Projecting productivity losses for cancer-related mortality 2011 - 2030

Alison Pearce, Cathy Bradley, Paul Hanly, Ciaran O'Neill, Audrey Alforque Thomas, Michal Molcho, Linda Sharp

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Background: When individuals stop working due to cancer this represents a loss to society – the loss of productivity. The aim of this analysis was to estimate productivity losses associated with premature mortality from all adult cancers and from the 20 highest mortality adult cancers in Ireland in 2011, and project these losses until 2030.

Methods: An incidence-based method was used to estimate the cost of cancer deaths between 2011 and 2030 using the Human Capital Approach. National data were used for cancer, population and economic inputs. Both paid work and unpaid household activities were included. Sensitivity analyses estimated the impact of assumptions around future cancer mortality rates, retirement ages, value of unpaid work, wage growth and discounting.

Results: The 233,000 projected deaths from all invasive cancers in Ireland between 2011 and 2030 will result in lost productivity valued at €73 billion; €13 billion in paid work and €60 billion in household activities. These losses represent approximately 1.4 % of Ireland’s GDP annually. The most costly cancers are lung (€14.4 billion), colorectal and breast cancer (€8.3 billion each). However, when viewed as productivity losses per cancer death, testis (€364,000 per death), cervix (€155,000 per death) and brain cancer (€136,000 per death) are most costly because they affect working age individuals. An annual 1 % reduction in mortality reduces productivity losses due to all invasive cancers by €8.5 billion over 20 years.

Conclusions: Society incurs substantial losses in productivity as a result of cancer-related mortality, particularly when household production is included. These estimates provide valuable evidence to inform resource allocation decisions in cancer prevention and control.
Original languageEnglish
JournalBMC Cancer
Issue number1
Publication statusPublished - 18 Oct 2016

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Export Date: 7 March 2017


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