Improvement of the software for modeling the dynamics of epidemics and developing a user-friendly interface

Abstract

The challenges humanity is facing due to the Covid-19 pandemic require timely and accurate forecasting of the dynamics of various epidemics to minimize the negative consequences for public health and the economy. One can use a variety of well-known and new mathematical models, taking into account a huge number of factors. However, complex models contain a large number of unknown parameters, the values of which must be determined using a limited number of observations, e.g., the daily datasets for the accumulated number of cases. Successful experience in modeling the COVID-19 pandemic has shown that it is possible to apply the simplest SIR model, which contains 4 unknown parameters. Application of the original algorithm of the model parameter identification for the first waves of the COVID-19 pandemic in China, South Korea, Austria, Italy, Germany, France, Spain has shown its high accuracy in predicting their duration and number of diseases. To simulate different epidemic waves and take into account the incompleteness of statistical data, the generalized SIR model and algorithms for determining the values of its parameters were proposed. The interference of the previous waves, changes in testing levels, quarantine or social behavior require constant monitoring of the epidemic dynamics and performing SIR simulations as often as possible with the use of a user-friendly interface. Such tool will allow predicting the dynamics of any epidemic using the data on the number of diseases over a limited period (e.g., 14 days). It will be possible to predict the daily number of new cases for the country as a whole or for its separate region, to estimate the number of carriers of the infection and the probability of facing such a carrier, as well as to estimate the number of deaths. Results of three SIR simulations of the COVID-19 epidemic wave in Japan in the summer of 2022 are presented and discussed. The predicted accumulated and daily numbers of cases agree with the results of observations, especially for the simulation based on the datasets corresponding to the period from July 3 to July 16, 2022. A user-friendly interface also has to ensure an opportunity to compare the epidemic dynamics in different countries/regions and in different years in order to estimate the impact of vaccination levels, quarantine restrictions, social behavior, etc. on the numbers of new infections, death, and mortality rates. As example, the comparison of the COVID-19 pandemic dynamics in Japan in the summer of 2020, 2021 and 2022 is presented. The high level of vaccinations achieved in the summer of 2022 did not save Japan from a powerful pandemic wave. The daily numbers of cases were about ten times higher than in the corresponding period of 2021. Nevertheless, the death per case ratio in 2022 was much lower than in 2020.