Evolution Scenarios and Mitigation Strategies for COVID-19 in Peru, from the Complexity Approach and Agent-Based Modeling

Abstract

The COVID-19 pandemic in Peru began during March 2020, generating a multidimensional crisis that has claimed 198,621 lives as of 8 September 2021. This study presents the simulation of multiple agents showing the emerging dynamics of the interaction and influence of a subset of biological and social factors in the development of the COVID-19 pandemic in Peru. The model is implemented in NetLogo to simulate different hypothetical scenarios that approximate the real behavior of the interaction between the virus, humans and their environment, adjusting demographic, medical, social, and institutional parameters associated with the evolution and spread of the virus. Four scenarios for the evolution of COVID-19 in Peru are investigated, with different levels of restriction on population mobility. This makes it possible to understand the country’s situation, the complex dynamics of the pandemic and simulate in a multidimensional context the non-linear effect of explanatory variables on the evolution of COVID-19. Social isolation is the measure that has the greatest impact on the behavior of the spread of the virus and, therefore, the one that most helps to prevent and slow down the spread of the infection.