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1.
J Infect Dis ; 2022 Nov 09.
Article in English | MEDLINE | ID: covidwho-2302153

ABSTRACT

BACKGROUND: Household transmission studies inform how viruses spread among close contacts, but few characterize household transmission of endemic coronaviruses. METHODS: We used data collected from 223 households with school-age children participating in weekly disease surveillance over two respiratory virus seasons (December 2015 to May 2017), to describe clinical characteristics of endemic human coronaviruses (HCoV-229E, HCoV-HKU1, HCoV-NL63, HCoV-OC43) infections, and community and household transmission probabilities using a chain-binomial model correcting for missing data from untested households. RESULTS: Among 947 participants in 223 households, we observed 121 infections during the study, most commonly subtype HCoV-OC43. Higher proportions of infected children (<19y) displayed ILI symptoms than infected adults (relative risk 3.0, 95% credible interval (CrI) 1.5, 6.9). The estimated weekly household transmission probability was 9% (95% CrI 6, 13) and weekly community acquisition probability was 7% (95% CrI 5, 10). We found no evidence for differences in community or household transmission probabilities by age or symptom status. Simulations suggest that our study was underpowered to detect such differences. CONCLUSION: Our study highlights the need for large household studies to inform household transmission, the challenges in estimating household transmission probabilities from asymptomatic individuals, and implications for controlling endemic CoVs.

2.
Journal of critical care medicine (Universitatea de Medicina si Farmacie din Targu-Mures) ; 8(1):14-22, 2021.
Article in English | EuropePMC | ID: covidwho-1733450

ABSTRACT

Introduction The predictive potential of demographics, clinical characteristics, and inflammatory markers at admission to determine future intubation needs of hospitalised CoVID-19 patients is unknown. The study aimed to determine the predictive potential of elevated serum inflammatory markers in determining the need for intubation in CoVID-19 Patients. Methods In a retrospective cohort study of hospitalised SARS-CoV2 positive patients, single and multivariable regression analyses were used to determine covariate effects on intubation odds, and a minimax concave penalty regularised logistic regression was used to build a predictive model. A second prospective independent cohort tested the model. Results Systemic inflammatory markers obtained at admission were higher in patients that required subsequent intubation, and adjusted odds of intubation increased for every standard deviation above the mean for c-reactive protein (CRP) OR:2.8 (95% CI 1.8-4.5, p<0.001) and lactate dehydrogenase OR:2.1 (95% CI 1.33.3, p=0.002). A predictive model incorporating C-reactive protein, lactate dehydrogenase, and diabetes status at the time of admission predicted intubation status with an area under the curve (AUC) of 0.78 with corresponding sensitivity of 86%, specificity of 63%. This predictive model achieved an AUC of 0.83, 91% sensitivity, and 41% specificity on the validation cohort. Conclusion In patients hospitalised with CoVID-19, elevated serum inflammatory markers measured within the first twenty-four hours of admission are associated with an increased need for intubation. Additionally, a model of C-reactive protein, lactate dehydrogenase, and the presence of diabetes may play a predictive role in determining the future need for intubation.

3.
J Occup Environ Med ; 63(3): 191-198, 2021 03 01.
Article in English | MEDLINE | ID: covidwho-1307590

ABSTRACT

OBJECTIVES: Define the seroprevalence and risk factors for SARS-CoV-2 antibodies in Arapahoe County, Colorado first responders (eg, law enforcement, human services, fire departments). METHODS: Two hundred sixty four first responders were enrolled June to July 2020. SARS-CoV-2 seropositivity was defined as detection of immunoglobulin G (IgG) antibodies to both spike receptor binding domain and nucleocapsid in venous blood by validated enzyme-linked immunosorbent assay. We compared risk factors for being seropositive versus seronegative. RESULTS: 4% (11/264) were SARS-CoV-2 seropositive. Seropositive participants were significantly more likely to have lung disease (% seropositive, % seronegative; P-value) (36%, 8%; P = 0.01), prior SARS-CoV-2/COVID-19 testing (36%, 8%; P ≤ 0.01), a prior positive result (18%, less than 1%), and to believe they previously had COVID-19 (64%, 15%; P < 0.01). Only 15% of those believing they had COVID-19 had anti-SARS-CoV-2 antibodies. CONCLUSIONS: Human services employees and individuals with lung disease are at SARS-CoV-2 exposure risk. Few individuals believed they had COVID-19 had prior exposure.


Subject(s)
COVID-19/epidemiology , Emergency Responders/statistics & numerical data , SARS-CoV-2/immunology , Adult , Antibodies, Viral/blood , COVID-19/diagnosis , COVID-19/pathology , COVID-19/transmission , COVID-19 Serological Testing , Colorado/epidemiology , Female , Humans , Immunoglobulin G/blood , Male , Middle Aged , Risk Factors , SARS-CoV-2/isolation & purification , Seroepidemiologic Studies
5.
Am J Trop Med Hyg ; 103(1): 25-27, 2020 07.
Article in English | MEDLINE | ID: covidwho-646970

ABSTRACT

The novel coronavirus disease (COVID-19) pandemic has unveiled underlying health inequities throughout the United States. The pandemic has spread across U.S. states, affecting different vulnerable populations, including both inner-city and rural populations, and those living in congregate settings such as nursing homes and assisted-living facilities. In addition, since early April, there has been an increasing number of outbreaks of COVID-19 in jails and prisons. We describe three overlapping epidemiologic waves of spread of COVID-19 linked to three different kinds of structural vulnerabilities.


Subject(s)
Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Vulnerable Populations , Aged , Betacoronavirus , COVID-19 , Crowding , Frail Elderly , Humans , Nursing Homes , Occupational Exposure , Pandemics , Prisons , Rural Population , SARS-CoV-2 , United States/epidemiology , Urban Population
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