Baselining the Impact of the COVID-19 Pandemic: Social, Behavioral, and Economic Data Resources for High Quality Insights

The COVID-19 pandemic presents research challenges for how we measure governmental, community, and population responses to a crisis. One strategy is to examine and extrapolate from past natural or human-caused disasters such as hurricanes, floods, earthquakes, outbreaks of malaria or cholera, and population displacement. However, COVID-19 presents a unique challenge. Drawing parallels to earlier epidemics such as 2009’s H1N1 pandemic, the 1918 Influenza Epidemic, and even the Black Plague can provide insight, but transformative changes in medical care, social behaviors, global integration, and our ability to operate on a 24-hour news and communication cycle all make the COVID-19 pandemic unique (Barry, 2005; Schelden, 2022). A second strategy compares the experience of COVID-19 itself to the immediate preceding period. Detailed and significant studies of the spread, containment, and treatment of COVID-19 are appearing, but our ability to interpret this data requires understanding of the immediate past. Unlike the understanding of the disease process itself, which continues to increase, behavioral and social science research techniques can examine social behaviors and life-course activities before the emergence of the virus and compare it to those same behaviors and activities after the onset, and over the course of, the COVID-19 pandemic. This understanding requires baseline measures and data sources to best interpret new behaviors and social outcomes after the crisis emerged, and how social behaviors have adapted and reasserted themselves during COVID-19.
The social and behavioral science community collects a wide range of data on quality of life, economic activity, social networks, criminal justice, family and child welfare, substance abuse, education, and other key measures of risk and resilience to crises such as the COVID-19 pandemic. In this paper, we identify and share high quality measures from the social 3 and behavioral sciences that were collected prior to the onset and that will facilitate research on the COVID-19 pandemic. Awareness of these baseline measures is critical to well-designed research projects that make it possible to identify the impact of the pandemic on social, economic, and behavioral outcomes. We prioritize studies that use standardized measures, especially those that have been endorsed by the National Library of Medicine’s (NLM) Common Data Elements (CDEs) (n.d.). CDEs are measures the National Institute of Health (NIH) encourages to be used in data collections, and thus will have been used in many other studies and allow comparison with other non-COVID-19 time periods.
This paper draws on the topical expertise of the staff and faculty at the Inter-university Consortium for Political and Social Research (ICPSR) and others. ICPSR maintains resources to facilitate COVID-19 research via the NIH-sponsored Social, Behavioral, and Economic COVID Coordinating Center (SBE CCC) (n.d.). The SBE CCC provides a searchable repository of COVID-related data that permits comparison of variables across studies. In this paper, we 1 examine the breadth of information available in the ICPSR collections and beyond, focusing on the critical issues of timeliness, consistency, and periodicity to suggest baseline measures concerning social responses to the COVID-19 crisis. This survey of existing data resources and approaches highlights data that was collected close to the onset of the pandemic (within the previous five years) and which are routinely re-collected. We also highlight data that are longitudinal, collected for sufficient duration prior to the pandemic, and with the expectation that it will continue during and after the pandemic so that comparisons can be made. We focus on data that are high quality and representative of a population, generally for the U.S. as a whole, but also for other countries or for groups within the U.S. for whom COVID-19 researchers might want a baseline.