Akademik Veri Yönetim Sistemi
4. Uluslararası Bilimsel Araştırmalar ve Yenilikçi Çalışmalar Sempozyumu, Balıkesir, Türkiye, 13 - 15 Mart 2024, ss.488
Humanity faces with different kinds of epidemics for centuries and one of the major
epidemics that we often hear about in history in 2019. Throughout the process, daily case and
death numbers were expected to be announced at the end of each day. Whether the number of
cases enters a rising or falling trend, or whether the number of deaths increases or decreases in
proportion to the number of cases, is a very critical point for such epidemics. The aim of this
study is to develop a statistical perspective on the spread rate of the epidemic and to determine
the factors affecting the spread rate of the epidemic. In this study, population, average
temperature, health infrastructure, tourist attraction coefficient and the rate of population over
the age of 65 are considered as factors thought to affect the spread rate. First, after the necessary
statistical analyses, extreme data namely outliers, are removed from the data set and two
different regression analysis are conducted. In the first regression model, the factors thought to
affect the spread rate are treated as independent variables, while the total number of cases is
treated as the dependent variable. In the second regression model, in addition to the factors
affecting the spread rate, the total number of cases is considered as an independent variable,
and the death number is the dependent variable. In the former, the factors affecting the total
number of cases emerged as the population rate over the age of 65 and the tourist attraction
coefficient. In the latter, on the other hand the factors affecting the total number of deaths
emerged as health infrastructure, population rate over 65 years of age, and total number of cases.
Keywords: Epidemic, regression analyses, statistic, machine learning