Recent El Niño events have emphasized the need to develop modelling techniques to assess climate-related health events. Experts agree that climate changes affect the spread of infectious diseases and that the geographic range of infectious diseases may expand as a result of these changes. Nevertheless, the world health modelling community cannot yet predict, with reasonable accuracy, when or where exactly these effects will occur or how large the threat of these diseases will be to particular populations. This study compared the spatiotemporal patterns of influenza mortality risk in the state of California during El Niño vs normal weather periods. By applying a stochastic methodology to county-specific mortality data, various sources of uncertainty were accounted for, and informative influenza mortality maps and profiles were generated. This methodology enabled the detection of significant effects of climate change on the influenza risk distributions. Geographical maps of risk variation during El Niño differed from those during normal weather, the corresponding covariances exhibited distinct space-time dependence features, and the temporal mean mortality profiles were considerably higher during normal weather than during El Niño. These rather unexpected results of spatiotemporal analysis are worth further investigation that seeks substantive and biologically plausible explanations. The findings of this study can offer a methodological framework to evaluate public health management strategies.