Health impact modelling for UVR and non-melanoma skin cancer
- The text on this page is taken from an equivalent page of the IEHIAS-project.
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.
Here, the methods used to model non-melanoma skin cancer (BCC and SCC) are described.
Explanation of the method
The assessment model utilised 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).
Calculation was done by combining modelled changes in ambient UVR (annual erythemal dose) with exposure-response functions for SCC and BCC (incidence) and (future) population estimates. ERFs were based on data provided by Lucas et al (2006), using ambient erythemally weighted UVR as the exposure metric.
Several runs of the health impact model were conducted to repersent the different scenarios and model assumptions (Table 1). The baseline model and model 1 use the baseline incidence rates per age group and gender. For model 2, future incidence rates per age group and gender are calculated by applying ERF and modelled change in ambient UVR to the baseline incidence rates. The (future) incidence rates are 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.
| Model run | Incidence/mortality rate | Population |
|---|---|---|
| Baseline model (2000) | Baseline incidence/mortality rates | Baseline population size and structure |
| Model 1 (2030 and 2050): population change only | Baseline incidence/mortality rates remain unchanged. | Future population size and structure: SRES A2 and B1 |
| Model 2 (2030 and 2050): population change combined with changes in ambient UVR | Future incidence rate is affected by changes in ambient UVR levels: SRES A2 and B1 | Future population size and structure: SRES A2 and B1 |
Current and future mortality (rates) per age group and gender were calculated using the age-specific incidence-mortality ratios, based on Lucas et al (2006).
Attributable incidence and mortality were calculated using the upper estimate of population attributable fractions (PAF) as reported by the WHO (Lucas et al. 2006). The upper PAF estimate for BCC is 0.9, while the lower estimate is 0.5. The upper PAF estimate for SCC is 0.7, while the lower estimate is 0.5.
Details of the models are given below.
Attributable incident cases at baseline
Attributable number of deaths at baseline
|
| The baseline incidence and mortality rates are combined with future population projections for A2 en B1 in order to explore the effects of population change only.
Model 1: future attributable incident cases for selected scenarios
Model 1: future attributable number of deaths for selected scenarios
|
| The future incidence and mortality rates are combined with future population data.
Model 2: future attributable incident cases for selected scenarios
Model 2: future attributable number of deaths for selected scenarios
|
where:
Population(baseline)x = population size at baseline (in 100000), age/gender group x
Population (scenario)x = population size (in 100000) in the selected scenario, age/gender group x
I(baseline)x = number of incident cases at baseline, age/gender group x
I(scenario)x = number of incident cases in the selected scenario, age/gender group x
i(baseline)x = baseline incidence rate per 100000, age/gender group x
i(scenario)x = incidence rate per 100000 in the selected scenario, age/gender group x
M(baseline)x = number of deaths at baseline, age/gender group x
M(scenario)x = number of deaths in the selected scenario, age/gender group x
m(baseline)x = baseline mortality rate per 100000, age/gender group x
m(scenario)x = mortality rate per 100000 in the selected scenario, age/gender group x
imr= incidence: mortality ratio
BAFx = biological amplification factor, age/gender group x
PAF= population attributable fraction, UVR
E(baseline)= modelled ambient UVR at baseline
E(scenario) = modelledambient UVR in selected scenario
Selected scenarios: SRES B1 2030, SRES B1 2050, SRES A2 2030, SRES A2 2050
References
- Lucas, R., T. McMichael, et al. 2006 Solar ultraviolet radiation: global burden of disease from solar ultraviolet radiation. Geneva: World Health Organization.
See also
- Changing ambient UVR and future melanoma skin cancer
- Changing ambient UVR and future non-melanoma skin cancer
