The Indian Ocean Dipole (IOD) is a global climate phenomenon that influences the spread of human infectious diseases through climate extremes including droughts and floods. The Dipole Mode Index (DMI), which measures the strength of the IOD, is one of the main indicators of rainfall variability across Australia. Using an ecological, time-series approach we examined the short-term and nonlinear relationship between the DMI and weekly cryptosporidiosis reported from 2001 to 2012 across the temperate, subtropical, and tropical climate zones in Australia, controlling for season, long-term trends, and cryptosporidiosis counts from the past week. The association of DMI with cryptosporidiosis was nonlinear and varied in the short term and by climatic zone. Including cryptosporidiosis counts from the previous week improved model fit in all three zones and modified the DMI-disease relationship in the subtropical and temperate regions. In the temperate zone, a 0.1 unit increase in an extreme positive DMI was associated with a higher risk of reported cryptosporidiosis [Relative Risk (RR) 1.23 (95% confidence interval (CI), 1.00-1.52)], compared to the risk associated with mean DMI. This methodology shows the potential for quantifying the short-term and nonlinear response of infections like cryptosporidiosis with climate variability. These findings also suggest that future models that account for lagged disease effects may better represent the time varying environmental exposure-disease relationship. The expected increases in the frequency of positive DMI events will likely result in decreased rainfall across temperate Australia, with potential implications for public health.