Characteristics of SARS-CoV-2 and COVID-19

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible and pathogenic coronavirus that emerged in late 2019 and has caused a pandemic of acute respiratory disease, named ‘coronavirus disease 2019’ (COVID-19), which threatens human health and public safety. In this Review, we describe the basic virology of SARS-CoV-2, including genomic characteristics and receptor use, highlighting its key difference from previously known coronaviruses. We summarize current knowledge of clinical, epidemiological and pathological features of COVID-19, as well as recent progress in animal models and antiviral treatment approaches for SARS-CoV-2 infection. We also discuss the potential wildlife hosts and zoonotic origin of this emerging virus in detail.

Introduction

Coronaviruses are a diverse group of viruses infecting many different animals, and they can cause mild to severe respiratory infections in humans. In 2002 and 2012, respectively, two highly pathogenic coronaviruses with zoonotic origin, severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV), emerged in humans and caused fatal respiratory illness, making emerging coronaviruses a new public health concern in the twenty-first century1. At the end of 2019, a novel coronavirus designated as SARS-CoV-2 emerged in the city of Wuhan, China, and caused an outbreak of unusual viral pneumonia. Being highly transmissible, this novel coronavirus disease, also known as coronavirus disease 2019 (COVID-19), has spread fast all over the world2,3. It has overwhelmingly surpassed SARS and MERS in terms of both the number of infected people and the spatial range of epidemic areas. The ongoing outbreak of COVID-19 has posed an extraordinary threat to global public health4,5. In this Review, we summarize the current understanding of the nature of SARS-CoV-2 and COVID-19. On the basis of recently published findings, this comprehensive Review covers the basic biology of SARS-CoV-2, including the genetic characteristics, the potential zoonotic origin and its receptor binding. Furthermore, we will discuss the clinical and epidemiological features, diagnosis of and countermeasures against COVID-19.

Emergence and spread

In late December 2019, several health facilities in Wuhan, in Hubei province in China, reported clusters of patients with pneumonia of unknown cause6. Similarly to patients with SARS and MERS, these patients showed symptoms of viral pneumonia, including fever, cough and chest discomfort, and in severe cases dyspnea and bilateral lung infiltration6,7. Among the first 27 documented hospitalized patients, most cases were epidemiologically linked to Huanan Seafood Wholesale Market, a wet market located in downtown Wuhan, which sells not only seafood but also live animals, including poultry and wildlife4,8. According to a retrospective study, the onset of the first known case dates back to 8 December 2019 (ref.9). On 31 December, Wuhan Municipal Health Commission notified the public of a pneumonia outbreak of unidentified cause and informed the World Health Organization (WHO)9 (Fig. 1).

figure1
Fig. 1: Timeline of the key events of the COVID-19 outbreak.

By metagenomic RNA sequencing and virus isolation from bronchoalveolar lavage fluid samples from patients with severe pneumonia, independent teams of Chinese scientists identified that the causative agent of this emerging disease is a betacoronavirus that had never been seen before6,10,11. On 9 January 2020, the result of this etiological identification was publicly announced (Fig. 1). The first genome sequence of the novel coronavirus was published on the Virological website on 10 January, and more nearly complete genome sequences determined by different research institutes were then released via the GISAID database on 12 January7. Later, more patients with no history of exposure to Huanan Seafood Wholesale Market were identified. Several familial clusters of infection were reported, and nosocomial infection also occurred in health-care facilities. All these cases provided clear evidence for human-to-human transmission of the new virus4,12,13,14. As the outbreak coincided with the approach of the lunar New Year, travel between cities before the festival facilitated virus transmission in China. This novel coronavirus pneumonia soon spread to other cities in Hubei province and to other parts of China. Within 1 month, it had spread massively to all 34 provinces of China. The number of confirmed cases suddenly increased, with thousands of new cases diagnosed daily during late January15. On 30 January, the WHO declared the novel coronavirus outbreak a public health emergency of international concern16. On 11 February, the International Committee on Taxonomy of Viruses named the novel coronavirus ‘SARS-CoV-2’, and the WHO named the disease ‘COVID-19’ (ref.17).

The outbreak of COVID-19 in China reached an epidemic peak in February. According to the National Health Commission of China, the total number of cases continued to rise sharply in early February at an average rate of more than 3,000 newly confirmed cases per day. To control COVID-19, China implemented unprecedentedly strict public health measures. The city of Wuhan was shut down on 23 January, and all travel and transportation connecting the city was blocked. In the following couple of weeks, all outdoor activities and gatherings were restricted, and public facilities were closed in most cities as well as in countryside18. Owing to these measures, the daily number of new cases in China started to decrease steadily19.

However, despite the declining trend in China, the international spread of COVID-19 accelerated from late February. Large clusters of infection have been reported from an increasing number of countries18. The high transmission efficiency of SARS-CoV-2 and the abundance of international travel enabled rapid worldwide spread of COVID-19. On 11 March 2020, the WHO officially characterized the global COVID-19 outbreak as a pandemic20. Since March, while COVID-19 in China has become effectively controlled, the case numbers in Europe, the USA and other regions have jumped sharply. According to the COVID-19 dashboard of the Center for System Science and Engineering at Johns Hopkins University, as of 11 August 2020, 216 countries and regions from all six continents had reported more than 20 million cases of COVID-19, and more than 733,000 patients had died21. High mortality occurred especially when health-care resources were overwhelmed. The USA is the country with the largest number of cases so far.

