Health impact modelling: ultraviolet radiation and melanoma skin cancer

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Main message:
Question:

What was the overall health impact of exposures to ultra-violet radiation (UVR) under different climate change scenarios?

Answer:

Given current knowledge, The assessment considered two sets of scenarios for the years 2030 and 2050: the IPCC SRES B1 scenario and SRES A2 scenario.Results suggest that further knowledge about the uncertain variables considered very likely would not have changed the decision


Scope

As part of the EU-funded INTARESE project, which contributed to the development of this Toolbox, a case study was carried out to assess health impacts of exposures to ultra-violet radiation (UVR) under different climate change scenarios.

The assessment considered two sets of scenarios for the years 2030 and 2050: the IPCC SRES B1 scenario and SRES A2 scenario. Health outcomes considered were basal cell carcinoma (BCC), squamous cell carcinoma (SCC) and malignant melanoma (CMM). Changes in UVR exposure were estimated, taking account of changes in stratospheric ozone associated with decreasing emission of ozone depleting substances and increasing emissions of CH4 and N2O. Allowance was also made for future demographic changes.

Below the methods used to model non-melanoma skin cancer are decribed. Details of the working procedures are given in the attached spreadsheet.


Explanation

INTARESE PROJECT-WP3.7-UVR

Example WP3.7-UVR melanoma health impact model (incidence, mortality) for Helsinki

We explore the effects of changing exposure to ambient ultraviolet radiation (UVR) on malignant melanoma, accounting for the recovery of the ozone layer due to decreasing emission of ODS. This recovery of the ozone layer is also affected by future emissions of CH4 and N20 (IPCC 2005). We include the following cities in our analyses: Rome, London, Helsinki. Baseline year for the assessment is 2001, while future health effects are explored for 2030 and 2050. The selected future scenarios are based on the SRES emissions scenarios developed by the Intergovernmental Panel on Climate Change (IPCC) (IPCC 2000). Health impact model 1 only accounts for future changes in population size and structure. Health impact model 2 accounts for these future demographic changes combined with the anticipated changes in stratospheric ozone and, accordingly, ambient UV.

We used the SRES emissions scenarios developed by the IPCC (2000) that quantify the emissions and concentrations of greenhouse gases and ozone depleting substances over the coming century, and their key drivers (population projections, economic growth, energy choices). Of the four SRES scenarios, we explored A1 and B2. For our assessment, the following scenario characteristics are important: see Table on the left.

SRES population scenarios were downscaled from the regional to the city-level: See factsheet WP3.7 population scenarios , available in the INTARESE toolbox.

Note: This spreadsheet includes links to the separate DALY spreadsheets that were developed in INTARESE WP3.7-UVR. See e.g. - Example WP3.7-UVR melanoma DALY calculations model for Helsinki, baseline (Excel), [LINK] available in INTARESE toolbox

IMPORTANT: This example spreadhseet (Helsinki) accompanies the WP3.7-UVR assessment report. It is not recommended to use (parts of this spreadsheet, without consulting the full description of the WP3.7-UVR assessment.

Explanation of the Method

The assessment model used Excel as a platform, in order to calculate the number of incident cases and the number of deaths at baseline. Calculations were performed for 5-year age groups (up to 85+), both for males and females, in three study areas (London, Rome and Helsinki).

In each case, future changes in ambient UVR (annual erythemal dose) were combined with exposure-response functions (ERF) for melanoma (incidence) and (future) population estimates. The ERFwas derived from Scotto and Fears’ (1987) estimation of the biological amplification factor (BAF= relative change in disease risk due to a 10% increase in UVR exposure), adjusted for age (Table 1).


