OVERVIEW (TR)
Row
confirmed
146,457death
4,055 (2.8%)inf
893,903 (16.4%)Ifr
0.5%Row
Daily cumulative cases by type (Turkey only)
SIR MODEL
Column
SIR Turkey: Based on the data from 1st of April to 11th of April
SIR Model results for Turkey
An SIR model is an epidemiological model that computes the theoretical number of people infected with a contagious illness in a closed population over time. The model divides the population into compartments: Susceptible, Infectious, Recovered. Between S and I, the transition rate βI/N, where β is the average number of contacts per person per time, multiplied by the probability of disease transmission in a contact between a susceptible and an infectious subject, and I/N is the fraction of contact occurrences that involve an infectious individual.Between I and R, the transition rate is γ (simply the rate of recovery or mortality,that is, γ = 1/D, where D is the duration of the infection. This analysis is done for the purpose of learning the basics of SIR modelling and the dynamics of the spread of a pandemic. See more details here and for its example for covid-19 here. 
Data and assumptions
The analysis is done on 12th of April. The covid-19 case data used in this modelling are from 1st of April until the 11th of April.(The raw data is pulled from Johns Hopkins University Center for Systems Science and Engineering).
Population of Turkey: 83154997 (TUÄ°K)
Mild symptomps= 80.9%, Severe cases= 13.8%, Intensive care= 4.7%. (According to this source;)
The case fatality rate= 2.1%, the infection fatality rate = 0.3%. (See About tab for the estimation).
Model statistics- Peak of the pandemic: Middle of May- Ro: 1.142374- Maximum number of infected: 703369- Total severe cases: 97150- Total number of cases in intensive care: 33058- Total deaths: 15048TREND
Column
Case growth after 100 cases on the logarithmic scale
Death growth after 5 deaths on the logarithmic scale
PROGRESSION
Column
Daily case progression as % of daily cases and linear trend line
Daily death progression as % of daily deaths and linear trend line
DAILY
Column
Daily new confirmed cases (2020-05-15) - Top 10 Countries
Daily new deaths (2020-05-15) - Top 10 Countries
Column
Daily new confirmed cases over time - Turkey
Daily new deaths over time - Turkey
CASE PROFILE
Column
Active cases and deaths (2020-05-16) - Turkey (Source: TR Ministry of Health)
FATALITY
Column
% change in the daily deaths plotted with the case fatality rate over time- Turkey (Source: JHU)
Column
% change in daily cases- Turkey (Source: JHU)
About
The Coronavirus Dashboard: Turkey
This Coronavirus dashboard: the case of Turkey provides an overview of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) epidemic for Turkey This dashboard is built with R using the R Markdown framework by Bcogan.
Code
This dashboard is adapted from here and here.
Data and Method
The input data for this dashboard is the dataset available from the {coronavirus} R package.The data and dashboard are updated on a daily basis.The raw data is pulled from the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus repository.
Projected cases: The forecast is calculated based on the logarithmic scale of the same data. The applied linear regression on the log scale is used to interpolate the raw data as an exponential model.
Estimated number of infected: The actual number of people who are infected is roughly estimated based on the calculated case growth rate and an assumed period of 5 days for symptoms to develop. It is also assumed that only 50% of infected people are symptomatic according to this source. This sourceuses a different method for estimating detection rate.
Infection fatality rate: See more detailed information about Infection fatality rate and case fatality rate here.
Progression: Progression rate for daily number of cases and deaths (second derivative of the daily number of cases and deaths) gives us information about the acceleration or deceleration rate of the daily cases and deaths. If the this rate is positive, that is if growth of the new cases per day is accelerating, the outbreak is exponentially growing. If the rate of variation is negative, even if the number of cases is still growing, the growth of the daily new cases is slowing down. For example, in the graph for the confirmed case progression; on 21st of March there were 19% less cases than the day before in UK, but 40% more deaths than the day before. In Germany on the same day, there were 48% less cases than the day before, and 26% less deaths. See more info here.
The Map tab was contributed by Art Steinmetz on this pull request.
Update
The data is as of Friday May 15, 2020