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1.
Transbound Emerg Dis ; 2022 Jun 01.
Article in English | MEDLINE | ID: covidwho-1879106

ABSTRACT

The ongoing coronavirus disease 2019 pandemic and its overlap with the influenza season lead to concerns over severe disease caused by the influenza virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) co-infections. Using a Syrian hamster co-infection model with SARS-CoV-2 and the pandemic influenza virus A/California/04/2009 (H1N1), we found (a) more severe disease in co-infected animals, compared to those infected with influenza virus alone but not SARS-CoV-2 infection alone; (b) altered haematological changes in only co-infected animals and (c) altered influenza virus tropism in the respiratory tracts of co-infected animals. Overall, our study revealed that co-infection with SARS-CoV-2 and influenza virus is associated with altered disease severity and tissue tropism, as well as haematological changes, compared to infection with either virus alone.

2.
Arch Virol ; 167(3): 871-879, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1680885

ABSTRACT

Coronavirus disease 2019 (COVID-19) is an acute respiratory infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Other coronaviruses (CoVs) can also infect humans, although the majority cause only mild respiratory symptoms. Because early diagnosis of SARS-CoV-2 is critical for preventing further transmission events and improving clinical outcomes, it is important to be able to distinguish SARS-CoV-2 from other SARS-related CoVs in respiratory samples. Therefore, we developed and evaluated a novel reverse transcription quantitative polymerase chain reaction (RT-qPCR) assay targeting the genes encoding the spike (S) and membrane (M) proteins to enable the rapid identification of SARS-CoV-2, including several new circulating variants and other emerging SARS-like CoVs. By analysis of in vitro-transcribed mRNA, we established multiplex RT-qPCR assays capable of detecting 5 × 10° copies/reaction. Using RNA extracted from cell culture supernatants, our multiple simultaneous SARS-CoV-2 assays had a limit of detection of 1 × 10° TCID50/mL and showed no cross-reaction with human CoVs or other respiratory viruses. We also validated our method using human clinical samples from patients with COVID-19 and healthy individuals, including nasal swab and sputum samples. This novel one-step multiplex RT-qPCR assay can be used to improve the laboratory diagnosis of human-pathogenic CoVs, including SARS-CoV-2, and may be useful for the identification of other SARS-like CoVs of zoonotic origin.


Subject(s)
COVID-19 , COVID-19/diagnosis , Clinical Laboratory Techniques , Feasibility Studies , Humans , Real-Time Polymerase Chain Reaction , SARS-CoV-2/genetics , Sensitivity and Specificity
3.
Vaccines ; 10(1), 2022.
Article in English | EuropePMC | ID: covidwho-1639960

ABSTRACT

Subtype H3N2 influenza A viruses (A(H3N2)) have been the dominant strain in some countries in the Western Pacific region since the 2009 influenza A(H1N1) pandemic. Vaccination is the most effective way to prevent influenza;however, low vaccine effectiveness has been reported in some influenza seasons, especially for A(H3N2). Antigenic mismatch introduced by egg-adaptation during vaccine production between the vaccine and circulating viral stains is one of the reasons for low vaccine effectiveness. Here we review the extent of this phenomenon, the underlying molecular mechanisms and discuss recent strategies to ameliorate this, including new vaccine platforms that may provide better protection and should be considered to reduce the impact of A(H3N2) in the Western Pacific region.

