Covectors is the collaboration between Kate Gibson (MFA, Painting and Printmaking, University of Cincinnati) and Emily Van Walleghen (MFA, Fine and Studio Art, University of Cincinnati; PhD, Human Nutrition, Food, and Exercise, Virginia Tech).
January, Not My Problem
In mid-March, the US shut down, and those who could retreated to their homes, drew the curtains, and waited as the Covid-19 pandemic began to sweep across the country. As the months pass by, the epidemic intensifies as states reopen. Private boundaries, public health, and politics have interwoven creating a national tapestry filled with rips and tangles. We explore public COVID-19 data and its visual representations and how both can be misinterpreted or used to mislead by re-interpreting technical depictions of data using historically female-gendered domestic techniques. Translating visual information from each month of the year 2020 into curtains, we propose:
1) Social isolation is a privilege
2) Graphs and charts obscure the human cost behind the pandemic
3) We must acknowledge our interconnectedness and interdependence at both the international and community levels.
January: “Not My Problem”
“We have it totally under control. It’s one person coming in from China, and we have it under control. It’s going to be just fine.” -Donald Trump, January 22nd, 2020.
“Trump Restricts Entry Into U.S. From China” -NY Times headline, January 31, 2020.
In January the US proceeded under the illusion that Covid-19 would be contained within China’s borders. The threat was perceived to be to the Chinese, approximately 18% of the world’s population. In 100 strands of beads an attempt was made to keep the infected separate via travel bans and racism. Yet at the bottom of the curtain the strands intertwine, a tangled mess of transmission and miscommunication. Beaded curtains have a long history in China, going back thousands of years- at one vibrant and unique entity that has evolved into the mass produced “made in China” curtains ubiquitous throughout the world. Virus and capital know few boundaries.
February: “Spectator Sport”
In February, confirmed Covid-19 cases were growing at an exponential rate. The graphs and charts were startling. Still operating under an illusion of safety, we in the US continued as if we were protected by imaginary boarders. Checking the news for daily recaps of death and infection across the Pacific brought voyeuristic pleasure. Online discussions about linear vs logarithmic scales erupted as we all became statisticians and epidemiologists from behind the safety of our computer screens.
The World Health Organization released daily reports on the total case numbers, new infections, new deaths, total deaths, new recoveries and total recoveries. While a graph may represent data, without a key or scale the numbers are meaningless, morphing into banners for sport.
March: “No Comfort Here”
March was the month of shut down. March was the month our world shifted. The reassurance of routine was gone and replaced with solitude. An initial knee jerk reaction was to seek solace in hoarding comfort items which sat in a box for months. As loneliness shifted to frustration, they were finally shredded.
March was the month when we started talking about “exponential growth” and “flattening the curve.” We became armchair biostatisticians.
We had the chance to stop the exponential growth and flatten the curve. We did neither. March is both what might have been and what actually transpired.
We weighed what happened...our failure warning “don’t let COVID-19 bite” and the exponential growth of March. We considered what might have been... a mirror image of exponential decline and the wish of “good night, sleep tight.”
The outcome was a very abnormal normal curve. Statistics are meaningless if the data is unreliable.
April: “Flatten the Curve”
Much of the country was under quarantine in April. The phrase “flatten the curve” became a national mantra, a goal. Children continued remote learning, those who could worked from home, essential workers faced constant risk and uncertainty. The collective hope was that these actions would stem the precipitous rise in cases, deaths, hospitalizations, occupied ICU beds, and ventilator shortages. Americans held onto the illusion that quarantine would be temporary as they watched the daily statistics crest and then fall during April in parallel with their emotions. The uncertainty was overwhelming as we helplessly monitored the information including that available at https://covid19.healthdata.org/united-states-of-america.
May: “True Colors”
By May, time slows, cracks form, and bleakness seeps in. We had exhausted any new sources of communication and any lifelines to the outside world, and life was reduced to a routine without the optimism of the spring. It became impossible to hide from the disease and death that seemed to lurk just beyond the next social interaction, so we retreated to our workspaces to try and find comforts. Historically, domestic arts would achieve this by creating decorative trinkets and useless items like embroidered samplers. Cheerful patterns and routines marking the days and weeks gave way to stitching along blindly without a plan. It had become difficult to look past the cynicism of empty slogans for a public health solution that was not going to come.
June: “Unequal Application”
Quarantined Americans began to grow weary of stay at home orders. With no unified messaging coming from the White House, state and community authorities were left alone to enforce and defend their public health mandates. Communities of color were disproportionately affected by the virus, leaving many white and rural communities wondering if we were all over reacting. A rebellion began bubbling up as people stormed statehouses, refusing to wear masks and demanding haircuts. Banal conveniences were conflated with civil rights as effigies of local leaders were hung from trees.
Quarantined Americans witnessed police officers murder yet another black American man as video of George Floyd dying circulated on the internet. Protests erupted across the country, spreading beyond our borders and becoming a global call to confront racial inequality. Using data from Ohio we have overlayed how the virus affected different populations over the arrests for breaking stay at home orders in four Ohio metro areas by race. In both sets of data it is clear that communities and people of color are disproportionately affected by both the virus and policing.
