Predictability of tick-borne encephalitis fluctuations

Abstract

SUMMARYTick-borne encephalitis is a serious arboviral infection with unstable dynamics and profound inter-annual fluctuations in case numbers. A dependable predictive model has been sought since the discovery of the disease. The present study demonstrates that four superimposed cycles, approximately 2·4, 3, 5·4, and 10·4 years long, can account for three-fifths of the variation in the disease fluctuations over central Europe. Using harmonic regression, these cycles can be projected into the future, yielding forecasts of sufficient accuracy for up to 4 years ahead. For the years 2016–2018, this model predicts elevated incidence levels in most parts of the region.