MIDAS researcher Daniel Forger seeks users for app that monitors biological rhythms during COVID-19 lockdown

By | News, Research

The app created by Danny Forger and team allows users to understand how their own body clocks have been impacted by social distancing and provides researchers with anonymized data to study the impact of disrupted circadian rhythms on a person’s health.

“Social Distancing and the lockdowns have affected our sleep and circadian (daily) rhythms. To address this, we have developed a “social rhythms” iPhone app that sends you a report on how your circadian timekeeping has changed since the COVID epidemic began, as well as general information about your circadian rhythms (e.g., when to seek light), based on phone, wearable data (iPhone, Fitbit, Mi Band…) and mathematical models and algorithms developed at the University of Michigan.

We hope this app can be helpful both while social distancing, and as we prepare for our new normal. The app works best for individuals who carry their phones around with them or use wearables. While your data is on our servers, we will use it for research, and hopefully, you will receive future reports through the app. You can also remove your data in the settings area of the app. All data and reports are sent anonymously. The more you and others use the app, the more we learn.”

Read more.

Research funded in part by a MIDAS Challenge Grant is published in Words That Matter: How the News and Social Media Shaped the 2016 Presidential Campaign

By | News, Research

Words That Matter: How the News and Social Media Shaped the 2016 Presidential Campaign assesses how the news media covered the extraordinary 2016 election and, more important, what information—true, false, or somewhere in between—actually helped voters make up their minds. Using journalists’ real-time tweets and published news coverage of campaign events, along with Gallup polling data measuring how voters perceived that reporting, the book traces the flow of information from candidates and their campaigns to journalists and to the public. The research project included is a Social Science Collaboration for Research on Communication and Learning based upon Big Data.

How quickly does coronavirus spread? MIDAS Fellow, Qianying Lin, works to answer the question

By | News, Research

Read more here: https://globalreach.med.umich.edu/articles/how-quickly-does-coronavirus-spread-u-m-data-science-fellow-works-answer-question

To see Qianying’s presentation, “COVID-19 Outbreak in Wuhan, China: in Retrospect and in Prospect” please click here.  A captioned version will be available soon.

Abstract: Since first confirmation in December 2019, the novel coronavirus diseases (COVID-19) infected more than 50,000 people and claimed over 2000 lives in Wuhan, China. It was transmitted across the whole country shortly, and now swept the world by causing more 20,000 infections in countries other than China. Using official reported cases and assuming changing reporting ratio, we investigated the early stage of the epidemic of COVID-19 in Wuhan and analysed its transmissibility. We then built up a conceptual model and incorporated the zoonotic introduction, emigration, individual reaction, and governmental action to simulate the trends of the outbreak in Wuhan and predicted the disease would be completely controlled by the end of April under current policies. These studies provide insights into not only the characteristics of COVID-19 itself, but the impact of governmental actions.