With the novel coronavirus causing a worldwide paradigm shift, I was genuinely tempted to jump into the data and analyze all possible permutations of what the potential impacts may be. Should I first plot the number of cases in Virginia with corresponding population densities on a map, or should I find causal connections between the age-distribution and COVID deaths in each of our 133 cities and counties? Will the impact on births be short or long term? How can we capture the symbiotic relationship between immigration rates and the labor market, amidst fears of a second wave? After the initial adrenaline rush of consuming all the data and attempting to produce a coherent narrative, I paused to consider the pitfalls of analysis paralysis. With all the chaotic commentary floating around us, I had to ask if my attempt would be adding value to the conversation, or just more noise.
Be it a clinician or an epidemiologist, an economist or a demographer, each in his or her own way is facing the challenges of dealing with the COVID-19 pandemic. My demographic dilemma stems from recognizing that there are so many “known unknowns” that I cannot in good faith put out a half-baked data analysis, which may be difficult to defend in the future.
My failed attempts included tracking other diseases of the recent or even the distant past—Spanish Flu, Ebola, Zika, Plague—which could serve as a template to help us understand the demographic fallouts of our current pandemic, but the comparisons did not seem to be “apples to apples”. I considered projecting scenarios of how COVID-19 could affect births or migration in Virginia, but that too would be an academic exercise at best, since offering 27 alternative scenarios is less useful than offering none.
Perhaps there are others too who are trying to make some sense of the numbers or seeking ways in which population research can contribute to the conversation at hand. To that end, here are some of the discussions we as demographers at the Cooper Center are having, as we seek to serve the Commonwealth in these strange times.
Data Discrepancies: This is the first hurdle I encountered, as my three main data sources (CDC, Johns Hopkins, and VDH) did not sync up. Since the data points were not clearly aligned due to either different update cycles, or different jurisdictions like county vs. health district vs. zip-code, it became difficult to decide which metric best represented Virginia’s story.
Timeline of Analysis: The data is released with some time lag and the situation on the ground is constantly evolving. While the latest live feeds attempt to capture this dynamism, the dates when data gets released or updated on the different platforms often vary. So the resulting analysis will either be a snapshot in time that will be irrelevant by the next day or else show a trend of the past which may not reveal any implication for the future.
Secondary Impacts: While the number of COVID cases, hospitalizations, and deaths is a direct consequence of the virus, there are numerous secondary impacts that we cannot identify. Unemployment figures and poverty rates continue to be calculated, but non-linear consequences or downstream effects, such as mental health crises, delays in elective medical procedures, food wastage due to transportation bottlenecks, or stalled research and development projects, may be difficult to capture.
Demographic Outcomes: A global pandemic will have a significant effect on the demographic makeup of our communities and societies, but the actual nuts and bolts of such shifts are difficult to pin down. While the deaths directly due to COVID are being regularly reported, we can only hypothesize about the other elements of the demographic trinity—births and migration—since the survey data capturing these trends will not be available for quite some time.
Economic Consequences: Economic fallout of the current pandemic will be just as dramatic as the demographic shifts, but equally hard to foresee. Some behavioral changes will be short term, while others may become permanent. Consumers of goods and services may become more conscious of the rift between necessities and luxuries. Individuals and institutions may alter their cost benefit calculations, and be forced to accept greater risks to avoid financial loss; for example, using public transport or reopening amusement parks. The immediate concerns of loss of lives and livelihoods is being felt, but there are other far-reaching consequences whose manifestations and magnitudes we may be unable to anticipate.
In Defense of Projections: As the world around us exploded with a myriad of projections on COVID-19, they were closely followed by disgruntled rumblings about how every model and prediction was wrong and that the goal post was constantly shifting. But the researchers and analysts developing these projections are acutely aware of how these numbers are inherently uncertain. Projections provide us with a direction, not a directive. Modelers have to use days- or weeks-old data to build projections, and by the time they churn out a set of results, the situation on the ground may have changed completely. Plus, sometimes projections provide worst case scenarios in order to inform policy makers, and by heeding these warnings and altering behaviors, we can course correct and avert a worse future. So in solidarity with every person who develops projections anywhere, I want to emphasize that projections are nearly always suggestive, not a precise picture of the future.
Given all the uncertainty and unknowns, we as demographers at the Cooper Center will still strive to provide useful and timely information that may be of value to fellow Virginians, such as providing analysis on the transition to online education formats, trends in homeschooling, telecommuting practices or capturing the impact of COVID-19 on Census 2020 for Virginia.