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• The examination of the pandemic data of Turkey (one of the most effected countries) is a very important issue for understanding the shape of the spread of the virus and its effects. • The one of the proposes of this study is to try to present a general view of COVID 19 in Turkey and understand the shape of the spread of the virus and its effects within the framework of the statistical data recorded officially during the pandemic. • The second propose of the study is to show that how the selected data for time series modeling and efficiency analysis can be used for serving the results to the policy makers. • The results and discussions can be beneficial indicator and useful guide for the researchers who work on the dispositions of possible future pandemics. 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. [ABSTRACT FROM AUTHOR]

• A novel multi-scale model of COVID-19 transmission dynamics • Simulation of COVID-19 dynamics in China and Italy • Panic situations increase the risk of disease transmission in crowds despite social distancing • Presymptomatic transmission accelerates the onset of exponential growth • Limited movement of the population flattens the epidemic curve Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus that emerged in Wuhan, China in December 2019. It has caused a global outbreak which represents a major threat to global health. Public health resorted to non-pharmaceutical interventions such as social distancing and lockdown to slow down the spread of the pandemic. However, the effect of each of these measures remains hard to quantify. We design a multi-scale model that simulates the transmission dynamics of COVID-19. We describe the motion of individual agents using a social force model. Each agent can be either susceptible, infected, quarantined, immunized or deceased. The model considers both mechanisms of direct and indirect transmission. We parameterize the model to reproduce the early dynamics of disease spread in Italy. We show that panic situations increase the risk of infection transmission in crowds despite social distancing measures. Next, we reveal that pre-symptomatic transmission accelerates the onset of the exponential growth of cases. After that, we demonstrate that the persistence of SARS-CoV-2 on hard surfaces determines the number of cases reached during the peak of the epidemic. Then, we show that the restricted movement of the individuals flattens the epidemic curve. Finally, model predictions suggest that measures stricter than social distancing and lockdown were used to control the epidemic in Wuhan, China. [ABSTRACT FROM AUTHOR]