Background The COVID-19 pandemic and its consequences have been associated with an increase in poor population mental health. We assessed how depressive symptoms changed among U.S. adults over the course of the COVID-19 pandemic and identified the key risk factors for these symptoms. Methods Longitudinal panel study of a nationally representative group of U.S. adults ages 18 years and older surveyed in March-April 2020 (Time 1; N=1441) and March-April 2021 (Time 2; N=1161) in the COVID-19 and Life Stressors Impact on Mental Health and Well-being study (CLIMB). The Patient Health Questionnaire-9 (PHQ-9) was used to define elevated depressive symptoms (cut-off ≥10) and depressive symptoms score (0-27). Findings The prevalence of elevated depressive symptoms persisted from 27.8% in 2020 (95% CI: 24.9, 30.9) to 32.8% in 2021 (95% CI: 29.1, 36.8). Over time, the central drivers of depressive symptoms were low household income, not being married, and experiencing multiple stressors during the COVID-19 pandemic. The odds ratio of elevated depressive symptoms for low income relative to high income persons increased from 2.3 (95% CI: 1.2, 4.2) in 2020 to 7.0 (95% CI: 3.7, 13.3) in 2021. Fewer people reported experiencing 4 or more COVID-19 stressors in 2021 than in 2020 (47.5% in 2020 vs 37.1% in 2021), but the odds ratio of elevated depressive symptoms associated with 4 or more stressors relative to 1 stressor or less increased from 1.9 (95% CI: 1.2, 3.1) in 2020 to 5.4 (95% CI: 3.2, 9.2) in 2021. Interpretation The burden of depressive symptoms in the U.S. adult population increased over the course of the COVID-19 pandemic. Mental health gaps grew between populations with different assets and stressor experiences during the COVID-19 pandemic. Funding CLIMB Time 1 was sponsored by the Rockefeller Foundation-Boston University 3-D Commission. CLIMB Time 2 was sponsored by the de Beaumont Foundation.

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TABLE 1. Characteristics of the governmental public health workforce -Public Health Workforce Interests and Needs Survey, United States, 2021 Characteristic Weighted estimate, % (95% CI) SHA-CO (n = 14,957) Large LHDs* (n = 19,663) Medium LHDs † (n = 7,270) National § (N = 41,890)

Context:The Public Health Workforce Interests and Needs Survey (PH WINS) was fielded in 2014 and 2017 and is the largest survey of the governmental public health workforce. It captures individual employees' perspectives on key issues such as workplace engagement and satisfaction, intention to leave, training needs, ability to address public health issues, as well as collects demographic information. This article describes the methods used for the 2021 PH WINS fielding. PH WINS 2021: PH WINS 2021 was fielded to a nationally representative sample of staff in State Health Agency-Central Offices (SHA-COs) and local health departments (LHDs) from September 13, 2021, to January 14, 2022. The instrument was revised to assess the pandemic's potential toll on the workforce, including deployment to COVID-19 response roles and well-being, and the country's renewed focus on health equity and "Racism as a Public Health Crisis." PH WINS 2021 had 3 sampling frames: SHAs, Big Cities Health Coalition (BCHC) members, and LHDs. All participating agencies were surveyed using a census approach. Participation: Overall, staff lists for 47 SHAs, 29 BCHC members, and 259 LHDs were collected, and the survey was sent to 137 446 individuals. PH WINS received a total of 44 732 responses, 35% of eligible respondents. The nationally representative SHA-CO frame includes a total of 14 957 individuals, and the nationally representative LHD frame includes 26 933 individuals from 439 LHDs (decentralized and nondecentralized). Considerations for Analysis: PH WINS now offers a multiyear, nationally representative sample of both SHA-CO and LHD staff. Both practice and academia can use PH WINS to better understand the strengths, needs, and opportunities of the workforce. When using PH WINS for additional data analysis, there are a number of considerations both within the 2021 data set and when conducting multiyear and multiple cross-sectional analyses.