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1.
Int J Infect Dis ; 121: 195-202, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1851259

ABSTRACT

OBJECTIVES: Because of the spread of the Omicron variant, many countries have experienced COVID-19 case numbers unseen since the start of the pandemic. We aimed to compare the epidemiological characteristics of Omicron with previous variants and different strains of influenza to provide context for public health responses. METHODS: We developed transmission models for SARS-CoV-2 variants and influenza, in which transmission, death, and vaccination rates were taken to be time-varying. We fit our model based on publicly available data in South Africa, the United States, and Canada. We used this model to evaluate the relative transmissibility and mortality of Omicron compared with previous variants and influenza. RESULTS: We found that Omicron is more transmissible and less fatal than both seasonal and 2009 H1N1 influenza and the Delta variant; these characteristics make Omicron epidemiologically more similar to influenza than it is to Delta. We estimate that as of February 7, 2022, booster doses have prevented 4.29×107 and 1.14×106 Omicron infections in the United States and Canada, respectively. CONCLUSION: Our findings indicate that the high infectivity of Omicron will keep COVID-19 endemic, similar to influenza. However, because of Omicron's lower fatality rate, our work suggests that human populations living with SARS-CoV-2 are most likely.


Subject(s)
COVID-19 , Influenza A Virus, H1N1 Subtype , Influenza, Human , Mutation , SARS-CoV-2 , COVID-19/epidemiology , COVID-19/virology , Humans , Influenza A Virus, H1N1 Subtype/genetics , Influenza A Virus, H1N1 Subtype/pathogenicity , Influenza, Human/prevention & control , Influenza, Human/virology , SARS-CoV-2/genetics , SARS-CoV-2/pathogenicity , United States/epidemiology
2.
STAR Protoc ; 3(1): 101051, 2022 03 18.
Article in English | MEDLINE | ID: covidwho-1575581

ABSTRACT

Here we describe a protocol for identifying metabolites in respiratory specimens of patients that are SARS-CoV-2 positive, SARS-CoV-2 negative, or H1N1 positive. This protocol provides step-by-step instructions on sample collection from patients, followed by metabolite extraction. We use ultra-high-pressure liquid chromatography (UHPLC) coupled with high-resolution mass spectrometry (HRMS) for data acquisition and describe the steps for data analysis. The protocol was standardized with specific customization for SARS-CoV-2-containing respiratory specimens. For complete details on the use and execution of this protocol, please refer to Maras et al. (2021).


Subject(s)
COVID-19/diagnosis , Chromatography, High Pressure Liquid/methods , Metabolomics/methods , COVID-19/metabolism , Computational Biology , Diagnostic Tests, Routine , Gene Expression Profiling , Genetic Techniques , Humans , Influenza A Virus, H1N1 Subtype/metabolism , Influenza A Virus, H1N1 Subtype/pathogenicity , Mass Spectrometry/methods , Metabolome , Reference Standards , SARS-CoV-2/metabolism , SARS-CoV-2/pathogenicity , Specimen Handling/methods
3.
STAR Protoc ; 3(1): 101045, 2022 03 18.
Article in English | MEDLINE | ID: covidwho-1537118

ABSTRACT

In this protocol, we describe global proteome profiling for the respiratory specimen of COVID-19 patients, patients suspected with COVID-19, and H1N1 patients. In this protocol, details for identifying host, viral, or bacterial proteome (Meta-proteome) are provided. Major steps of the protocol include virus inactivation, protein quantification and digestion, desalting of peptides, high-resolution mass spectrometry (HRMS)-based analysis, and downstream bioinformatics analysis. For complete details on the use and execution of this profile, please refer to Maras et al. (2021).


Subject(s)
COVID-19/diagnosis , Genomics/methods , Proteomics/methods , COVID-19/metabolism , Chromatography, Liquid/methods , Computational Biology , Diagnostic Tests, Routine , Gene Expression Profiling , Genetic Techniques , Genome, Viral/genetics , Humans , Influenza A Virus, H1N1 Subtype/metabolism , Influenza A Virus, H1N1 Subtype/pathogenicity , Peptides , Proteome , SARS-CoV-2/metabolism , SARS-CoV-2/pathogenicity , Specimen Handling/methods , Tandem Mass Spectrometry/methods , Virome/genetics , Virome/physiology
5.
Sci Rep ; 11(1): 14341, 2021 07 12.
Article in English | MEDLINE | ID: covidwho-1307345

