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1.
China Tropical Medicine ; 23(4):378-382, 2023.
Article in Chinese | GIM | ID: covidwho-20243598

ABSTRACT

Objective: To evaluate the influence of coronavirus disease 2019 (COVID-19) prevention and control measures on the transmission and epidemic of influenza in Chongqing, so as to provide references for formulating targeted influenza prevention and control strategies. Methods: The influenza surveillance data, during the year 2018 to 2020, were collected through the "China Influenza Surveillance Information System", and the seasonal characteristics of influenza epidemic were analyzed. The percentage of influenza like cases (ILI%) and influenza virus positive rate between 2020 and 2018-2019 were compared, so as to evaluate the impact of COVID-19 prevention and control measures on influenza epidemic characteristics. Results: The annual proportions of ILI cases in Chongqing were respectively 3.53%, 2.23% and 1.2% from 2018 to 2020, while the positive rates of influenza virus were respectively 13.97%, 23.81% and 2.65%. The distribution trend of ILI% from 2018 to 2019 fluctuated were similar, but it continued to drop and remain at a low level since February 2020. The positive rate of influenza virus showed an epidemic peak from December to March in 2018-2019, also peaked from November 2019 to January 2020, but decreased to 0 in March. ILI% was positively correlated with the positive rate of influenza virus (r=0.404 8, P < 0.05). In 2020, compared with the same period of 2018-2019, the growth rate of ILI% was -66.09% and -46.32%, respectively. The positive rate of influenza virus in 2020 decreased by 81.03% and 88.87% compared with the same period of 2018-2019, respectively. The growth rates of influenza virus positive rate in January 2020 were decreased with a small rate of about 39.87%, and with a significantly decline of more than 93.65% from February. No influenza epidemic was found after March. Conclusions: Since COVID-19 prevention and control measures were implemented in January 2020 in Chongqing, the ILI% and the positive rate of influenza virus in sentinel hospitals decreased significantly. In the season of high incidence of respiratory infectious diseases, personal protection and other measures can effectively reduce influenza virus infection.

2.
China CDC Wkly ; 4(46): 1039-1042, 2022 Nov 18.
Article in English | MEDLINE | ID: covidwho-2113793

ABSTRACT

What is already known about this topic?: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron subvariant has a stronger transmission capacity and faster transmission speed than the previous strain. What is added by this report?: The first coronavirus disease 2019 (COVID-19) case infected with the SARS-CoV-2 Omicron subvariant BA.2.76 who caused local transmission was reported in Chongqing Municipality on August 16, 2022. For 35 minutes, the Patient Zero jogged along a lake at a local park without wearing a mask. Among the 2,836 people potentially exposed at the time, 39 tested positive. Overall, 38 out of 39 cases did not wear a mask on the morning of August 16. All 39 cases lacked any previous exposure to the variant before testing positive on their nucleic acid test. What are the implications for public health practice?: It is essential to maintain personal wellbeing by ensuring one maintains personal protection and follows regulated guidelines such as maintaining safe distances from others both indoors and outdoors.

3.
Practical Geriatrics ; 34(9):984-987, 2020.
Article in Chinese | GIM | ID: covidwho-2033890

ABSTRACT

Objective: To analyze the clinical characteristics of novel coronavirus pneumonia (COVID-19) in the elderly.

5.
Clin Lab ; 67(7)2021 Jul 01.
Article in English | MEDLINE | ID: covidwho-1310227

ABSTRACT

BACKGROUND: COVID-19 is caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which was discovered in 2019 and spread around the world in a short time. SARS-CoV-2 nucleic acid amplification tests (NAATs) have been rapidly developed and quickly applied to clinical testing of COVID-19. Aim of this study was to evaluate the performance of four NAAT assays. METHODS: Limit of detection (LOD), precision, accuracy, analytical specificity and analytical interference studies on four NAATs (Daan, Sansure, Hybribio, and Bioperfectus) were performed according to Clinical Laboratory Standards Institute protocols and guidelines. The four NAATs were compared using 46 clinical samples. RESULTS: The LOD of the N gene for Daan, Sansure, and Hybribio was 500 copies/mL, and that for Bioperfectus was 1,000 copies/mL. The LOD of the ORF1ab gene for Daan, Bioperfectus, and Hybribio was 3,000 copies/mL, and that for Sansure was 2,000 copies/mL. A good precision was shown at the concentration above 20% of the LOD for all four NAATs, with all individual coefficients of variation below 3.6%. Satisfactory results were also observed in the accuracy, analytical specificity, and analytical interference tests. The results of the comparison test showed that Daan, Sansure, and Hybribio NAATs could detect the samples with a specificity of 100% (30/30) and a sensitivity of 100% (16/16), whereas Bioperfectus NAAT detected the samples with a specificity of 100% (30/30) and a sensitivity of 81.25% (13/16). However, no significant difference in sensitivity was found between Bioperfectus NAAT and the three other NAATs (p > 0.05). CONCLUSIONS: The four SARS-CoV-2 NAATs showed comparable performance, with the LOD of the N gene lower than the LOD of the ORF1ab gene.


