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1.
JAMA Netw Open ; 5(6): e2216176, 2022 06 01.
Article in English | MEDLINE | ID: covidwho-1888474

ABSTRACT

Importance: Aerosol-borne SARS-CoV-2 has not been linked specifically to nosocomial outbreaks. Objective: To explore the genomic concordance of SARS-CoV-2 from aerosol particles of various sizes and infected nurses and patients during a nosocomial outbreak of COVID-19. Design, Setting, and Participants: This cohort study included patients and nursing staff in a US Department of Veterans Affairs inpatient hospital unit and long-term-care facility during a COVID-19 outbreak between December 27, 2020, and January 8, 2021. Outbreak contact tracing was conducted using exposure histories and screening with reverse transcriptase-polymerase chain reaction (RT-PCR) for SARS-CoV-2. Size-selective particle samplers were deployed in diverse clinical areas of a multicampus health care system from November 2020 to March 2021. Viral genomic sequences from infected nurses and patients were sequenced and compared with ward nurses station aerosol samples. Exposure: SARS-CoV-2. Main Outcomes and Measures: The primary outcome was positive RT-PCR results and genomic similarity between SARS-CoV-2 RNA in aerosols and human samples. Air samplers were used to detect SARS-CoV-2 RNA in aerosols on hospital units where health care personnel were or were not under routine surveillance for SARS-CoV-2 infection. Results: A total of 510 size-fractionated air particle samples were collected. Samples representing 3 size fractions (>10 µm, 2.5-10 µm, and <2.5 µm) obtained at the nurses station were positive for SARS-CoV-2 during the outbreak (3 of 30 samples [10%]) and negative during 9 other collection periods. SARS-CoV-2 partial genome sequences for the smallest particle fraction were 100% identical with all 3 human samples; the remaining size fractions shared >99.9% sequence identity with the human samples. Fragments of SARS-CoV-2 RNA were detected by RT-PCR in 24 of 300 samples (8.0%) in units where health care personnel were not under surveillance and 7 of 210 samples (3.3%; P = .03) where they were under surveillance. Conclusions and Relevance: In this cohort study, the finding of genetically identical SARS-CoV-2 RNA fragments in aerosols obtained from a nurses station and in human samples during a nosocomial outbreak suggests that aerosols may have contributed to hospital transmission. Surveillance, along with ventilation, masking, and distancing, may reduce the introduction of community-acquired SARS-CoV-2 into aerosols on hospital wards, thereby reducing the risk of hospital transmission.


Subject(s)
COVID-19 , Cross Infection , Nursing Stations , Aerosols , COVID-19/epidemiology , Cohort Studies , Cross Infection/epidemiology , Cross Infection/prevention & control , Disease Outbreaks , Hospitals , Humans , RNA, Viral , SARS-CoV-2/genetics , United States
2.
Open Forum Infect Dis ; 9(5): ofac161, 2022 May.
Article in English | MEDLINE | ID: covidwho-1831310

ABSTRACT

In a low-income cohort in the Southeastern United States, 5% of participants avoided emergency medical care during the coronavirus disease 2019 pandemic, primarily due to fear and visitor restrictions. Younger age, self-perceived lower health status, lack of a personal doctor, and decreased income were associated with greater likelihood of deferring emergency care.

3.
Environ Res ; 210: 113016, 2022 07.
Article in English | MEDLINE | ID: covidwho-1699535

ABSTRACT

Exposure to particulate matter (PM) could increase both susceptibility to SARS-CoV-2 infection and severity of COVID-19 disease. Prior studies investigating associations between PM and COVID-19 morbidity have only considered PM2.5 or PM10, rather than PM1. We investigated the associations between daily-diagnosed COVID-19 morbidity and average exposures to ambient PM1 starting at 0 through 21 days before the day of diagnosis in 12 cities in China using a two-step analysis: a time-series quasi-Poisson analysis to analyze the associations in each city; and then a meta-analysis to estimate the overall association. Diagnosed morbidities and PM1 data were obtained from National Health Commission in China and China Meteorological Administration, respectively. We found association between short-term exposures to ambient PM1 with COVID-19 morbidity was significantly positive, and larger than the associations with PM2.5 and PM10. Percent increases in daily-diagnosed COVID-19 morbidity per IQR/10 PM1 for different moving averages ranged from 1.50% (-1.20%, 4.30%) to 241% (95%CI: 80.7%, 545%), with largest values for exposure windows starting at 17 days before diagnosis. Our results indicate that smaller particles are more highly associated with COVID-19 morbidity, and most of the effects from PM2.5 and PM10 on COVID-19 may be primarily due to the PM1. This study will be helpful for implementing measures and policies to control the spread of COVID-19.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollutants/toxicity , Air Pollution/adverse effects , Air Pollution/analysis , COVID-19/epidemiology , China/epidemiology , Environmental Exposure/analysis , Humans , Morbidity , Particulate Matter/analysis , SARS-CoV-2
4.
J Public Health Res ; 11(1)2021 Sep 24.
Article in English | MEDLINE | ID: covidwho-1438790

