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1.
JAMA Netw Open ; 6(5): e2313436, 2023 05 01.
Article in English | MEDLINE | ID: covidwho-2322993

ABSTRACT

This survey study examines the prevalence of incentive receipt for COVID-19 vaccination and the association of various sociodemographic characteristics with perspectives on incentives' influence on trust in the COVID-19 vaccine.


Subject(s)
COVID-19 , Motivation , Humans , Trust , COVID-19 Vaccines/therapeutic use , COVID-19/prevention & control
2.
Am J Public Health ; 111(3): 494-497, 2021 03.
Article in English | MEDLINE | ID: covidwho-1040090

ABSTRACT

Objectives. To examine the impact of COVID-19 shutdowns on food insecurity among a predominantly African American cohort residing in low-income racially isolated neighborhoods.Methods. Residents of 2 low-income African American food desert neighborhoods in Pittsburgh, Pennsylvania, were surveyed from March 23 to May 22, 2020, drawing on a longitudinal cohort (n = 605) previously followed from 2011 to 2018. We examined longitudinal trends in food insecurity from 2011 to 2020 and compared them with national trends. We also assessed use of food assistance in our sample in 2018 versus 2020.Results. From 2018 to 2020, food insecurity increased from 20.7% to 36.9% (t = 7.63; P < .001) after steady declines since 2011. As a result of COVID-19, the United States has experienced a 60% increase in food insecurity, whereas this sample showed a nearly 80% increase, widening a preexisting disparity. Participation in the Supplemental Nutrition Assistance Program (52.2%) and food bank use (35.9%) did not change significantly during the early weeks of the pandemic.Conclusions. Longitudinal data highlight profound inequities that have been exacerbated by COVID-19. Existing policies appear inadequate to address the widening gap.


Subject(s)
Black or African American/statistics & numerical data , COVID-19/epidemiology , Food Insecurity , Poverty/statistics & numerical data , Humans , Longitudinal Studies , Pandemics , Pennsylvania/epidemiology , Residence Characteristics/statistics & numerical data , Risk Factors , SARS-CoV-2 , United States/epidemiology
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