Seasonal models can quantify the dependency of herpangina and hand-foot-mouth disease on weather parameters and predict increased cases with warmer climate conditions.
In order to investigate the effects of global warming, we attempted to establish seasonal models to predict fluctuations in rates of herpangina (HA) and hand-foot-mouth disease (HFMD) associated with weather conditions and calendar months in Tokyo, Japan. Surveillance data tracking HA/HFMD incidences in Tokyo was retrieved from the Infectious Agents Surveillance Report, published by the National Institute of Infectious Diseases in Japan. From the Meteorological Agency, we obtained data for 54 weather condition parameters. The annual fluctuations in reported HA cases comprising start, peak, and end weeks almost exactly matched the model, although peak levels for each fluctuation did not always match in HFMD. Furthermore, for the HA model, 88% of the variations among observed HA cases were explained by the linear relationship with the seasonal parameters investigated, which was higher than the 64% observed for the HFMD model. The HA and HFMD models were applied to data from the years 1999 to 2002, and demonstrated correlations of 86% and 64%, respectively. These models predicted that warmer climate conditions would lead to an increased number of HA and HFMD cases. These results suggest that our seasonal models may quantify the dependency of infectious diseases on seasonal parameters and simulate the impact of global warming.
Urashima et al. (2003) studied this question.