Sharif Digital Repository

In recent studies, it has been shown that a cooperative interaction in a co-infection spread can lead to a discontinuous transition at a decreased threshold. Here, we have investigated effects of immunization on the threshold and the type of phase transitions in a cooperative spread of two diseases. It has been assumed that the immunization begins at the start of the spread and it is perfect, meaning that the vaccinated are immune for ever. We have used the SIR model for the spread of two diseases and scrutinized phase transitions through a mean field approach. This study is divided into three parts. In the first part, vaccination with a fixed rate has been introduced in the symmetric spread... 

An infectious disease can spread through different communities via mobility networks. In this study we address three basic questions related to this matter in the meta-population approximation: firstly, where did the disease start? Secondly, when did the disease start? Thirdly, how does it spread in the network? To answer these questions, we introduce a generic mathematical framework with appropriate physical assumptions and study the spread of diseases. Then, with analytical solutions, we bring up different algorithms in order to answer these three questions. Using these algorithms, we redefine the effective distance and arriving time and unveil the simple geometry of the disease outbreak  

In this thesis, we attempt to construct a model that can predict whether someone will retweet a tweet. For this purpose, we construct a machine learning model and we use Twitter’s network features as our model’s input. We collect about 1300 random tweets and their retweets to make retweet cascades. By collecting or calculating users’ features in each retweet cascade, we construct our desired input data for our model. We test both random forest and neural networks as our machine learning section of the model. Random forest is the most accurate of the two models, predicting retweet actions with an accuracy of 0.89. Additionally, we find out that two features of the network have the greatest... 

SIS and SIR are common models for describing and predicting the epidemics of the contagious diseases. But these models fail to predict patterns of spreading dynamics in the case of co-infective diseases, i.e. getting infected by one disease, alters the chance of getting infected by the other one. Coinfection has been studied in the mean field approximation and on complex networks with different topologies. Another study shows temporal correlations of the underlying transmission network, play role on co-infection dynamics.In this research we investigate the effects of various temporal correlation on epidemic order parameters of independent infection and co-infection.For this purpose, we... 

Epidemics are one of the most important issues in social environments, economics systems, medicine, and other environments. In the study of the epidemics, some behaviors have been observed that are very similar to the phase transition in critical systems. For example, by changing the parameters that the epidemics process is characterized, the system’s epidemic behavior changes. Depending on the type of problem, this behavior change may be similar to continuous or discontinuous phase transitions. One of the fascinating issues that have just been taken into consideration in this area is the cooperation of two or more diseases. This means that the rate of transmission of a disease depends on...