ABSTRACT

Computational models for large, resurgent epidemics are recognized as a crucial tool for predicting the spread of infectious diseases. It is widely agreed, that such models can be augmented with realistic multiscale population models and by incorporating human mobility patterns. Nevertheless, a large proportion of recent studies, aimed at better understanding global epidemics, like influenza, measles, H1N1, SARS, and COVID-19, underestimate the role of heterogeneous mixing in populations, characterized by strong social structures and geography. Motivated by the reduced tractability of studies employing homogeneous mixing, which make conclusions hard to deduce, we propose a new, very fine-grained model incorporating the spatial distribution of population into geographical settlements, with a hierarchical organization down to the level of households (inside which we assume homogeneous mixing). In addition, population is organized heterogeneously outside households, and we model the movement of individuals using travel distance and frequency parameters for inter- and intra-settlement movement. Discrete event simulation, employing an adapted SIR model with relapse, reproduces important qualitative characteristics of real epidemics, like high variation in size and temporal heterogeneity (e.g., waves), that are challenging to reproduce and to quantify with existing measures. Our results pinpoint an important aspect, that epidemic size is more sensitive to the increase in distance of travel, rather that the frequency of travel. Finally, we discuss implications for the control of epidemics by integrating human mobility restrictions, as well as progressive vaccination of individuals.


Subject(s)
COVID-19/epidemiology , Communicable Diseases/epidemiology , Influenza, Human/epidemiology , COVID-19/virology , Communicable Diseases/virology , Computer Simulation , Epidemics/prevention & control , Epidemics/statistics & numerical data , Family Characteristics , Humans , Influenza A Virus, H1N1 Subtype/pathogenicity , Influenza, Human/virology , SARS-CoV-2/pathogenicity , Travel/statistics & numerical data
6.
PLoS Pathog ; 17(7): e1009381, 2021 07.
Article in English | MEDLINE | ID: covidwho-1291654

ABSTRACT

Clearance of viral infections, such as SARS-CoV-2 and influenza A virus (IAV), must be fine-tuned to eliminate the pathogen without causing immunopathology. As such, an aggressive initial innate immune response favors the host in contrast to a detrimental prolonged inflammation. The complement pathway bridges innate and adaptive immune system and contributes to the response by directly clearing pathogens or infected cells, as well as recruiting proinflammatory immune cells and regulating inflammation. However, the impact of modulating complement activation in viral infections is still unclear. In this work, we targeted the complement decay-accelerating factor (DAF/CD55), a surface protein that protects cells from non-specific complement attack, and analyzed its role in IAV infections. We found that DAF modulates IAV infection in vivo, via an interplay with the antigenic viral proteins hemagglutinin (HA) and neuraminidase (NA), in a strain specific manner. Our results reveal that, contrary to what could be expected, DAF potentiates complement activation, increasing the recruitment of neutrophils, monocytes and T cells. We also show that viral NA acts on the heavily sialylated DAF and propose that the NA-dependent DAF removal of sialic acids exacerbates complement activation, leading to lung immunopathology. Remarkably, this mechanism has no impact on viral loads, but rather on the host resilience to infection, and may have direct implications in zoonotic influenza transmissions.


Subject(s)
CD55 Antigens/physiology , Influenza A Virus, H1N1 Subtype/isolation & purification , Lung/immunology , Viremia/immunology , Animals , Bronchoalveolar Lavage Fluid/immunology , CD55 Antigens/chemistry , CD55 Antigens/deficiency , Chemotaxis, Leukocyte , Complement Activation , Hemagglutinin Glycoproteins, Influenza Virus/physiology , Host Adaptation , Host Specificity , Host-Pathogen Interactions , Influenza A Virus, H1N1 Subtype/enzymology , Influenza A Virus, H1N1 Subtype/pathogenicity , Influenza A Virus, H1N1 Subtype/physiology , Interferon-gamma/analysis , Lung/pathology , Lung/virology , Mice , Mice, Inbred C57BL , N-Acetylneuraminic Acid , Neuraminidase/physiology , Orthomyxoviridae Infections/immunology , Orthomyxoviridae Infections/pathology , Viral Load , Viral Proteins/physiology , Virulence , Virus Replication , Weight Loss
7.
Viruses ; 13(6)2021 06 15.
Article in English | MEDLINE | ID: covidwho-1270129

