Twenty-first-century medicine faces a paradox: never before have we had so much access to health information, yet we still struggle with recurring outbreaks, epidemics, and the rise of chronic diseases. In this context, statistical modeling emerges as an essential tool to transform large volumes of data into knowledge capable of saving lives.
Statistics have always been present in medicine, but their role has taken on a new dimension with the expansion of clinical, environmental, and social databases. Today, we have decades of time series data on diseases such as tuberculosis, dengue, or leptospirosis, in addition to climatic and socioeconomic variables that influence their occurrence. The challenge is not only to describe the past, but also to predict future scenarios and, in doing so, guide preventive measures before problems arise.