Dataset Information

Examining the spatial and temporal relationship between social vulnerability and stay-at-home behaviors in New York City during the COVID-19 pandemic.

ABSTRACT: Social distancing and particularly staying at home are effective public health responses to the COVID-19 pandemic. The sheer scale of behavior changes across a mass population scale is unprecedented and will undoubtedly cause disproportionate hardships for certain vulnerable groups of population and marginalized communities during different periods of the pandemic. However, at the community level, few studies have considered the spatial and temporal variations in such public health behavior changes during this pandemic. We applied a geographically and temporally weighted regression (GTWR) to analyze the spatiotemporal pattern of community stay-at-home behaviors against social vulnerability indicators at the census tract level in New York City from March to August 2020. Our findings are generally supporting the conventional wisdom of social vulnerability yet they also offer new insights. Despite the spatial variations in the effects of social vulnerability on stay-at-home behaviors, people from different vulnerable groups are also exhibiting varying reactions to the pandemic over the duration of this study, thereby highlighting the importance of understanding the spatiotemporal pattern of public health behaviors to develop an effective policy response to avoid the risk of deepening inequalities and to promote a just and sustainable urban future.

SUBMITTER: Fu X

PROVIDER: S-EPMC7857012 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Examining the spatial and temporal relationship between social vulnerability and stay-at-home behaviors in New York City during the COVID-19 pandemic.

Fu Xinyu X Zhai Wei W

Sustainable cities and society 20210203

Social distancing and particularly staying at home are effective public health responses to the COVID-19 pandemic. The sheer scale of behavior changes across a mass population scale is unprecedented and will undoubtedly cause disproportionate hardships for certain vulnerable groups of population and marginalized communities during different periods of the pandemic. However, at the community level, few studies have considered the spatial and temporal variations in such public health behavior chan ...[more]

PMID: 33558841

Similar Datasets

Project description:ImportanceHome health care workers care for community-dwelling adults and play an important role in supporting patients with confirmed and suspected coronavirus disease 2019 (COVID-19) who remain at home. These workers are mostly middle-aged women and racial/ethnic minorities who typically earn low wages. Despite being integral to patient care, these workers are often neglected by the medical community and society at large; thus, developing a health care system capable of addressing the COVID-19 crisis and future pandemics requires a better understanding of the experiences of home health care workers.ObjectiveTo understand the experiences of home health care workers caring for patients in New York City during the COVID-19 pandemic.Design, setting, and participantsFrom March to April 2020, a qualitative study with 1-to-1 semistructured interviews of 33 home health care workers in New York City was conducted in partnership with the 1199SEIU Home Care Industry Education Fund, a benefit fund of the 1199 Service Employees International Union United Healthcare Workers East, the largest health care union in the US. Purposeful sampling was used to identify and recruit home health care workers.Main outcomes and measuresAudio-recorded interviews were professionally transcribed and analyzed using grounded theory. Major themes and subthemes were identified.ResultsIn total, 33 home health care workers employed by 24 unique home care agencies across the 5 boroughs of New York City participated. Participants had a mean (SD) age of 47.6 (14.0) years, 32 (97%) were women, 21 (64%) were Black participants, and 6 (18%) were Hispanic participants. Five major themes emerged: home health care workers (1) were on the front lines of the COVID-19 pandemic but felt invisible; (2) reported a heightened risk for virus transmission; (3) received varying amounts of information, supplies, and training from their home care agencies; (4) relied on nonagency alternatives for support, including information and supplies; and (5) were forced to make difficult trade-offs in their work and personal lives.Conclusions and relevanceIn this qualitative analysis, home health care workers reported providing frontline essential care, often at personal risk, during the COVID-19 pandemic. They experienced challenges that exacerbated the inequities they face as a marginalized workforce. Interventions and policies to better support these frontline health care professionals are urgently needed.