ABSTRACT

Influenza is a highly known contagious viral infection that has been responsible for the death of many people in history with pandemics. These pandemics have been occurring every 10 to 30 years in the last century. The most recent global pandemic prior to COVID-19 was the 2009 influenza A (H1N1) pandemic. A decade ago, the H1N1 virus caused 12,500 deaths in just 19 months globally. Now, again, the world has been challenged with another pandemic. Since December 2019, the first case of a novel coronavirus (COVID-19) infection was detected in Wuhan. This infection has risen rapidly throughout the world; even the World Health Organization (WHO) announced COVID-19 as a worldwide emergency to ensure human health and public safety. This review article aims to discuss important issues relating to COVID-19, including clinical, epidemiological, and pathological features of COVID-19 and recent progress in diagnosis and treatment approaches for the COVID-19 infection. We also highlight key similarities and differences between COVID-19 and influenza A to ensure the theoretical and practical details of COVID-19.


Subject(s)
COVID-19/epidemiology , Influenza A Virus, H1N1 Subtype/pathogenicity , Influenza, Human/epidemiology , SARS-CoV-2/pathogenicity , Global Health , Humans , Pandemics/prevention & control , Pandemics/statistics & numerical data , World Health Organization
8.
Emerg Microbes Infect ; 10(1): 1191-1199, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1246663

ABSTRACT

The ongoing COVID-19 pandemic has led to more than 159 million confirmed cases with over 3.3 million deaths worldwide, but it remains mystery why most infected individuals (∼98%) were asymptomatic or only experienced mild illness. The same mystery applies to the deadly 1918 H1N1 influenza pandemic, which has puzzled the field for a century. Here we discuss dual potential properties of the 1918 H1N1 pandemic viruses that led to the high fatality rate in the small portion of severe cases, while about 98% infected persons in the United States were self-limited with mild symptoms, or even asymptomatic. These variations now have been postulated to be impacted by polymorphisms of the sialic acid receptors in the general population. Since coronaviruses (CoVs) also recognize sialic acid receptors and cause severe acute respiratory syndrome epidemics and pandemics, similar principles of influenza virus evolution and pandemicity may also apply to CoVs. A potential common principle of pathogen/host co-evolution of influenza and CoVs under selection of host sialic acids in parallel with different epidemic and pandemic influenza and coronaviruses is discussed.


Subject(s)
COVID-19/pathology , Influenza, Human/pathology , Receptors, Cell Surface/genetics , Receptors, Virus/genetics , Sialic Acids/metabolism , Asymptomatic Diseases , Biological Evolution , COVID-19/mortality , Humans , Influenza A Virus, H1N1 Subtype/genetics , Influenza A Virus, H1N1 Subtype/pathogenicity , Influenza A Virus, H5N1 Subtype/genetics , Influenza A Virus, H5N1 Subtype/pathogenicity , Influenza A Virus, H7N9 Subtype/genetics , Influenza A Virus, H7N9 Subtype/pathogenicity , Influenza, Human/mortality , Receptors, Cell Surface/metabolism , Receptors, Virus/metabolism , SARS-CoV-2/genetics , Saliva/metabolism , Saliva/virology
9.
Brief Bioinform ; 22(6)2021 11 05.
Article in English | MEDLINE | ID: covidwho-1217814

ABSTRACT

Two thousand nineteen novel coronavirus SARS-CoV-2, the pathogen of COVID-19, has caused a catastrophic pandemic, which has a profound and widespread impact on human lives and social economy globally. However, the molecular perturbations induced by the SARS-CoV-2 infection remain unknown. In this paper, from the perspective of omnigenic, we analyze the properties of the neighborhood perturbed by SARS-CoV-2 in the human interactome and disclose the peripheral and core regions of virus-host network (VHN). We find that the virus-host proteins (VHPs) form a significantly connected VHN, among which highly perturbed proteins aggregate into an observable core region. The non-core region of VHN forms a large scale but relatively low perturbed periphery. We further validate that the periphery is non-negligible and conducive to identifying comorbidities and detecting drug repurposing candidates for COVID-19. We particularly put forward a flower model for COVID-19, SARS and H1N1 based on their peripheral regions, and the flower model shows more correlations between COVID-19 and other two similar diseases in common functional pathways and candidate drugs. Overall, our periphery-core pattern can not only offer insights into interconnectivity of SARS-CoV-2 VHPs but also facilitate the research on therapeutic drugs.


