Free Standard AU & NZ Shipping For All Book Orders Over $80!
Register      Login
Microbiology Australia Microbiology Australia Society
Microbiology Australia, bringing Microbiologists together
RESEARCH ARTICLE

The SARS-CoV-2 ‘perfect storm’: from humble betacoronavirus to global pandemic

Annaleise R Howard-Jones A D and Jen Kok B C
+ Author Affiliations
- Author Affiliations

A Department of Infectious Diseases and Microbiology, The Children’s Hospital at Westmead, Westmead, NSW, Australia

B Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health, Pathology–Institute of Clinical Pathology and Medical Research, Westmead Hospital, Westmead, NSW, Australia

C Marie Bashir Institute for Infectious Diseases and Biosecurity, University of Sydney, Westmead Hospital, Westmead, NSW, Australia

D Tel.: +61 2 9845 0000 Email: annaleise.howard-jones@health.nsw.gov.au

Microbiology Australia 41(3) 150-156 https://doi.org/10.1071/MA20040
Published: 18 August 2020

Abstract

The novel betacoronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a global pandemic unprecedented in modern times. Understanding the key features that have enabled this virus to propagate so widely in the global community is critical to current and future clinical and public health efforts. High proportions of mild disease and peak viral loads at, and likely prior to, symptom onset have hindered efforts to identify and isolate infected persons effectively, facilitating undetected spread of the virus. In countries with limited diagnostic and/or contact tracing capabilities, population-wide transmission escalated beyond a critical threshold, challenging even well-developed healthcare systems. This ‘perfect storm’ for transmissibility has led to widespread outbreaks and deaths in many regions around the world. Extensive testing and contact tracing, together with Australia’s geographic advantage, tightening of international travel restrictions, physical distancing and public health messaging measures, have contributed to limiting the extent of coronavirus disease 2019 (COVID-19) spread in the country, but recent case escalation in Victoria highlights the country’s vulnerability to future outbreaks due to low population immunity.


References

[1]  Levi, M. et al. (2020) Coagulation abnormalities and thrombosis in patients with COVID-19. Lancet Haematol. 7, e438–e440.
Coagulation abnormalities and thrombosis in patients with COVID-19.Crossref | GoogleScholarGoogle Scholar | 32407672PubMed |

[2]  Viner, R.M. and Whittaker, E. (2020) Kawasaki-like disease: emerging complication during the COVID-19 pandemic. Lancet 395, 1741–1743.
Kawasaki-like disease: emerging complication during the COVID-19 pandemic.Crossref | GoogleScholarGoogle Scholar | 32410759PubMed |

[3]  Verdoni, L. et al. (2020) An outbreak of severe Kawasaki-like disease at the Italian epicentre of the SARS-CoV-2 epidemic: an observational cohort study. Lancet 395, 1771–1778.
An outbreak of severe Kawasaki-like disease at the Italian epicentre of the SARS-CoV-2 epidemic: an observational cohort study.Crossref | GoogleScholarGoogle Scholar | 32410760PubMed |

[4]  Toubiana, J. et al. (2020) Kawasaki-like multisystem inflammatory syndrome in children during the covid-19 pandemic in Paris, France: prospective observational study. BMJ 369, m2094.
Kawasaki-like multisystem inflammatory syndrome in children during the covid-19 pandemic in Paris, France: prospective observational study.Crossref | GoogleScholarGoogle Scholar | 32493739PubMed |

[5]  Satarker, S. and Nampoothiri, M. (2020) Structural proteins in Severe Acute Respiratory Syndrome Coronavirus-2. Arch. Med. Res. , .
Structural proteins in Severe Acute Respiratory Syndrome Coronavirus-2.Crossref | GoogleScholarGoogle Scholar | 32493627PubMed |

[6]  Lu, R. et al. (2020) Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet 395, 565–574.
Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding.Crossref | GoogleScholarGoogle Scholar | 32007145PubMed |

[7]  Hayward, A.C. et al. (2014) Comparative community burden and severity of seasonal and pandemic influenza: results of the Flu Watch cohort study. Lancet Respir. Med. 2, 445–454.
Comparative community burden and severity of seasonal and pandemic influenza: results of the Flu Watch cohort study.Crossref | GoogleScholarGoogle Scholar | 24717637PubMed |

[8]  WHO (2003) Cumulative number of reported probable cases of SARS. https://www.who.int/csr/sars/country/2003_07_11/en/ (accessed 14 June 2020).

[9]  WHO (2019) MERS-CoV global summary and assessment of risk – November 2019. http://applications.emro.who.int/docs/EMRPUB-CSR-241-2019-EN.pdf?ua=1&ua=1&ua=1 (accessed 14 June 2020).

[10]  Johns Hopkins University (2020) Johns Hopkins University: Coronavirus Resource Center. https://coronavirus.jhu.edu/ (accessed 29 July 2020).

[11]  WHO (2003) Consensus document on the epidemiology of severe acute respiratory syndrome (SARS). https://www.who.int/csr/sars/WHOconsensus.pdf?ua=1 (accessed 14 June 2020).

