A close look at 2019 novel coronavirus (COVID 19) infections in Turkey using time series analysis & efficiency analysis

Harun Kınacı; Mehmet Güray Ünsal; Reşat Kasap

doi:10.1016/j.chaos.2020.110583

A close look at 2019 novel coronavirus (COVID 19) infections in Turkey using time series analysis & efficiency analysis

Chaos Solitons Fractals. 2021 Feb:143:110583. doi: 10.1016/j.chaos.2020.110583. Epub 2020 Dec 23.

Authors

Harun Kınacı¹, Mehmet Güray Ünsal², Reşat Kasap³

Affiliations

¹ Erciyes University, Faculty of Economics and Administrative Sciences Department of Business, 38225, Kayseri, Turkey.
² Usak University, Faculty of Art and Science, Department of Statistics, Usak, Turkey.
³ Gazi University, Faculty of Science, Department of Statistics, Ankara, Turkey.

Abstract

2019 novel coronavirus (COVID 19) infections detected as the first official records of the disease in Wuhan, China, affected almost all countries worldwide, including Turkey. Due to the number of infected cases, Turkey is one of the most affected countries in the world. Thus, an examination of the pandemic data of Turkey is a critical issue to understand the shape of the spread of the virus and its effects. In this study, we have a close look at the data of Turkey in terms of the variables commonly used during the pandemic to set an example for possible future pandemics. Both time series modeling and popular efficiency measurement methods are used to evaluate the data and enrich the results. It is believed that the results and discussions are useful and can contribute to the language of numbers for pandemic researchers working on the elimination of possible future pandemics.

Keywords: AICA, Akaike Information Criterion; ARIMA, Autoregressive Integrated Moving Average; CE, Cross Efficiency Evaluation; COVID 19; DEA, Data Envelopment Analysis; DNOC, Daily Number of Cases; DNOD, Daily Number of Deaths; DNOR, Daily Number of Recovered Cases; DNOT, Daily Number of Tests; DROC, Daily Rate of Cases; Efficiency analysis; MAE, Mean Absolute Error; Pandemic; RC, Rate of Cases; RD, Rate of Deaths; SC, Speed of Cases; SD, Speed of Deaths; SFA, Stochastic Frontier Analysis; TNOC, Total Number of Cases; TNOD, Total Number of Deaths; TNOE, Total Number of İntubated Cases; TNOIC, Total Number of The Cases İn İntensive Care Unit; TNOR, Total Number of Recovered Cases; TNORC, Total Number of Remaining Cases; Time series analysis.