Subject(s)
COVID-19/genetics , Drug Repositioning , SARS-CoV-2/genetics , COVID-19/pathology , COVID-19/virology , Host-Pathogen Interactions/genetics , Humans , Influenza A Virus, H1N1 Subtype/drug effects , Influenza A Virus, H1N1 Subtype/pathogenicity , SARS-CoV-2/pathogenicity , COVID-19 Drug Treatment
10.
PLoS One ; 15(12): e0242403, 2020.
Article in English | MEDLINE | ID: covidwho-963802

ABSTRACT

Globally, public health measures like face masks, hand hygiene and maintaining social distancing have been implemented to delay and reduce local transmission of COVID-19. To date there is emerging evidence to provide effectiveness and compliance to intervention measures on COVID-19 due to rapid spread of the disease. We synthesized evidence of community interventions and innovative practices to mitigate COVID-19 as well as previous respiratory outbreak infections which may share some aspects of transmission dynamics with COVID-19. In the study, we systematically searched the literature on community interventions to mitigate COVID-19, SARS (severe acute respiratory syndrome), H1N1 Influenza and MERS (middle east respiratory syndrome) epidemics in PubMed, Google Scholar, World Health Organization (WHO), MEDRXIV and Google from their inception until May 30, 2020 for up-to-date published and grey resources. We screened records, extracted data, and assessed risk of bias in duplicates. We rated the certainty of evidence according to Cochrane methods and the GRADE approach. This study is registered with PROSPERO (CRD42020183064). Of 41,138 papers found, 17 studies met the inclusion criteria in various settings in Low- and Middle-Income Countries (LMICs). One of the papers from LMICs originated from Africa (Madagascar) with the rest from Asia 9 (China 5, Bangladesh 2, Thailand 2); South America 5 (Mexico 3, Peru 2) and Europe 2 (Serbia and Romania). Following five studies on the use of face masks, the risk of contracting SARS and Influenza was reduced OR 0.78 and 95% CI = 0.36-1.67. Equally, six studies on hand hygiene practices reported a reduced risk of contracting SARS and Influenza OR 0.95 and 95% CI = 0.83-1.08. Further two studies that looked at combined use of face masks and hand hygiene interventions showed the effectiveness in controlling the transmission of influenza OR 0.94 and 95% CI = 0.58-1.54. Nine studies on social distancing intervention demonstrated the importance of physical distance through closure of learning institutions on the transmission dynamics of disease. The evidence confirms the use of face masks, good hand hygiene and social distancing as community interventions are effective to control the spread of SARS and influenza in LMICs. However, the effectiveness of community interventions in LMICs should be informed by adherence of the mitigation measures and contextual factors taking into account the best practices. The study has shown gaps in adherence/compliance of the interventions, hence a need for robust intervention studies to better inform the evidence on compliance of the interventions. Nevertheless, this rapid review of currently best available evidence might inform interim guidance on similar respiratory infectious diseases like Covid-19 in Kenya and similar LMIC context.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Early Medical Intervention/methods , Coronavirus Infections/epidemiology , Developing Countries , Disease Outbreaks , Hand Hygiene/trends , Humans , Income , Influenza A Virus, H1N1 Subtype/pathogenicity , Kenya/epidemiology , Masks/trends , Pandemics , Pneumonia, Viral/epidemiology , Public Health , SARS-CoV-2 , Severe Acute Respiratory Syndrome/epidemiology
11.
J Clin Virol ; 134: 104709, 2021 01.
Article in English | MEDLINE | ID: covidwho-957191

ABSTRACT

BACKGROUND: The Influenza-like Illness Surveillance Network (ILINet) can indicate the presence of novel, widespread community pathogens. Comparing week-to-week reported influenza-like illness percentages may identify the time of year a novel pathogen is introduced. However, changes in health-seeking behavior during the COVID-19 pandemic call in to question the reliability of 2019-2020 ILINet data as a comparison to prior years, potentially rendering this system less reliable as a novel pathogen surveillance tool. Corroboration of trends seen in the 2019-2020 ILINet data lends confidence to the validity of those trends. This study compares predicted versus reported influenza and influenza-like illnesses in vaccinated adults as a surrogate measure of novel pathogen surveillance. METHODS: An online survey was used to ask US adults their influenza vaccination status, whether they were diagnosed with influenza after vaccination, and whether they experienced an influenza-like illness other than flu. RESULTS: Prevalence of self-reported flu diagnosis in adults age 18-64 who received the flu vaccine between September 1, 2019 and April 15, 2020 (n = 3,225) was 5.8 %, while self-reported flu or flu-like illness (without a flu diagnosis) was 17.9 %. CONCLUSION: Flu and flu-like illness in this sample of flu-vaccinated U.S. adults is significantly higher than predicted, consistent with substantially higher ILI's in 2019-20 compared to ILI's from 2018-19, suggesting that the ILI values reported during the COVID-19 pandemic may be appropriate for comparison to prior years.


