Skip to main content

PERSPECTIVE article

Front. Trop. Dis.
Sec. Disease Prevention and Control Policy
Volume 5 - 2024 | doi: 10.3389/fitd.2024.1465856
This article is part of the Research Topic Digital Tools and Innovation for the Prevention and Control of Vector-borne Diseases View all 5 articles

A Framework for Early-Detection and Prediction of Dengue Outbreaks for the Republic of Panama

Provisionally accepted
Grimaldo E. Ureña Grimaldo E. Ureña 1Yamilka Diaz Yamilka Diaz 2Sandra Laurence Lopez-Verges Sandra Laurence Lopez-Verges 2Juan M. Pascale Juan M. Pascale 2Javier E. Sanchez-Galan Javier E. Sanchez-Galan 1*
  • 1 Technological University of Panama, Panama, Panama
  • 2 Gorgas Memorial Institute of Health Studies, Panama City, Panama

The final, formatted version of the article will be published soon.

    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, consequently the number of infectious cases increases. DENV is 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 is of the utmost importance by having an early detection system. To tackle this task, we propose an overall surveillance system framework tailored for 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.

    Keywords: Dengue Virus, arboviburs, epidemiological surveillance, outbreak, One Health, Mosquito vectors, Early detection

    Received: 17 Jul 2024; Accepted: 30 Dec 2024.

    Copyright: © 2024 Ureña, Diaz, Lopez-Verges, Pascale and Sanchez-Galan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Javier E. Sanchez-Galan, Technological University of Panama, Panama, Panama

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.