4.
Pathogens ; 10(11)2021 Nov 18.
Article in English | MEDLINE | ID: covidwho-1524101

ABSTRACT

Guangdong province, located in South China, is an important economic hub with a large domestic migrant population and was among the earliest areas to report COVID-19 cases outside of Wuhan. We conducted a cross-sectional, age-stratified serosurvey to determine the seroprevalence of antibodies against SARS-CoV-2 after the emergence of COVID-19 in Guangdong. We tested 14,629 residual serum samples that were submitted for clinical testing from 21 prefectures between March and June 2020 for SARS-CoV-2 antibodies using a magnetic particle based chemiluminescent enzyme immunoassay and validated the results using a pseudovirus neutralization assay. We found 21 samples positive for SARS-CoV-2 IgG, resulting in an estimated age- and sex-weighted seroprevalence of 0.15% (95% CI: 0.06-0.24%). The overall age-specific seroprevalence was 0.07% (95% CI: 0.01-0.24%) in persons up to 9 years old, 0.22% (95% CI: 0.03-0.79%) in persons aged 10-19, 0.16% (95% CI: 0.07-0.33%) in persons aged 20-39, 0.13% (95% CI: 0.03-0.33%) in persons aged 40-59 and 0.18% (95% CI: 0.07-0.40%) in persons ≥60 years old. Fourteen (67%) samples had pseudovirus neutralization titers to S-protein, suggesting most of the IgG-positive samples were true-positives. Seroprevalence of antibodies to SARS-CoV-2 was low, indicating that there were no hidden epidemics during this period. Vaccination is urgently needed to increase population immunity to SARS-CoV-2.

5.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-292354

ABSTRACT

The pandemic coronavirus disease 2019 (COVID-19) is characterized as an acute respiratory infection in the majority of cases and is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, other coronaviruses (CoVs) can infect humans, although the majority only cause mild respiratory symptoms. As early diagnosis of SARS-CoV-2 is critical to prevent further transmission events and to improve clinical outcomes, it is important to be able to distinguish SARS-CoV-2 from other CoVs in respiratory samples. Therefore, we developed and evaluated a novel quantitative reverse transcription PCR (RT-qPCR) assay, targeting the spike (S) and membrane (M) genes, to enable the rapid identification of SARS-CoV-2 including several new circulating variants, and other emerging pan-SARS-like CoVs. Using RNA extracted from cell culture supernatants, our multiple simultaneous SARS-CoV-2 assays confirmed a limit of detection of 1 × 10 0 TCID 50 /ml and no cross-reaction with human coronaviruses or other respiratory viruses. We also validated our method using human clinical samples from COVID-19 patients and healthy individuals, including nasal swab and sputum samples. This novel one-step multiplex RT-qPCR assay can be used to improve the laboratory diagnosis of human-pathogenic coronaviruses, including SARS-CoV-2, and may be useful for the identification of other pan-SARS-like CoVs of zoonotic origin.

8.
Nat Commun ; 11(1): 3543, 2020 07 15.
Article in English | MEDLINE | ID: covidwho-974925

ABSTRACT

The sudden deterioration of patients with novel coronavirus disease 2019 (COVID-19) into critical illness is of major concern. It is imperative to identify these patients early. We show that a deep learning-based survival model can predict the risk of COVID-19 patients developing critical illness based on clinical characteristics at admission. We develop this model using a cohort of 1590 patients from 575 medical centers, with internal validation performance of concordance index 0.894 We further validate the model on three separate cohorts from Wuhan, Hubei and Guangdong provinces consisting of 1393 patients with concordance indexes of 0.890, 0.852 and 0.967 respectively. This model is used to create an online calculation tool designed for patient triage at admission to identify patients at risk of severe illness, ensuring that patients at greatest risk of severe illness receive appropriate care as early as possible and allow for effective allocation of health resources.


Subject(s)
Coronavirus Infections/diagnosis , Coronavirus Infections/pathology , Deep Learning/statistics & numerical data , Pneumonia, Viral/diagnosis , Pneumonia, Viral/pathology , Triage/methods , Betacoronavirus , COVID-19 , Critical Illness , Hospitalization , Humans , Middle Aged , Models, Theoretical , Pandemics , Prognosis , Risk , SARS-CoV-2 , Survival Analysis
9.
J Thorac Dis ; 12(8): 4434-4449, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-782595

