Recent Posts

The Backstory: Rising Cases of Measles Despite High Vaccination Coverage This explainer is about my recent paper published in PNAS. Even though US measles vaccination rates were on average higher than 95%, which is the WHO vaccination coverage target and threshold for maintaining herd immunity for measles, there were 1,282 cases of measles in 31 states in 2019.

I just finished teaching my first course at Michigan, which was called Theory and Applications of Spatial Epidemiology. At the end of the term, one of the students asked for suggestions for further reading.

Note: This post is part of a series on reproducibility. With any luck, it will make sense on its own. But it may be helpful to start from the beginning.

Note: This post is part of a series on reproducibility. With any luck, it will make sense on its own. But it may be helpful to start from the beginning.

Note: This post is part of a series on reproducibility. With any luck, it will make sense on its own. But it may be helpful to start from the beginning.

Reproducibility is becoming more and more a part of the conversation when it comes to public health and social science research. A lot has been said about p-hacking, the file drawer effect, and other subtle and unsubtle biases that can make replicating published results difficult with new data.

Note: This post is part of a series on reproducibility. With any luck, it will make sense on its own. But it may be helpful to start from the beginning.

I was excited to see this recent article by Mosoka Fallah and coauthors in PLOS Negected Tropical Diseases on the impact of socioeconomic status (SES) on transmission rates in the recent Ebola outbreak in West Africa.

The figure below is from my recent paper on multi-drug resistant TB in Lima, Peru in the Journal of Infectious Diseases, with Ted Cohen at the Yale School of Public Health, Megan Murray, Mercedes Becerra, and others at the Harvard School of Public Health and Partners in Health/Socios en Salud in Lima.

Although I know I’m decidedly late to the party, I’ve recently rediscovered the incredible usefulness of Make, particularly as part of a reproducible scientific workflow. In my own work, which runs towards the computational, the easy reproducibility you get from make is critical not just for the usual reasons about being able to prove you did what you said you did, but also for being able to easily make changes when I’ve stepped away from a project for awhile and forgotten how some of the layers work, or when it’s time to do revisions and I can’t remember how something was done.