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.
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.
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.
Collecting DNA samples for human genetic studies can be an expensive, lengthy process that has often made it difficult to include diverse populations. Now, University of Michigan researchers believe they have found a way to harness the power of social media to recruit a large, diverse participant pool.
From understanding the influence of congressional members’ Twitter accounts to discussing why the global crude oil price rose again after 2016, the second annual Data for Public Good Symposium will showcase the unique ways in which students, faculty, staff and community members have analyzed and assessed data to benefit others.
In the 1950s, most cars didn’t come with seatbelts standard. Now, your car won’t let you drive across the parking lot without dinging until you buckle up. Just how important is empirical data in evaluating public health risks and shaping public policy?