directives are represented by rates of flow into these compartments, as well as by a reduction in contacts that lessens disease transmission. The dynamical behavior of this system is analyzed, under various different rate control strategies, and the sensitivity of the basic reproduction number to various parameters is studied. One of the striking features of this model is the existence of a critical implementation delay (CID) in issuing distancing mandates: while a delay of about two weeks does not have an appreciable effect on the peak number of infections, issuing mandates even slightly after this critical time results in a far greater incidence of infection. Thus, there is a nontrivial but tight “window of opportunity” for commencing social distancing in order to meet the capacity of healthcare resources. However, if one wants to also delay the timing of peak infections – so as to take advantage of potential new therapies and vaccines – action must be taken much faster than the CID. Different relaxation strategies are also simulated, with surprising results. Periodic relaxation policies suggest a schedule which may significantly inhibit peak infective load, but that this schedule is very sensitive to parameter values and the schedule’s frequency. Furthermore, we considered the impact of steadily reducing social distancing measures over time. We find that a too-sudden reopening of society may negate the progress achieved under initial distancing guidelines, but the negative effects can be mitigated if the relaxation strategy is carefully designed.</description><subject>Asymptomatic Infections - epidemiology</subject><subject>Basic Reproduction Number - statistics & numerical data</subject><subject>COVID-19</subject><subject>COVID-19 - epidemiology</subject><subject>COVID-19 - prevention & control</subject><subject>COVID-19 - transmission</subject><subject>Disease Susceptibility - epidemiology</subject><subject>Epidemic modeling</subject><subject>Humans</subject><subject>Mathematical Concepts</subject><subject>Models, Biological</subject><subject>Pandemics - prevention & control</subject><subject>Pandemics - statistics & numerical data</subject><subject>Physical Distancing</subject><subject>SARS-CoV-2</subject><subject>Social distancing</subject><subject>Systems Biology</subject><subject>Time Factors</subject><issn>0022-5193</issn><issn>1095-8541</issn><issn>1095-8541</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9UU1vEzEQXSEQTQt_gAPykcsGf27WEkKqApRKlXoBrpZjz6YTre1l7QT6f_ihOEqp4MLJ1rw3b2bea5pXjC4ZZd3b3XJXNrjklNcCo0roJ82CUa3aXkn2tFlQynmrmBZnzXnOO0qplqJ73pwJwSWXvV40vy5JTAcYyfr22_WHlmkCE3oImMa0RWdHEpKv8A8sdwR-TiM6LCTvs4Op4GYEYqMnNt-HqaRgCzqCOY31kyJxKUx2LgFiyWSGA9gxk32sMuAK-IrHDN_3EB1kkgZSMGDckpwc1sEec7HR1cqL5tlQW-Hlw3vRfP308cv6c3tze3W9vrxpnVSqtHbDvOVcUuk7qr31vda9pkwJoE5qGLrB2Y4r78FSvZKghOx7Jyz1q2EQIC6a9yfdab8J4F3de7ajmWYMdr43yaL5F4l4Z7bpYFa9pFyrKvDmQWBO9a5cTMDq1DjaCGmfDZedkpLxjlUqP1HdnHKeYXgcw6g5xmt25hivOcZrTvHWptd_L_jY8ifPSnh3IkC16YAwm-zw6K_HuXpufML_6f8GVH68ew</recordid><startdate>20210207</startdate><enddate>20210207</enddate><creator>Gevertz, Jana L.</creator><creator>Greene, James M.</creator><creator>Sanchez-Tapia, Cynthia H.</creator><creator>Sontag, Eduardo D.</creator><general>Elsevier Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20210207</creationdate><title>A novel COVID-19 epidemiological model with explicit susceptible and asymptomatic isolation compartments reveals unexpected consequences of timing social distancing</title><author>Gevertz, Jana L. ; Greene, James M. ; Sanchez-Tapia, Cynthia H. ; Sontag, Eduardo D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c455t-ab1da22404d609dad899890153e0c49ef6fca625ddea0974e53488c3a0d7ff3e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Asymptomatic Infections - epidemiology</topic><topic>Basic Reproduction Number - statistics & numerical data</topic><topic>COVID-19</topic><topic>COVID-19 - epidemiology</topic><topic>COVID-19 - prevention & control</topic><topic>COVID-19 - transmission</topic><topic>Disease Susceptibility - epidemiology</topic><topic>Epidemic modeling</topic><topic>Humans</topic><topic>Mathematical Concepts</topic><topic>Models, Biological</topic><topic>Pandemics - prevention & control</topic><topic>Pandemics - statistics & numerical data</topic><topic>Physical Distancing</topic><topic>SARS-CoV-2</topic><topic>Social distancing</topic><topic>Systems Biology</topic><topic>Time Factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gevertz, Jana L.