Predicting the progress of COVID-19: the case for Turkey [COVID-19'un ilerleme sürecinin tahmini: Türkiye örneği]

Özdinç, Mesut and Şenel, Kerem and Öztürkcan, Didem Selcen and Akgül, Ahmet (2020) Predicting the progress of COVID-19: the case for Turkey [COVID-19'un ilerleme sürecinin tahmini: Türkiye örneği]. Turkiye Klinikleri Journal of Medical Sciences, 40 (2). pp. 117-119. ISSN 1300-0292 (Print) 2146-9040 (Online)

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COVID-19 has proven to be the worst pandemic in modern times in terms of both mortality and infectiousness since the flu pandemic that took place in the early 20th century, which is also known as the Spanish Flu. First being detected in China on December 8, 2019, the COVID-19 disease has spread swiftly into other countries and continents, which eventually led to its classification as “pandemic” by the World Health Organization (WHO) on March 12, 2020. After the first confirmed case in Turkey was de- tected on March 11, 2019, the number of confirmed cases has increased rapidly and reached 95,591 as of April 21, 2020, according to the Ministry of Health - Turkey. In order to devise an appropriate policy response, it is imperative to forecast the progress of the pandemic in the coming days, weeks, and months. For instance, if the maximum number of infected people can be predicted, then it will be easier to gauge whether the capacity of healthcare institutions will be sufficient, particularly in terms of ER units and ven- tilators. Another critical decision is the timing for eas- ing and eventually lifting limitations such as curfews and closure of schools and businesses. If the limitations are eased and/or lifted prematurely, then there is a substantial risk of rebound. On the other hand, as long as such limitations remain, economic hardship for millions of people is exacerbated. Hence, the optimal policy response demands a prediction model, which is aimed in this manuscript.
Item Type: Article
Additional Information: Scopus Document Type: Editorial
Subjects: R Medicine > R Medicine (General) > R858-859.7 Computer applications to medicine. Medical informatics
Divisions: Sabancı Business School
Depositing User: Selcen Öztürkcan
Date Deposited: 15 Sep 2020 13:10
Last Modified: 26 Apr 2022 10:17

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