AccScience Publishing / EJMO / Volume 4 / Issue 2 / DOI: 10.14744/ejmo.2020.60998
RESEARCH ARTICLE

Case Fatality Rate estimation of COVID-19 for European Countries: Turkey’s Current Scenario Amidst a Global Pandemic; Comparison of Outbreaks with European Countries

Fadime Öztoprak1,2 Aadil Javed3
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1 Izmir Biomedicine and Genome Center, Balcova, Izmir, Turkey
2 International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Turkey
3 Department of Biotechnology, Graduate School of Natural and Applied Sciences, Ege University, Izmir, Turkey
EJMO 2020, 4(2), 149–159; https://doi.org/10.14744/ejmo.2020.60998
Submitted: 18 March 2020 | Accepted: 9 April 2020 | Published: 9 April 2020
© 2020 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

Objectives: SARS-CoV-2, which belongs to the Coronaviridae family of RNA viruses, caused an epidemic in China, leading to the pandemic of COVID-19. Various international and national authorities around the world have been attempting to halt the spread of the deadly virus by providing awareness of the disease including daily confirmed cases and deaths related to the pandemic. At this early stage of the outbreak, epidemiological patterns are required for healthcare officials and public, to understand the ongoing situation. The case fatality rate is one of the key parameters for the epidemiology of this type of epidemic. In this study, we aimed to compute the CFR for European countries and Turkey until 31st March 2020.

Methods: We used linear regression analysis on the cumulative number of cases and deaths to generate a slope to estimate CFR values of COVID-19 in selected countries. We compared the calculated CFR values of Turkey until 31st March (15 days since first COVID-19 death) with similar first fifteen days’ data since the report of first death from Italy, Spain, the UK, France, Germany, Switzerland, Belgium, Austria, the Netherlands and Portugal. We then calculated CFR values for these countries from their cumulative confirmed cases and cumulative deaths up to March 31st. Results: Based on This data-driven analysis showed that CFR for Turkey was 1.85 (95% CI: 1.513-2.181) with an R2 value of 0.92 which was comparable to fa ifteen day analysis of France as 1.979 (95% CI: 1.798-2.159) and an R2 value of 0.98. However, CFRs for selected countries increased in subsequent analysis when the threshold of fifteen days was released until March 31, 2020. However, the CFR estimates are time-dependent and show a linear trend in the initial stages of the outbreak. 

Results: Based on This data-driven analysis showed that CFR for Turkey was 1.85 (95% CI: 1.513-2.181) with an R2 value of 0.92 which was comparable to fa ifteen day analysis of France as 1.979 (95% CI: 1.798-2.159) and an R2 value of 0.98. However, CFRs for selected countries increased in subsequent analysis when the threshold of fifteen days was released until March 31, 2020. However, the CFR estimates are time-dependent and show a linear trend in the initial stages of the outbreak.

Conclusions: Our findings suggest that the CFR of COVID-19 in Turkey at initial stages of the outbreak was similar to France. However, SARS-CoV-2 seemed to have spread quicker in Turkey since the report of first death, as compared to other countries based on the number of confirmed cases. This study was aimed at recording an update on the current epidemiological situation of COVID-19 for Turkey in comparison to European countries during a global pandemic.

Keywords
COVID-19
epidemiology
public health
SARS-CoV-2
Turkey
virology
Conflict of interest
None declared.
References

1.Wassenaar TM, Zou Y. 2019_nCoV: Rapid classification of betacoronaviruses and identification of traditional Chinese medicine as potential origin of zoonotic coronaviruses. Letters in Applied Microbiology. 2020.

2. Paraskevis D, Kostaki EG, Magiorkinis G, Panayiotakopoulos G, Sourvinos G, Tsiodras S. Full-genome evolutionary analysis of the novel corona virus (2019-nCoV) rejects the hypothesis of emergence as a result of a recent recombination event. Infection, Genetics and Evolution. 2020;79:104212.

3. Walls AC, Park YJ, Tortorici MA, Wall A, McGuire AT, Veesler D. Structure, function, and antigenicity of the SARS-CoV-2 spike glycoprotein. Cell. 2020 Mar 9.

4. Liu C, Yang Y, Gao Y, Shen C, Ju B, Liu C, Tang X, Wei J, Ma X, Liu W, Xu S. Viral Architecture of SARS-CoV-2 with Post-Fusion Spike Revealed by Cryo-EM. bioRxiv. 2020 Jan 1.

5. Gorbalenya AE. Severe acute respiratory syndrome-related coronavirus–The species and its viruses, a statement of the Coronavirus Study Group. BioRxiv. 2020 Jan 1.

6. Benvenuto D, Giovanetti M, Ciccozzi A, Spoto S, Angeletti S, Ciccozzi M. The 2019‐new coronavirus epidemic: evidence for virus evolution. Journal of Medical Virology 2020;92:455–9.

