Anali Mečnikìvsʹkogo Institutu. 2016;(4):18-26 DOI 10.5281/zenodo.192296


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Journal Title: Anali Mečnikìvsʹkogo Institutu

ISSN: 1993-4327 (Online)

Publisher: Mechnikov Institute of Microbiology and immunology

Society/Institution: Mechnikov institute of microbiology and immunology

LCC Subject Category: Medicine: Medicine (General)

Country of publisher: Ukraine

Language of fulltext: Russian, Ukrainian, English

Full-text formats available: PDF



Soloviov S. O
Dzyublyk I.V
Zaliska O.M
Sakhno A. O


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Instructions for authors

Time From Submission to Publication: 8 weeks


Abstract | Full Text

Background: Viruses play a leading role in human pathology development, causing a large number of infectious diseases in acute, persistent or chronic forms. Although the number of deaths caused by viral infections have decreased significantly today, they continue to be a significant factor in reducing of the population overall productivity. Viral diseases cause additional losses in community related to the duration of the course or disease or its chronization, increased use of health care, loss of working hours, premature death etc. Introduction of the new antiviral drugs into medical practice is accompanied by the emergence of questions to assess its effectiveness and including into existing clinical protocols. So the aim of this work is the development of methodology of choosing and justification of optimal treatment strategy for viral diseases that could be included into certain clinical protocols for managing patients with certain viral diseases. Methodology justification: The methodology based on the method of pharmacoeconomic analysis "cost of illness", takes into account the economic burden of viral diseases: direct costs for treating of disease, indirect costs related to the disease and intangible costs. Algorithm of treatment scheme choice depends on the cost of treatment for the patient without viral disease also as for patient with viral disease. It was proposed to use lower limit priori probability (critical prevalence) of viral disease as decision rule in the choice of treatment scheme. Results: Examples of the proposed methodology use show that the choice of the optimal therapeutic scheme for patients with suspected viral disease depends on the current prevalence of this disease among patients with similar clinical symptoms of the disease and its cost, depending on the chosen strategy of therapy. The proposed methodology determines the critical level of viral infection prevalence, which comparing to the current prevalence level is the criterion for inclusion of certain antiviral drug into treatment scheme. Conclusions: The implementation of developed methodology requires a dynamic and updated database of patients with similar clinical symptoms, which will include information of etiological agent, chosen treatment scheme, number of bed days and costs associated with viral disease for each patient.