COVID-19 Modelling: The Effects of Social Distancing.
The purpose of this article is to reach all those who find it difficult to become well informed about the steps that have been implemented to tackle the COVID-19 pandemic and to spark discussion and thought. Here, we use simple stochastic simulations to evaluate different approaches taken to manage...
| Publicado en: | Interdisciplinary Perspectives on Infectious Diseases pp. 1 - 8 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Wiley-Blackwell
12/3/2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=147361630&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 147361630 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1687708X 8NCE jtl: Interdisciplinary Perspectives on Infectious Diseases issn: 1687708X maglogo: N pubinfo: dt: 12/3/2020 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 147361630 10.1155/2020/2041743 147361630 ppf: 1 ppct: 7 formats: tig: atl: COVID-19 Modelling: The Effects of Social Distancing. aug: au: Bendtsen Cano, Oliva Cano Morales, Sabrina Bendtsen, Claus affil: Stephen Perse Foundation, Cambridge, UK sug: ab: The purpose of this article is to reach all those who find it difficult to become well informed about the steps that have been implemented to tackle the COVID-19 pandemic and to spark discussion and thought. Here, we use simple stochastic simulations to evaluate different approaches taken to manage the crisis. We then compare these results with updated data of what really happened in the UK and in South Africa. The initial simulations aligned well with how the pandemic has evolved throughout five months following lockdown. The models are, as expected, not fully accurate, but exact enough to be used as a guideline to the evolution of the disease in both high- and middle-income countries. This is shown through simulations formed by an open source code, which allows evaluation of the outcomes from different intervention scenarios or conditions. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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