Analysis of income inequality measures on human immunodeficiency virus mortality: a spatiotemporal Bayesian perspective

type="main" xml:id="rssa12062-abs-0001"> Social, economic, environmental and behavioural factors impacting health are well recognized in the literature. We consider the use of various income inequality measures in addition to a poverty measure and investigate their effects on human immunodeficiency virus (HIV) mortality. In doing so, we make use of models that can capture zero inflation and spatiotemporal effects. The research is motivated by the lack of studies from an inference and modelling perspectives in explaining HIV mortality by using measures that take into account socio-economic status as well as time and location. Such a study can help policy makers to identify cases of environmental injustice and areas of outstanding health risk to assist in resource allocation problems. In our numerical example, we make use of mortality data obtained for the state of New York, estimate model parameters from a Bayesian inference perspective and discuss the implications and interpretations of various income inequality measures. The methodological novelty of our study is the introduction of a zero-inflated Poisson model that can account for both spatial and temporal effects across 5 years (2000–2004). The practical novelty of our study is its attempt to find inequality measures which can improve our understanding of HIV mortality risk. Our results indicate that, for the data at hand, if inequality is calculated on the basis of county-specific income shares rather than the whole state, HIV mortality can be better explained. In addition, accounting for temporal and spatial effects was found to contribute to our understanding of HIV mortality risk.