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Covid-19 is the most recently discovered infectious disease affecting the countries all around the world. SARS-CoV-2, which is a member of coronavirus family, is the virus that makes the infection. Until the 28th of September 2020, almost 34 million people infected by the virus and more than 1 million people died all around the world. One of the most discussed ideas about the disease to die out is vaccination. In our study, we tried to analyze this idea and show the effect of vaccine for Covid-19. Our work starts with constructing an SVI mathematical model. Afterwards, we made the analyze of our model. Then, by taking into consideration of incoming passengers and precautions that should be taken, we used the vaccination idea with changing the percentage of vaccinated people in a population. In last section, we used numerical simulations to support our idea. In our work, we conclude that vaccination is substantially effective if we consider the other things that affect the disease which is incoming passengers and precautions like wearing mask, maintaining social distance, etc. [ABSTRACT FROM AUTHOR]

In this study, it was aimed to determine the course of COVID-19 infection in Libya with a new modified mathematical modeling and to show the possible number of cases and deaths in the upcoming period. We performed detailed analyzes with the help of the analytical solution of the time-dependent logistics model that we obtained. The results obtained separately on a total and daily basis were shown graphically. In the last part, it is emphasized how important individual and public precautions in order to decrease the spread rate of the disease and to be better controlled. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019, also known as Covid-19, is an infectious disease that has infected more than nineteen million people all around the world. This virus is a member of coronavirus family but it is the most mortal one. It has named as 2019-nCoV by World Health Organization(WHO) after Chinese Center for Disease Control and Prevention(CDC) discovered a new coronavirus from a swab sample of a patient. As we know this pandemic started December 2019 in China, and it is still spreading and causing deaths all around the world. In this paper, we aimed to estimate the right size of epidemic. For that purpose, we chose 10 countries, which are affected by, and still fighting with this disease, to forecast the upcoming death rates by using the previous week deaths. These 10 countries are Argentina, Austria, Brazil, France, Iran, Italy, Sweden, Turkey, United Kingdom, and United States of America. We used the death data of WHO with assumption that data is accurate. For this estimation, firstly, we used the assumption that the reported death delay distributed according to a gamma distribution. Then, we used a binomial distribution for assumption of deaths. This binomial formula led us to find a posterior distribution which is an extension of Bayes' theorem for death ratio. Lastly, we compared our estimations with real data. [ABSTRACT FROM AUTHOR]

In this paper, a fractional order mathematical model is constructed to study the dynamics of coronavirus. The model consists of a system of eight non-linear fractional order differential equations in Caputo sense. Existence and uniqueness of the solution of the model are studied. [ABSTRACT FROM AUTHOR]

The aim of this paper is to show how North Cyprus fights Covid-19 by using the basic reproduction number R0 and effective reproduction number Rt. According to the Wikipedia page with title Covid-19 pandemic in Northern Cyprus, North Cyprus is the first country in Europe to free from Covid-19. One of the important reasons of this is that the government decided for tackling Covid-19 pandemic by using R0 and Rt daily. For R0, we constructed a new SEIR model by using the real data for North Cyprus. From March 11, 2020 to May 15, 2020 R0, varies from 0.65 to 2.38. [ABSTRACT FROM AUTHOR]