Health impact modelling: ultraviolet radiation and melanoma skin cancer

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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

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).

	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.

   * Purpose defines the specific information need of the decision-making and the research question that is asked.

Boundaries

   * Boundaries define which parts of the reality are taken into the assessment and which are excluded within 
     spatial, temporal and other dimensions.

Scenarios

   * Scenarios define particular conditions that are of interest irrespective whether they describe 
     reality or not (e.g. what-if scenarios).

Intended users

   * Intended users are those for whom the assessment is made.

Participants

   * Participants are those who may participate in the making of the assessment. 
     The minimum group of people for a successful assessment is always described. 
     If some groups must be excluded, this must be explicitly motivated.

Definition

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Decision variables

   * Decision variables: decisions that are considered.

Indicators

   * Indicators: outcome variables of interest.

Value variables

   * Value variables: value judgements (usually about indicators).

Other variables

   * Other variables: any variables that link to the causal network and are within the boundaries of the assessment.

Analyses

   * Analyses: statistical and other analyses that contain two or more variables, e.g. optimizing.

Indices

   * Indices: lists of particular locations along spatial, temporal, or other dimensions. 

Result

   * Results of indicators and assessment-specific analyses. 

Conclusions

   * Conclusions are based on the results, given the scope.