Although genetic evidence suggests that SARS-CoV-2 is a natural virus that likely originated in animals, there is no conclusion yet about when and where the virus first entered humans. As some of the first reported cases in Wuhan had no epidemiological link to the seafood market22, it has been suggested that the market may not be the initial source of human infection with SARS-CoV-2. One study from France detected SARS-CoV-2 by PCR in a stored sample from a patient who had pneumonia at the end of 2019, suggesting SARS-CoV-2 might have spread there much earlier than the generally known starting time of the outbreak in France23. However, this individual early report cannot give a solid answer to the origin of SARS-CoV-2 and contamination, and thus a false positive result cannot be excluded. To address this highly controversial issue, further retrospective investigations involving a larger number of banked samples from patients, animals and environments need to be conducted worldwide with well-validated assays.

For More Information: https://www.nature.com/articles/s41579-020-00459-7

C-Reactive Protein Level May Predict the Risk of COVID-19 Aggravation

Authors: Guyi Wang 1Chenfang Wu 1Quan Zhang 2Fang Wu 3Bo Yu 1Jianlei Lv 2Yiming Li 4Tiao Li 5Siye Zhang 1Chao Wu 6 7 8Guobao Wu 1Yanjun Zhong 1Affiliations expand

Abstract

Background: Clinical findings indicated that a fraction of coronavirus disease 2019 (COVID-19) patients diagnosed as mild early may progress to severe cases. However, it is difficult to distinguish these patients in the early stage. The present study aimed to describe the clinical characteristics of these patients, analyze related factors, and explore predictive markers of the disease aggravation.

Methods: Clinical and laboratory data of nonsevere adult COVID-19 patients in Changsha, China, were collected and analyzed on admission. A logistic regression model was adopted to analyze the association between the disease aggravation and related factors. The receiver operating characteristic curve (ROC) was utilized to analyze the prognostic ability of C-reactive protein (CRP).

Results: About 7.7% (16/209) of nonsevere adult COVID-19 patients progressed to severe cases after admission. Compared with nonsevere patients, the aggravated patients had much higher levels of CRP (median [range], 43.8 [12.3-101.9] mg/L vs 12.1 [0.1-91.4] mg/L; P = .000). A regression analysis showed that CRP was significantly associated with aggravation of nonsevere COVID-19 patients, with an area under the curve of 0.844 (95% confidence interval, 0.761-0.926) and an optimal threshold value of 26.9 mg/L.

Conclusions: CRP could be a valuable marker to anticipate the possibility of aggravation of non-severe adult COVID-19 patients, with an optimal threshold value of 26.9 mg/L.

For More Information: https://pubmed.ncbi.nlm.nih.gov/32455147/

Elevated level of C‐reactive protein may be an early marker to predict risk for severity of COVID‐19

Authors: Nurshad Ali 1

The outbreak of coronavirus disease‐2019 (COVID‐19) is an emerging global health threat. The healthcare workers are facing challenges in reducing the severity and mortality of COVID‐19 across the world. Severe patients with COVID‐19 are generally treated in the intensive care unit, while mild or non‐severe patients treated in the usual isolation ward of the hospital. However, there is an emerging challenge that a small subset of mild or non‐severe COVID‐19 patients develops into a severe disease course. Therefore, it is important to early identify and give the treatment of this subset of patients to reduce the disease severity and improve the outcomes of COVID‐19. Clinical studies demonstrated that altered levels of some blood markers might be linked with the degree of severity and mortality of patients with COVID‐19. 1 Of these clinical parameter, serum C‐reactive protein (CRP) has been found as an important marker that changes significantly in severe patients with COVID‐19. 3 CRP is a type of protein produced by the liver that serves as an early marker of infection and inflammation. 6 In blood, the normal concentration of CRP is less than 10 mg/L; however, it rises rapidly within 6 to 8 hours and gives the highest peak in 48 hours from the disease onset. 7 Its half‐life is about 19 hours 8 and its concentration decreases when the inflammatory stages end and the patient is healing. CRP preferably binds to phosphocholine expressed highly on the surface of damaged cells. 9 This binding makes active the classical complement pathway of the immune system and modulates the phagocytic activity to clear microbes and damaged cells from the organism. 7 When the inflammation or tissue damage is resolved, CRP concentration falls, making it a useful marker for monitoring disease severity. 7

