Minimização de anos de vida perdidos em eventos epidêmicos considerando aspectos econômicos

Abstract

The COVID-19 pandemic has caused huge human and economic losses. With the rapid spread and little information on the onset of the disease, governments around the world have adopted several non-pharmaceutical interventions to try to mitigate or suppress infections. In order to measure the human and economic losses caused by the pandemic from a perspective of impacts on human health, the Years of Life Lost indicator was used. Therefore, this study aimed to develop a mathematical model to minimize the years of life lost in situations of epidemic events, which considers the adoption of non-pharmaceutical interventions and their effects on the economy. Following the guidelines of the PRISMA statement, a systematic review of the literature was conducted to find models that could serve as a basis for developing the mathematical model proposed in this work. The proposed model determines the ideal allocation of non-pharmaceutical interventions and considers the capacities of health resources, to minimize the Years of Life Lost in a population, resulting from both human and economic losses caused by COVID-19. The developed model was formulated as a Mixed Integer Nonlinear Programming, which was transformed into a Mixed Integer Linear Programming model through the linearization of the quadratic terms. The model was applied using real data from the COVID-19 pandemic for the 27 federated units of Brazil, considering three different scenarios. The results indicate the predominance of Years of Life Lost resulting from economic losses. The results highlight the model’s usefulness guiding decision-makers regarding a portfolio of non-pharmaceutical interventions, considering the impact of these decisions on health and the economy, to minimize potential impacts on human health. The model and the analyses can also be extended to manage eventual future epidemics.