Subject(s)
COVID-19/epidemiology , Influenza, Human/epidemiology , Pandemics , Vaccination/statistics & numerical data , Adolescent , Adult , Female , Health Surveys/statistics & numerical data , Humans , Immunologic Surveillance , Influenza A Virus, H1N1 Subtype/pathogenicity , Influenza Vaccines/administration & dosage , Influenza, Human/prevention & control , Male , Middle Aged , SARS-CoV-2/pathogenicity , Self Report , United States/epidemiology
12.
Infect Dis Poverty ; 9(1): 163, 2020 Dec 02.
Article in English | MEDLINE | ID: covidwho-954569

ABSTRACT

BACKGROUND: There is an urgent need to better understand the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), for that the coronavirus disease 2019 (COVID-19) continues to cause considerable morbidity and mortality worldwide. This paper was to differentiate COVID-19 from other respiratory infectious diseases such as avian-origin influenza A (H7N9) and influenza A (H1N1) virus infections. METHODS: We included patients who had been hospitalized with laboratory-confirmed infection by SARS-CoV-2 (n = 83), H7N9 (n = 36), H1N1 (n = 44) viruses. Clinical presentation, chest CT features, and progression of patients were compared. We used the Logistic regression model to explore the possible risk factors. RESULTS: Both COVID-19 and H7N9 patients had a longer duration of hospitalization than H1N1 patients (P < 0.01), a higher complication rate, and more severe cases than H1N1 patients. H7N9 patients had higher hospitalization-fatality ratio than COVID-19 patients (P = 0.01). H7N9 patients had similar patterns of lymphopenia, neutrophilia, elevated alanine aminotransferase, C-reactive protein, lactate dehydrogenase, and those seen in H1N1 patients, which were all significantly different from patients with COVID-19 (P < 0.01). Either H7N9 or H1N1 patients had more obvious symptoms, like fever, fatigue, yellow sputum, and myalgia than COVID-19 patients (P < 0.01). The mean duration of viral shedding was 9.5 days for SARS-CoV-2 vs 9.9 days for H7N9 (P = 0.78). For severe cases, the meantime from illness onset to severity was 8.0 days for COVID-19 vs 5.2 days for H7N9 (P < 0.01), the comorbidity of chronic heart disease was more common in the COVID-19 patients than H7N9 (P = 0.02). Multivariate analysis showed that chronic heart disease was a possible risk factor (OR > 1) for COVID-19, compared with H1N1 and H7N9. CONCLUSIONS: The proportion of severe cases were higher for H7N9 and SARS-CoV-2 infections, compared with H1N1. The meantime from illness onset to severity was shorter for H7N9. Chronic heart disease was a possible risk factor for COVID-19.The comparison may provide the rationale for strategies of isolation and treatment of infected patients in the future.


Subject(s)
COVID-19/pathology , COVID-19/virology , Influenza, Human/pathology , Influenza, Human/virology , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/diagnosis , COVID-19/mortality , Child , Child, Preschool , Comorbidity , Disease Progression , Female , Hospitalization , Humans , Influenza A Virus, H1N1 Subtype/pathogenicity , Influenza A Virus, H7N9 Subtype/pathogenicity , Influenza, Human/diagnosis , Influenza, Human/mortality , Lung/diagnostic imaging , Lung/pathology , Male , Middle Aged , Risk Factors , SARS-CoV-2/pathogenicity , Virus Shedding , Young Adult
13.
J Dev Orig Health Dis ; 12(5): 683-687, 2021 10.
Article in English | MEDLINE | ID: covidwho-917501

