Yaroslav Vyklyk

Yaroslav Vyklyk


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2023 in Journal of the Geographical Institute "Jovan Cvijic", SASA
Verified
Journal Article
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YVYaroslav Vyklyk
Yaroslav Vyklyk
NNNevinskyi Nevinskyi
Nevinskyi Nevinskyi
NBNataliya Boyko
Nataliya Boyko
In this paper the initialization of the city is considered, which consists of several steps, including the creation of city objects with their locations, creation of residents with their attributes and own daily schedules, etc. A description of the model is provided as a tuple of attributes. The adequacy of the simulation model is checked based on the statistical data from the city of Lviv, Ukraine. Generated locations of city ecosystem objects are presented. The daily schedule of residents is simulated. A possible work schedule for each specialty is given, and separate schedules are created for working days and holidays. A unique schedule is predicted for the resident, which depends on their age and work specialty. The dynamics of visits to facilities by residents on weekdays and at weekends are analyzed. Based on the conducted experiments, the adequacy of the model and its realistic reflection of the functioning of the city's ecosystem during the day are proven. It means that by using this model, researchers can assess the impact of different behavioral scenarios on the residents within the city ecosystem more reliably. This enables a better understanding of how certain actions or changes in behavior can affect the spread and control of diseases in a specific geographic area. This model has the potential to serve as a foundation for future modeling of systems at the medium and macro scales.

27 April 2024 in New Microbes and New Infections
Verified
Journal Article
Open access
YVYaroslav Vyklyk
Yaroslav Vyklyk
ISIhor Semianiv
Ihor Semianiv
NNNevinskyi Nevinskyi
Nevinskyi Nevinskyi
LTLilia Todoriko
Lilia Todoriko
NBNataliya Boyko
Nataliya Boyko
Introduction: The paper presents epidemiological process modeling, with a focus on tuberculosis utilizing multiagent system. Material and methods: This study involves the development of an algorithm that harnesses the potential of artificial intelligence to create a geospatial model that highlights the different pathways of TB transmission. The modeling process itself is characterized by a series of key stages, including initialization of the city, calibration of health parameters, simulation of the working day, propagation of the spread of infection, the evolution of disease trajectories, rigorous statistical calculations and transition to the following day. A comprehensive description of the course of active tuberculosis is presented, following the official hypothesis recommended by the World Health Organization. A comprehensive simulation, illustrating the propagation of tuberculosis in an entirely healthy environment devoid of any preventive or therapeutic measures, is presented. To ascertain the adequacy of the model and its sensitivity to the principal parameters governing the course of tuberculosis, a series of experiments were meticulously conducted, employing three distinct approximations, namely: the basic model, the model incorporating mortality factors, and the comprehensive model, encompassing all relevant aspects. Conclusions: The model ' s results exhibit stability and lack of significant fluctuations. The statistical values obtained for infected, latent, and recovered individuals align well with known medical data, confirming the model ' s adequacy.