International travelers and genomics uncover a ‘hidden’ Zika outbreak

Nathan D. Grubaugh; Sharada Saraf; Karthik Gangavarapu; Alexander Watts; Amanda L. Tan; Rachel J. Oidtman; Jason T. Ladner; Glenn Oliveira; Nathaniel L. Matteson; Moritz U.G. Kraemer; Chantal B.F. Vogels; Aaron Hentoff; Deepit Bhatia; Danielle Stanek; Blake Scott; Vanessa Landis; Ian Stryker; Marshall R. Cone; Edgar W. Kopp; Andrew C. Cannons; Lea Heberlein-Larson; Stephen White; Leah D. Gillis; Michael J. Ricciardi; Jaclyn Kwal; Paola K. Lichtenberger; Diogo M. Magnani; David I. Watkins; Gustavo Palacios; Davidson H. Hamer; Lauren M. Gardner; T. Alex Perkins; Guy Baele; Kamran Khan; Andrea Morrison; Sharon Isern; Scott F. Michael; Kristian G. Andersen

Infectious disease surveillance of international travelers has long been an effective method to detect pathogens circulating in resource-limited areas (Hamer et al., 2017; Harvey et al., 2013; Leder et al., 2013 Leder et al., , 2017 Wilder-Smith et al., 2012) . We hypothesized that similar frameworks could be leveraged to improve Zika virus surveillance, as many regions in the Americas affected by the epidemic attract large volumes of international visitors from countries with stronger healthcare and surveillance systems (Wilder-Smith et al., 2018) . In this study, we used international travel data, coupled with virus genomics, to detect ongoing Zika virus transmission that was missed by local reporting. We discovered a large Zika outbreak in Cuba that was not reported to PAHO (PAHO, 2017a) or other public health agencies, and thus went undetected to the international community. We show that the outbreak in Cuba peaked in 2017, when the epidemic in the rest of the Americas was waning (PAHO, 2017a) , and estimate that it was as large as those in neighboring countries that occured the year before. By sequencing Zika virus from infected travelers, we also show that the outbreak in Cuba was caused by multiple introductions from elsewhere in the Caribbean and Central America. Overall, our study outlines a framework for how traveler surveillance data, combined with virus genomics, can detect 'hidden' outbreaks and reconstruct transmission dynamics when local data are insufficient.