ABSTRACT

The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused nations to adopt unprecedented control measures in order to curb its spread. As the first nation to respond, China's aggressive control measures appeared to have been effective in suppressing the first wave and keeping new cases under control. Here, we provide the historical context and details of China's public health response to COVID-19. We highlight the lessons and impact of the 2002-2003 SARS outbreak, which demonstrated the importance of transparency, surveillance and testing laboratories during an outbreak. We provide an overview of China's response strategy that was based on the principles of early detection, isolation, management and treatment and involved not only the large-scale coordination of multiple governmental bodies but also grass-root community participation throughout the country. These community-based organizations conducted active surveillance for febrile cases and provided support for those in quarantine and communities in lockdown. Importantly, these broader measures were supported by digital technology, including the extensive use of internet-based platforms and mobile applications (APPs). While there have been no significant increases in case numbers since April, there is still much concern over a second wave, considering the resumption of work and school, the lifting of travel restrictions and the outbreaks occurring globally. Control measures has since been implemented by provincial authorities, which includes continued surveillance and rapid testing. Although China's strict control measures may not suit every nation, the principles of early detection and isolation continue to hold true and have been a cornerstone of the initial and ongoing response to the COVID-19.

10.
Viruses ; 12(7), 2020.
Article in English | MEDLINE | ID: covidwho-662389

ABSTRACT

The host innate defence against influenza virus infection is an intricate system with a plethora of antiviral factors involved. We have identified host histone deacetylase 6 (HDAC6) as an anti-influenza virus factor in cultured cells. Consistent with this, we report herein that HDAC6 knockout (KO) mice are more susceptible to influenza virus A/PR/8/1934 (H1N1) infection than their wild type (WT) counterparts. The KO mice lost weight faster than the WT mice and, unlike WT mice, could not recover their original body weight. Consequently, more KO mice succumbed to infection, which corresponded with higher lung viral loads. Conversely, the expression of the critical innate antiviral response genes interferon alpha/beta, CD80, CXCL10 and IL15 was significantly downregulated in KO mouse lungs compared to WT mouse lungs. These data are consistent with the known function of HDAC6 of de-acetylating the retinoic acid inducible gene-I (RIG-I) and activating the host innate antiviral response cascade. Loss of HDAC6 thus leads to a blunted innate response and increased susceptibility of mice to influenza A virus infection.

11.
J Med Chem ; 63(22): 13205-13227, 2020 11 25.
Article in English | MEDLINE | ID: covidwho-741659

ABSTRACT

The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to more than 20 million people infected worldwide with an average mortality rate of 3.6%. This virus poses major challenges to public health, as it not only is highly contagious but also can be transmitted by asymptomatic infected individuals. COVID-19 is clinically difficult to manage due to a lack of specific antiviral drugs or vaccines. In this article, Chinese therapy strategies for treating COVID-19 patients, including current applications of traditional Chinese medicine (TCM), are comprehensively reviewed. Furthermore, 72 small molecules from natural products and TCM with reported antiviral activity against human coronaviruses (CoVs) are identified from published literature, and their potential applications in combating SARS-CoV-2 are discussed. Among these, the clinical efficacies of some accessible drugs such as remdesivir (RDV) and favipiravir (FPV) for COVID-19 are emphatically summarized. We hope this review provides a foundation for managing the worsening pandemic and developing antivirals against SARS-CoV-2.


Subject(s)
Antiviral Agents/therapeutic use , COVID-19/drug therapy , Coronavirus Protease Inhibitors/therapeutic use , Drugs, Chinese Herbal/therapeutic use , SARS-CoV-2/drug effects , Small Molecule Libraries/therapeutic use , COVID-19/epidemiology , China/epidemiology , Humans , Medicine, Chinese Traditional , SARS-CoV-2/enzymology
12.
Influenza Other Respir Viruses ; 15(1): 7-12, 2021 01.
Article in English | MEDLINE | ID: covidwho-735924

ABSTRACT

To inform seroepidemiological studies, we characterized the IgG- responses in COVID-19 patients against the two major SARS-CoV-2 viral proteins, spike (S) and nucleocapsid (N). We tested 70 COVID-19 sera collected up to 85 days post-symptom onset and 230 non-COVID-19 sera, including 27 SARS sera from 2003. Although the average SARS-CoV-2 S and N-IgG titers were comparable, N-responses were more variable among individuals. S- and N-assay specificity tested with non-COVID-19 sera were comparable at 97.5% and 97.0%, respectively. Therefore, S will make a better target due to its lower cross-reactive potential and its' more consistent frequency of detection compared to N.


