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0425 An occupational epidemiology model for climate change impact assessment
  1. Tord Kjellstrom1,2,
  2. Matthias Otto3,
  3. Bruno Lemke3,
  4. Chris Freyberg4,
  5. David Briggs5,
  6. Lauren Lines6
  1. 1Centre for Technology Research and Innovation, Limassol, Cyprus
  2. 2Australian National University, Canberra, Australia
  3. 3Nelson-Marlborough Institute of Technology, Nelson, New Zealand
  4. 4Massey University, Palmerston North, New Zealand
  5. 5Imperial College, London, UK
  6. 6Canterbury University, Christchurch, New Zealand


Thermal physiology science shows the health threats to workers caused by exposure to heat when doing heavy physical labour. Climate change increases environmental heat levels in most of the world and it is a key issue for climate change and health research. Our model links climate and workforce data (current and predicted) and estimates work capacity loss at individual and population level and related economic loss. The model incorporates climate conditions, population estimates, workforce distributions, heat exposure estimates, exposure-response relationships, and socio-economic impact functions. The basis of the model is occupational epidemiology.

Much of the data upon which heat stress health risk functions are based comes from thermal physiology laboratory research. While this research has provided valuable information about human function at different heat exposures, the individuals studied are generally not the same mix of ages and physical conditions of typical working populations. Very few published studies have included the quantitative occupational epidemiology analysis needed for climate change related health risk assessments. For example, different model settings produce annual moderate intensity work hours lost due to heat (in the shade) by the 2050s at 0.7%–1.6% for USA and 1.1%–3.0% for China. Many of these lost hours will reduce the annual GDP, estimated at 34 trillion USD in the USA and 58 trillion in China (2050). Even a small loss creates many billion USD of economic losses. Our model can identify evidence missing for reducing the uncertainties in impact estimates, which can guide decisions about climate change mitigation and adaptation.

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