Age Group Sex Baseline

Population in thousand

B1 2030

Population in thousand

B1 2050

Population in thousand

A2 2030

Population in thousand

A2 2050

Population in thousand

0-4 m 14.6 12.0 8.3 15.3 12.5
5-9 m 14.8 10.9 7.1 13.8 10.7
10-14 m 13.4 10.4 8.6 13.1 12.0
15-19 m 13.4 10.3 11.1 12.5 14.6
20-24 m 20.7 15.6 16.8 17.7 21.2
25-29 m 24.3 23.9 20.2 23.9 25.3
30-34 m 24.5 24.4 16.4 24.4 20.5
35-39 m 23.0 24.2 13.4 24.2 20.5
40-44 m 19.6 22.5 15.4 22.5 17.3
45-49 m 18.0 20.7 21.8 20.7 21.8
50-54 m 20.0 19.4 21.8 19.4 21.8
55-59 m 15.3 15.4 23.6 15.4 23.6
60-64 m 10.8 16.4 18.0 16.4 18.0
65-69 m 8.8 15.3 10.6 15.3 10.6
70-74 m 7.1 12.3 14.4 12.3 14.4
75-79 m 4.7 9.9 13.8 9.9 13.8
80-84 m 2.7 8.7 7.6 8.7 7.6
85+ m 1.8 5.5 13.4 5.5 13.4
all m 257.4 277.9 262.0 291.0 295.1
0-4 f 14.1 12.2 8.1 15.4 12.6
5-9 f 14.2 11.2 7.3 14.1 11.0
10-14 f 12.7 10.6 8.7 13.4 12.3
15-19 f 13.8 11.1 11.8 13.3 15.4
20-24 f 23.9 19.7 20.7 22.3 26.1
25-29 f 25.6 26.5 23.1 26.5 29.0
30-34 f 24.8 25.0 17.3 25.0 21.6
35-39 f 23.2 24.3 13.1 24.3 15.7
40-44 f 20.5 22.7 15.1 22.7 16.9
45-49 f 20.6 20.7 22.8 20.7 22.8
50-54 f 23.4 18.6 25.5 18.6 25.5
55-59 f 18.2 15.5 25.7 15.5 25.7
60-64 f 13.8 18.3 16.4 18.3 16.4
65-69 f 12.0 18.2 10.2 18.2 10.3
70-74 f 11.6 16.1 16.3 16.1 16.3
75-79 f 10.5 15.3 16.2 15.3 16.2
80-84 f 7.7 15.0 11.0 15.0 11.0
85+ f 7.6 12.8 28.7 12.8 28.7
all f 298.1 313.6 298.1 327.5 333.5


Incident cases Number of deaths
0.00 0.00
0.00 0.00
0.07 0.00
0.07 0.01
0.46 0.08
0.68 0.12
1.27 0.28
1.82 0.41
2.39 0.68
3.45 0.97
5.01 1.42
3.97 1.27
2.54 0.81
4.31 1.58
3.32 1.22
2.06 1.26
1.59 0.97
34.82 11.50
0.00 0.00
0.13 0.01
0.00 0.00
0.22 0.02
0.72 0.06
1.61 0.13
1.96 0.24
2.74 0.34
2.64 0.33
2.02 0.36
3.58 0.63
4.16 0.74
3.70 0.89
3.47 0.83
3.20 1.05
3.45 1.13
2.85 1.44
2.81 1.42
39.25 9.63


Face, head or neck (FHN), upper extremity (UE) * Trunk & lower extremity (TL) **
Male 8% 6%
Female 10% 5%

*higher risk estimate; standard model setting;** lower risk estimate


Several health impact model runs were carried out (Table 2). The baseline model and model 1 used the baseline incidence rates per age group and gender. For model 2, future incidence rate per age group and gender were calculated by applying the BAF and the future percental change in modelled ambient UVR to the baseline incidence rates. The (future) incidence rates were combined with the baseline and future population estimates in order to calculate skin cancer incidence (number of cases).

The results were then combined with the baseline and future population estimates in order to calculate skin cancer incidence (number of cases). Thus:

  • Baseline model: baseline incidence rates and baseline population estimates are applied.
  • Model 1: baseline incidence rates and future population estimates are applied.
  • Model 2: estimated future incidence rates and future population estimates are applied.


See Also


Reference

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