A framework for the early detection and prediction of dengue outbreaks in the Republic of Panama

The dengue virus (DENV) is endemic in most tropical regions of Central and South America. It is known that when the number of mosquito vectors ( Aedes aegypti and Aedes albopictus) for this disease becomes abundant, the number of infectious cases increases. DENV has been known to be continuously circulating in Panama since 1993, with an increasing number of cases reported in recent years after the COVID-19 pandemic, as well as other vector-borne diseases. Preventing dengue outbreaks by having an early detection system is of the utmost importance. To tackle this task, we propose an overall surveillance system framework tailored to the Panamanian situation but applicable to many countries suffering the same maladies. This manuscript presents a transdisciplinary vision that encompasses aspects of sample management, vector surveillance, sharing of weather information, and georeferencing of cases in a Geographic Information System and defining data-driven software solutions for prediction of possible outbreaks.