ABSTRACT

BACKGROUND: Widespread disruptions of medical care to mitigate COVID-19 spread and reduce burden on healthcare systems may have deleterious public health consequences. DESIGN AND METHODS: To examine factors contributing to healthcare interruptions during the pandemic, we conducted a COVID-19 impact survey between 10/7-12/14/2020 among participants of the Southern Community Cohort Study, which primarily enrolled low-income individuals in 12 southeastern states from 2002-2009. COVID survey data were combined with baseline and follow-up data. RESULTS: Among 4,463 respondents, 40% reported having missed/delayed a health appointment during the pandemic; the common reason was provider-initiated cancellation or delay (63%). In a multivariable model, female sex was the strongest independent predictor of interrupted care, with odds ratio (OR) 1.63 (95% confidence interval [CI] 1.40-1.89). Those with higher education (OR 1.27; 95% CI 1.05-1.54 for college graduate vs ≤high school) and household income (OR 1.47; 95% CI 1.16-1.86 for >$50,000 vs <$15,000) were at significantly increased odds of missing healthcare.  Having greater perceived risk for acquiring (OR 1.42; 95% CI 1.17-1.72) or dying from COVID-19 (OR 1.25; 95% CI 1.04-1.51) also significantly increased odds of missed/delayed healthcare. Age was inversely associated with missed healthcare among men (OR for 5-year increase in age 0.88; 95% CI 0.80-0.96) but not women (OR 0.97; 95% CI 0.91-1.04; p-interaction=0.04). Neither race/ethnicity nor comorbidities were associated with interrupted healthcare. CONCLUSIONS: Disruptions to healthcare disproportionately affected women and were primarily driven by health system-initiated deferrals and individual perceptions of COVID-19 risk, rather than medical co-morbidities or other traditional barriers to healthcare access.

5.
Microbiol Spectr ; 9(1): e0032721, 2021 09 03.
Article in English | MEDLINE | ID: covidwho-1361971

ABSTRACT

In the absence of genome sequencing, two positive molecular tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) separated by negative tests, prolonged time, and symptom resolution remain the best surrogate measure of possible reinfection. Using a large electronic health record database, we characterized clinical and testing data for 23 patients with repeatedly positive SARS-CoV-2 PCR test results ≥60 days apart, separated by ≥2 consecutive negative test results. The prevalence of chronic medical conditions, symptoms, and severe outcomes related to coronavirus disease 19 (COVID-19) illness were ascertained. The median age of patients was 64.5 years, 40% were Black, and 39% were female. A total of 83% smoked within the prior year, 61% were overweight/obese, 83% had immunocompromising conditions, and 96% had ≥2 comorbidities. The median interval between the two positive tests was 77 days. Among the 19 patients with 60 to 89 days between positive tests, 17 (89%) exhibited symptoms or clinical manifestations consistent with COVID-19 at the time of the second positive test and 14 (74%) were hospitalized at the second positive test. Of the four patients with ≥90 days between two positive tests (patient 2 [PT2], PT8, PT14, and PT19), two had mild or no symptoms at the second positive test and one, an immunocompromised patient, had a brief hospitalization at the first diagnosis, followed by intensive care unit (ICU) admission at the second diagnosis 3 months later. Our study demonstrated a high prevalence of compromised immune systems, comorbidities, obesity, and smoking among patients with repeatedly positive SARS-CoV-2 tests. Despite limitations, including a lack of semiquantitative estimates of viral load, these data may help prioritize suspected cases of reinfection for investigation and continued surveillance. IMPORTANCE The comprehensive characterization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing and clinical data for patients with repeatedly positive SARS-CoV-2 tests can help prioritize suspected cases of reinfection for investigation in the absence of genome sequencing data and for continued surveillance of the potential long-term health consequences of SARS-CoV-2 infection.


