IMPORTANCE An accurate understanding of the distributional implications of public health policies is critical for ensuring equitable responses to the COVID-19 pandemic and future public health threats. OBJECTIVE To identify and quantify the association of race/ethnicity-based, sex-based, and income-based inequities of state-specific lockdowns with 6 well-being dimensions in the United States. DESIGN, SETTING, AND PARTICIPANTS This pooled, repeated cross-sectional study used data from 14 187 762 households who participated in phase 1 of the population-representative US 2020 Household Pulse Survey (HPS). Households were invited to participate by email, text message, and/or telephone as many as 3 times. Data were collected via an online questionnaire from April 23 to July 21, 2020, and participants lived in all 50 US states and the District of Columbia. EXPOSURES Indicators of race/ethnicity, sex, and income and their intersections. MAIN OUTCOMES AND MEASURES Unemployment; food insufficiency; mental health problems;no medical care received for health problems; default on last month's rent or mortgage; and class cancellations with no distance learning. Race/ethnicity, sex, income, and their intersections were used to measure distributional implications across historically marginalized populations; statespecific, time-varying population mobility was used to measure lockdown intensity. Logistic regression models with pooled repeated cross-sections were used to estimate risk of dichotomous outcomes by social group, adjusted for confounding variables.

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Growing concerns over the potential release and threat of silver nanoparticles (AgNPs) to environmental and biological systems urge researchers to investigate their fate and behavior. However, current analytical techniques cannot meet the requirements for rapidly, sensitively and reliably probing AgNPs in complex matrices. Surface-enhanced Raman spectroscopy (SERS) has shown great capability for rapid detection of AgNPs based on an indicator molecule that can bind on the AgNP surface. The objective of this study was to exploit SERS to detect AgNPs in environmental and biological samples through optimizing the Raman indicator for SERS. Seven indicator molecules were selected and determined to obtain their SERS signals at optimal concentrations. Among them, 1,2-di(4-pyridyl)ethylene (BPE), crystal violet and ferric dimethyl-dithiocarbamate (ferbam) produced the highest SERS intensities. Further experiments on binding competition between each two of the three candidates showed that ferbam had the highest AgNPs-binding ability. The underlying mechanism lies in the strong binding affinity of ferbam with AgNPs via multiple sulfur atoms. We further validated ferbam to be an effective indicator for SERS detection of as low as 0.1mg/L AgNPs in genuine surface water and 0.57 mg/L in spinach juice. Moreover, limited interference on SERS detection of AgNPs was found from environmentally relevant inorganic ions, organic matter, inorganic particles, as well as biologically relevant components, demonstrating the ferbam-assisted SERS is an effective and sensitive method to detect AgNPs in complex environmental and biological samples.