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1.
Open Forum Infect Dis ; 7(6): ofaa210, 2020 Jun.
Article in English | MEDLINE | ID: covidwho-1387982

ABSTRACT

BACKGROUND: Posterior oropharyngeal saliva is increasingly recognized as a valid respiratory specimen for SARS-CoV-2 diagnosis. It is easy to collect and suitable for community-wide screening. The optimal timing of collection is currently unknown, and we speculate that an early-morning specimen before oral hygiene and breakfast would increase the diagnostic yield. METHODS: Posterior oropharyngeal saliva was collected at 5 different time points within the same day from 18 patients with previously confirmed SARS-CoV-2 infection by molecular testing. Cycle threshold (Ct) values were compared. RESULTS: There was an overall trend of lower Ct values from specimens collected in the early morning, with a gradual decrease of viral load towards nighttime, but reaching statistical significance only when compared with the specimens collected at bedtime. Eight out of 13 subjects had a higher viral load in the early morning than the rest of the 4 time points (before lunch, before teatime at 3 pm, before dinner, before bedtime). CONCLUSIONS: The result suggests a diurnal variation of viral shedding from the upper respiratory tract with a trend showing higher viral load in the early morning. For community screening purposes, posterior oropharyngeal saliva could be taken throughout the day, but preferably in the early morning to maximize the yield.

2.
Emerg Infect Dis ; 27(1): 196-204, 2021 01.
Article in English | MEDLINE | ID: covidwho-993249

ABSTRACT

Initial cases of coronavirus disease in Hong Kong were imported from mainland China. A dramatic increase in case numbers was seen in February 2020. Most case-patients had no recent travel history, suggesting the presence of transmission chains in the local community. We collected demographic, clinical, and epidemiologic data from 50 patients, who accounted for 53.8% of total reported case-patients as of February 28, 2020. We performed whole-genome sequencing to determine phylogenetic relationship and transmission dynamics of severe acute respiratory syndrome coronavirus 2 infections. By using phylogenetic analysis, we attributed the community outbreak to 2 lineages; 1 harbored a common mutation, Orf3a-G251V, and accounted for 88.0% of the cases in our study. The estimated time to the most recent common ancestor of local coronavirus disease outbreak was December 24, 2019, with an evolutionary rate of 3.04 × 10-3 substitutions/site/year. The reproduction number was 1.84, indicating ongoing community spread.


Subject(s)
COVID-19/epidemiology , COVID-19/virology , Disease Outbreaks , Adult , Aged , Aged, 80 and over , COVID-19/transmission , Cluster Analysis , Disease Hotspot , Evolution, Molecular , Female , Hong Kong/epidemiology , Humans , Male , Middle Aged , Mutation , Phylogeny , Phylogeography , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , Viroporin Proteins/genetics , Whole Genome Sequencing , Young Adult
3.
Int J Infect Dis ; 101: 74-82, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-758909

ABSTRACT

OBJECTIVES: To develop: (1) two validated risk prediction models for coronavirus disease-2019 (COVID-19) positivity using readily available parameters in a general hospital setting; (2) nomograms and probabilities to allow clinical utilisation. METHODS: Patients with and without COVID-19 were included from 4 Hong Kong hospitals. The database was randomly split into 2:1: for model development database (n = 895) and validation database (n = 435). Multivariable logistic regression was utilised for model creation and validated with the Hosmer-Lemeshow (H-L) test and calibration plot. Nomograms and probabilities set at 0.1, 0.2, 0.4 and 0.6 were calculated to determine sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). RESULTS: A total of 1330 patients (mean age 58.2 ± 24.5 years; 50.7% males; 296 COVID-19 positive) were recruited. The first prediction model developed had age, total white blood cell count, chest x-ray appearances and contact history as significant predictors (AUC = 0.911 [CI = 0.880-0.941]). The second model developed has the same variables except contact history (AUC = 0.880 [CI = 0.844-0.916]). Both were externally validated on the H-L test (p = 0.781 and 0.155, respectively) and calibration plot. Models were converted to nomograms. Lower probabilities give higher sensitivity and NPV; higher probabilities give higher specificity and PPV. CONCLUSION: Two simple-to-use validated nomograms were developed with excellent AUCs based on readily available parameters and can be considered for clinical utilisation.


Subject(s)
COVID-19/diagnosis , SARS-CoV-2 , Adult , Aged , Aged, 80 and over , Area Under Curve , COVID-19/etiology , Female , Hospitals , Humans , Logistic Models , Male , Middle Aged , Nomograms , Probability
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