From c16c75e6ddb58d4fa4c74f61a4e63e8412ea7fa2 Mon Sep 17 00:00:00 2001 From: Dina Mistry Date: Sun, 20 May 2018 20:16:52 -0400 Subject: [PATCH] add image --- _layouts/default.html | 2 ++ publications/index.html | 2 +- research/index.html | 24 ++++++++++++++++++++++++ visualizations/Maharashtra_CM_85_H.pdf | Bin 0 -> 36852 bytes 4 files changed, 27 insertions(+), 1 deletion(-) create mode 100755 research/index.html create mode 100644 visualizations/Maharashtra_CM_85_H.pdf diff --git a/_layouts/default.html b/_layouts/default.html index 3fbf246..8b780c3 100644 --- a/_layouts/default.html +++ b/_layouts/default.html @@ -15,7 +15,9 @@
  • About
  • CV
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  • Research
  • Publications
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  • Visualizations
  • diff --git a/publications/index.html b/publications/index.html index 356725b..053140b 100755 --- a/publications/index.html +++ b/publications/index.html @@ -1,6 +1,6 @@ --- layout: default -title: Publications +title: Publications Dina Mistry ---
    diff --git a/research/index.html b/research/index.html new file mode 100755 index 0000000..f8a59a7 --- /dev/null +++ b/research/index.html @@ -0,0 +1,24 @@ +--- +layout: default +title: Research Dina Mistry +--- + +
    +

    Research

    + + +

    Contact patterns in the context of infectious disease spreading

    + +

    The aim of this work is to infer the social contact patterns underlying the dynamics of infectious disease transmission in different populations around the world. In the context of airborne infectious diseases, social contacts refer to those whom an individual spends time with in close physical proximity and thus can infect or be infected by with the pathogen. To this end, we employ a data-driven computational approach to infer the contact networks in the social settings where people spend most of their time and thus are likely to spread airborne diseases like influenza; namely the household, school, workplace, and general community.

    + +

    Check out the github project repo for the latest on this work.

    + + + + + + + + + +
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