Modeling COVID-19 response in Cuba: a hybrid approach combining agent-based modeling and time series analysis

Population Health Metrics. 2025. Vol. 23. Article 71.

Orlando G., Bufalo M., Назарова В. В.

The COVID-19 pandemic has disproportionately impacted vulnerable populations, such as low-income households, exacerbating existing health and economic challenges. In Cuba, the crisis exposed the effects of long-standing economic difficulties, worsened by sanctions, but the country’s robust public health system and independent vaccine development enabled an effective response. This study addresses the gap in understanding how socio- economic factors and individual behaviors interact to influence disease spread. It proposes a hybrid, efficient, and parsimonious model combining ABM (Agent-Based Modeling) and ARIMAX (AutoRegressive Integrated Moving Average with eXogenous variables) time series analysis to forecast COVID-19 cases, offering valuable insights for policymakers to tailor interventions and enhance crisis management.

Ключевые слова: abm, COVID-19, PCA, ARIMAX, Health Policies