Project description:Recent epidemiological studies have examined the associations between air pollution and birth outcomes. Regulatory air quality monitors often used in these studies, however, were spatially sparse and unable to capture relevant within-city variation in exposure during pregnancy.This study developed two-week average exposure estimates for fine particles (PM2.5) and nitrogen dioxide (NO2) during pregnancy for 274,996 New York City births in 2008-2010. The two-week average exposures were constructed by first developing land use regression (LUR) models of spatial variation in annual average PM2.5 and NO2 data from 150 locations in the New York City Community Air Survey and emissions source data near monitors. The annual average concentrations from the spatial models were adjusted to account for city-wide temporal trends using time series derived from regulatory monitors. Models were developed using Year 1 data and validated using Year 2 data. Two-week average exposures were then estimated for three buffers of maternal address and were averaged into the last six weeks, the trimesters, and the entire period of gestation. We characterized temporal variation of exposure estimates, correlation between PM2.5 and NO2, and correlation of exposures across trimesters.The LUR models of average annual concentrations explained a substantial amount of the spatial variation (R2 = 0.79 for PM2.5 and 0.80 for NO2). In the validation, predictions of Year 2 two-week average concentrations showed strong agreement with measured concentrations (R2 = 0.83 for PM2.5 and 0.79 for NO2). PM2.5 exhibited greater temporal variation than NO2. The relative contribution of temporal vs. spatial variation in the estimated exposures varied by time window. The differing seasonal cycle of these pollutants (bi-annual for PM2.5 and annual for NO2) resulted in different patterns of correlations in the estimated exposures across trimesters. The three levels of spatial buffer did not make a substantive difference in estimated exposures.The combination of spatially resolved monitoring data, LUR models and temporal adjustment using regulatory monitoring data yielded exposure estimates for PM2.5 and NO2 that performed well in validation tests. The interaction between seasonality of air pollution and exposure intervals during pregnancy needs to be considered in future studies.

Project description:OBJECTIVES:To determine whether asthma hospitalisations of children and adults in the five boroughs of New York City are correlated with influenza hospitalisations temporally and spatially. DESIGN:A longitudinal ecological study. INCLUSION CRITERIA:We reviewed the Statewide Planning and Research Cooperative System's records of hospitalisations in Manhattan, Bronx, Queens, Brooklyn and Staten Island from 2002 to 2012. All hospitalisations with a primary diagnosis of either asthma or influenza were identified using the International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes. METHODS:A time-series regression analysis was performed using aggregate monthly counts of influenza hospitalisations as predictors of asthma hospitalisations. Time-series regression models were also applied to different age groups and boroughs to examine the magnitude of influenza and asthma correlations across strata. The per cent excess risk was also calculated across age groups and boroughs. RESULTS:Time-series analysis of the overall population revealed a significant positive correlation between influenza and asthma hospitalisations (p=0.011). When stratifying by age, there was a significant positive correlation between asthma and influenza hospitalisations for individuals 18 and older (p<0.01), and no significant correlation found for age groups younger than 18. Percentages of excess risk of influenza-related asthma hospitalisations also increased with increasing age with adults 18-44, 45-64 and 65+ having?excess risk percentages of 2.9%, 3.4% and 4%, respectively. Time-series analysis by location revealed positive significant correlations between asthma and influenza hospitalisations in Brooklyn (p=0.03) and Manhattan (p<0.01). Manhattan and Brooklyn had a 2.5% and 1.6%, respectively, percentage of excess risk of influenza-related asthma hospitalisations. CONCLUSION:Influenza and asthma hospitalisations are significantly associated at the population level among adults. These associations vary by age and geographical location. Influenza prevention strategies targeting adult populations, particularly individuals living in Manhattan and Brooklyn, have the potential for meaningful reduction of influenza-related asthma hospitalisations.

Dataset Information

Examining the spatial and temporal relationship between social vulnerability and stay-at-home behaviors in New York City during the COVID-19 pandemic.

Publications

Examining the spatial and temporal relationship between social vulnerability and stay-at-home behaviors in New York City during the COVID-19 pandemic.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets