Supporting data for "Analyzing climate variations on multiple timescales can guide Zika virus response measures"
Dataset type: Climate
Data released on September 20, 2016
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.
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.
Here we provide the data upon which we based our interpretations. As described in the manuscript these have been aquired from the full data, which are available at http://iridl.ldeo.columbia.edu/maproom/Health/index.html and http://datoteca.ole2.org/maproom/Sala_de_Salud-Clima/index.html.es
Read the peer-reviewed publication(s):
Muñoz, Á. G., Thomson, M. C., Goddard, L., & Aldighieri, S. (2016). Analyzing climate variations at multiple timescales can guide Zika virus response measures. GigaScience, 5(1). doi:10.1186/s13742-016-0146-1