ABSTRACT

The 1918 Influenza pandemic had long-term impacts on the cohort exposed in utero which experienced earlier adult mortality, and more diabetes, ischemic heart disease, and depression after age 50. It is possible that the Coronavirus Disease 2019 (COVID-19) pandemic will also have long-term impacts on the cohort that was in utero during the pandemic, from exposure to maternal infection and/or the stress of the pandemic environment. We discuss how COVID-19 disease during pregnancy may affect fetal and postnatal development with adverse impacts on health and aging. Severe maternal infections are associated with an exaggerated inflammatory response, thromboembolic events, and placental vascular malperfusion. We also discuss how in utero exposure to the stress of the pandemic, without maternal infection, may impact health and aging. Several recently initiated birth cohort studies are tracking neonatal health following in utero severe acute respiratory syndrome virus 2 (SARS-CoV-2) exposure. We suggest these cohort studies develop plans for longer-term observations of physical, behavioral, and cognitive functions that are markers for accelerated aging, as well as methods to disentangle the effects of maternal infection from stresses of the pandemic environment. In utero exposure to COVID-19 disease could cause developmental difficulties and accelerated aging in the century ahead. This brief review summarizes elements of the developmental origins of health, disease, and ageing and discusses how the COVID-19 pandemic might exacerbate such effects. We conclude with a call for research on the long-term consequences of in utero exposure to maternal infection with COVID-19 and stresses of the pandemic environment.


Subject(s)
Aging/physiology , COVID-19/physiopathology , Influenza, Human/physiopathology , Pregnancy Complications, Infectious/physiopathology , Prenatal Exposure Delayed Effects/physiopathology , Adult , Aged , COVID-19/transmission , COVID-19/virology , Child , Child Development/physiology , Child, Preschool , Female , History, 20th Century , Humans , Infant , Infant, Newborn , Infectious Disease Transmission, Vertical/history , Influenza A Virus, H1N1 Subtype/pathogenicity , Influenza Pandemic, 1918-1919/history , Influenza Pandemic, 1918-1919/statistics & numerical data , Influenza, Human/history , Influenza, Human/virology , Middle Aged , Pandemics/history , Pandemics/statistics & numerical data , Pregnancy , Pregnancy Complications, Infectious/virology , Prenatal Exposure Delayed Effects/virology , SARS-CoV-2/pathogenicity
14.
Front Immunol ; 11: 552909, 2020.
Article in English | MEDLINE | ID: covidwho-803900

ABSTRACT

The 2019 novel coronavirus (SARS-CoV-2) pandemic has caused a global health emergency. The outbreak of this virus has raised a number of questions: What is SARS-CoV-2? How transmissible is SARS-CoV-2? How severely affected are patients infected with SARS-CoV-2? What are the risk factors for viral infection? What are the differences between this novel coronavirus and other coronaviruses? To answer these questions, we performed a comparative study of four pathogenic viruses that primarily attack the respiratory system and may cause death, namely, SARS-CoV-2, severe acute respiratory syndrome (SARS-CoV), Middle East respiratory syndrome (MERS-CoV), and influenza A viruses (H1N1 and H3N2 strains). This comparative study provides a critical evaluation of the origin, genomic features, transmission, and pathogenicity of these viruses. Because the coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 is ongoing, this evaluation may inform public health administrators and medical experts to aid in curbing the pandemic's progression.


Subject(s)
Betacoronavirus/genetics , Coronavirus Infections/epidemiology , Influenza A Virus, H1N1 Subtype/genetics , Influenza A Virus, H3N2 Subtype/genetics , Influenza, Human/epidemiology , Middle East Respiratory Syndrome Coronavirus/genetics , Pneumonia, Viral/epidemiology , Severe Acute Respiratory Syndrome/epidemiology , Severe acute respiratory syndrome-related coronavirus/genetics , Animals , Betacoronavirus/pathogenicity , Birds/virology , COVID-19 , Coronavirus Infections/transmission , Coronavirus Infections/virology , Genome, Viral , Humans , Influenza A Virus, H1N1 Subtype/pathogenicity , Influenza A Virus, H3N2 Subtype/pathogenicity , Influenza in Birds/epidemiology , Influenza in Birds/transmission , Influenza in Birds/virology , Influenza, Human/transmission , Influenza, Human/virology , Middle East Respiratory Syndrome Coronavirus/pathogenicity , Pandemics , Pneumonia, Viral/transmission , Pneumonia, Viral/virology , Severe acute respiratory syndrome-related coronavirus/pathogenicity , SARS-CoV-2 , Severe Acute Respiratory Syndrome/transmission , Severe Acute Respiratory Syndrome/virology , Virulence/immunology
15.
Rev Med Virol ; 31(2): e2171, 2021 03.
Article in English | MEDLINE | ID: covidwho-777663