Subject(s)
COVID-19 , Clinical Laboratory Services , Humans , Limit of Detection , Nucleic Acid Amplification Techniques , SARS-CoV-2 , Sensitivity and Specificity
6.
Diagn Microbiol Infect Dis ; 99(2): 115169, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-1064997

ABSTRACT

We evaluated simple laboratory variables to discriminate COVID-19 from bacterial pneumonia or influenza and for the prospective grading of COVID-19. Multivariate logistic regression and receiver operating characteristic curve were used to estimate the diagnostic performance of the significant discriminating variables. A comparative analysis was performed with different severity. The leukocytosis (P = 0.017) and eosinopenia (P = 0.001) were discriminating variables between COVID-19 and bacterial pneumonia with area under the curve (AUC) of 0.778 and 0.825. Monocytosis (P = 0.003), the decreased lymphocyte-to-monocyte ratio (P < 0.001), and the increased neutrophil-to-lymphocyte ratio (NLR) (P = 0.028) were predictive of influenza with AUC of 0.723, 0.895, and 0.783, respectively. Serum amyloid protein, lactate dehydrogenase, CD3+ cells, and the fibrinogen degradation products had a good correlation with the severity of COVID-19 graded by age (≥50) and NLR (≥3.13). Simple laboratory variables are helpful for rapid diagnosis on admission and hierarchical management of COVID-19 patients.


Subject(s)
COVID-19/diagnosis , Influenza, Human/diagnosis , Pneumonia, Bacterial/diagnosis , Severity of Illness Index , Adolescent , Adult , Amyloidogenic Proteins/blood , Child , Child, Preschool , Diagnosis, Differential , Eosinophilia/pathology , Female , Fibrinogen/metabolism , Humans , L-Lactate Dehydrogenase/blood , Leukocytosis/pathology , Lymphocyte Count , Male , Middle Aged , Monocytes/cytology , Neutrophils/cytology , Retrospective Studies , SARS-CoV-2 , Young Adult
7.
Hum Vaccin Immunother ; 16(7): 1668-1674, 2020 07 02.
Article in English | MEDLINE | ID: covidwho-133495

ABSTRACT

PURPOSE: To estimate influenza-associated excess mortality rates (EMRs) in Chongqing from 2012 to 2018. METHODS: We obtained weekly mortality data for all-cause and four underlying causes of death (circulatory and respiratory disease (CRD), pneumonia and influenza (P&I), chronic obstructive pulmonary disease (COPD) and ischemic heart disease (IDH)), and influenza surveillance data, from 2012 to 2018. A negative-binomial regression model was used to estimate influenza-associated EMRs in two age groups (<65 years and ≥65 years). RESULTS: It was estimated that an annual average of 10025 influenza-associated deaths occurred in Chongqing, corresponding to 5.2% of all deaths. The average EMR for all-cause death associated with influenza was 33.5 (95% confidence interval (CI): 31.5-35.6) per 100 000 persons, and in separate cause-specific models we attributed 24.7 (95% CI: 23.3-26.0), 0.8 (95% CI: 0.7-0.8), 8.5 (95% CI: 8.1-9.0) and 5.0 (95% CI: 4.7-5.3) per 100 000 persons EMRs to CRD, P&I, COPD and IDH, respectively. The estimated EMR for influenza B virus was 20.6 (95% CI: 20.3-21.0), which was significantly higher than the rates of 5.3 (95% CI: 4.5-6.1) and 7.5 (95% CI: 6.7-8.3) for A(H3N2) and A(H1N1) pdm09 virus, respectively. The estimated EMR was 152.3 (95% CI: 136.1-168.4) for people aged ≥65 years, which was significantly higher than the rate for those aged <65 years (6.8, 95% CI: 6.3-7.2). CONCLUSIONS: Influenza was associated with substantial EMRs in Chongqing, especially among elderly people. Influenza B virus caused a relatively higher excess mortality impact compared with A(H1N1)pdm09 and A(H3N2). It is advisable to optimize future seasonal influenza vaccine reimbursement policy in Chongqing to curb disease burden.


Subject(s)
Influenza A Virus, H1N1 Subtype , Influenza Vaccines , Influenza, Human , Aged , China/epidemiology , Humans , Influenza A Virus, H3N2 Subtype , Influenza, Human/epidemiology , Seasons
8.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.03.25.20037721

ABSTRACT

Background With evidence of sustained transmission in more than 190 countries, coronavirus disease 2019 (COVID-19) has been declared a global pandemic. As such, data are urgently needed about risk factors associated with clinical outcomes. Methods A retrospective chart review of 323 hospitalized patients with COVID-19 in Wuhan was conducted. Patients were classified into three disease severity groups (non-severe, severe, and critical), based on their initial clinical presentation. Clinical outcomes were designated as favorable and unfavorable, based on disease progression and response to treatments. Logistic regression models were performed to identify factors associated with clinical outcomes, and logrank test was conducted for the association with clinical progression. Results Current standard treatments did not show significant improvement on patient outcomes in the study. By univariate logistic regression model, 27 risk factors were significantly associated with clinical outcomes. Further, multivariate regression indicated that age over 65 years, smoking, critical disease status, diabetes, high hypersensitive troponin I (>0.04 pg/mL), leukocytosis (>10 x 109/L) and neutrophilia (>75 x 109/L) predicted unfavorable clinical outcomes. By contrast, the use of hypnotics was significantly associated with favorable outcomes. Survival analysis also confirmed that patients receiving hypnotics had significantly better survival. Conclusions To our knowledge, this is the first indication that hypnotics could be an effective ancillary treatment for COVID-19. We also found that novel risk factors, such as higher hypersensitive troponin I, predicted poor clinical outcomes. Overall, our study provides useful data to guide early clinical decision making to reduce mortality and improve clinical outcomes of COVID-19.


Subject(s)
COVID-19 , Leukocytosis , Diabetes Mellitus
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