</creatorcontrib><creatorcontrib>Greene, James M.</creatorcontrib><creatorcontrib>Sanchez-Tapia, Cynthia H.</creatorcontrib><creatorcontrib>Sontag, Eduardo D.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of theoretical biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gevertz, Jana L.</au><au>Greene, James M.</au><au>Sanchez-Tapia, Cynthia H.</au><au>Sontag, Eduardo D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A novel COVID-19 epidemiological model with explicit susceptible and asymptomatic isolation compartments reveals unexpected consequences of timing social distancing</atitle><jtitle>Journal of theoretical biology</jtitle><addtitle>J Theor Biol</addtitle><date>2021-02-07</date><risdate>2021</risdate><volume>510</volume><spage>110539</spage><epage>110539</epage><pages>110539-110539</pages><artnum>110539</artnum><issn>0022-5193</issn><issn>1095-8541</issn><eissn>1095-8541</eissn><abstract>•A novel mathematical model of COVID-19 explicitly includes social-distancing.•Short delay of distancing mandates has no appreciable effects on flattening the curve.•Effect of periodic relaxation of distancing is highly sensitive to timing.•Rate of gradual relaxation determines presence of a second wave, and its severity.
Motivated by the current COVID-19 epidemic, this work introduces an epidemiological model in which separate compartments are used for susceptible and asymptomatic “socially distant” populations. Distancing directives are represented by rates of flow into these compartments, as well as by a reduction in contacts that lessens disease transmission. The dynamical behavior of this system is analyzed, under various different rate control strategies, and the sensitivity of the basic reproduction number to various parameters is studied. One of the striking features of this model is the existence of a critical implementation delay (CID) in issuing distancing mandates: while a delay of about two weeks does not have an appreciable effect on the peak number of infections, issuing mandates even slightly after this critical time results in a far greater incidence of infection. Thus, there is a nontrivial but tight “window of opportunity” for commencing social distancing in order to meet the capacity of healthcare resources. However, if one wants to also delay the timing of peak infections – so as to take advantage of potential new therapies and vaccines – action must be taken much faster than the CID. Different relaxation strategies are also simulated, with surprising results. Periodic relaxation policies suggest a schedule which may significantly inhibit peak infective load, but that this schedule is very sensitive to parameter values and the schedule’s frequency. Furthermore, we considered the impact of steadily reducing social distancing measures over time. We find that a too-sudden reopening of society may negate the progress achieved under initial distancing guidelines, but the negative effects can be mitigated if the relaxation strategy is carefully designed.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>33242489</pmid><doi>10.1016/j.jtbi.2020.110539</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Asymptomatic Infections - epidemiology Basic Reproduction Number - statistics & numerical data COVID-19 COVID-19 - epidemiology COVID-19 - prevention & control COVID-19 - transmission Disease Susceptibility - epidemiology Epidemic modeling Humans Mathematical Concepts Models, Biological Pandemics - prevention & control Pandemics - statistics & numerical data Physical Distancing SARS-CoV-2 Social distancing Systems Biology Time Factors |
title | A novel COVID-19 epidemiological model with explicit susceptible and asymptomatic isolation compartments reveals unexpected consequences of timing social distancing |
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