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1.
Am J Respir Crit Care Med ; 205(6): 651-662, 2022 03 15.
Artículo en Inglés | MEDLINE | ID: covidwho-1562065

RESUMEN

Rationale: Risk factors for coronavirus disease (COVID-19) mortality may include environmental exposures such as air pollution. Objectives: To determine whether, among adults hospitalized with PCR-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), long-term air pollution exposure is associated with the risk of mortality, ICU admission, or intubation. Methods: We performed a retrospective analysis of SARS-CoV-2 PCR-positive patients admitted to seven New York City hospitals from March 8, 2020, to August 30, 2020. The primary outcome was mortality; secondary outcomes were ICU admission and intubation. We estimated the annual average fine particulate matter (particulate matter ⩽2.5 µm in aerodynamic diameter [PM2.5]), nitrogen dioxide (NO2), and black carbon (BC) concentrations at patients' residential address. We employed double robust Poisson regression to analyze associations between the annual average PM2.5, NO2, and BC exposure level and COVID-19 outcomes, adjusting for age, sex, race or ethnicity, hospital, insurance, and the time from the onset of the pandemic. Results: Among the 6,542 patients, 41% were female and the median age was 65 (interquartile range, 53-77) years. Over 50% self-identified as a person of color (n = 1,687 [26%] Hispanic patients; n = 1,659 [25%] Black patients). Air pollution exposure levels were generally low. Overall, 31% (n = 2,044) of the cohort died, 19% (n = 1,237) were admitted to the ICU, and 16% (n = 1,051) were intubated. In multivariable models, a higher level of long-term exposure to PM2.5 was associated with an increased risk of mortality (risk ratio, 1.11 [95% confidence interval, 1.02-1.21] per 1-µg/m3 increase in PM2.5) and ICU admission (risk ratio, 1.13 [95% confidence interval, 1.00-1.28] per 1-µg/m3 increase in PM2.5). In multivariable models, neither NO2 nor BC exposure was associated with COVID-19 mortality, ICU admission, or intubation. Conclusions: Among patients hospitalized with COVID-19, a higher long-term PM2.5 exposure level was associated with an increased risk of mortality and ICU admission.


Asunto(s)
Contaminación del Aire/efectos adversos , COVID-19/epidemiología , Exposición a Riesgos Ambientales/efectos adversos , Adulto , Anciano , COVID-19/diagnóstico , COVID-19/terapia , Carbono/efectos adversos , Cuidados Críticos , Femenino , Hospitalización , Humanos , Intubación Intratraqueal , Masculino , Persona de Mediana Edad , Ciudad de Nueva York , Dióxido de Nitrógeno/efectos adversos , Material Particulado/efectos adversos , Respiración Artificial , Estudios Retrospectivos , Factores de Riesgo , Factores de Tiempo
2.
Am J Public Health ; 111(6): 1113-1122, 2021 06.
Artículo en Inglés | MEDLINE | ID: covidwho-1186640

RESUMEN

Objectives. To create a tool to rapidly determine where pandemic demand for critical care overwhelms county-level surge capacity and to compare public health and medical responses.Methods. In March 2020, COVID-19 cases requiring critical care were estimated using an adaptive metapopulation SEIR (susceptible‒exposed‒infectious‒recovered) model for all 3142 US counties for future 21-day and 42-day periods from April 2, 2020, to May 13, 2020, in 4 reactive patterns of contact reduction-0%, 20%, 30%, and 40%-and 4 surge response scenarios-very low, low, medium, and high.Results. In areas with increased demand, surge response measures could avert 104 120 additional deaths-55% through high clearance of critical care beds and 45% through measures such as greater ventilator access. The percentages of lives saved from high levels of contact reduction were 1.9 to 4.2 times greater than high levels of hospital surge response. Differences in projected versus actual COVID-19 demands were reasonably small over time.Conclusions. Nonpharmaceutical public health interventions had greater impact in minimizing preventable deaths during the pandemic than did hospital critical care surge response. Ready-to-go spatiotemporal supply and demand data visualization and analytics tools should be advanced for future preparedness and all-hazards disaster response.


Asunto(s)
COVID-19/epidemiología , COVID-19/mortalidad , Cuidados Críticos , Necesidades y Demandas de Servicios de Salud , Hospitales , Análisis Espacial , Capacidad de Reacción , COVID-19/transmisión , Humanos
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