MMSL 2021, 90(3):146-153 | DOI: 10.31482/mmsl.2021.016

THE ROLE OF EPIDEMIC MODELLING IN POLICYMAKING AND THE CASES OF SARS AND COVID-19Review article

Chiara Artico1, Vanda Bostik ORCID...2*
1 International Master’s in Security, Intelligence and Strategic Studies (IMSISS), University of Glasgow (UK)
2 Department of Epidemiology, Faculty of Military Health Sciences, University of Defence, Hradec Kralove, Czech Republic

Over the past two decades, the world has witnessed the onset of three different coronaviruses: severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV) and the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Each of these has resulted in features that have made it in some ways stronger than the previous one. Predictive epidemic models are widely recognised as one of the most reliable and valuable tools to help policymakers take decisions regarding the management of sanitary crises and have been helping governments by calculating potential consequences and benefits of related containment measures. A comparison of epidemic models that were elaborated on SARS-CoV, which caused severe acute respiratory syndrome (SARS), and on SARS-CoV-2, which is currently causing coronavirus disease 2019 (COVID-19) will lead to an overview of the potential reasons why the current one has led the world into an ongoing pandemic, while the other two remained relatively delimited.

Keywords: coronaviruses; SARS-CoV-2; predictive epidemic modelling; pandemic; WHO; lockdowns; vaccination

