Evaluation of the epidemiological pattern of COVID-19 applying basic reproduction number: An educational review article

authors:

avatar Majid Mirmohammadkhani ORCID , avatar Fatemeh Paknazar ORCID , * , avatar Ali Rashidy-Pour

Koomesh: Vol.22, issue 3; 373-379
published online: September 02, 2020
article type: Review Article
received: March 09, 2020
accepted: April 02, 2020

how to cite: Mirmohammadkhani M, Paknazar F, Rashidy-Pour A. Evaluation of the epidemiological pattern of COVID-19 applying basic reproduction number: An educational review article. koomesh. 2020;22(3):e153191. 

Abstract

After the onset of the COVID-19 outbreak in Wuhan, China, and its spread to other countries, confrontation with it as an international emergency in all countries was seriously on the agenda of governments. Our country was not immune to this outbreak. Effective measures to combat this new virus would be certainly based on a proper understanding of the epidemiological pattern and its evaluation in the community. Under these circumstances, proper understanding and use of epidemiology-based indicators or approaches are more than ever needed by authorities and decision-makers. One of the most important and commonly used indices that have been used in most epidemics, including the COVID-19 outbreak, is the Basic Reproduction Number (R_0). Given the increasing need for the medical community and health care staff to deepen their understanding of the epidemiological concepts in dealing with epidemics, this article aimed to define R_0 and its application in the evaluation and monitoring of the COVID-19 epidemiological pattern in society

References

  • 1.

    Zu ZY, Jiang MD, Xu PP, Chen W, Ni QQ, Lu GM, Zhang LJ. Coronavirus disease 2019 (COVID-19): a perspective from China. Radiology 2020; 200490.

  • 2.

    MacKenzie D. Covid-19 goes global. Elsevier; 2020.

  • 3.

    Coronavirus disease (COVID-19) outbreak, Situation Report-86 WHO; 2020 [March 8]; Available from: https://www.who.int/emergencies/diseases/novel-coronavirus-2019.

  • 4.

    Tuite AR, Bogoch I, Sherbo R, Watts A, Fisman DN, Khan K. Estimation of COVID-2019 burden and potential for international dissemination of infection from Iran. Med Rxiv 2020.

  • 5.

    Chen D, Zhou T. Control Efficacy on COVID-19. ArXiv preprint arXiv: 200300305 2020.

  • 6.

    Lipsitch M, Cohen T, Cooper B, Robins JM, Ma S, James L, et al. Transmission dynamics and control of severe acute respiratory syndrome. Science 2003; 300: 1966-1970.

  • 7.

    Lipsitch M, Swerdlow DL, Finelli L. Defining the epidemiology of Covid-19-studies needed. N E J Med 2020; 382: 1194-1196.

  • 8.

    Gilbert M, Pullano G, Pinotti F, Valdano E, Poletto C, Bolle PY, et al. Preparedness and vulnerability of African countries against importations of COVID-19: a modelling study. The Lancet 2020; 395: 871-877.

  • 9.

    Peng L, Yang W, Zhang D, Zhuge C, Hong L. Epidemic analysis of COVID-19 in China by dynamical modeling. arXiv preprint arXiv:200206563 2020.

  • 10.

    Castillo-Chavez C, Feng Z, Huang W. On the computation of ro and its role on. Mathematical approaches for emerging and reemerging infectious diseases: an introduction. 2002; 1: 229.

  • 11.

    Blackwood JC, Childs LM. An introduction to compartmental modeling for the budding infectious disease modeler. Lett Biomath 2018; 5: 195-221.

  • 12.

    Chen S, Yang J, Yang W, Wang C, Brnighausen T. COVID-19 control in China during mass population movements at New Year. The Lancet 2020; 395: 764-766.

  • 13.

    Giesecke J. Modern infectious dsisease epidemiology. second ed. London: Arnold; 2002.

  • 14.

    Choi S, Ki M. Estimating the reproductive number and the outbreak size of Novel Coronavirus disease (COVID-19) using mathematical model in Republic of Korea. Epidemiol Health 2020; e2020011.

  • 15.

    Cao Z, Zhang Q, Lu X, Pfeiffer D, Jia Z, Song H, Zeng DD. Estimating the effective reproduction number of the 2019-nCoV in China. medRxiv 2020.

  • 16.

