Coronavirus was low risk until it wasn’t. Climate change is the same.

The hidden risk of pandemics and climate change.

Nate Upham
5 min readMar 27, 2020

by Liliana M. Dávalos and Nathan S. Upham

The Covid-19 pandemic and human-induced climate change share many parallels, from decades of warnings about their risks by scientists and policy experts, to profit-driven resistance to change by politicians and business interests. But for us scientists who study extinction risk, the tightest parallel between Covid-19 (the disease caused by the novel coronavirus SARS-Cov2) and global climate change is that they both present risks to society that increase nonlinearly through time. That means that climate change — like coronavirus — will require ambitious collective action, from global data sharing to socioeconomic restructuring, to prevent catastrophic outcomes.

Nonlinear risks mean that dangerous events will be twice as likely to occur later as they are today, with rapid doubling in frequency unless checked. Our linear minds find nonlinear growth counterintuitive, but this is familiar to many biologists. Invasive plants, for example, often establish their populations covertly until they are suddenly everywhere. How can this be? A common example goes like this: if the water hyacinth doubles its population every day and covers a pond in 28 days, on what day has it covered half the pond? Even biologists may get it wrong, for the mind, unfamiliar with nonlinear dynamics of exponential growth, recoils from the answer: the pond is half covered on day 27. For the pond’s fish, their risk of being enclosed by plants grows exponentially too. Land managers aiming to save those fish must act early, well before day 27, to “flatten the curve” of nonlinear risk for the fish to survive.

Increasingly high risks of the “nonlinear world” can sneak up on us because they look similar to low risks from the “linear world.” Here, the term “linear world” is used to refer to our expectations built from everyday experiences that rare events will occur at predictably rare intervals. Events of large magnitude are either very rare, and thus are not worth worrying about (constant low risk), or else they are more common and then dealt with right away (constant high risk). In contrast, the “nonlinear world” of invasive plants, coronavirus, and climate change involves risks that become increasingly more risky through time. The danger comes when linear-world thinking causes us to confuse early stages of nonlinear risk with constant low risk — if ignored for too long, nonlinear risks will explode into global pandemics and catastrophic extreme weather conditions. Image credit: NS Upham

Thinking of each person as potential habitat for Covid-19 can help visualize the same process, since we are all vulnerable to this vaccine-less coronavirus. As with the water hyacinth, without forceful intervention, the expansion of Covid-19 is governed by its rate of growth. For virus-borne diseases, this is the average number of people infected by any one infected person (what epidemiologists call the basic reproductive number). For this novel coronavirus, it is estimated that every infected person passes the virus to between 2 and 4 new people. Any number greater than 1 translates into nonlinear, exponential growth as the infected person more than replaces their own infection. Imagine we are the fish in the pond and together with world governments we are land managers helping to flatten our own nonlinear risk, but in this case of contracting Covid-19.

Climate change has similar nonlinear dynamics, modeled for over four decades as the higher risk of extreme weather events with more greenhouse gases like CO2 (carbon dioxide) and warmer global temperatures. Back in the 1990s, when scholars believed policy would soon follow the best scientific models, one target for stabilizing atmospheric CO2 concentration was 350 ppm (parts per million). That CO2 target would have limited global average temperature to about 1.5°F warmer than a pre-industrial climate, and thereby lessened negative consequences for society. However, that target was missed (we now exceed 410 ppm), and we are headed toward scenarios of catastrophic >3°F average warming by 2030 unless coordinated global action is taken. With warmer lands and oceans, the intensity and irregularity of weather events are growing increasingly extreme — these are nonlinear climate risks to humanity.


Climate change is bringing a “new normal” in which storms, droughts, fires, and floods usually observed at 100-year intervals are happening several times annually. Previously rare events are more and more common. We are again fish in the pond, only this time the apparently slow-moving threat is climate change. At first distant in space by melting far-away icecaps, and in time by only affecting future generations, now the threat of climate change covers nearly half the global “pond.” However, instead of having another four decades to avert a global crisis, we have under 10 years left to act decisively. The latest report of the Intergovernmental Panel on Climate Change calls for dramatic cuts of up to 45% of current CO2 emissions by 2030 to prevent what 3°F warming brings: erratic and stronger storms, rising oceans, famine, political instability.

Seeing the parallels between Covid-19 and climate change — an initially distant threat that grows exponentially larger to impact billions of lives — we now call for purposeful action on both fronts. Flattening the nonlinear curve of coronavirus infection risk is the same concept as flattening the risk curve for CO2-fueled extreme weather events. What we lack is the socio-political will to disrupt the comforting illusion that these are still linear times. They are not. Science — epidemiology and ecology for Covid-19, climatology and physics for climate change — has built predictive models that capture the nonlinear risks, and thus catastrophic costs, of inaction. Let us now heed those models, and do so before day 27.

  • Dr. Liliana M. Dávalos (@LabDavalos) is a Professor in the Department of Ecology and Evolution at Stony Brook University specializing in genomics, biodiversity, conservation, and tropical deforestation.
  • Dr. Nathan S. Upham (@n8_upham) is an Assistant Research Professor in the School of Life Sciences at Arizona State University, and Research Associate at Yale University and the Field Museum of Natural History. He specializes in mammal evolution, genomics, and conservation.
  • Both Dávalos and Upham study extinction risk of wild animals relative to human and natural causes.

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Nate Upham

I am an Assistant Research Professor & Associate Curator of Mammals at Arizona State University, studying biodiversity, extinction, and evolutionary rates.