Lung-Chang Chien and  Francisco Sy (Department of Environmental and Occupational Health) co-authored "Surveillance on the endemic of Zika virus (ZIKV) infection by meteorological factors in Colombia: a population-based spatial and temporal study" in BMC Infectious Diseases to propose an early warning surveillance system for ZIKV infection by using a spatiotemporal modeling approach, which uses meteorological measurement to predict the outbreak of ZIKV infection. They applied the method in Colombia, one of the most prevalent countries suffering ZIKV since 2015.

They determined three weather conditions in terms of temperature, average humidity, and rainfall from 15 meteorological measurements to best predict ZIKV outbreaks. The surveillance system can predict ZIKV outbreaks at least 14 weeks earlier. The spatial analysis resulted in that the high-risk areas are most likely located between the equator and 6 degrees north. This is the first epidemiological research for ZIKV infection prediction in a large space-time scale, and the early warning surveillance system can be built with flexible modifications in any other area with a high prevalence of ZIKV infection.