    Lauer SA, Grantz KH, Bi Q, Jones FK, Zheng Q, Meredith HR, et al. The incubation period of coronavirus disease 2019 (COVID-19) from publicly reported confirmed cases: estimation and application. Ann Internal Med 2020.

  • 17.

    Liu Y, Yan LM, Wan L, Xiang TX, Le A, Liu JM, et al. Viral dynamics in mild and severe cases of COVID-19. The Lancet Infec Dis 2020.

  • 18.

    Ferguson N, Laydon D, Nedjati Gilani G, Imai N, Ainslie K, Baguelin M, et al. Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand. 2020.

  • 19.

    Colson P, Rolain JM, Lagier JC, Brouqui P, Raoult D. Chloroquine and hydroxychloroquine as available weapons to fight COVID-19. Int J Antimicrob Agents 2020; 105932.

  • 20.

    Zhou D, Dai SM, Tong Q. COVID-19: a recommendation to examine the effect of hydroxychloroquine in preventing infection and progression. J Antimicrob Chem 2020.

  • 21.

    Zhang S, Diao M, Yu W, Pei L, Lin Z, Chen D. Estimation of the reproductive number of novel coronavirus (COVID-19) and the probable outbreak size on the Diamond Princess Cruise ship: A data-driven analysis. Int J Infect Dis 2020; 93: 201-204.

  • 22.

    Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Eng J Med 2020.

  • 23.

    Liu T, Hu J, Kang M, Lin L, Zhong H, Xiao J, He G, Song T, Huang Q, Rong Z. Transmission dynamics of 2019 novel coronavirus (2019-nCoV). 2020.

  • 24.

    Abbott S, Hellewell J, Munday J, Funk S, group Cnw. The transmissibility of novel Coronavirus in the early stages of the 2019-20 outbreak in Wuhan: Exploring initial point-source exposure sizes and durations using scenario analysis. Well Open Res 2020; 5: 17.

  • 25.

    Kucharski AJ, Russell TW, Diamond C, Liu Y, Edmunds J, Funk S, et al. Early dynamics of transmission and control of COVID-19: a mathematical modelling study. Lancet Infect Dis 2020.

  • 26.

    Sanche S, Lin YT, Xu C, Romero-Severson E, Hengartner NW, Ke R. The novel coronavirus, 2019-nCoV, is highly contagious and more infectious than initially estimated. arXiv preprint arXiv:200203268 2020.

  • 27.

    Alimohamadi Y, Taghdir M, Sepandi M. The estimate of the basic reproduction number for novel coronavirus disease (COVID-19): a systematic review and meta-analysis. J Prevent Med Public Health 2020.

  • 28.

    Stein RA. Super-spreaders in infectious diseases. Int J Infect Dis 2011; 15: e510-e513.

  • 29.

    Hilton J, Keeling MJ. Estimation of country-level basic reproductive ratios for novel Coronavirus (COVID-19) using synthetic contact matrices. medRxiv 2020.

  • 30.

    Shao N, Cheng J, Chen W. The reproductive number R0 of COVID-19 based on estimate of a statistical time delay dynamical system. medRxiv 2020.

  • 31.

    Conyn-van Spaendonck MA, De Melker HE, Abbink F, Elzinga-Gholizadea N, Kimman TG, van Loon T. Immunity to poliomyelitis in The Netherlands. Am J Epidemiol 2001; 153: 207-214.

  • 32.

    Fine P, Eames K, Heymann DL. "Herd immunity": a rough guide. Clin Infect Dis 2011; 52: 911-916.

  • 33.

    Plans P, Torner N, Godoy P, Jane M. Lack of herd immunity against measles in individuals aged 35 years could explain re-emergence of measles in Catalonia (Spain). Int J Infect Dis 2014; 18: 81-83.

  • 34.

    Murdoch DR, French NP. COVID-19: another infectious disease emerging at the animal-human interface. N Zealand Med J 2020; 133: 12.

  • 35.

    Ahmed SF, Quadeer AA, McKay MR. Preliminary identification of potential vaccine targets for the COVID-19 coronavirus (SARS-CoV-2) based on SARS-CoV immunological studies. Viruses 2020; 12: 254.

  • 36.

    Hellewell J, Abbott S, Gimma A, Bosse NI, Jarvis CI, Russell TW, et al. Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. The Lancet Global Health 2020.

  • 37.

    Mukhtar F, Mukhtar N. Coronavirus (Covid-19): let's prevent not panic. J Ayub Med College Abbottabad 2020; 32##.