7. Lu R, Zhao X, Li J, Niu P, Yang B, Wu H, Wang W, Song H, Huang B, Zhu N, Bi Y. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. The Lancet 2020;395:565–74.

8. Jiang F, Deng L, Zhang L, Cai Y, Cheung CW, Xia Z. Review of the clinical characteristics of coronavirus disease 2019 (COVID-19). Journal of General Internal Medicine 2020:1–5.

9. Rodriguez-Morales AJ, Cardona-Ospina JA, Gutiérrez-Ocampo E, Villamizar-Peña R, Holguin-Rivera Y, Escalera-Antezana JP, Alvarado-Arnez LE, Bonilla-Aldana DK, Franco-Paredes C, Henao-Martinez AF, Paniz-Mondolfi A. Clinical, laboratory and imaging features of COVID-19: A systematic review and metaanalysis. Travel medicine and infectious disease 2020:101623.

10. de Wit E, van Doremalen N, Falzarano D, Munster VJ. SARS and MERS: recent insights into emerging coronaviruses. Nature Reviews Microbiology 2016;14:523.

11. Song Z, Xu Y, Bao L, Zhang L, Yu P, Qu Y, Zhu H, Zhao W, Han Y, Qin C. From SARS to MERS, thrusting coronaviruses into the spotlight. Viruses 2019;11:59. 12. World Health Organization. Coronavirus disease 2019 (COVID-19): situation report, 59.

13. Lai A, Bergna A, Acciarri C, Galli M, Zehender G. Early phylogenetic estimate of the effective reproduction number of SARS‐ CoV‐2. Journal of medical virology. 2020 Feb 25.

14. Battegay, M., Kuehl, R., Tschudin-Sutter, S., Hirsch, H.H., Widmer, A.F. and Neher, R.A., 2020. 2019-novel Coronavirus (2019- nCoV): estimating the case fatality rate–a word of caution. Swiss medical weekly, 150(0506).

15. Wu JT, Leung K, Leung GM. Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. The Lancet 2020;395:689–97.

16. Zhao S, Musa SS, Lin Q, Ran J, Yang G, Wang W, Lou Y, Yang L, Gao D, He D, Wang MH. Estimating the unreported number of novel coronavirus (2019-nCoV) cases in China in the first half of January 2020: a data-driven Modelling analysis of the early outbreak. Journal of clinical medicine 2020;9:388.

17. Donnelly CA, Ghani AC, Leung GM, Hedley AJ, Fraser C, Riley S, Abu-Raddad LJ, Ho LM, Thach TQ, Chau P, Chan KP. Epidemiological determinants of spread of causal agent of severe acute respiratory syndrome in Hong Kong. The Lancet 2003;361:1761–6.

18. Jia N, Feng D, Fang LQ, Richardus JH, Han XN, Cao WC, De Vlas SJ. Case fatality of SARS in mainland China and associated risk factors. Tropical Medicine & International Health 2009;14:21– 7.

19. Majumder MS, Rivers C, Lofgren E, Fisman D. Estimation of MERS-coronavirus reproductive number and case fatality rate for the spring 2014 Saudi Arabia outbreak: insights from publicly available data. PLoS Currents. 2014 Dec 18;6.

20. Lin Q, Chiu AP, Zhao S, He D. Modeling the spread of Middle East respiratory syndrome coronavirus in Saudi Arabia. Statistical methods in medical research 2018;27:1968–78.

21. De Silva UC, Warachit J, Waicharoen S, Chittaganpitch M. A preliminary analysis of the epidemiology of influenza A (H1N1) v virus infection in Thailand from early outbreak data, June-July 2009. Eurosurveillance 2009;14:19292.

22. Joshi AB, Luman ET, Nandy R, Subedi BK, Liyanage JB, Wierzba TF. Measles deaths in Nepal: estimating the national case-fatality ratio. Bulletin of the World Health Organization 2009;87:456–65.

23. Mizumoto K, Endo A, Chowell G, Miyamatsu Y, Saitoh M, Nishiura H. Real-time characterization of risks of death associated with the Middle East respiratory syndrome (MERS) in the Republic of Korea, 2015. BMC medicine 2015;13:228.

24. Yang S, Cao P, Du P, Wu Z, Zhuang Z, Yang L, Yu X, Zhou Q, Feng X, Wang X, Li W. Early estimation of the case fatality rate of COVID-19 in mainland China: a data-driven analysis. Annals of Translational Medicine 2020;8.

25. Porcheddu R, Serra C, Kelvin D, Kelvin N, Rubino S. Similarity in Case Fatality Rates (CFR) of COVID-19/SARS-COV-2 in Italy and China. The Journal of Infection in Developing Countries 2020;14:125–8.

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Eurasian Journal of Medicine and Oncology, Electronic ISSN: 2587-196X Print ISSN: 2587-2400, Published by AccScience Publishing