Zika virus early warning system

Florida and Brazil

Zika virus transmission is now a global pandemic, for which the WHO has declared an international emergency. In the U.S., Florida is “ground zero” for Zika, with already hundreds of locally-transmitted cases in multiple counties. While this disease can cause illness and paralysis in adults, it is linked to a variety of devastating birth defects, including brain deformities (microcephaly), frequent seizures, and skeletal abnormalities. However, there is no cure for Zika, and a vaccine is years away. Thus, the only method to reduce the spread of the disease is through timely surveillance and targeted mosquito control.

Therefore, we are developing an early warning system for Zika virus. A collaboration between Prof. Ryan Carney, Prof. Sean Ahearn (CUNY), and several international institutions, this geospatial model will build upon our team’s previously successful results predicting and controlling epidemics of similar mosquito-borne viruses: dengue and West Nile. This model will be implemented in Florida and Brazil, for the early and accurate identification of areas at high risk for Zika virus transmission. Real-time risk maps will be generated and supplied to local agencies, in order to target mosquito control, surveillance, and public education campaigns. Plans also include developing this predictive model into a free, open-source software solution to fight the spread of Zika virus around the world.

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Contact our DYCAST specialist Prof. Ryan Carney: ryancarneyusf.edu

Schematic of the Dynamic Continuous-Area Space-Time (DYCAST) procedure

From: Carney et al 2011 Emerging Infectious Diseases

West Nile virus early warning system (red=high risk, black=human cases).

From: Carney et al 2011 Emerging Infectious Diseases

West Nile virus early warning system (red=high risk, black=human cases).

From: Carney et al 2011 Emerging Infectious Diseases

Open Source


DYCAST 1.0 by Alan McConchie

DYCAST papers

Early warning system for West Nile virus risk areas, California, USA

Carney RM, Ahearn SC, McConchie A, Glaser C, Jean C, Barker C, Park B, Padgett K, Parker E, Aquino E, Kramer V. 2011. Emerging Infectious Diseases 17(8):1445-54. PDF

GIS-based early warning system for predicting high-risk areas of dengue virus transmission, Ribeirão Preto, Brazil

Carney RM. 2010. Masters Thesis, Yale University. PDF

First evidence of West Nile virus amplification and relationship to human infections

Theophilides, C. N., Ahearn, S. C., Binkowski, E. S., Paul, W. S., & Gibbs, K. (2006). International Journal of Geographical Information Science, 20(1):103-115. Link

Identifying West Nile virus risk areas: the dynamic continuous-area space-time system

Theophilides, C. N., Ahearn, S. C., Grady, S., & Merlino, M. (2003). American Journal of Epidemiology, 157(9):843-854. Link

A Comparison of two Significance Testing Methodologies for the Knox Test.

Theophilides, C. N., E. S. Binkowski, S. C. Ahearn, & W. S. Paul. (2008). International Journal of Geoinformatics 4(3).

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