RT Journal Article SR Electronic T1 Analyzing climate variations on multiple timescales can guide Zika virus response measures JF bioRxiv FD Cold Spring Harbor Laboratory SP 059808 DO 10.1101/059808 A1 Á.G. Muñoz A1 M. C. Thomson A1 L. Goddard A1 S. Aldighieri YR 2016 UL http://biorxiv.org/content/early/2016/08/10/059808.abstract AB Background The emergence of Zika virus (ZIKV) as a public health emergency in Latin America and the Caribbean (LAC) occurred during a period of severe drought and unusually high temperatures. Speculation in the literature exists that these climate conditions were associated with the 2015/2016 El Niño event and/or climate change but to date no quantitative assessment has been made. Analysis of related flaviviruses –such as dengue and chikungunya, which are transmitted by the same vectors– suggests that ZIKV dynamics is sensitive to climate seasonality and longer-term variability and trends. A better understanding the climate conditions conducive to the 2014-2016 epidemic may permit the development of climate-informed short- and long-term strategies for ZIKV prevention and control.Results Using a novel timescale-decomposition methodology, we demonstrate that extreme climate anomalies observed in most parts of South America during the current epidemic are not caused exclusively by El Niño or climate change –as speculated–, but are the result of a particular combination of climate signals acting at multiple timescales. In Brazil, the heart of the epidemic, we find that dry conditions present during 2013-2015 are explained primarily by year-to-year variability superimposed on decadal variability, but with little contribution of long-term trends. In contrast, the extreme warm temperatures of 2014-2015 resulted from the compound effect of climate change, decadal and year-to-year climate variability.Conclusions ZIKV response strategies adapted for a drought context in Brazil during El Niño 2015/2016 may need to be revised to accommodate the likely return of heavy rainfall associated with the probable 2016/2017 La Niña. Temperatures are likely to remain warm given the importance of long term and decadal scale climate signals.