Subject(s)
Antibodies, Viral/blood , Coronavirus Nucleocapsid Proteins/immunology , SARS-CoV-2/immunology , Spike Glycoprotein, Coronavirus/immunology , Adult , Aged , Aged, 80 and over , Cross Reactions , Humans , Middle Aged , Phosphoproteins/immunology , SARS Virus/immunology
14.
Eur Respir J ; 55(6)2020 06.
Article in English | MEDLINE | ID: covidwho-622479

ABSTRACT

BACKGROUND: During the outbreak of coronavirus disease 2019 (COVID-19), consistent and considerable differences in disease severity and mortality rate of patients treated in Hubei province compared to those in other parts of China have been observed. We sought to compare the clinical characteristics and outcomes of patients being treated inside and outside Hubei province, and explore the factors underlying these differences. METHODS: Collaborating with the National Health Commission, we established a retrospective cohort to study hospitalised COVID-19 cases in China. Clinical characteristics, the rate of severe events and deaths, and the time to critical illness (invasive ventilation or intensive care unit admission or death) were compared between patients within and outside Hubei. The impact of Wuhan-related exposure (a presumed key factor that drove the severe situation in Hubei, as Wuhan is the epicentre as well the administrative centre of Hubei province) and the duration between symptom onset and admission on prognosis were also determined. RESULTS: At the data cut-off (31 January 2020), 1590 cases from 575 hospitals in 31 provincial administrative regions were collected (core cohort). The overall rate of severe cases and mortality was 16.0% and 3.2%, respectively. Patients in Hubei (predominantly with Wuhan-related exposure, 597 (92.3%) out of 647) were older (mean age 49.7 versus 44.9 years), had more cases with comorbidity (32.9% versus 19.7%), higher symptomatic burden, abnormal radiologic manifestations and, especially, a longer waiting time between symptom onset and admission (5.7 versus 4.5 days) compared with patients outside Hubei. Patients in Hubei (severe event rate 23.0% versus 11.1%, death rate 7.3% versus 0.3%, HR (95% CI) for critical illness 1.59 (1.05-2.41)) have a poorer prognosis compared with patients outside Hubei after adjusting for age and comorbidity. However, among patients outside Hubei, the duration from symptom onset to hospitalisation (mean 4.4 versus 4.7 days) and prognosis (HR (95%) 0.84 (0.40-1.80)) were similar between patients with or without Wuhan-related exposure. In the overall population, the waiting time, but neither treated in Hubei nor Wuhan-related exposure, remained an independent prognostic factor (HR (95%) 1.05 (1.01-1.08)). CONCLUSION: There were more severe cases and poorer outcomes for COVID-19 patients treated in Hubei, which might be attributed to the prolonged duration of symptom onset to hospitalisation in the epicentre. Future studies to determine the reason for delaying hospitalisation are warranted.


