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

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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

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Project description:Stay-at-home restrictions such as closure of non-essential businesses were effective at reducing SARS-CoV-2 transmission in New York City (NYC) in the spring of 2020. Relaxation of these restrictions was desirable for resuming economic and social activities, but could only occur in conjunction with measures to mitigate the expected resurgence of new infections, in particular social distancing and mask-wearing. We projected the impact of individuals' adherence to social distancing and mask-wearing on the duration, frequency, and recurrence of stay-at-home restrictions in NYC. We applied a stochastic discrete time-series model to simulate community transmission and household secondary transmission in NYC. The model was calibrated to hospitalizations, ICU admissions, and COVID-attributable deaths over March-July 2020 after accounting for the distribution of age and chronic health conditions in NYC. We projected daily new infections and hospitalizations up to May 31, 2021 under the different levels of adherence to social distancing and mask-wearing after relaxation of stay-at-home restrictions. We assumed that the relaxation of stay-at-home policies would occur in the context of adaptive reopening, where a new hospitalization rate of ≥ 2 per 100,000 residents would trigger reinstatement of stay-at-home restrictions while a new hospitalization rate of ≤ 0.8 per 100,000 residents would trigger relaxation of stay-at-home restrictions. Without social distancing and mask-wearing, simulated relaxation of stay-at-home restrictions led to epidemic resurgence and necessary reinstatement of stay-at-home restrictions within 42 days. NYC would have stayed fully open for 26% of the time until May 31, 2021, alternating reinstatement and relaxation of stay-at-home restrictions in four cycles. At a low (50%) level of adherence to mask-wearing, NYC would have needed to implement stay-at-home restrictions between 8% and 32% of the time depending on individual adherence to social distancing. At moderate to high levels of adherence to mask-wearing without social distancing, NYC would have needed to implement stay-at-home restrictions. In threshold analyses, avoiding reinstatement of stay-at-home restrictions required a minimum of 60% adherence to mask-wearing at 50% adherence to social distancing. With low adherence to mask-wearing and social distancing, reinstatement of stay-at-home restrictions in NYC was inevitable. High levels of adherence to social distancing and mask-wearing could have attributed to avoiding recurrent surges without reinstatement of stay-at-home restrictions.

Project description:Pharmacies that sell over-the-counter (OTC) syringes are a major source of sterile syringes for injection drug users in cities and states where such sales are legal. In these cities and states, however, black injectors are markedly less likely to acquire syringes from pharmacies than white injectors. The present analysis documents spatial and temporal trends in OTC pharmacy access in New York City health districts over time (2001-2006) and investigates whether these trends are related to district racial/ethnic composition and to local need for OTC pharmacies. For each year of the study period, we used kernel density estimation methods to characterize spatial access to OTC pharmacies within each health district. Higher values on this measure indicate better access to these pharmacies. "Need" was operationalized using two different measures: the number of newly diagnosed injection-related AIDS cases per 10,000 residents (averaged across 1999-2001), and the number of drug-related hospital discharges per 10,000 residents (averaged across 1999-2001). District sociodemographic characteristics were assessed using 2000 US decennial census data. We used hierarchical linear models (HLM) for descriptive and inferential analyses and investigated whether the relationship between need and temporal trajectories in the Expanded Syringe Access Demonstration Program access varied by district racial/ethnic composition, controlling for district poverty rates. HLM analyses indicate that the mean spatial access to OTC pharmacies across New York City health districts was 12.71 in 2001 and increased linearly by 1.32 units annually thereafter. Temporal trajectories in spatial access to OTC pharmacies depended on both need and racial/ethnic composition. Within high-need districts, OTC pharmacy access was twice as high in 2001 and increased three times faster annually, in districts with higher proportions of non-Hispanic white residents than in districts with low proportions of these residents. In low-need districts, "whiter" districts had substantially greater baseline access to OTC pharmacies than districts with low proportions of non-Hispanic white residents. Access remained stable thereafter in low-need districts, regardless of racial/ethnic composition. Conclusions were consistent across both measures of "need" and persisted after controlling for local poverty rates. In both high- and low-need districts, spatial access to OTC pharmacies was greater in "Whiter" districts in 2001; in high-need districts, access also increased more rapidly over time in "whiter" districts. Ensuring equitable spatial access to OTC pharmacies may reduce injection-related HIV transmission overall and reduce racial/ethnic disparities in HIV incidence among injectors.

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.

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