Associational and plausible causal effects of COVID-19 public health policies on economic and mental distress

Abstract: Background The COVID-19 pandemic has increased mental distress globally. The proportion of people reporting anxiety is 26%, and depression is 34% points. Disentangling associational and causal contributions of behavior, COVID-19 cases, and economic distress on mental distress will dictate different mitigation strategies to reduce long-term pandemic-related mental distress. Methods We use the Household Pulse Survey (HPS) April 2020 to February 2021 data to examine mental distress among U.S. citizens attributable to COVID-19. We combined HPS survey data with publicly available state-level weekly: COVID-19 case and death data from the Centers for Disease Control, public policies, and Apple and Google mobility data. Finally, we constructed economic and mental distress measures to estimate structural models with lag dependent variables to tease out public health policies' associational and causal path coefficients on economic and mental distress. Findings From April 2020 to February 2021, we found that anxiety and depression had steadily climbed in the U.S. By design, mobility restrictions primarily affected public health policies where businesses and restaurants absorbed the biggest hit. Period t-1 COVID-19 cases increased job loss by 4.1% and economic distress by 6.3% points in the same period. Job-loss and housing insecurity in t-1 increased period t mental distress by 29.1% and 32.7%, respectively. However, t-1 food insecurity decreased mental distress by 4.9% in time t. The pandemic-related potential causal path coefficient of period t-1 economic distress on period t depression is 57.8%, and anxiety is 55.9%. Thus, we show that period t-1 COVID-19 case information, behavior, and economic distress may be causally associated with pandemic related period t mental distress.