Assessment of cancer prevalence based on analysis of statistics from the Municipal Indicator database created by the Rosstat

Cancer diseases are a major health concern in Russia and many other countries. A national strategy for cancer control has been adopted in the Russian Federation, with primary prevention being one of its key components. However, studies in this area, including municipal-level modeling, are scarce. This work is useful for identifying the relationship between cancer prevalence in a territory and a set of contributing factors. The aim of the study is to develop a predictive regression model. The empirical basis for the model is a sample of 56 observations representing municipalities of the Altai Territory, most of which are rural areas. The results are practically applicable, as they rely on open official data, and the model's accuracy is sufficiently high. The dependent variable is the number of cancer patients registered at the end of year t. The observations include five factors introduced with different time lags; three of them underwent nonlinear transformation. Additionally, two qualitative factors characterizing territorial features were included, with their categories encoded by three dummy variables. A linear regression model was estimated using ordinary least squares. The resulting model achieved a mean absolute percentage error (MAPE) of less than 1%. In external validation on other municipalities, the MAPE ranged from 1.5 % to 2.4 %. The model enables one-year-ahead forecasts of cancer prevalence for a large number of municipalities in Russia. Forecasting examples are illustrated with graphs for seven cities in the Volga region and two territories in the Krasnoyarsk region over several years. Such forecasts are valuable for designing health, social, and environmental policies at the municipal level.

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