Detecting and Attributing Health Burdens to Climate Change

Environ Health Perspect. 2017 Aug 7;125(8):085004. doi: 10.1289/EHP1509.

Abstract

Background: Detection and attribution of health impacts caused by climate change uses formal methods to determine a) whether the occurrence of adverse health outcomes has changed, and b) the extent to which that change could be attributed to climate change. There have been limited efforts to undertake detection and attribution analyses in health.

Objective: Our goal was to show a range of approaches for conducting detection and attribution analyses.

Results: Case studies for heatwaves, Lyme disease in Canada, and Vibrio emergence in northern Europe highlight evidence that climate change is adversely affecting human health. Changes in rates and geographic distribution of adverse health outcomes were detected, and, in each instance, a proportion of the observed changes could, in our judgment, be attributed to changes in weather patterns associated with climate change.

Conclusions: The results of detection and attribution studies can inform evidence-based risk management to reduce current, and plan for future, changes in health risks associated with climate change. Gaining a better understanding of the size, timing, and distribution of the climate change burden of disease and injury requires reliable long-term data sets, more knowledge about the factors that confound and modify the effects of climate on health, and refinement of analytic techniques for detection and attribution. At the same time, significant advances are possible in the absence of complete data and statistical certainty: there is a place for well-informed judgments, based on understanding of underlying processes and matching of patterns of health, climate, and other determinants of human well-being. https://doi.org/10.1289/EHP1509.

Publication types

  • Review

MeSH terms

  • Canada / epidemiology
  • Climate Change*
  • Environmental Health* / methods
  • Europe / epidemiology
  • Extreme Heat / adverse effects*
  • Humans
  • Lyme Disease / epidemiology*
  • Lyme Disease / microbiology
  • Vibrio Infections / epidemiology*
  • Vibrio Infections / microbiology