Temperature Stress Mortality Simulator

Temperature Stress Mortality Simulator: for the older (70+ years) population of West Dorset, UK using the UKCP09 SRES A1B Emission Scenario.

Temperature Stress Mortality Simulator: for the older (70+ years) population of West Dorset, UK using the UKCP09 SRES A1B Emission Scenario.
This simulator allows interactive exploration of future temperature stress mortality (both heat and cold) on the older population of West Dorset, England.
This simulator is driven using a future climate scenario (UKCP09) that is the basis of much climate adaptation policy in the United Kingdom. It is 'downscaled' to the West Dorset region producing plausible daily temperature values for both the climate scenario (2044) and a control period (contemporary observed climate).
Simulated climate data and scenarios details are found here.
The climate is not the only thing that is forecast to change in West Dorset by 2044...
The population of West Dorset, like that of the United Kingdom is ageing. In addition to an aging population, there has been a retirement migration movement to the Dorset region for many years. This is likely to continue.
Population projection data, from the Office of National Statistics, is detailed in this folder.
The climate is expected to warm and the population is expected to age.
Human physiology responds to ambient temperatures. If it is too warm or too cold the human body is stressed. This is most noticeable during major heatwaves when most of the population can feel the 'heat stress'.
However, temperature stress occurs far more frequently that we might think -- and in Dorset at almost any time of year. Additionally, as we age, we tend to 'feel' the cold or heat more. In other words, we experience more temperature stress.
We have adapted a model that estimates the mortality associated with temperature stress in the West Dorset climate. It uses a 'base mortality rate' (more on this later) for a population to estimate the temperature stress related 'excess mortality'. This model shows that for every 1 degree C in temperature over either a heat or cold threshold excess mortality increases by 2%. This is the fundamental relationship upon which this simulator is based.
The relationship between temperature and the base mortality rate is how we define 'temperature stress'. But where do these 'base mortality rates' come from?
Base mortality rates are produced in the United kingdom for different groups by age, gender and socio-economic class (SEC), bacause it is well established that there are significant inequalities across these groups.
This simulator allows the user to set the age group (4 groups for the over 70+ population are available), sex and socio-economic class (SEC 1-7 is from highest to lowest and 8 is for all classes).
It is worth noting at this point that even in a warmer West Dorset of 2044, mortality from cold stress will still be much higher than mortality from heat stress. Counter intuitive perhaps, but true. Of course excess mortality due to cold stress will be lower in the future (although still much higher than heat stress). More on this later -- it has implications for public health interventions.
There are four 'daily excess mortality' values estimated: excess mortality from future heat and cold stress and for comparison 'control excess mortalities' are also estimated.
You can compare these sources of excess mortality as they accumulate over the simulation period.
So what public health interventions might be taken in order to assist the target population in adapting to more heat stress?
You have the option of trialling an intervention for either heat or cold stress, but not both at the same time. The default setting is for NO intervention. 'Intervention Targeting' is the variable used to set which intervention will be made.
All public health interventions have three basic variables: the proportion of the target population you can reach, the proportion of the population that comply with the intervention and the efficacy (how effective it is at doing what it is supposed to do) of the intervention.
This 'simulate' button produces the default simulation for a population with all age groups, all socio-economic classes and all both sexes included as a single population. Additionally, there are 10 years of simulated temperature data available (this default simulation setting uses the first 365 days). However, the 'Settings' button at the top of the window allows the user to set the start and duration of the simulation period. The user will be presented with two daily excess mortality graphs (one for the future and one for the control), a combined accumulated deaths (both future and control) and a table of accumulated deaths.
Do you see the three graph 'tabs' above the graph? You can move between the visuals during the simulation. You can change the speed of the simulation and rerun it.
ACKOWLEDGEMENTS: We would like to thank Communities Living Sustainably for funding this project from a Big Lotteries grant and all my colleagues at Dorset Public Health who made this project happen -- Chris Ricketts wrote the proposal and guided its early development, Rebecca Pearce managed the project and Dave Lemon undertook the modelling work to adapt temperature stress to West Dorset.
The introduction to this model is now complete. You can 'Exit Story' (bottom left of screen) and explore the model, it's variables and its construction at your own pace. If you are unfamiliar with the Insight Maker modelling environment, you may wish to further explore that -- all models are open source -- set up your own free account to copy and modify this or any model for your own use and share with colleagues.

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