ABSTRACT
New York City is the hot spot of the COVID-19 pandemic in the United States. This paper merges information on the number of tests and the number of infections at the New York City zip code level with demographic and socioeconomic information from the decennial census and the American Community Surveys. People residing in poor or immigrant neighborhoods were less likely to be tested;but the likelihood that a test was positive was larger in those neighborhoods, as well as in neighborhoods with larger households or predominantly black populations. The rate of infection in the population depends on both the frequency of tests and on the fraction of positive tests among those tested. The non-randomness in testing across New York City neighborhoods indicates that the observed correlation between the rate of infection and the socioeconomic characteristics of a community tells an incomplete story of how the pandemic evolved in a congested urban setting.
ABSTRACT
Employment rates in the United States fell dramatically between February 2020 and April 2020 as the repercussions of the COVID-19 pandemic reverberated through the labor market. This paper uses data from the CPS Basic Monthly Files to document that the employment decline was particularly severe for immigrants. Historically, immigrant men were more likely to be employed than native men. The COVID-related labor market disruptions eliminated the immigrant employment advantage. By April 2020, immigrant men had lower employment rates than native men. Part of the relative increase in the immigrant rate of job loss arises because immigrants were less likely to work in jobs that could be performed remotely and suffered disparate employment consequences as the lockdown permitted workers with more “remotable” skills to continue their work from home. Undocumented men were particularly hard hit by the pandemic, with their rate of job loss far exceeding the rate of job loss of legal immigrants.
ABSTRACT
INTRODUCTION: In response to the coronavirus disease 2019 (COVID-19) pandemic, New York City closed all nonessential businesses and restricted the out-of-home activities of residents as of March 22, 2020. This order affected different neighborhoods differently, as stores and workplaces are not randomly distributed across the city, and different populations may have responded differently to the out-of-home restrictions. This study examines how the business closures and activity restrictions affected COVID-19 testing results. An evaluation of whether such actions slowed the spread of the pandemic is a crucial step in designing effective public health policies. METHODS: Daily data on the fraction of COVID-19 tests yielding a positive result at the zip code level were analyzed in relation to the number of visits to local businesses (based on smartphone location) and the number of smartphones that stayed fixed at their home location. The regression model also included vectors of fixed effects for the day of the week, the calendar date, and the zip code of residence. RESULTS: A large number of visits to local businesses increased the positivity rate of COVID-19 tests, while a large number of smartphones that stayed at home decreased it. A doubling in the relative number of visits increases the positivity rate by about 12.4 percentage points (95% CI, 5.3 to 19.6). A doubling in the relative number of stay-at-home devices lowered it by 2.0 percentage points (95% CI, -2.9 to -1.2). The business closures and out-of-home activity restrictions decreased the positivity rate, accounting for approximately 25% of the decline observed in April and May 2020. CONCLUSION: Policy measures decreased the likelihood of positive results in COVID-19 tests. These specific policy tools may be successfully used when comparable health crises arise in the future.