Application of mathematical models of the dynamics of the epidemic acute respiratory viral infections to increase the efficiency of epidemiological surveillance

Uncertainty in the calculations of forecasts of the spread of epidemic acute respiratory infections obtained using mathematical models, associated with data error and uncertainty in the choice of a model, as well as the lack of verification of modeling results by interdisciplinary teams including epidemiology specialists, prevent the correct prediction of the effectiveness of disease control measures. In this paper, we propose a solution to these problems by using a software package consisting of a family of epidemic models, methods for estimating the error of output data depending on the error of the initial morbidity data, as well as a graphical interface with the possibility of manual correction of the results of automatic calibration and generation of epidemic bulletins. The novelty of the presented study is the methodology for integrating epidemic models into software tools used by supervisory authorities, which allows to supplement weekly bulletins and annual epidemiological reports in semi-automatic mode with a quantitative interval estimation of the error of calculated indicators. The ultimate goal is to provide the supervisory authorities with informative and promptly obtained calculated data for decision-making in the field of infection control.