A disease cluster (aka, a hot spot) is when a specific type of illness occurs in an isolated area within a given period of time and the number of people with the illness in this area substantially exceeds the disease rate elsewhere. Cluster detection is an essential tool in the public health domain, which has the goal of detecting anomalous areas of heightened disease activity. Clusters have distinctive risks of an event of interest, typically substantially elevated relative to background variation. Systemic lupus erythematosus (SLE) is a complex multisystem autoimmune disease with epidemiologic evidence of association with many environmental factors, but considerable knowledge gaps remain regarding potential mechanisms by which these environmental factors may be involved in the pathogenesis of SLE.

We hypothesize that clusters of disease activity in lupus are associated with atmospheric and environmental factors and propose development and application of spatial-temporal analytical methods of lupus disease activity which would lay the foundation for a new approach in the discovery of potential environmental and atmospheric factors and their role in lupus. The following specific aims are proposed:

Specific Aim 1. Identify environmental, atmospheric, demographic, and other patient level determinants that are predictive of organ specific lupus flares.

Specific Aim 2. Perform spatial-temporal cluster detection analyses on the maps of organ-specific flares

Specific Aim 3. Using the results from Aim 1, repeat the cluster detection analyses from Aim 2 to assess the degree to which environmental, atmospheric, and other variables explain lupus clusters.

The proposed study meets the first Fiscal Year 2018 Lupus Research Program Focus Area, with its goal of understanding lupus disease heterogeneity through cluster analysis, by being an environmental and epidemiological study.

The identification of clusters of organ-specific lupus flares could lay the foundation for a novel approach to the study of environmental factors in lupus. This would potentially open new avenues in the understanding of lupus as an autoimmune disease, it would allow environmental modification as a potential treatment target, it could add an important aspect to lupus trials which may be affected by as yet unrecognized environmental factors, and ultimately it could allow predictive modelling of lupus flares that would revolutionize the approach to treatment.