County-Level Factors That Influenced the Trajectory of COVID-19 Incidence in the New York City Area
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Abstract
More than a century of research has shown that sociodemographic conditions affect infectious disease transmission. In the late spring and early summer of 2020, reports of the effects of sociodemographic variables on the spread of COVID-19 were used in the media with minimal scientific proof attached. With new cases of COVID-19 surging in the United States at that time, it became essential to better understand how the spread of COVID-19 was varying across all segments of the population. We used hierarchical exponential growth curve modeling techniques to examine whether community socioeconomic characteristics uniquely influence the incidence of reported COVID-19 cases in the urban built environment. We show that as of July 19, 2020, confirmed coronavirus infections in New York City and surrounding areas—one of the early epicenters of the COVID-19 pandemic in the United States—were concentrated along demographic and socioeconomic lines. Furthermore, our data provides evidence that after the onset of the pandemic, timely enactment of physical distancing measures such as school closures was essential to limiting the extent of the coronavirus spread in the population. We conclude that in a pandemic, public health authorities must impose physical distancing measures early on as well as consider community-level factors that associate with a greater risk of viral transmission.
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SciScore for 10.1101/2020.05.05.20092254: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This study, however, is not without limitations. As this devastating pandemic continues to unfold in this epicenter of the outbreak in the United States, we assume that the number of Covid-19 confirmed cases will likely shift in response to improved testing and reporting practices, and thus, over time, enable the emergence of more …
SciScore for 10.1101/2020.05.05.20092254: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This study, however, is not without limitations. As this devastating pandemic continues to unfold in this epicenter of the outbreak in the United States, we assume that the number of Covid-19 confirmed cases will likely shift in response to improved testing and reporting practices, and thus, over time, enable the emergence of more accurate and useful data. Still, we use the latest data available to us [8]. Similarly, our sample is drawn from the New York metropolitan region, reducing the generalizability of our findings to a particular portion of people in the City of New York and surrounding areas, through May 3, 2020. Furthermore, in order to reduce virus transmission and keep case-fatality rates as low as possible, the New York State government instituted a number of mitigation efforts aside from school closures, including social distancing, school and workplace closures, cancellation of large-scale public gatherings, and stay-at-home orders [24]. In the present analysis, we use school closure dates to account for variation in time of enactment of physical distancing measures across counties. Thus, our inclusion of one variable is by no means comprehensive. However, if school closures were the only measure enacted, intervention effectiveness would be substantially reduced and variation in Covid-19 incidence across counties would be magnified [20-21]. Similarly, although we are unable to confirm whether individuals who tested positive for SARS-CoV-2 reside in the area where...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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