<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.9.5">Jekyll</generator><link href="https://mdz01.github.io/feed.xml" rel="self" type="application/atom+xml" /><link href="https://mdz01.github.io/" rel="alternate" type="text/html" /><updated>2024-07-22T13:32:07-07:00</updated><id>https://mdz01.github.io/feed.xml</id><title type="html">Mengdie Zhuang</title><subtitle>Lecturer (Assistant Prof.) in Data Science at University of Sheffield</subtitle><author><name>Mengdie Zhuang</name><email>m.zhuang@sheffield.ac.uk</email></author><entry><title type="html">Household mixing during COVID-19: our research suggests adherence to lockdowns in England declined over time</title><link href="https://mdz01.github.io/posts/2021/11/blog-post-1/" rel="alternate" type="text/html" title="Household mixing during COVID-19: our research suggests adherence to lockdowns in England declined over time" /><published>2021-11-25T00:00:00-08:00</published><updated>2021-11-25T00:00:00-08:00</updated><id>https://mdz01.github.io/posts/2021/11/householdvisitation</id><content type="html" xml:base="https://mdz01.github.io/posts/2021/11/blog-post-1/"><![CDATA[]]></content><author><name>Mengdie Zhuang</name><email>m.zhuang@sheffield.ac.uk</email></author><summary type="html"><![CDATA[in our latest research, we analysed mobility data collected from almost one million people in England between January 2020 and May 2021, seeking to understand trends in home visits during the pandemic.]]></summary></entry><entry><title type="html">England’s contact-tracing system needs better data handling to beat COVID-19</title><link href="https://mdz01.github.io/posts/2020/10/blog-post-2/" rel="alternate" type="text/html" title="England’s contact-tracing system needs better data handling to beat COVID-19" /><published>2020-10-29T00:00:00-07:00</published><updated>2020-10-29T00:00:00-07:00</updated><id>https://mdz01.github.io/posts/2020/10/contacttracing</id><content type="html" xml:base="https://mdz01.github.io/posts/2020/10/blog-post-2/"><![CDATA[]]></content><author><name>Mengdie Zhuang</name><email>m.zhuang@sheffield.ac.uk</email></author><summary type="html"><![CDATA[“Contact-tracing systems represent a critical pillar of any coronavirus response… It is therefore paramount that the little information we have is used optimally “]]></summary></entry><entry><title type="html">COVID Response Dashboard (COVIDRED)</title><link href="https://mdz01.github.io/posts/2020/10/blog-post-1/" rel="alternate" type="text/html" title="COVID Response Dashboard (COVIDRED)" /><published>2020-10-28T00:00:00-07:00</published><updated>2020-10-28T00:00:00-07:00</updated><id>https://mdz01.github.io/posts/2020/10/covidred</id><content type="html" xml:base="https://mdz01.github.io/posts/2020/10/blog-post-1/"><![CDATA[]]></content><author><name>Mengdie Zhuang</name><email>m.zhuang@sheffield.ac.uk</email></author><summary type="html"><![CDATA[Is the health system capturing everyone that needs to be? Is our response to COVID-19 in England improving? - The UCL i-sense COVID RED dashboard is developed to explore public available data under five key stages to suppressing the virus: Find, Test, Trace, Isolate, and Support, and illustrate its performance. This work has been featured in the Guardian, Telegraph, Sky news etc.]]></summary></entry></feed>