Risk may be defined as the average probability of disease developing in an individual during a specified time interval. It may be estimated by dividing the number of disease events by the number of subjects at risk in a specified time interval. Yet, drawing individual-level conclusions about risk from group-level data has its limits (Morgenstern 1998).
Relative risk (RR) is often estimated for a sub-group of study subjects as the ratio of that group's average risk to a baseline measure of disease risk. In those cases when an appropriate referent group cannot be identified, either the average risk over the entire set of study subjects or a national average may be used as the baseline risk for comparison.
Some of the spatial methods require an understanding of risk or relative risk as a function of space. Suppose that exposure to a point-source (focus) elevated the risk for a particular type of disease, and distance to the point-source served as a proxy estimate of the amount of exposure experienced. We could create a function by which degree of exposure would be estimated according to distance from the focus (postulated degree of exposure). The RR could peak at the point-source, and decline with increasing distance. It may be difficult to anticipate the appropriate model form, and the fit of the final model to the actual data should be considered. But please note, using the observed spatial disease pattern to estimate the risk or RR function is circular and invalidates statistical inference. A priori knowledge should contribute to the specification of the function parameters.