Statistical Ambiguities in Epidemics of Coronavirus Disease 2019 (COVID-19)
Abstract
Abstract Abstract Abstract
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2. Benvenuto D, Giovannetti M, Ciccozzi A, Spoto S,
Angeletti S, Ciccozzi M. The 2019-new coronavirus epidemic: evidence for virus evolution. J Med Virol 2020;92:455-9.
3. Coronavirus. GitHub. (Accessed at https://github.com/RamiKrispin/coronavirus.)
4. Bhat UN. An introduction to queueing theory: modeling and analysis in applications. New York: Birkhäuser Basel, 2015.
5. Ji Y, Ma Z, Peppelenbosch MP, Pan Q. Potential association between COVID-19 mortality and health-care resource availability. Lancet Glob Health 2020;8:e480
6. Osmani F, Rasekhi A, Hajizadeh E, Akbari ME. Simultaneous modeling of multiple recurrences in breast cancer patients. Koomesh. 2020;22:359-64.
7. SeyedAlinaghi S, Jam S, Mehrkhani F, Fattahi F, Sabzvari D, Kourorian Z, Jabbari H, Mohraz M. Hepatitis-C and Hepatitis-B Co-Infections in Patients with Human Immunodeficiency Virus in Tehran, Iran. Acta Med Iran 49:252-7.
| Files | ||
| Issue | Vol 58, No 3 (2020) | |
| Section | Letter to the Editor | |
| DOI | https://doi.org/10.18502/acta.v58i3.3780 | |
| Keywords | ||
| COVID-19 Statistics Iran Coronavirus | ||
| Rights and permissions | |
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
Osmani F. Statistical Ambiguities in Epidemics of Coronavirus Disease 2019 (COVID-19). Acta Med Iran. 2020;58(3):142-143.
