Fighting the COVID-19 Pandemic with Data Science

Matthew Schipper and team developed an App to compare the risk of postponing cancer treatment versus undergoing surgery, chemotherapy, or radiation during the pandemic.

Zhenke Wu and team develop predictive models of disease progression of COVID-19 patients with severe and mild symptoms.

Optofluidic Bioassay, co-founded by Xudong Fan, professor of biomedical engineering, is developing a device for COVID-19 antibody testing.

Al Hero, Professor of Electrical Engineering and Computer Science, on predicting the transmission of infectious disease among people who are pre-symptomatic or asymptomatic and how it relates to COVID-19.

The Center for Integrative Research in Critical Care (MCIRCC) is developing an early intervention tool to help COVID-19 patients.

A team led by Prof. Jenna Wiens, are collaborating with researchers in IHPI and Michigan Medicine to guide clinical and operational work.

MIDAS affiliated faculty and colleagues validate the Epic Deterioration Index (EDI), a predictive model implemented in over 100 U.S. hospitals that has been recently promoted for use in COVID-19 patients.

Joseph Eisenberg describes how epidemiological models provide insights to guide state and federal strategies and policymaking to control transmission.

Quan Nguyen, Christopher Brooks and Daniel Romero (School of Information) lead their team to understand how students use campus spaces and their mobility patterns, using network analysis. Their research will identify which student groups and which campus spaces are most vulnerable for infection, which are vital information as universities are planning to reopen the campus.

Maximizing COVID-safe behavior is a new goal of a multiscale game theory project funded with $6.5 million from the Department of Defense.

Veera Baladandayuthapani and team create a visualization tool for obtaining state-level projections for COVID-19 in India

Professor of Electrical Engineering and Computer Science and owner of Voxel51 developed the Physical Distancing Index (PDI) to measure the impact of COVID-19 & subsequent calls for physical distancing on social behavior

Marisa Eisenberg, Associate Professor of Complex Systems, Epidemiology, and Math, is collaborating with researchers in IHPI and Michigan Medicine to guide clinical and operational work.

MIDAS Fellow presented her COVID-19 research. Her team is among the first to publish using computational models to estimate the spread of the virus.

Bhramar Mukherjee, Chair of Biostatistics, and team used the susceptible, infected, and removed (recoveries & deaths) (SIR) model to predict the impact of India’s lockdown.

Q&A with Peter Song, Professor of Biostatistics, on “Social Distancing: Data Models for a Model Response to an Outbreak”.

Assistant Professor of Epidemiology, working with the Michigan DHHS to develop high-res maps of COVID-19 testing, incidence, & mortality. They aim to identify transmission clusters that can be targeted for intervention, both during the current outbreak and when social distancing measures are gradually lifted.

Siqian Shen, with support from Microsoft’s AI for Health program, is designing a cloud-based system that will analyze data to better organize the logistics of testing.

Michigan COVID-19 Recovery Surveillance Study is a collaboration between U-M School of Public Health and the Michigan DHHS. The goal is to conduct public health surveillance of people who have had a COVID-19 diagnosis in Michigan. Topics include symptoms, health care seeking behavior, access to basic needs, and the impact of the pandemic on social engagement and mental health, with an emphasis on health disparities.

Mike Cafarella from EECS and team are producing the unified medical institution and unified government office auxiliary databases to inform urgent action as well as to answer novel and pressing questions.

Mark Daskin, and Emily Tucker, PhD, from the Department of Industrial and Operations Engineering discuss how COVID-19 will test the strength of the medical supply chain.

Where to site COVID-19 testing facilities and how to stock them. How to triage patients and allocate hospital resources. The best ways to manage supply chains for food and other essentials.

Siqian Shen, with support from Microsoft’s AI for Health program, is designing a cloud-based system that will analyze data to better organize the logistics of testing.

Shu-Fang Shih and team received a grant from the National Science Foundation to study how behaviors and acceptance of a COVID-19 vaccine change over time.

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.

Ceren Budak and team take a first look at sharing COVID-19 information and misinformation on social media.

Drs. Jacob Fisher and Yajuan Si (Institute for Social Research) are using survey data to generate estimates on how people of different age groups and in different parts of Michigan are in contact with each other in public places, schools, workplaces and homes. Their results will provide critical information to policymakers on how to minimize both the spread of infection and economic disruption.

Moulinath Banerjee and Ya'acov Ritov, Professors of Statistics, are developing cutting-edge statistical models of the pandemic, including mobility patterns, testing capacity/pressure on the healthcare system, and active decision making strategies. Their model will help policymakers understand both the short and long-term impact of the pandemic on human health and the economy.

Kentaro Toyama and Joseph Eisenberg, speak about measures to reduce the spread of the coronavirus.

A team led by Prof. Robert Hampshire from the Ford School of Public Policy will provide data and policy analysis to two of Detroit’s pilot programs.

Aradhna Krishna, Professor of Marketing and pioneer in the field of sensory marketing discusses how COVID-19 is affecting consumer attitudes and shopping.

Rada Mihalcea and team are developing NLP methods to understand the changes in mental health associated with the outbreak, and whether certain people are more susceptible to be affected by these changes.

Rada Mihalcea and team are building an online interface where people can write about the major issues they are facing and receive personalized feedback and pointers to useful resources.

Shobita Parthasarathy, director of the Ford School of Public Policy’s Science, Technology, and Public Policy program, is studying the different ways several countries grapple with the COVID-19.

The usage of U-M alumus, Jack Griffin's, FoodFinder app, has soared as the number of people facing food insecurity rises during the pandemic.

Richard Gonzalez, professor of psychology and statistics, illustrates statistical analyses and data visualization with COVID-19 data.

The Inter-University Consortium for Political and Social Research (ICPSR) released “Best Practices for Measuring the Social, Behavioral, and Economic Impact of Epidemics” for data scientists.

Guidelines on data sharing and re-use for COVID-19 researchers to maximize efficiency

The Statistics Online Computational Resource (SOCR) Web-based BrainViewer displays multimodal brain data, atlases, and tractography models.