Never let a good crisis go to waste

11 05 2020

pandemic

First published in the Millennium Alliance for Humanity and the Biosphere Blog on 5 May 2020.

by Professor Dan Blumstein (University of California at Los Angeles), Professor Paul Ehrlich (Stanford University), and Corey Bradshaw (Flinders University)

Winston Churchill’s words have never been more important than today as we experience the society- and life-changing consequences of the COVID-19 pandemic.

The extent and severity of the disease is a result of ignoring decades of warnings by scientists about the general deterioration of humanity’s epidemiological environment, and specific warnings about confining live, wild animals in markets. The situation was made even more lethal by ignoring the warnings from epidemiologists and disease ecologists once it became clear that an imminent pandemic most likely arose from this practice. Many countries, including the United States, are still ignoring those warnings and the required actions to lessen the impact.

Accordingly, we should ask ourselves, “what else are we missing?” What other huge problems are hiding in plain sight where science could guide policy to avoid catastrophic future failures? For instance, there are two principal health threats that must be addressed immediately, and we must strike while the iron is hot.

The overuse of antibiotics in agriculture will cause widespread deaths from formerly treatable bacterial diseases because of the evolution of antibiotic resistance in microbes. The evolution of resistance is well-known, predictable, and obvious — not in retrospect, but now. By feeding antibiotics to otherwise healthy livestock, animals can be housed in higher densities and they grow faster. Read the rest of this entry »





Projecting global deaths from covid19

18 03 2020

covid

I know that it’s not the best way to project expected deaths from a pandemic disease, but being something of a demographer, I just couldn’t help myself.

I therefore took the liberty of punching in some basic probabilities into our world population model to see how many people could potentially die from covid19. But this is not an epidemiological model, so I’m probably vastly over-estimating the total death rates.

Nonetheless, the results were revealing.

I first took the expected mortality by age class based on the Chinese data so far. I then assumed a worst-case scenario of a 60% infection rate (i.e., 3 out of 5 of us will eventually catch the virus). I assumed these values across the entire globe (not taking into account greater or lesser susceptibility or probability of death among countries or regions).

I also considered two more scenarios: (i) double the mortality rate (in each age class), and (ii) the disease outbreak lasting two years instead of just one.

The graph below shows the four different outcomes based on these scenarios relative to the baseline (no covid): Read the rest of this entry »