Subject(s)
COVID-19 Testing , COVID-19/diagnosis , COVID-19/epidemiology , Electronic Health Records , SARS-CoV-2/isolation & purification , Adult , Aged , Comorbidity , Databases, Factual , Female , Health Surveys , Humans , Immune System , Male , Middle Aged , Obesity , Polymerase Chain Reaction , Risk Factors , Smoking , Viral Load
6.
Science of The Total Environment ; : 146799, 2021.
Article in English | ScienceDirect | ID: covidwho-1157723

ABSTRACT

The Coronavirus Disease 2019 (COVID-19) pandemic spread rapidly despite extraordinary screening and social distancing measures. Such rapid spread was due in part to the fact that the disease transmission, particularly via airborne spread, is poorly understood. Characterizing the airborne size distribution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential to understanding the risk of airborne transmission. We collected size-fractionated (≤2.5, 2.5-10, and ≥10 μm) samples using a cascade impactor at more than 30 locations inside and outside Jaber Hospital and the nearby Temporary Quarantine Facility in Kuwait from April to July 2020. We hypothesized that airborne SARS-CoV-2 would be present in all size fractions, including fine particles, and in a size distribution that differed by sampling location. We found 6% of the samples (13 out of 210) were positive for SARS-CoV-2 RNA. Concentrations ranged from 3 to 25 copies/m3. The size distribution of particle-associated SARS-CoV-2 was different for each location. Large (≥10 μm) particles with the virus were found in symptomatic patient rooms. Fine (≤2.5 μm) particle-associated SARS-CoV-2 was detected in rooms with intubated patients and outside the hospital entrance gates. Coarse (2.5-10 μm) virus-laden particles were present in all locations with positive samples. This is the most comprehensive study to date on size-fractionated airborne SARS-CoV-2 RNA. Our findings support location-specific precautions that mitigate the spread of particles including fine particulate matter over distances greater than 1 meter, including in locations outside the hospital.

7.
Respir Res ; 22(1): 73, 2021 Feb 26.
Article in English | MEDLINE | ID: covidwho-1105712

ABSTRACT

BACKGROUND: The mechanism for spread of SARS-CoV-2 has been attributed to large particles produced by coughing and sneezing. There is controversy whether smaller airborne particles may transport SARS-CoV-2. Smaller particles, particularly fine particulate matter (≤ 2.5 µm in diameter), can remain airborne for longer periods than larger particles and after inhalation will penetrate deeply into the lungs. Little is known about the size distribution and location of airborne SARS-CoV-2 RNA. METHODS: As a measure of hospital-related exposure, air samples of three particle sizes (> 10.0 µm, 10.0-2.5 µm, and ≤ 2.5 µm) were collected in a Boston, Massachusetts (USA) hospital from April to May 2020 (N = 90 size-fractionated samples). Locations included outside negative-pressure COVID-19 wards, a hospital ward not directly involved in COVID-19 patient care, and the emergency department. RESULTS: SARS-CoV-2 RNA was present in 9% of samples and in all size fractions at concentrations of 5 to 51 copies m-3. Locations outside COVID-19 wards had the fewest positive samples. A non-COVID-19 ward had the highest number of positive samples, likely reflecting staff congregation. The probability of a positive sample was positively associated (r = 0.95, p < 0.01) with the number of COVID-19 patients in the hospital. The number of COVID-19 patients in the hospital was positively associated (r = 0.99, p < 0.01) with the number of new daily cases in Massachusetts. CONCLUSIONS: More frequent detection of positive samples in non-COVID-19 than COVID-19 hospital areas indicates effectiveness of COVID-ward hospital controls in controlling air concentrations and suggests the potential for disease spread in areas without the strictest precautions. The positive associations regarding the probability of a positive sample, COVID-19 cases in the hospital, and cases in Massachusetts suggests that hospital air sample positivity was related to community burden. SARS-CoV-2 RNA with fine particulate matter supports the possibility of airborne transmission over distances greater than six feet. The findings support guidelines that limit exposure to airborne particles including fine particles capable of longer distance transport and greater lung penetration.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Hospitals, Veterans/trends , Particle Size , SARS-CoV-2/isolation & purification , Boston/epidemiology , COVID-19/diagnosis , Emergency Service, Hospital/trends , Humans , Intensive Care Units/trends
8.
J Air Waste Manag Assoc ; 70(8): 739-744, 2020 08.
Article in English | MEDLINE | ID: covidwho-720891
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