ABSTRACT

From 2002 to 2019, three deadly human coronaviruses (hCoVs), severe acute respiratory syndrome coronavirus (SARS-CoV), Middle Eastern respiratory syndrome coronavirus (MERS-CoV) and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) emerged to produce outbreaks of SARS, MERS and coronavirus disease 2019 (Covid-19), respectively. All three hCoVs are members of the Betacoronavirus genus in the subfamily Orthocoronavirinae and share many similarities in virology and epidemiology. However, the pattern and scale of Covid-19 global spread is similar to 2009 pandemic H1N1 influenza (H1N1pdm09), rather than SARS or MERS. Covid-19 exhibits high viral shedding in the upper respiratory tract at an early stage of infection, and has a high proportion of transmission competent individuals that are pre-symptomatic, asymptomatic and mildly symptomatic, characteristics seen in H1N1pdm09 but not in SARS or MERS. These two traits of Covid-19 and H1N1pdm09 result in reduced efficiency in identification of transmission sources by symptomatic screening and play important roles in their ability to spread unchecked to cause pandemics. To overcome these attributes of Covid-19 in community transmission, identifying the transmission source by testing for virus shedding and interrupting chains of transmission by social distancing and public masking are required.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Influenza, Human/epidemiology , Pandemics/prevention & control , Severe Acute Respiratory Syndrome/epidemiology , Severe Acute Respiratory Syndrome/transmission , Animals , COVID-19/virology , Disease Outbreaks/prevention & control , Humans , Influenza A Virus, H1N1 Subtype/pathogenicity , Influenza, Human/transmission , Influenza, Human/virology , Middle East Respiratory Syndrome Coronavirus/pathogenicity , Severe acute respiratory syndrome-related coronavirus/pathogenicity , SARS-CoV-2/pathogenicity , Severe Acute Respiratory Syndrome/virology
16.
Blood Adv ; 4(13): 2967-2978, 2020 07 14.
Article in English | MEDLINE | ID: covidwho-625455

ABSTRACT

Thrombocytopenia is a common complication of influenza virus infection, and its severity predicts the clinical outcome of critically ill patients. The underlying cause(s) remain incompletely understood. In this study, in patients with an influenza A/H1N1 virus infection, viral load and platelet count correlated inversely during the acute infection phase. We confirmed this finding in a ferret model of influenza virus infection. In these animals, platelet count decreased with the degree of virus pathogenicity varying from 0% in animals infected with the influenza A/H3N2 virus, to 22% in those with the pandemic influenza A/H1N1 virus, up to 62% in animals with a highly pathogenic A/H5N1 virus infection. This thrombocytopenia is associated with virus-containing platelets that circulate in the blood. Uptake of influenza virus particles by platelets requires binding to sialoglycans and results in the removal of sialic acids by the virus neuraminidase, a trigger for hepatic clearance of platelets. We propose the clearance of influenza virus by platelets as a paradigm. These insights clarify the pathophysiology of influenza virus infection and show how severe respiratory infections, including COVID-19, may propagate thrombocytopenia and/or thromboembolic complications.


Subject(s)
Blood Platelets/virology , Influenza A virus/pathogenicity , Influenza, Human/complications , N-Acetylneuraminic Acid/metabolism , Polysaccharides/metabolism , Thrombocytopenia/etiology , Animals , Blood Platelets/metabolism , Blood Platelets/pathology , Disease Models, Animal , Ferrets , Host-Pathogen Interactions , Humans , Influenza A Virus, H1N1 Subtype/pathogenicity , Influenza A Virus, H1N1 Subtype/physiology , Influenza A Virus, H3N2 Subtype/pathogenicity , Influenza A Virus, H3N2 Subtype/physiology , Influenza A Virus, H5N1 Subtype/pathogenicity , Influenza A Virus, H5N1 Subtype/physiology , Influenza A virus/physiology , Influenza, Human/metabolism , Influenza, Human/pathology , Influenza, Human/virology , Orthomyxoviridae Infections/complications , Orthomyxoviridae Infections/metabolism , Orthomyxoviridae Infections/pathology , Orthomyxoviridae Infections/virology , Thrombocytopenia/metabolism , Thrombocytopenia/pathology , Thrombocytopenia/virology , Virus Internalization
17.
Am J Infect Control ; 48(8): 880-882, 2020 08.
Article in English | MEDLINE | ID: covidwho-472917

