Background: This study aims to estimate the total number of infected people, evaluate the effects of NPIs on the healthcare system, and predict the expected number of cases, deaths, hospitalizations due to COVID-19 in Turkey.Methods: This study was carried out according to three dimensions. In the first, the actual number of infected people was estimated. In the second, the expected total numbers of infected people, deaths, hospitalizations have been predicted in the case of no intervention. In the third, the distribution of the expected number of infected people and deaths, and ICU and non-ICU bed needs over time has been predicted via a SEIR-based simulator (TURKSAS) in four scenarios.Results: According to the number of deaths, the estimated number of infected people in Turkey on March 21 was 123,030. In the case of no intervention the expected number of infected people is 72,091,595 and deaths is 445,956, the attack rate is 88.1%, and the mortality ratio is 0.54%. The ICU bed capacity in Turkey is expected to be exceeded by 4.4-fold and non-ICU bed capacity by 3.21-fold. In the second and third scenarios compliance with NPIs makes a difference of 94,303 expected deaths. In both scenarios, the predicted peak value of occupied ICU and non-ICU beds remains below Turkey's capacity.Discussion: Predictions show that around 16 million people can be prevented from being infected and 94,000 deaths can be prevented by full compliance with the measures taken. Modeling epidemics and establishing decision support systems is an important requirement.

Background: A new type of coronavirus (later named Sars-Cov-2) drew attention in 31 December 2019 after the reporting of 27 unidentified pneumonia cases detected in Wuhan, China to the World Health Organization (WHO). Rapid progression of the COVID-19 pandemic has revealed the necessity of epidemic modeling studies to evaluate the course of the epidemic and its burden on the health system. This study aims to estimate the total number of infected people, evaluate the consequences of social interventions on the healthcare system and predict the expected number of cases, intensive care needs, hospitalizations and mortality rates in Turkey according to possible scenarios via the SEIR-based epidemic modeling method. Methods:This study was carried out in three dimensions. In the first, the actual number of people infected in the community has been estimated using the number of deaths in Turkey. In the second, the expected total numbers of infected people, total deaths, total hospitalizations, and intensive care unit (ICU) bed needs have been predicted in case of no intervention. In third, distribution of the expected number of infected people and deaths, ICU and non-ICU bed needs over time has predicted based on SEIR modelling. A simulator (TURKSAS) has been developed and predictions made in 4 scenarios for Turkey.Results: According to deaths, estimated number of infected people in Turkey on March 21 was 123,030.In the case of no intervention (1 st scenario) the expected total number of infected people is 72,091,595, the total number of deaths is 445,956, the attack rate is 88.1%, the mortality ratio is 0.54%. The ICU bed capacity in Turkey is expected to exceed 4.4-fold and non-ICU bed capacity exceed 3.21fold. In 2 nd and 3 rd scenario according to the calculations made by considering the social compliance rates of the NPIs, the value of R0 is estimated to decrease from 3 to 1.38 level. Compliance with NPIs makes a 94,303 difference in the expected number of deaths. In both scenarios, the predicted peak value of occupied ICU and non-ICU beds remains below the Turkey's capacity. While this study conducted, curfew for >65 and <20 age groups was in force in Turkey. If the curfew is declared for the 21-64 age population (4 th scenario), the R0 value drops below 1 (0.98), the expected deaths are 14,230 and the peak values of daily ICU and non-ICU bed demand are below the country's capacity. Discussion:Modeling epidemics with assumptions supported by scientific literature and establishing decision support systems based on objective criteria is an important requirement. According to scientific data for the population of Turkey, the situation is not expected to be of worse than predictions presented in the second dimension. Predictions show that 16 million people can be prevented from being infected and 100,000 deaths can be prevented by full compliance with the measures taken. Complete control of the pandemic is possible by keeping R0 below 1. For this, additional evidence-based measures are needed.

The aim of the present study is to determine the relationship between selfperceptions and social behaviors of gifted primary school children. The target population of the study consists of 874 third and fourth grade students who are from a district on the European side of Istanbul. These students are labeled as gifted according to the Primary Mental Abilities Test (7-11). 368 students (211 girls and 157 boys) participated in the research conducted in 16 primary schools. The Piers-Harris Children's Self-Concept Scale was used in the study to determine the self-perception levels while the School Social Behavior Scales (SSBS) was used to assess the social behaviors of the gifted children. According to the findings of the study, it was found that the self-perceptions of gifted children predicted the social competence and antisocial behaviors (p <.01). It was seen that as the children's self-perception levels increased, their social competence increased (r = .186) and antisocial behaviors decreased (r = .160).

Background and ObjectivesThe official number of daily cases and deaths are the most prominent indicators used to plan actions against the COVID-19 pandemic but are insufficient to see the real impact. Official numbers vary due to testing policy, reporting methods, etc. Therefore, critical interventions are likely to lose their effectiveness and better-standardized indicators like excess deaths/mortality are needed. In this study, excess deaths in Istanbul were examined and a web-based monitor was developed.MethodsDaily all-cause deaths data between January 1, 2015- November 11, 2021 in Istanbul is used to estimate the excess deaths. Compared to the pre-pandemic period, the % increase in the number of deaths was calculated as the ratio of excess deaths to expected deaths (P-Scores). The ratio of excess deaths to official figures (T) was also examined.ResultsThe total number of official and excess deaths in Istanbul are 24.218 and 37.514, respectively. The ratio of excess deaths to official deaths is 1.55. During the first three death waves, maximum P-Scores were 71.8, 129.0, and 116.3% respectively.ConclusionExcess mortality in Istanbul is close to the peak scores in Europe. 38.47% of total excess deaths could be considered as underreported or indirect deaths. To re-optimize the non-pharmaceutical interventions there is a need to monitor the real impact beyond the official figures. In this study, such a monitoring tool was created for Istanbul. The excess deaths are more reliable than official figures and it can be used as a gold standard to estimate the impact more precisely.