Received: February 21, 2021; Revised: April 19, 2021; Accepted: April 19, 2021; Prepublished online: April 22, 2021; Published: September 3, 2021  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Artico, C., & Bostik, V. (2021). THE ROLE OF EPIDEMIC MODELLING IN POLICYMAKING AND THE CASES OF SARS AND COVID-19. MMSL, 90(3), 146-153. doi: 10.31482/mmsl.2021.016
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. World Health Organization (WHO) Ebola virus disease [Internet]. Who.int 2021 [cited 15 February 2021]. Available from: https://www.who.int/news-room/fact-sheets/detail/ebola-virus-disease.
    2. World Health Organization (WHO) Zika virus disease [Internet]. Who.int 2021 [cited 15 February 2021]. Available from: https://www.who.int/health-topics/zika-virus-disease#tab=tab_1.
    3. LePan N, Routley N, Schell H. [Internet]. Visualising the History of Pandemics. 2021 [cited 31 January 2021]. Available from: https://www.visualcapitalist.com/history-of-pandemics-deadliest/.
    4. Maxmen A. [Internet]. Why did the world's pandemic warning system fail when COVID hit? 2021 [cited 31 January 2021]. Available from: https://www.nature.com/articles/d41586-021-00162-4.
    5. Poletto C, Scarpino S, Volz E. Applications of predictive modelling early in the COVID-19 epidemic. The Lancet Digital Health. 2020;2(10):e498-e499. Go to original source... Go to PubMed...
    6. Desai A, Kraemer M, Bhatia S, et al. Real-time Epidemic Forecasting: Challenges and Opportunities. Health Security. 2019;17(4):268-275. Go to original source... Go to PubMed...
    7. Li M. Y. An Introduction to Mathematical Modeling of Infectious. Cham: Springer International Publishing; 2018. Go to original source...
    8. Xue L, Jing S, Miller J, et al. A data-driven network model for the emerging COVID-19 epidemics in Wuhan, Toronto and Italy. Mathematical Biosciences. 2020; 26:108391. Go to original source... Go to PubMed...
    9. Becker N. The Uses of Epidemic Models. Biometrics. 1979; 35(1). Go to original source...
    10. Baudoin F. Stochastic Processes. In: Peterson P, Baker E, McGaw B, ed. by. International Encyclopedia of Education [Internet]. 3rd ed. Elsevier; 2010 [cited 31 January 2021]. 451-452. Available from: https://doi.org/10.1016/B978-0-08-044894-7.01369-5. Go to original source...
    11. Andersson H, Britton T. Stochastic Epidemic Models and Their Statistical Analysis. New York: Springer; 2000. Go to original source...
    12. Lipsitch M. Transmission Dynamics and Control of Severe Acute Respiratory Syndrome. Science. 2003;300(5627):1966-1970. Go to original source... Go to PubMed...
    13. Petersen E, Koopmans M, Go U, et al. Comparing SARS-CoV-2 with SARS-CoV and influenza pandemics. The Lancet Infectious Diseases. 2020;20(9):e238-e244. Go to original source... Go to PubMed...
    14. Rothman K, Greenland S, Lash T. Modern epidemiology. 3rd ed. Philadelphia: Lippincott Williams & Wilkins; 2013.
    15. Giordano G, Blanchini F, Bruno R, et al. Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy. Nature Medicine. 2020;26(6):855-860. Go to original source... Go to PubMed...
    16. Home - Johns Hopkins Coronavirus Resource Center [Internet]. Johns Hopkins Coronavirus Resource Center. 2021 [cited 31 January 2021]. Available from: https://coronavirus.jhu.edu/.
    17. Asrani P, Hasan G, Sohal S, et al. Molecular Basis of Pathogenesis of Coronaviruses: A Comparative Genomics Approach to Planetary Health to Prevent Zoonotic Outbreaks in the 21st Century. OMICS: A Journal of Integrative Biology. 2020;24(11):634-644. Go to original source... Go to PubMed...
    18. Shi Z, Hu Z. A review of studies on animal reservoirs of the SARS coronavirus. Virus Research. 2008;133(1):74-87. Go to original source... Go to PubMed...
    19. Zheng B, Guan Y, Wong K, et al. SARS-related Virus Predating SARS Outbreak, Hong Kong. Emerging Infectious Diseases. 2004;10(2):176-178. Go to original source... Go to PubMed...
    20. Paden C, Yusof M, Al Hammadi Z, et al. Zoonotic origin and transmission of Middle East respiratory syndrome coronavirus in the UAE. Zoonoses and Public Health. 2017;65(3):322-333. Go to original source... Go to PubMed...
    21. Alshukairi A, Zheng J, Zhao J, et al. High Prevalence of MERS-CoV Infection in Camel Workers in Saudi Arabia. mBio. 2018;9(5):e01985-01918. Go to original source... Go to PubMed...
    22. Chan J, Kok K, Zhu Z, et al. Genomic characterisation of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan. Emerging Microbes & Infections. 2020;9(1):221-236. Go to original source... Go to PubMed...
    23. Jin YH, Cai L, Cheng ZS, et al. A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version). Military Medical Research. 2020; 7(1).
    24. Jewers C. China denies entry to team of WHO experts due to investigate the origins of Covid-19 pandemic amid growing suspicions of a cover-up [Internet]. DailyMail.co.uk. 2021 [cited 31 January 2021]. Available from: https://www.dailymail.co.uk/news/article-9116715/China-denies-entry-team-experts-investigate-origins-Covid-19.html.
    25. Kaur N, Singh R, Dar Z, et al. Genetic comparison among various coronavirus strains for the identification of potential vaccine targets of SARS-CoV2. Infection, Genetics and Evolution. 2020;89:104490. Go to original source... Go to PubMed...
    26. Hamming I, Timens W, Bulthuis M, et al. Tissue distribution of ACE2 protein, the functional receptor for SARS coronavirus. A first step in understanding SARS pathogenesis. The Journal of Pathology. 2004;203(2):631-637. Go to original source... Go to PubMed...
    27. Chowell G, Castillo-Chavez C, Fenimore P, et al. Model Parameters and Outbreak Control for SARS. Emerging Infectious Diseases. 2004;10(7):1258-1263. Go to original source... Go to PubMed...
    28. Breban R, Riou J, Fontanet A. Interhuman transmissibility of Middle East respiratory syndrome coronavirus: estimation of pandemic risk. The Lancet. 2013;382(9893):694-699. Go to original source... Go to PubMed...
    29. COVID-19 - a global pandemic. What do we know about SARS-CoV-2 and COVID-19? [Internet]. Who.int. 2020 [cited 21 February 2021]. Available from: https://www.who.int/docs/default-source/coronaviruse/risk-comms-updates/update-28-covid-19-what-we-know-may-2020.pdf?sfvrsn=ed6e286c_2.
    30. Billah M, Miah M, Khan M. Reproductive number of coronavirus: A systematic review and meta-analysis based on global level evidence. PLOS ONE. 2020;15(11):e0242128. Go to original source... Go to PubMed...
    31. Katul G, Mrad A, Bonetti S, et al. Global convergence of COVID-19 basic reproduction number and estimation from early-time SIR dynamics. PLOS ONE. 2020;15(9):e0239800. Go to original source... Go to PubMed...
    32. Smith M. What is viral shedding? [Internet]. WebMD. 2020 [cited 31 January 2021]. Available from: https://www.webmd.com/lung/qa/what-is-viral-shedding.
    33. Cevik M, Tate M, Lloyd O, et al. SARS-CoV-2, SARS-CoV, and MERS-CoV viral load dynamics, duration of viral shedding, and infectiousness: a systematic review and meta-analysis. The Lancet Microbe. 2020;2(1):e13-e22. Go to original source...
    34. Cheng P, Wong D, Tong L, et al. Viral shedding patterns of coronavirus in patients with probable severe acute respiratory syndrome. The Lancet. 2004;363(9422):1699-1700. Go to original source... Go to PubMed...
    35. Knight G, Dharan N, Fox G, et al. Bridging the gap between evidence and policy for infectious diseases: How models can aid public health decision-making. International Journal of Infectious Diseases. 2016;42:17-23. Go to original source... Go to PubMed...

    Return to the content