The monitoring, analysis and prediction of epidemic spread in the region require the construction of mathematical model, big data processing and visualization because the amount of population and the size of the region could be huge. One of the important steps is refinement of mathematical model, i.e. determination of initial data and coefficients of system of differential equations of epidemiologic processes using additional information. We analyze numerical method for solving inverse problem of epidemiology based on genetic algorithm and traditional optimization approach. Our algorithms are applied to analysis and prediction of epidemic situation in regions of Russian Federation, Republic of Kazakhstan and People’s Republic of China. Due to a great amount of data we use a special software ”Digital Earth” for visualization of epidemic.

中文翻译：

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基于反演与预测的结核传播地理信息系统

由于该地区的人口数量和规模可能很大，因此对该区域流行病的监测，分析和预测需要构建数学模型，进行大数据处理和可视化。重要的步骤之一是完善数学模型，即使用附加信息确定流行病学过程的初始数据和微分方程系统的系数。我们基于遗传算法和传统的优化方法，分析了解决流行病学逆问题的数值方法。我们的算法被用于分析和预测俄罗斯联邦，哈萨克斯坦共和国和中华人民共和国地区的流行情况。由于有大量数据，我们使用特殊的软件“ Digital Earth”对疫情进行可视化显示。