Download
journal.pone.0247182.pdf 1,71MB
WeightNameValue
1000 Titel
  • Development of an interactive, agent-based local stochastic model of COVID-19 transmission and evaluation of mitigation strategies illustrated for the state of Massachusetts, USA
1000 Autor/in
  1. Kirpich, Alexander |
  2. Koniukhovskii, Vladimir |
  3. Shvartc, Vladimir |
  4. Skums, Pavel |
  5. Weppelmann, Thomas |
  6. Imyanitov, Evgeny |
  7. Semyonov, Semyon |
  8. Barsukov, Konstantin |
  9. Gankin, Yuriy |
1000 Erscheinungsjahr 2021
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-02-17
1000 Erschienen in
1000 Quellenangabe
  • 16(2):e0247182
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1371/journal.pone.0247182 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7888623 |
1000 Ergänzendes Material
  • https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0247182#sec009 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Since its discovery in the Hubei province of China, the global spread of the novel coronavirus SARS-CoV-2 has resulted in millions of COVID-19 cases and hundreds of thousands of deaths. The spread throughout Asia, Europe, and the Americas has presented one of the greatest infectious disease threats in recent history and has tested the capacity of global health infrastructures. Since no effective vaccine is available, isolation techniques to prevent infection such as home quarantine and social distancing while in public have remained the cornerstone of public health interventions. While government and health officials were charged with implementing stay-at-home strategies, many of which had little guidance as to the consequences of how quickly to begin them. Moreover, as the local epidemic curves have been flattened, the same officials must wrestle with when to ease or cease such restrictions as to not impose economic turmoil. To evaluate the effects of quarantine strategies during the initial epidemic, an agent based modeling framework was created to take into account local spread based on geographic and population data with a corresponding interactive desktop and web-based application. Using the state of Massachusetts in the United States of America, we have illustrated the consequences of implementing quarantines at different time points after the initial seeding of the state with COVID-19 cases. Furthermore, we suggest that this application can be adapted to other states, small countries, or regions within a country to provide decision makers with critical information necessary to best protect human health.
1000 Sacherschließung
lokal Epidemiology
gnd 1206347392 COVID-19
lokal Geography
lokal SARS CoV 2
lokal Respiratory infections
lokal Social distancing
lokal Agent-based modeling
lokal Graphs
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/S2lycGljaCwgQWxleGFuZGVy|https://frl.publisso.de/adhoc/uri/S29uaXVraG92c2tpaSwgVmxhZGltaXI=|https://frl.publisso.de/adhoc/uri/U2h2YXJ0YywgVmxhZGltaXI=|https://orcid.org/0000-0003-4007-5624|https://orcid.org/0000-0002-7031-0069|https://frl.publisso.de/adhoc/uri/SW15YW5pdG92LCBFdmdlbnk=|https://frl.publisso.de/adhoc/uri/U2VteW9ub3YsIFNlbXlvbg==|https://frl.publisso.de/adhoc/uri/QmFyc3Vrb3YsIEtvbnN0YW50aW4=|https://orcid.org/0000-0003-0046-1037
1000 Label
1000 Dateien
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6428036.rdf
1000 Erstellt am 2021-06-08T12:59:17.856+0200
1000 Erstellt von 284
1000 beschreibt frl:6428036
1000 Bearbeitet von 25
1000 Zuletzt bearbeitet 2021-11-09T12:56:12.802+0100
1000 Objekt bearb. Tue Nov 09 12:55:50 CET 2021
1000 Vgl. frl:6428036
1000 Oai Id
  1. oai:frl.publisso.de:frl:6428036 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

View source