Akdi Yılmaz, Emre Karamanoğlu Yunus, Ünlü Kamil Demirberk, Baş Cem
Department of Statistics, Faculty of Science, Ankara University, Ankara, Turkey.
Gendarmerie and Coast Guard Academy, Ankara, Turkey.
J Appl Stat. 2022 Jan 31;50(11-12):2360-2372. doi: 10.1080/02664763.2022.2028744. eCollection 2023.
The new coronavirus disease, called COVID-19, has spread extremely quickly to more than 200 countries since its detection in December 2019 in China. COVID-19 marks the return of a very old and familiar enemy. Throughout human history, disasters such as earthquakes, volcanic eruptions and even wars have not caused more human losses than lethal diseases, which are caused by viruses, bacteria and parasites. The first COVID-19 case was detected in Turkey on 12 March 2020 and researchers have since then attempted to examine periodicity in the number of daily new cases. One of the most curious questions in the pandemic process that affects the whole world is whether there will be a second wave. Such questions can be answered by examining any periodicities in the series of daily cases. Periodic series are frequently seen in many disciplines. An important method based on harmonic regression is the focus of the study. The main aim of this study is to identify the hidden periodic structure of the daily infected cases. Infected case of Turkey is analyzed by using periodogram-based methodology. Our results revealed that there are 4, 5 and 62 days cycles in the daily new cases of Turkey.
新型冠状病毒病，即COVID-19，自2019年12月在中国被发现以来，已迅速蔓延至200多个国家。COVID-19标志着一个非常古老且熟悉的敌人再次出现。在人类历史上，诸如地震、火山爆发甚至战争等灾难造成的人员损失都不及由病毒、细菌和寄生虫引起的致命疾病。2020年3月12日在土耳其发现了首例COVID-19病例，此后研究人员一直试图研究每日新增病例数的周期性。在这场影响全球的大流行过程中，最令人好奇的问题之一是是否会出现第二波疫情。此类问题可通过研究每日病例序列中的任何周期性来解答。周期性序列在许多学科中都很常见。基于谐波回归的一种重要方法是本研究的重点。本研究的主要目的是识别每日感染病例的隐藏周期性结构。采用基于周期图的方法对土耳其的感染病例进行分析。我们的结果显示，土耳其每日新增病例存在4天、5天和62天的周期。
