Application of type-2 heptagonal fuzzy sets with multiple operators in multi-criteria decision-making for identifying risk factors of Zika virus

This study introduces an advanced decision-support system for healthcare professionals to systematically identify and prioritize Zika virus risk factors. By leveraging type-2 heptagonal fuzzy sets, the framework effectively captures and processes uncertainty stemming from incomplete epidemiological data, imprecise expert assessments, and subjective linguistic evaluations. The consistency of rankings across multiple MCDM methods, along with sensitivity analysis confirming their stability, demonstrates the model's reliability. These findings provide a scientifically grounded tool for improving risk analysis and strategic public health interventions.