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Madeline Jarvis-Cross1, Devin Kirk2,3, Leila Krichel1

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Early warning signals (EWS) for climate-mediated epidemics may produce false positives. Our study found EWS were detected even without an epidemic, limiting their reliability for predicting disease outbreaks.

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Area of Science:

  • Ecology
  • Epidemiology
  • Climate Science

Background:

  • Climate change influences parasite transmission and epidemic emergence.
  • Predicting climate-mediated epidemics is crucial for public health and ecological stability.
  • Early warning signals (EWS) are theoretical predictors of epidemic emergence.

Purpose of the Study:

  • To experimentally test the predictive power of EWS for climate-mediated epidemic emergence.
  • To analyze time series data for EWS in a model disease system under varying temperatures.
  • To assess the reliability of EWS in the context of climate change impacts on disease dynamics.

Main Methods:

  • Utilized experimental and simulated time series data of disease spread in Daphnia magna.
  • Manipulated temperature to induce transitions between sub-epidemic and epidemic states.
  • Analyzed time series for the presence of statistical early warning signals (EWS).

Main Results:

  • Early warning signals (EWS) were detected in populations at sub-epidemic temperatures.
  • EWS were also detected in populations experiencing warming treatments that induced epidemic spread.
  • The detection rate of EWS was similar in both sub-epidemic and epidemic conditions.

Conclusions:

  • The experimental detection of EWS in non-epidemic conditions suggests a high rate of false positives.
  • False positives may limit the practical reliability and utility of EWS for predicting climate-mediated epidemics.
  • Further research is needed to refine EWS or develop complementary methods for accurate epidemic prediction.