Analyzing climate variations at multiple timescales can guide Zika virus response measures

Gigascience. 2016 Oct 6;5(1):1-6. doi: 10.1186/s13742-016-0146-1.

Abstract

Background: The emergence of Zika virus (ZIKV) in Latin America and the Caribbean in 2014-2016 occurred during a period of severe drought and unusually high temperatures, conditions that have been associated with the 2015-2016 El Niño event, and/or climate change; however, no quantitative assessment has been made to date. Analysis of related flaviviruses transmitted by the same vectors suggests that ZIKV dynamics are sensitive to climate seasonality and longer-term variability and trends. A better understanding of 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 the extreme climate anomalies observed in most parts of South America during the current epidemic are not caused exclusively by El Niño or climate change, but by a combination of climate signals acting at multiple timescales. In Brazil, the dry conditions present in 2013-2015 are primarily explained by year-to-year variability superimposed on decadal variability, but with little contribution of long-term trends. In contrast, the warm temperatures of 2014-2015 resulted from the compound effect of climate change, decadal and year-to-year climate variability.

Conclusions: ZIKV response strategies made in Brazil during the drought concurrent with the 2015-2016 El Niño event, may require revision in light of the likely return of rainfall associated with the borderline La Niña event expected in 2016-2017. Temperatures are likely to remain warm given the importance of long term and decadal scale climate signals.

Keywords: Brazil; Climate; Climate change; Decadal; Drought; El Niño; Epidemic; Inter-annual; Vector control; Zika virus.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Brazil / epidemiology
  • Climate Change*
  • Droughts
  • El Nino-Southern Oscillation
  • Humans
  • Interrupted Time Series Analysis
  • Zika Virus / pathogenicity
  • Zika Virus Infection / epidemiology*