The available studies that have determined serum concentration of CRP in patients with COVID‐19 are presented in Table 1. A significant increase of CRP was found with levels on average 20 to 50 mg/L in patients with COVID‐19. 10 12 21 Elevated levels of CRP were observed up to 86% in severe COVID‐19 patients. 10 11 13 Patients with severe disease courses had a far elevated level of CRP than mild or non‐severe patients. For example, a study reported that patients with more severe symptoms had on average CRP concentration of 39.4 mg/L and patients with mild symptoms CRP concentration of 18.8 mg/L. 12 CRP was found at increased levels in the severe group at the initial stage than those in the mild group. 1 In another study, the mean concentration of CRP was significantly higher in severe patients (46 mg/L) than non‐severe patients (23 mg/L). 21 The patients who died from COVID‐19 had about 10 fold higher levels of CRP than the recovered patients (median 100 vs 9.6 mg/L). 16 A recent study showed that about 7.7% of non‐severe COVID‐19 patients were progressed to severe disease courses after hospitalization, 3 and compared to non‐severe cases, the aggravated patients had significantly higher concentrations of CRP (median 43.8 vs 12.1 mg/L). A significant association was observed between CRP concentrations and the aggravation of non‐severe patients with COVID‐19 [1], and the authors proposed CRP as a suitable marker for anticipating the aggravation probability of non‐severe COVID‐19 patients, with an optimal threshold value of 26.9 mg/L. 3 The authors also noted that the risk of developing severe events is increased by 5% for every one‐unit increase in CRP concentration in patients with COVID‐19.

For More Information: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7301027/

The role of C-reactive protein as a prognostic marker in COVID-19

Authors: Dominic Stringer,1Philip Braude,2Phyo K Myint,3Louis Evans,4Jemima T Collins,5Alessia Verduri,6Terry J Quinn,7Arturo Vilches-Moraga,8Michael J Stechman,9Lyndsay Pearce,10Susan Moug,11Kathryn McCarthy,12Jonathan Hewitt,13 and Ben Carter1

Abstract

Background

C-reactive protein (CRP) is a non-specific acute phase reactant elevated in infection or inflammation. Higher levels indicate more severe infection and have been used as an indicator of COVID-19 disease severity. However, the evidence for CRP as a prognostic marker is yet to be determined. The aim of this study is to examine the CRP response in patients hospitalized with COVID-19 and to determine the utility of CRP on admission for predicting inpatient mortality.

Methods

Data were collected between 27 February and 10 June 2020, incorporating two cohorts: the COPE (COVID-19 in Older People) study of 1564 adult patients with a diagnosis of COVID-19 admitted to 11 hospital sites (test cohort) and a later validation cohort of 271 patients. Admission CRP was investigated, and finite mixture models were fit to assess the likely underlying distribution. Further, different prognostic thresholds of CRP were analyzed in a time-to-mortality Cox regression to determine a cut-off. Bootstrapping was used to compare model performance [Harrell’s C statistic and Akaike information criterion (AIC)].

Results

The test and validation cohort distribution of CRP was not affected by age, and mixture models indicated a bimodal distribution. A threshold cut-off of CRP ≥40 mg/L performed well to predict mortality (and performed similarly to treating CRP as a linear variable).

Conclusions

The distributional characteristics of CRP indicated an optimal cut-off of ≥40 mg/L was associated with mortality. This threshold may assist clinicians in using CRP as an early trigger for enhanced observation, treatment decisions and advanced care planning.

For More Information: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7989395/

Can we predict the severe course of COVID-19 – a systematic review and meta-analysis of indicators of clinical outcome?

  1. Authors: Stephan Katzenschlager ,Alexandra J. Zimmer ,Claudius Gottschalk, Jürgen Grafeneder,Stephani Schmitz, Sara Kraker, Marlene Ganslmeier, Amelie Muth, Alexander Seitel, Lena Maier-Hein, Andrea Benedetti, Jan Larmann, Markus A. Weigand, Sean McGrath , Claudia M. Denkinger  

Abstract

Background

COVID-19 has been reported in over 40million people globally with variable clinical outcomes. In this systematic review and meta-analysis, we assessed demographic, laboratory and clinical indicators as predictors for severe courses of COVID-19.

Methods

This systematic review was registered at PROSPERO under CRD42020177154. We systematically searched multiple databases (PubMed, Web of Science Core Collection, MedRvix and bioRvix) for publications from December 2019 to May 31st 2020. Random-effects meta-analyses were used to calculate pooled odds ratios and differences of medians between (1) patients admitted to ICU versus non-ICU patients and (2) patients who died versus those who survived. We adapted an existing Cochrane risk-of-bias assessment tool for outcome studies.

Results

Of 6,702 unique citations, we included 88 articles with 69,762 patients. There was concern for bias across all articles included. Age was strongly associated with mortality with a difference of medians (DoM) of 13.15 years (95% confidence interval (CI) 11.37 to 14.94) between those who died and those who survived. We found a clinically relevant difference between non-survivors and survivors for C-reactive protein (CRP; DoM 69.10 mg/L, CI 50.43 to 87.77), lactate dehydrogenase (LDH; DoM 189.49 U/L, CI 155.00 to 223.98), cardiac troponin I (cTnI; DoM 21.88 pg/mL, CI 9.78 to 33.99) and D-Dimer (DoM 1.29mg/L, CI 0.9 to 1.69). Furthermore, cerebrovascular disease was the co-morbidity most strongly associated with mortality (Odds Ratio 3.45, CI 2.42 to 4.91) and ICU admission (Odds Ratio 5.88, CI 2.35 to 14.73).

For More Information: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0255154