[12]  Yang, S. et al. (2020) Early estimation of the case fatality rate of COVID-19 in mainland China: a data-driven analysis. Ann. Transl. Med. 8, 128.
Early estimation of the case fatality rate of COVID-19 in mainland China: a data-driven analysis.Crossref | GoogleScholarGoogle Scholar | 32175421PubMed |

[13]  Fu, L. et al. (2020) Clinical characteristics of coronavirus disease 2019 (COVID-19) in China: a systematic review and meta-analysis. J. Infect. 80, 656–665.
Clinical characteristics of coronavirus disease 2019 (COVID-19) in China: a systematic review and meta-analysis.Crossref | GoogleScholarGoogle Scholar | 32283155PubMed |

[14]  Park, M. et al. (2020) COVID-19: lessons from SARS and MERS. Eur. J. Immunol. 50, 308–311.
COVID-19: lessons from SARS and MERS.Crossref | GoogleScholarGoogle Scholar | 32779732PubMed |

[15]  Cauchemez, S. et al. (2014) Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility. Lancet Infect. Dis. 14, 50–56.
Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility.Crossref | GoogleScholarGoogle Scholar | 24239323PubMed |

[16]  Chan, J.F. et al. (2015) Middle East respiratory syndrome coronavirus: another zoonotic betacoronavirus causing SARS-like disease. Clin. Microbiol. Rev. 28, 465–522.
Middle East respiratory syndrome coronavirus: another zoonotic betacoronavirus causing SARS-like disease.Crossref | GoogleScholarGoogle Scholar | 25810418PubMed |

[17]  Poletto, C. et al. (2014) Assessment of the Middle East respiratory syndrome coronavirus (MERS-CoV) epidemic in the Middle East and risk of international spread using a novel maximum likelihood analysis approach. Euro Surveill. 19, 20824.
Assessment of the Middle East respiratory syndrome coronavirus (MERS-CoV) epidemic in the Middle East and risk of international spread using a novel maximum likelihood analysis approach.Crossref | GoogleScholarGoogle Scholar | 24957746PubMed |

[18]  Li, Q. et al. (2020) Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N. Engl. J. Med. 382, 1199–1207.
Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia.Crossref | GoogleScholarGoogle Scholar | 31995857PubMed |

[19]  Wilson-Clark, S.D. et al. (2006) Household transmission of SARS, 2003. CMAJ 175, 1219–1223.
Household transmission of SARS, 2003.Crossref | GoogleScholarGoogle Scholar | 17098951PubMed |

[20]  Lau, J.T. et al. (2004) Probable secondary infections in households of SARS patients in Hong Kong. Emerg. Infect. Dis. 10, 236–243.
Probable secondary infections in households of SARS patients in Hong Kong.Crossref | GoogleScholarGoogle Scholar |

[21]  Goh, D.L. et al. (2004) Secondary household transmission of SARS, Singapore. Emerg. Infect. Dis. 10, 232–234.
Secondary household transmission of SARS, Singapore.Crossref | GoogleScholarGoogle Scholar | 15030688PubMed |

[22]  Drosten, C. et al. (2014) Transmission of MERS-coronavirus in household contacts. N. Engl. J. Med. 371, 828–835.
Transmission of MERS-coronavirus in household contacts.Crossref | GoogleScholarGoogle Scholar | 25162889PubMed |

[23]  Jing, Q.L. et al.. (2020) Household secondary attack rate of COVID-19 and associated determinants in Guangzhou, China: a retrospective cohort study. Lancet Infect. Dis. , .
Household secondary attack rate of COVID-19 and associated determinants in Guangzhou, China: a retrospective cohort study.Crossref | GoogleScholarGoogle Scholar | 32562601PubMed |

[24]  Kim, K.H. et al. (2017) Middle East respiratory syndrome coronavirus (MERS-CoV) outbreak in South Korea, 2015: epidemiology, characteristics and public health implications. J. Hosp. Infect. 95, 207–213.
Middle East respiratory syndrome coronavirus (MERS-CoV) outbreak in South Korea, 2015: epidemiology, characteristics and public health implications.Crossref | GoogleScholarGoogle Scholar | 28153558PubMed |

[25]  Assiri, A. et al. (2013) Hospital outbreak of Middle East respiratory syndrome coronavirus. N. Engl. J. Med. 369, 407–416.
Hospital outbreak of Middle East respiratory syndrome coronavirus.Crossref | GoogleScholarGoogle Scholar | 23782161PubMed |

[26]  Al-Abdely, H.M. et al. (2019) Middle East respiratory syndrome coronavirus infection dynamics and antibody responses among clinically diverse patients, Saudi Arabia. Emerg. Infect. Dis. 25, 753–766.
Middle East respiratory syndrome coronavirus infection dynamics and antibody responses among clinically diverse patients, Saudi Arabia.Crossref | GoogleScholarGoogle Scholar | 30882305PubMed |

[27]  Onder, G. et al. (2020) Case-fatality rate and characteristics of patients dying in relation to COVID-19 in Italy. JAMA 323, 1775–1776.
Case-fatality rate and characteristics of patients dying in relation to COVID-19 in Italy.Crossref | GoogleScholarGoogle Scholar |

[28]  Wu, Z. and McGoogan, J.M. (2020) Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. JAMA , .
Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention.Crossref | GoogleScholarGoogle Scholar | 32091533PubMed |

[29]  He, X. et al. (2020) Temporal dynamics in viral shedding and transmissibility of COVID-19. Nat. Med. 26, 672–675.
Temporal dynamics in viral shedding and transmissibility of COVID-19.Crossref | GoogleScholarGoogle Scholar | 32296168PubMed |

[30]  Wölfel, R. et al. (2020) Virological assessment of hospitalized patients with COVID-2019. Nature 58, 465–469.
Virological assessment of hospitalized patients with COVID-2019.Crossref | GoogleScholarGoogle Scholar |

[31]  Arons, M.M. et al. (2020) Presymptomatic SARS-CoV-2 Infections and transmission in a skilled nursing facility. N. Engl. J. Med. 382, 2081–2090.
Presymptomatic SARS-CoV-2 Infections and transmission in a skilled nursing facility.Crossref | GoogleScholarGoogle Scholar | 32329971PubMed |