ABSTRACT

BACKGROUND: The need for protective masks greatly exceeds their global supply during the current COVID-19 pandemic. METHODS: We optimized the temperature used in the dry heat pasteurization method to destroy pathogens and decontaminate masks while retaining their filtering capacity. RESULTS: The current study showed that dry heat at both 60°C and 70°C for 1 hour could successfully kill 6 species of respiratory bacteria and one fungi species, and inactivate the H1N1 indicator virus. After being heated at 70°C for 1, 2, and 3 hours, the N95 respirators and surgical face masks showed no changes in their shape and components. The filtering efficiency of bacterial aerosol for N95 respirators were 98%, 98%, and 97% after being heated for 1, 2, and 3 hour, respectively, all of which were over the 95% efficiency required and similar to the value before being heated (99%). The filtering efficiency for surgical face masks was 97%, 97%, and 96% for 1, 2, and 3 hours of heating, respectively, all of which were also similar to the value before being heated (97%). CONCLUSIONS: This method can be used at home and can significantly resolve the current shortage of masks.


Subject(s)
Decontamination/methods , Masks/virology , Pasteurization/methods , Respiratory Protective Devices/virology , Betacoronavirus/pathogenicity , COVID-19 , Coronavirus Infections/prevention & control , Coronavirus Infections/virology , Hot Temperature , Humans , Influenza A Virus, H1N1 Subtype/pathogenicity , Occupational Exposure/prevention & control , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Pneumonia, Viral/virology , SARS-CoV-2 , Ventilators, Mechanical/virology
19.
Anesth Analg ; 131(2): 345-350, 2020 08.
Article in English | MEDLINE | ID: covidwho-196118

ABSTRACT

This review highlights the ultrasound findings reported from a number of studies and case reports and discusses the unifying findings from coronavirus disease (COVID-19) patients and from the avian (H7N9) and H1N1 influenza epidemics. We discuss the potential role for portable point-of-care ultrasound (PPOCUS) as a safe and effective bedside option in the initial evaluation, management, and monitoring of disease progression in patients with confirmed or suspected COVID-19 infection.


Subject(s)
Betacoronavirus/pathogenicity , Coronavirus Infections/diagnostic imaging , Lung/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Point-of-Care Systems , Point-of-Care Testing , Ultrasonography , Adult , Aged , Aged, 80 and over , COVID-19 , Coronavirus Infections/therapy , Coronavirus Infections/transmission , Coronavirus Infections/virology , Female , Humans , Infection Control , Infectious Disease Transmission, Patient-to-Professional/prevention & control , Influenza A Virus, H1N1 Subtype/pathogenicity , Influenza A Virus, H7N9 Subtype/pathogenicity , Influenza, Human/diagnostic imaging , Influenza, Human/virology , Lung/virology , Male , Middle Aged , Occupational Exposure/adverse effects , Occupational Exposure/prevention & control , Pandemics , Pneumonia, Viral/therapy , Pneumonia, Viral/transmission , Pneumonia, Viral/virology , Predictive Value of Tests , Prognosis , Risk Factors , SARS-CoV-2 , Ultrasonography/adverse effects
20.
Clin Ther ; 42(5): 736-740, 2020 05.
Article in English | MEDLINE | ID: covidwho-47131

ABSTRACT

The severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV2) pandemic that has engulfed the globe has had incredible effects on health care systems and economic activity. Social distancing and school closures have played a central role in public health efforts to counter the coronavirus disease 2019 (COVID)-19 pandemic. The most recent global pandemic prior to COVID-19 was the 2009 pandemic, hemagglutinin type 1 and neuraminidase type 1 (H1N1) influenza. The course of events in 2009 offer some rich lessons that could be applied to the current COVID-19 pandemic. This commentary highlights some of the most relevant points and a discussion of possible outcomes of the COVID-19 pandemic.


Subject(s)
Betacoronavirus/pathogenicity , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Influenza A Virus, H1N1 Subtype/pathogenicity , Influenza, Human/epidemiology , Influenza, Human/transmission , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Quarantine/statistics & numerical data , Analysis of Variance , COVID-19 , Coronavirus Infections/physiopathology , Disaster Planning/organization & administration , Humans , Influenza, Human/physiopathology , Pandemics , Pneumonia, Viral/physiopathology , SARS-CoV-2 , Time Factors
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