Forecasting the dynamics of the spread of anemia in the regions of Russia based on an agent-based model

Abstract

According to the World Health Organization (World Health Organization, 2019), anemia is a common disease worldwide that affects both developed and developing countries. The causes of anemia vary depending on the geographical location of the state, the sex and age of its inhabitants. However, diet-related iron deficiency anemia remains the leading global cause of anemia (Thejpal, 2015). Experimental and epidemiological evidence suggests that impairments can be reversible through well-chosen measures taken by the health care system . These measures should include supplementing the diet with foods rich in micro- and macronutrients and vitamins, and fortifying staple foods with micronutrients and supplements (DeMaeyer et al., 2019). The task of implementing a balanced food policy becomes especially urgent in the context of rising food prices and declining incomes of the population during the COVID-19 pandemic, and the directions of such a policy can be state regulation of prices, various types of subsidies to the population, investment support and tax incentives for domestic manufacturers, as well as updating healthy nutrition standards and informing the population about them. The analysis of the whole variety of policy parameters and its possible consequences is a complex task, which requires the use of modern tools, in particular information systems for predicting the consequences of political decisions (Tracy, Cerda, Keyes, 2018). The aim of our study, implemented by an international team of specialists from Russia , India, and the Republic of South Africa, is to create tools for predicting the prevalence of anemia in the BRICS countries, based on agent-based modeling methods . Based on the interaction of various micro-level risk indicators, this method will help develop appropriate intervention strategies to reduce anemia among a vulnerable population. The objectives of the study include the development of the structure and algorithms of the agent-based model, its software implementation and information content, as well as scenario calculations that take into account epidemiological and external economic risks.