2024-02-11: Symbolic algebra and typing

2023-08-01: Population waves

2023-05-18: Math of telephone billing mystery

2023-05-05: Franklin and DNA More information…

2023-04-25: On angle and dimension

2023-02-20: On Leonardo da Vinci and Gravity

2022-04-29: Fabricating Evidence to catch Carmen Sandiego

2022-03-04: Probabilistic law of the excluded middle

2020-05-04: Archimedes and the sphere

2019-05-16: Glow worms return

2019-04-11: Original memetic sin

2019-01-31: The theory of weight

2018-11-06: Origins of telephone network theory

2018-10-24: Modern thought

2018-09-10: Feeding a controversy

2018-06-11: Glow worm distribution

2018-04-23: Outlawing risk

2017-08-22: A rebuttal on the beauty in applying math

2017-04-22: Free googles book library

2016-11-02: In search of Theodore von Karman

2016-09-25: Amath Timeline

2016-02-24: Math errors and risk reporting

2016-02-20: Apple VS FBI

2016-02-19: More Zika may be better than less

2016-02-17: Dependent Non-Commuting Random Variable Systems

2016-01-14: Life at the multifurcation

2015-09-28: AI ain't that smart

2015-06-24: Mathematical Epidemiology citation tree

2015-03-31: Too much STEM is bad

2015-03-24: Dawn of the CRISPR age

2015-02-12: A Comment on How Biased Dispersal can Preclude Competitive Exclusion

2015-02-09: Hamilton's selfish-herd paradox

2015-02-08: Risks and values of microparasite research

2014-11-10: Vaccine mandates and bioethics

2014-10-18: Ebola, travel, president

2014-10-17: Ebola comments

2014-10-12: Ebola numbers

2014-09-23: More stochastic than?

2014-08-17: Feynman's missing method for third-orders?

2014-07-31: CIA spies even on congress

2014-07-16: Rehm on vaccines

2014-06-21: Kurtosis, 4th order diffusion, and wave speed

2014-06-20: Random dispersal speeds invasions

2014-05-06: Preservation of information asymetry in Academia

2014-04-16: Dual numbers are really just calculus infinitessimals

2014-04-14: More on fairer markets

2014-03-18: It's a mad mad mad mad prisoner's dilemma

2014-03-05: Integration techniques: Fourier--Laplace Commutation

2014-02-25: Fiber-bundles for root-polishing in two dimensions

2014-02-17: Is life a simulation or a dream?

2014-01-30: PSU should be infosocialist

2014-01-12: The dark house of math

2014-01-11: Inconsistencies hinder pylab adoption

2013-12-24: Cuvier and the birth of extinction

2013-12-17: Risk Resonance

2013-12-15: The cult of the Levy flight

2013-12-09: 2013 Flu Shots at PSU

2013-12-02: Amazon sucker-punches 60 minutes

2013-11-26: Zombies are REAL, Dr. Tyson!

2013-11-22: Crying wolf over synthetic biology?

2013-11-21: Tilting Drake's Equation

2013-11-18: Why \(1^{\infty} eq 1\)

2013-11-15: Adobe leaks of PSU data + NSA success accounting

2013-11-14: 60 Minutes misreport on Benghazi

2013-11-11: Making fairer trading markets

2013-11-10: L'Hopital's Rule for Multidimensional Systems

2013-11-09: Using infinitessimals in vector calculus

2013-11-08: Functional Calculus

2013-11-03: Elementary mathematical theory of the health poverty trap

2013-11-02: Proof of the circle area formula using elementary methods

Ebola numbers

The ebola epidemic is a big deal. It's killing people, and it's going to kill many more.

One of the things people in goverment do these days when confronted with a problem is turn to the STEM experts and ask them "What's going to happen?" Sometimes, we can give good answers. But often, those answers are miscommunicated. One current example is this washington post article. The article talks about how the reproduction number for ebola is 1.5-2, and needs to come down.

The reproductive number use useful, but alone, not informative. We also need to know the serial interval of transmissions, which appears to be about 15 days (shorter than the 3 weeks sometimes quoted). This serial interval is the bright spot in the omnious dark cloud on the horizon. Influenza has a serial interval of only 3.6 days!

The CDC has done some more extensive modelling work, but you can get the basic idea with some highschool math and the formula

\[ \text{cases} \approx \mathcal{R}_0^{t/s} \]

where \(\mathcal{R}_0\) is the basic reproduction number and \(s\) is the serial interval.

With a serial interval of 15 days, it will take 2 - 3 months for the Ebola epidemic to grow from 10,000 to 100,000 cases, and 4-6 months to hit 1 million. If Ebola had Flu's serial interval, it would only take 24-40 days!

This makes things more of a slow, crushing disaster than most of what we have recently experienced. Let's put the numbers into context. The plague of Justinian(540 AD) we guess killed maybe 50 million people, and the Black Death killed maybe 100 million. Right now, it doesn't look like we're going to hit those numbers. But the Indonesian tidal wave killed 1/4 million people in 2004, and that kind of number is well-within reach. This will dwarf the impact of tornadoe disasters. The deadlyest earthquake in the last century only killed 300,000 (Haiti, 2010), while it seems quite possible that Ebola will hit 500,000 in early 2015. But on the other hand, this is still a small number compared to the 2.5 million Americans that die every year! It will take a full year from now before the Ebola epidemic starts competing with that number.

We have vaccines against Ebola already in clinical trials, and every indication is that vaccines will work against Ebola. The big question for us in the USA is how fast we can scale up production of our best vaccinees. Of course, if we fail to get a vaccine, the world may be a very different place in 2 years. Another risk is if Ebola evolves to have a faster serial interval or easier transmission, in which case we might be talking about 10 or 100 times greater impacts.