While tools available at the time were inadequate for predicting the 2015 Zika (ZIKV) outbreak, a new seasonal forecasting system now available to researchers probably could have detected warning signs of an impending epidemic, according to a presentation on Monday at TropMed17.
Anna Stewart-Ibarra, of the State University of New York Upstate Medical University, presented a study in which researchers employed a new disease forecasting tool that focuses on climate conditions to show that the Zika outbreak could have been predicted at least one month prior to its arrival. The system they used is one of a growing number of approaches that connect climate to health to improve disease risk assessments. And with the impact of global warming looming large, there is considerable interest in the public health community in developing climate models that can generate clues about an impending outbreak.
What exactly links ZIKV and climate change together? Mosquitoes. Serving as a vector for the disease, ZIKV has been seen mainly in geographical locations hospitable to the Aedes aegypti mosquito. Aedes prefers warm and wet climates and typically inhabits human-populated urban locations.
While Stewart-Ibarra’s study demonstrated that an early warning system is possible, she said there are too many factors that influence the arrival of an epidemic to utilize the model as a formal predictive tool. But she believes it is a useful guide for public health interventions and policy. Regardless, she believes it’s time to start investing more in work that explores the link between climate and disease.
Stewart-Ibarra finished her presentation with a sobering reminder. She said that these “fancy” predictive models are only as good as the community’s ability to respond to their warnings. She noted that it is ultimately the “social climate” on the ground that has the biggest influence on epidemic severity.
This blog was written by Paris Hantzidiamantis, SUNY Upstate Medical University
He is attending #TropMed17 as Benjamin H. Kean Travel Fellow in Tropical Medicine.