Subject(s)
Coronavirus Infections/mortality , Hospitalization , Pneumonia, Viral/mortality , Adult , Aged , Betacoronavirus , COVID-19 , Cardiovascular Diseases/epidemiology , China , Cohort Studies , Comorbidity , Coronavirus Infections/complications , Coronavirus Infections/diagnostic imaging , Cough/etiology , Diabetes Mellitus/epidemiology , Disease Outbreaks , Dyspnea/etiology , Fatigue/etiology , Female , Fever/etiology , Geography , Humans , Hypertension/epidemiology , Intensive Care Units/statistics & numerical data , Lung/diagnostic imaging , Male , Middle Aged , Pandemics , Pharyngitis/etiology , Pneumonia, Viral/complications , Pneumonia, Viral/diagnostic imaging , Prognosis , Proportional Hazards Models , Respiration, Artificial/statistics & numerical data , Retrospective Studies , SARS-CoV-2 , Severity of Illness Index , Time Factors , Time-to-Treatment/statistics & numerical data , Tomography, X-Ray Computed
15.
Influenza Other Respir Viruses ; 14(6): 688-699, 2020 11.
Article in English | MEDLINE | ID: covidwho-612437

ABSTRACT

BACKGROUND: Severe COVID-19 patients typically test positive for SARS-CoV-2 RNA for extended periods of time, even after recovery from severe disease. Due to the timeframe involved, these patients may have developed humoral immunity to SARS-CoV-2 while still testing positive for viral RNA in swabs. Data are lacking on exposure risks in these situations. Here, we studied SARS-CoV-2 environmental contamination in an ICU and an isolation ward caring for such COVID-19 patients. METHODS: We collected air and surface samples in a hospital caring for critical and severe COVID-19 cases from common areas and areas proximal to patients. RESULTS: Of the 218 ICU samples, an air sample contained SARS-CoV-2 RNA. Of the 182 isolation ward samples, nine contained SARS-CoV-2 RNA. These were collected from a facemask, the floor, mobile phones, and the air in the patient room and bathroom. Serum antibodies against SARS-CoV-2 were detected in these patients at the beginning of the study. CONCLUSIONS: While there is a perception of increased risk in the ICU, our study demonstrates that isolation wards may pose greater risks to healthcare workers and exposure risks remain with clinically improved patients, weeks after their initial diagnoses. As these patients had serum antibodies, further studies may be warranted to study the utility of serum antibodies as a surrogate of viral clearance in allowing people to return to work. We recommend continued vigilance even with patients who appear to have recovered from COVID-19.


Subject(s)
Betacoronavirus/isolation & purification , Coronavirus Infections/virology , Environmental Microbiology , Pneumonia, Viral/virology , Adult , Aged, 80 and over , Antibodies, Viral/blood , Betacoronavirus/genetics , Betacoronavirus/immunology , COVID-19 , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Female , Humans , Intensive Care Units , Male , Middle Aged , Pandemics , Patient Isolation , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , RNA, Viral/genetics , RNA, Viral/isolation & purification , SARS-CoV-2 , Viral Load
16.
J Thorac Dis ; 12(3): 165-174, 2020 Mar.
Article in English | MEDLINE | ID: covidwho-48351

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) outbreak originating in Wuhan, Hubei province, China, coincided with chunyun, the period of mass migration for the annual Spring Festival. To contain its spread, China adopted unprecedented nationwide interventions on January 23 2020. These policies included large-scale quarantine, strict controls on travel and extensive monitoring of suspected cases. However, it is unknown whether these policies have had an impact on the epidemic. We sought to show how these control measures impacted the containment of the epidemic. METHODS: We integrated population migration data before and after January 23 and most updated COVID-19 epidemiological data into the Susceptible-Exposed-Infectious-Removed (SEIR) model to derive the epidemic curve. We also used an artificial intelligence (AI) approach, trained on the 2003 SARS data, to predict the epidemic. RESULTS: We found that the epidemic of China should peak by late February, showing gradual decline by end of April. A five-day delay in implementation would have increased epidemic size in mainland China three-fold. Lifting the Hubei quarantine would lead to a second epidemic peak in Hubei province in mid-March and extend the epidemic to late April, a result corroborated by the machine learning prediction. CONCLUSIONS: Our dynamic SEIR model was effective in predicting the COVID-19 epidemic peaks and sizes. The implementation of control measures on January 23 2020 was indispensable in reducing the eventual COVID-19 epidemic size.

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