Author:
Cardenas Rocio,Hussain-Alkhateeb Laith,Benitez-Valladares David,Sánchez-Tejeda Gustavo,Kroeger Axel
Abstract
Abstract
Background
In the Americas, endemic countries for Aedes-borne diseases such as dengue, chikungunya, and Zika face great challenges particularly since the recent outbreaks of CHIKV and ZIKV, all transmitted by the same insect vectors Aedes aegypti and Ae. albopictus. The Special Program for Research and Training in Tropical Diseases (TDR-WHO) has developed together with partners an Early Warning and Response System (EWARS) for dengue outbreaks based on a variety of alarm signals with a high sensitivity and positive predictive value (PPV). The question is if this tool can also be used for the prediction of Zika and chikungunya outbreaks.
Methodology
We conducted in nine districts of Mexico and one large city in Colombia a retrospective analysis of epidemiological data (for the outbreak definition) and of climate and entomological data (as potential alarm indicators) produced by the national surveillance systems for dengue, chikungunya and Zika outbreak prediction covering the following outbreak years: for dengue 2012–2016, for Zika 2015–2017, for chikungunya 2014–2016. This period was divided into a “run in period” (to establish the “historical” pattern of the disease) and an “analysis period” (to identify sensitivity and PPV of outbreak prediction).
Results
In Mexico, the sensitivity of alarm signals for correctly predicting an outbreak was 100% for dengue, and 97% for Zika (chikungunya data could not be obtained in Mexico); the PPV was 83% for dengue and 100% for Zika. The time period between alarm and start of the outbreak (i.e. the time available for early response activities) was for Zika 4–5 weeks. In Colombia the sensitivity of the outbreak prediction was 92% for dengue, 93% for chikungunya and 100% for Zika; the PPV was 68% for dengue, 92% for chikungunya and 54% for Zika; the prediction distance was for dengue 3–5 weeks, for chikungunya 10–13 weeks and for Zika 6–10 weeks.
Conclusion
EWARS demonstrated promising capability of timely disease outbreak prediction with an operational design likely to improve the coordination among stakeholders. However, the prediction validity varied substantially across different types of diseases and appeared less optimal in low endemic settings.
Funder
“Formación de Capital Humano de Alto Nivel para el Departamento de Norte de Santander”
German Research Foundation (DFG) and the University of Freiburg, funding programme Open Access Publishing.
TDR-IHM-PAT
Universitätsklinikum Freiburg
Publisher
Springer Science and Business Media LLC
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