The primary motivation for using complex designs is to enhance the validity and reliability of study outcomes. Simple designs often fall short in accounting for confounding variables, biases, and the dynamic nature of disease transmission. Complex designs help mitigate these issues by incorporating multiple layers of data and analytical approaches, enabling a more comprehensive understanding of the epidemiological phenomena.
