Why it is so hard to predict epidemics

Epidemics accompany mankind as death follows life. AIDS, SARS, Ebola, and now Zika. The Spanish flu of 1918 may have killed up to 100 million people in the aftermath of World War One. Some are epochal, like the Black Death that arrived in the 14th century from the East. But predicting an epidemic or pandemic is unusually difficult because they are triggered by a random event: a pathogen crosses into humans from another species. The very same technological processes that contribute to accelerate the spread of these viruses—chiefly, the explosion of international travel—allows us to marshal the resources to fight them, which owe quite a bit to the renewed interest in medicine that followed the Black Death.

Apple and the Bikini Parable

Aaron Levenstein, a business professor, compared statistics to bikinis: what they show is important but what they hide is essential. The same applies to the usual reactions of panic at Wall Street whenever growth slows. Apple hit a plateau, indeed: in its earnings report, the company acknowledged that iPhone sales had their slowest growth ever in the last quarter. But, as Farhad Manjoo of the New York Times reminds us, the $18.4 billion profit that Apple reported “is the most ever earned by any company in a single quarter.” So if you have invested in Apple or are worried that the company is on its last throes and you will not see all these marvels being churned off every year, relax, and maybe spend a day on the beach.

Three minutes to midnight

Failure to address the threats posed by nuclear proliferation and climate change has moved forth the long hand of the Doomsday Clock: the symbolic countdown was created by the Bulletin of the Atomic Scientists in 1947 to warn about man-made existential perils to humanity. It now stands at three minutes to midnight, the closest the clock has ticked towards doomsday since 1984, at the height of the Cold War. It may be no coincidence at all if it sounds Orwellian.