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The scale and dynamics of COVID-19 epidemics across Europe

Dye, Christopher

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        <foaf:name>Dye, Christopher</foaf:name>
            <foaf:name>Oxford University*</foaf:name>
    <dct:title>The scale and dynamics of COVID-19 epidemics across Europe</dct:title>
    <dct:issued rdf:datatype="">2020</dct:issued>
    <dct:issued rdf:datatype="">2020-09-29</dct:issued>
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    <dct:description>&lt;p&gt;The number of COVID-19 deaths reported from European countries has varied more than 100-fold. In terms of coronavirus transmission, the relatively low death rates in some countries could be due to low intrinsic (e.g. low population density) or imposed contact rates (e.g. non-pharmaceutical interventions) among individuals, or because fewer people were exposed or susceptible to infection (e.g. smaller populations). Here we develop a flexible empirical model (skew-logistic) to distinguish among these possibilities. We find that countries reporting fewer deaths did not generally have intrinsically lower rates of transmission and epidemic growth, and flatter epidemic curves. Rather, countries with fewer deaths locked down earlier, had shorter epidemics that peaked sooner, and smaller populations. Consequently, as lockdowns are eased we expect, and are starting to see, a resurgence of COVID-19 across Europe.&lt;/p&gt;</dct:description>
    <dct:description xml:lang="">&lt;p&gt;The data used for analysis are provided in the Excel files, in which cells contain formulae for carrying out basic computations. Graphics in the paper are also presented in the Excel files, which point to the source data in each file. Click "don't update" when opening Excel files. Although the SEIR and skew-logistic models cna be run from the Excel files provided, readers can also construct these models from the information given in the Supplementary Materials (included with the manuscript).&lt;/p&gt; &lt;p&gt;Funding provided by: Oxford Martin School, University of Oxford&lt;br&gt;Crossref Funder Registry ID:;br&gt;Award Number: &lt;/p&gt;</dct:description>
        <rdfs:label>&lt;p&gt;File "SEIRModel Germany Fig 1.xlsm" is a SEIR model, described in the Supplementary Materials and implemnted in Excel. Instructions for entering the data are on sheet "Data". Insrructions for running the model are on sheets "SEIRModel (eqs)" and "Fit". Visual Basic Macros are visible in "Developer". &lt;/p&gt; &lt;p&gt;Two main public data sources, used as described in the Supplementary Materials (included with the manuscript):&lt;/p&gt; &lt;p&gt;Figs 2 &amp;amp; 3 were drawn from public data provided by European Centre for Disease Prevention and Control, COVID-19. 2020, which can be downloaded from:&lt;/p&gt; &lt;p&gt; (data in "Data skew-logistic Figs 2&amp;amp;3")&lt;/p&gt; &lt;p&gt;Fig 4 was drawn from public data provided by T. Hale, S. Webster, A. Petherick, T. Phillips, B. Kira. (Blavatnik School of Government, Oxford, 2020), which can be downloaded from:&lt;/p&gt; &lt;p&gt; (data in "Containment index Fig 4").&lt;/p&gt; &lt;p&gt;Fitting of the skew-logistic model is carried out in "Skew Logistic fit template Fig 2.xlsm" as described on sheet "Instructions". Visual Basic Macros are visible in "Developer". &lt;/p&gt;</rdfs:label>
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        <rdfs:label>Open Access</rdfs:label>
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            <rdfs:label>Creative Commons Zero v1.0 Universal</rdfs:label>
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