S.V. Ivanov – Senior Research Scientist, National Research University of Information Technologies, Mechanics and Optics. E-mail: firstname.lastname@example.org, email@example.com
D.A. Nasonov – Ph.D. (Eng.), Junior Research Scientist, National Research University of Information Technologies, Mechanics and Optics. E-mail: firstname.lastname@example.org
The modern approach to the study of infectious diseases is based on the concept of the virtual computer simulations in various ranges of the epidemiological process representation, starting from the cell level and ending with the level of the population. The implementation of this approach is related with the provision of access to distributed information (including cloud) resources that provide researchers with analytical tools for modeling and analysis of clinical, immunological and other data. Now the most interesting are integrated models that describe the spread of infection as the progress of a complex system, where the combination of different levels of modeling enables the most accurate study of the infectious process in general and to offer reasonable steps to prevent the spread of infection. The main objective of such an approach is not only studying fundamental processes at every level of simulation, but in a mutual understanding of the effect of various levels of modeling and the system behavior as a whole. The most significant result of the study of the epidemiological process is the building of decision support systems that can help in fighting the spread of infection at the level of the general population and individual patients in choosing treatment strategies (eg. for ranking drugs in the HIV treatment). One of the elements of the system for modeling the spread of viral infections, which include HIV epidemiological model is the population level. This kind of model in addition to providing useful information about the possible scenarios are also a means of verification models of a lower level, as well as allowing to determine in advance the success of these or other actions for fight the infection. This paper describes an approach to modeling the dynamics of HIV in the form of high-performance composite application that implements the two competing (and partly complementary) approaches based on the complex networks and differential equations. Composite application in the article refers to an application that is built on the basis of existing programs, supplemented with new functionality and integrated with a unified interface. In this case, the cloud environment CLAVIRE serves as a platform for the implementation of a unified interface. Designed application can solve the following set of tasks:
• Reproduction of the dynamics of HIV infection and AIDS (terminal stage of HIV) in a given region / country.
• Reproduction of the hidden dynamics of HIV infection, including the early stages of the epidemic in conditions of incomplete statistics.
• Forecast of the dynamics of infection, including HIV, AIDS and mortality.
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