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No illusion. Covid19 is closer to us than we imagine. And getting closer day by day. Globally, in big cities and small centres alike, people are sliding into a sort of dystopian fiction as if empty streets, latex gloves, face masks and self-isolation were the new normal. Last Sunday, India with its population of over 1.3 billion citizens, had a first try at a total shutdown from 7am to 9pm, in a country where 1.8 million are homeless and 73 million don’t have a decent home.

The media of the entire planet is gripped by coronavirus. Never before has a virus stopped the entire world’s gears. Deep concern has spread throughout, and finally we start to see governments engineering some mass planning for worst-case scenarios. As it should be, the repercussions move from the global health sphere into business and politics.

The Coronavirus shockwave will end, at some point. Meanwhile, it is forcing a Copernican re-thinking of the interconnected global economy we have had in place for over three decades. Covid19 is not the first wake-up call to the world of the twenty-first century. The first seismic shock came with the terrorist attack of 9/11, followed by the global financial crisis which boiled over in 2008, with the collapse of Lehman Brothers. Yet again, this invisible and silent virus – a minuscule RNA packet enveloped in a protein capsule – has shaped up to be an enormous stress test for globalization, shaking up all our certainties and individual lives.

We are re-discovering just how vulnerable nations and people are. Just how fragile the globalized economy is, with its productive arrangement. In his latest book on inequalities, Walter Scheidel reminded us that epidemics have always been one of the most transformative events in human history[i]. Nothing new under the sun. Except that we don’t seem to learn the key lessons that the past, including the recent past, offers us.

Since the start of the millennium we’ve had repeated species jumps of the coronavirus variety. The first occurred in China with SARS in 2002-2003, then in 2012 with MERS in Saudi Arabia and Jordan. Other species jumps occurred with swine flu (H1N1) in 2009, bird flu in 2013 and 2017 (H7N9), and other pathogens like Zika and Ebola (still active in Africa). For decades, experts from the science community have warned about the need to prepare for another pandemic like the 1918 Spanish flu (“the Great Influenza”), which killed over 50 million people worldwide, but their premonitions have gone unheeded. Now that we are in it, SARS-CoV2 looks pretty much like the pathogen that scientists had been waiting for. It kills healthy adults as well as elderly people. Covid19’s global 3.4% fatality rate, according to the figure of the World Health Organization (WHO), is much higher than the 2% of the Spanish pandemic. It is true that we lack reliable evidence on how many people have been infected. Figures are calculated by divining the number of officially confirmed cases, but there are many more mild or simply undetected cases that go uncounted, and that would bring the mortality rate significantly down.

What we do know for certain, though, is that the virus has an exponential transmission rate: one affected person may pass it on to 2-3 people, 10 people if the vector is a doctor or a nurse. The efficiency of the contagion applies equally to symptomless and pre-symptomatic individuals, or people with few symptoms[ii]. This means that Covid19 is much harder to contain than SARS, which had a slower transmission pace, and only through symptomatic persons. Covid19 has caused 10 times more cases than SARS already, in a quarter of the time.

Citations

[1] Global Homelessness Statistics - Homeless World Cup ➤ https://homelessworldcup.org/homelessness-statistics/[2] The Scientific Response to a Pandemic ➤ https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.0020009[3] In the coronavirus pandemic, we're making decisions without reliable data ➤ https://www.statnews.com/2020/03/17/a-fiasco-in-the-making-as-the-coronavirus-pandemic-takes-hold-we-are-making-decisions-without-reliable-data/[4]https://www.nejm.org/doi/full/10.1056/NEJMp2003762