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    <title>Tim Churches Health Data Science Blog</title>
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    <description>A blog dedicated to noodlings about health data science.
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      <title>Don't speculate, simulate!</title>
      <dc:creator>Tim Churches</dc:creator>
      <link>https://timchurches.github.io/blog/posts/2020-03-20-dont-speculate-simulate</link>
      <description>Just a pointer to a further post on COVID-19 simulation that I wrote for the R-Views blog.</description>
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      <category>COVID-19</category>
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      <pubDate>Fri, 20 Mar 2020 00:00:00 +0000</pubDate>
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      <title>Modelling the effects of public health interventions on COVID-19 transmission using R - part 2</title>
      <dc:creator>Tim Churches</dc:creator>
      <link>https://timchurches.github.io/blog/posts/2020-03-18-modelling-the-effects-of-public-health-interventions-on-covid-19-transmission-part-2</link>
      <description>This is the second of several posts which examine the effect of various public health interventions on the local epidemic spread of COVID-19 infection using stochastic individual compartmental models (ICMs) implemented by the `EpiModel` library for R. In this post we extend the ICM SIR model provided by `EpiModel` in various ways to improve its verisimilitude and utility for COVID-19 simulation.</description>
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      <category>COVID-19</category>
      <guid>https://timchurches.github.io/blog/posts/2020-03-18-modelling-the-effects-of-public-health-interventions-on-covid-19-transmission-part-2</guid>
      <pubDate>Wed, 18 Mar 2020 00:00:00 +0000</pubDate>
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      <title>Modelling the effects of public health interventions on COVID-19 transmission using R - part 1</title>
      <dc:creator>Tim Churches</dc:creator>
      <link>https://timchurches.github.io/blog/posts/2020-03-10-modelling-the-effects-of-public-health-interventions-on-covid-19-transmission-part-1</link>
      <description>This is the first post of several that examines the effect of various public health interventions on the local epidemic spread of COVID-19 infection using stochastic compartmental models implemented by the `EpiModel` library for R.</description>
      <category>R</category>
      <category>COVID-19</category>
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      <pubDate>Tue, 10 Mar 2020 00:00:00 +0000</pubDate>
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      <title>COVID-19 call-to-arms</title>
      <dc:creator>Tim Churches</dc:creator>
      <link>https://timchurches.github.io/blog/posts/2020-03-06-covid-19-call-to-arms</link>
      <description>A new blog post has been published which is a call-to-arms for epidemiologists and data scientists in the fight against COVID-19.</description>
      <category>R</category>
      <category>COVID-19</category>
      <guid>https://timchurches.github.io/blog/posts/2020-03-06-covid-19-call-to-arms</guid>
      <pubDate>Fri, 06 Mar 2020 00:00:00 +0000</pubDate>
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      <title>Analysing COVID-19 (2019-nCoV) outbreak data with R - part 2</title>
      <dc:creator>Tim Churches</dc:creator>
      <link>https://timchurches.github.io/blog/posts/2020-03-01-analysing-covid-19-2019-ncov-outbreak-data-with-r-part-2</link>
      <description>A further exploration of COVID-19 incidence data using R tools and packages.</description>
      <category>R</category>
      <category>COVID-19</category>
      <guid>https://timchurches.github.io/blog/posts/2020-03-01-analysing-covid-19-2019-ncov-outbreak-data-with-r-part-2</guid>
      <pubDate>Sun, 01 Mar 2020 00:00:00 +0000</pubDate>
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      <title>Analysing COVID-19 (2019-nCoV) outbreak data with R - part 1</title>
      <dc:creator>Tim Churches</dc:creator>
      <link>https://timchurches.github.io/blog/posts/2020-02-18-analysing-covid-19-2019-ncov-outbreak-data-with-r-part-1</link>
      <description>An exploration of COVID-19 incidence data using R tools and packages.</description>
      <category>R</category>
      <category>COVID-19</category>
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      <pubDate>Tue, 18 Feb 2020 00:00:00 +0000</pubDate>
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