epidemiology

Introducing the ACSH Science Dispatch Podcast — the weekly show where we separate science fact from science fiction.
A recent study found that moderate alcohol consumption — even one drink a day — could shrink your brain. The explosion of context-free headlines predictably followed. Let's dive a little deeper and examine what most reporters missed.
A new paper attempts to create the best estimate for the COVID infection-fatality rate (IFR), which answers the question, "If I get sick, what is the chance that I will die?" Beware: The virus discriminates.
Data suggest that about 3% of Americans, or nearly 10 million people, have been infected with coronavirus. Unfortunately, this data comes from late April and early May, and the virus has spread even further since then. The official COVID-19 case tally, therefore, is a dramatic undercount.
While coronavirus is obviously concerning and a very real threat to some people (namely, the elderly and immunocompromised), these data also show that the risk for the rest of the population is quite low.
A walk on the thoughtful “wild side” of why old-school epidemiology has over-promised and under-delivered, discovering that population density is more than how tightly we are packed, an alternative hypothesis for how sleep refreshes our bodies and spirits, and an update on a maligned energy source, fusion.  
The COVID-19 lockdown is responsible for both the loss of economic activity and human lives. Two independent groups of researchers concluded that the lockdown may be costing more lives than it saves.
"Track and Trace" is the latest COVID-19 catchphrase. It describes the process of identifying the ill and exposed, which then can make it safer for us to mingle socially once again. As a program gets underway in the U.S., what lessons can we learn from Asia?
It's quite likely that the human toll from COVID-19 will not be as bad as the prediction models forecasted. That's because models contain simplifying assumptions that rarely hold true in the real world; our human response is probably the least predictable of all. And yet, while all models are useful, all models are also wrong.
Different countries may appear to have different death rates, but only because they have applied different sampling and reporting policies to their accounting efforts. It's not necessarily because they are managing the virus any better, or that the virus has infected fewer, or more, people.
There is a lot of malicious misinformation on the internet about glyphosate. Much of it comes from academia.
Influenza is far deadlier than the Wuhan coronavirus, but few people worry about it. However, new diseases are scary and when information is limited, over-reactions are rational.