This paper presents an approach for predicting the self-rated health of individuals in a future population utilising the individuals' socio-economic characteristics. An open-source microsimulation is used to project Ireland's population into the future where each individual is defined by a number of demographic and socio-economic characteristics. The model is disaggregated spatially at the Electoral Division level, allowing for analysis of results at that, or any broader geographical scales. Ordinal regression is utilised to predict an individual's self-rated health based on their socio-economic characteristics and this method is shown to match well to Ireland's 2022 distribution of health statuses. Due to differences in the health status distributions of the health microdata and the national data, an alignment technique is proposed to bring predictions closer to real values. It is illustrated for one potential future population that the effects of an ageing population may outweigh other improvements in socio-economic outcomes to disimprove Ireland's mean self-rated health slightly. Health modelling at this kind of granular scale could offer local authorities a chance to predict and combat health issues which may arise in their local populations in the future.

翻译：本文提出了一种利用个体社会经济特征预测未来人口自评健康状况的方法。通过开源微观模拟技术对爱尔兰未来人口进行预测，其中每个个体由多项人口统计与社会经济特征定义。该模型在选举分区层面进行空间解构，支持在该层级或更广泛地理尺度上分析结果。研究采用序数回归方法，依据个体社会经济特征预测其自评健康状况，该方法被证明与爱尔兰2022年健康状况分布高度吻合。针对健康微观数据与国家数据在健康状况分布上的差异，本文提出一种校准技术以提升预测值的真实性。通过对一个潜在未来人口的模拟表明：人口老龄化效应可能抵消社会经济状况的其他改善，导致爱尔兰平均自评健康水平轻微下降。此类精细化健康建模可为地方当局提供预测和应对未来辖区人口健康问题的决策支持。