Cartographies of COVID-19: Our Unclear Path Forward

11. The frustration with getting good data–or indeed relying on the Center for Disease Control (CDC) for information, exacerbated by the lack of clarity and poor policy decisions that prevented testings from being accelerated in February, after the CDC failed to expedite delivery of test kits and prevented laboratories from developing new test kits, and distributed faulty test kits, may have led to a crowd-sourced mapping of “CovidNearYou” that mapped self-reported symptoms and those taken tests–providing a way of integrating oneself within the map!

All too often, if the discourse of the map was containment, the coronavirus had already spread far outside any horizon of containment; besieged by a range of successive visualizations of “latest” numbers of infection and the tallies of deaths, we have been hardly been to process over time, let alone place them in a recognizable narrative.

Has the closure of borders, mental as well as administrative, been in a sense a cause, as it was promoted by the Trump’s White House as a ‘cure’ for a pandemic that they could not process or admit? While President Trump mis-maps the spread of COVID-19, using hugely limited undercounts of infections that are officially “confirmed”–and delaying further testing–we seem to use maps to try to come to terms, embody, and grasp the exponential spread of the virus SARS-CoV-2 in spatial term–but the peaks of its intensity, the uncertainty of data about who is infected, at a time when testing is restricted to those who display symptoms, asymptomatic infected going uncounted,–cumulative fatalities tied to COVID-19 are magnified and distorted by commorbidities difficult to parse on the front lines–if they reached roughly 70-80% among those requiring hospitalization, the data is just not there.

We need data to visualize the impact of a slippery disease that doesn’t respect borders, in short, but risk misconceptions by mapping the disease.

Was the failure to map the global impact of the disease–whose genome was being mapped in a global context as the World Health Organization declared it a global pandemic at the very late date of March 13, 2020, a problem of integrating the choropleths in which we watched abstract disks sized to reported infection rates–if often built from bad data, and inheriting a visualization tool of the nineteenth century, hardy fit to the mortality rates or scale of a twenty-first century problem–part of the problem? Or was the difficulty of linking multiple scales–the spatial progress of the pace of infection, which was centered in counts of cases clustered in China’s shores, but which shores or national boundaries didn’t make much sense to count–save in a map of nation-states and stable borders–provide a poor map to how the virus multiplied in different strains, or worked its way in human bodies?

While the virus was non-living, were we mapping it in human terms, by maps that perpetuated nations as discrete entities, that masked the scale at which the RNA strain replicated in human hosts, and moved in man-made spaces, as it was conveyed in record time across the planet, outpacing our categories of spatial constructs in its exponential growth? If we had continued by mid-March to center the global map of COVID-19 in China, viewing the deep blue buffer as a source of strains, the mother lode, the global remapping of cases grew along its own curve, and developed its own pace, eerily related to our own motion over global space, but moving at a level of RNA strains that mutate across that space.

Genomic Map of COVID-19 from 13, 2020

Mapping of travel and mutation of the virus over space has allowed the team at NextStrain to assemble an online resource tracking evolution of the disease-causing organism in real time in invaluable ways, much as it has provided tools to track previous outbreaks of infectious diseases as Zika, Ebola and Dengue: the ability to map the tremendous speed of its spread and infection, using a massive databank of mutations of the non-living virus that was tracked in real time through human hosts. Real samples help understand the virus over a global space, as one strain grew in China’s Hubei Province, and mutations developed and contracted in Washington, Germany, France and South America. By connecting the outbreaks of diseases over space in real time by tracking the weekly mutation rates of its life cycle, however, as the organization mapped the mutation of the SARS genome–and which had taken over three months to sequence–accelerated remarkably in an unprecedented data sharing across borders to meet the nature of the emergency and current needs, publishing the entire SARS-CoV-2 genome online within days of its identification by Chinese scientists–a tremendous acceleration.

Ability to plot an accurate distribution of viral strains aggregated from individual samples help understand the virus over a global space: but we mapped by national blocks.

Did the spatial spread of the virus truly seem so remote? Dispersal of the virus over geographic space was tracked in detail for its genomics, the possibility of its spatial spread or contraction across borders seemed remote. The open data allowed assembly of an animated map revealed the velocity of spatial proliferation of 700 different genomic signatures of the novel coronavirus, visualizing the course of the novel virus’ paths crucial to developing antiviral drugs we have never worked to develop, or thought we would need–because it was never considered ever to be so dangerous to humans.

The very possibility of the outbreak of the virus beyond China seemed remote. Even as it extended to Iran and northern Italy, allowing us to imagine the exponential transmission of the disease on an adequate scale. The lack of any models to place a global pandemic’s spread is disturbing. Even after China openly raised a red flag about COVID-19’s rapid spread of infection at the end of February, infections rising to almost 80,000, and expanding, we mapped the virus as distant and imagined it as remote; if we understood the world was globally interconnected, we could not recognize the inapplicability of early models of viral transmission or infection to the exponential growth of SARS-CoV-2 or the disease COVID-19.

To be sure, no comparable global narrative existed–we turned to apocalyptic narratives with ease, the growth of infections so unheard of in scale, continuity, or incidence. Was there a true denial of the absence of social safety nets that had eroded over time, as if the progressive draining of underground aquifers had progressed under our feet in ways that we tacitly acknowledged, but had not really registers, until we faced the prospect of multiple overpopulated cities suddenly going dry? E.O. Wilson has listed the exhaustion of freshwater supplies as among the three major emergencies faced by humanity–with global warming and mass extinction–but it has received less attention.

The ground has similarly shifted beneath our feet in the landscape of COVID-19, as we turn to maps to grapple with infection’s spread. We ponder the increased vulnerability among those with considerably higher chronic medical conditions, and a staggering 40.6 million living without savings who face a lack of income, we risk returning to an ancien regime society administered local feudal lords more reminiscent of a dystopia than civil society.


Filed under data visualization, disease maps, infectious diseases, public health, US Politics

2 responses to “Cartographies of COVID-19: Our Unclear Path Forward

  1. Rachel brownstein

    It is amazing that his response is to close the borders. Has to be something weirder than denial, as you suggest. Border closing as both cause and “cure”.

    • The denial might be strategic, in part, as well as cognitive. The desire to bracket the danger of the problem suggests not only a cavalier nature to reality, and the hubris of being in control of the situation, but inability to acknowledge the responsibility of governments and the desire to be able to shift discussion to a story of personal ability. The crisis offers an opportunity to achieve an existing goal–as about American companies leaving China!–but as able to be leveraged to his own good in multiple ways.

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