We have a new preprint available. This is a deviation from the usual business of paleo- and ecological communities, in that we examine cascading unemployment in socio-economic systems when subjected to outbreaks of COVID-19. It is of course inspired by our eco-evolutionary modelling, where we’ve shown that the manner in which systems are structured, particularly how species are partitioned among functions and how those functions interact are critical determinants of system stability and persistence. Below is a plain-language summary, and the preprint may be found here. The figure above shows forecasts of workers lost in the city of Fresno, California, over a 151 day interval from the beginning of an outbreak. is the infamous initial transmission rate, and we modeled scenarios of ranging from 0.9 to 6.0. The upper grey surface is the fraction of initial employment (February, 2020) lost to severe illness and death, and the lower surface is the total fraction of employment lost as the initial losses cascade through the economic systems and are amplified by inter-industry dependencies.
Plain language summary
We use a coupled epidemiological-economic model to predict the unemployment that would be incurred by major Californian socio-economic systems if outbreaks of COVID-19 were permitted to run their courses. This is a baseline against which it is important to compare contrasting approaches that prioritize either non-pharmaceutical actions intended to disrupt spread of the disease, or safeguards to uninterrupted economic activity. We find that high unemployment would be unavoidable as the effects of worker death or debilitating illness cascade through the economic network. While predicted unemployment is lower than actual unemployment during the pandemic, that benefit comes at the cost of greatly elevated mortality. The impact would also be disproportionately more severe among smaller, goods producing, and typically inland socio-
Erratum The figures for economic losses at the end of the third paragraph, pg. 9, should read $168.25 billion and $1.7 trillion respectively.