Global Public Health

global hotspots on a digital map

Surveillance Testing: Gathering the Data on COVID-19

Q&A with Emily Martin

Emily Martin is an associate professor of epidemiology at the University of Michigan School of Public Health and an expert in viral respiratory illnesses. She explains what surveillance testing is and how it can help us in the process of slowing the spread of this virus.

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Coronavirus Modeling, Impact on India's Pandemic Response

Q&A with Bhramar Mukherjee

Bhramar Mukherjee, a professor and chair of biostatistics at the University of Michigan's School of Public Health, leads a team of researchers that, as the coronavirus pandemic unfolded around the world, used standard epidemiologic models to do a situational assessment of the crisis in India—providing real-time data for authorities to assist leadership in addressing this global pandemic.

Hotspot map of the world with Coronavirus cases.

Digesting the Data: Tips for Understanding and Acting on the Coronavirus Numbers

Q&A with Neil K. Mehta

Humans produce a lot of data, and it seems the current epidemic crisis has accelerated our production of and engagement with numbers, graphs, and maps. But we can learn a lot from all the statistics, especially if we know how to digest and interpret it all. Demography expert Neil Mehta shares his thoughts on how to follow and understand the coronavirus outbreak in a meaningful way.

Colorized view of coronavirus.

Coronavirus Information and Updates

Michigan Public Health Experts

As the 2019 Novel Coronavirus continues to spread, University of Michigan School of Public Health experts provide these answers to questions for the media and the general public about the virus itself, how it is transmitted, and how concerned we should be.

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Social Distancing: Data Models for a Model Response to an Outbreak

Q&A with Peter Song

Biostatistics expert Peter Song and team have created a tool to assess the effectiveness of preventive measures in the fight against the COVID-19, still a new disease with many unknowns. The model lets us compare the impact of different levels of intervention so different locales can develop better strategies and policies to flatten the coronavirus curve.