Associations between Meteorological Factors and Reported Mumps Cases from 1999 to 2020 in Japan.

The present study investigated associations between epidemiological mumps patterns and meteorological factors in Japan. We used mumps surveillance data and meteorological data from all 47 prefectures of Japan from 1999 to 2020. A time-series analysis incorporating spectral analysis and the least-squares method was adopted. In all power spectral densities for the 47 prefectures, spectral lines were observed at frequency positions corresponding to 1-year and 6-month cycles. Optimum least-squares fitting (LSF) curves calculated with the 1-year and 6-month cycles explained the underlying variation in the mumps data. The LSF curves reproduced bimodal and unimodal cycles that are clearly observed in northern and southern Japan, respectively. In investigating factors associated with the seasonality of mumps epidemics, we defined the contribution ratios of a 1-year cycle (Q1) and 6-month cycle (Q2) as the contributions of amplitudes of 1-year and 6-month cycles, respectively, to the entire amplitude of the time series data. Q1 and Q2 were significantly correlated with annual mean temperature. The vaccine coverage rate of a measles-mumps-rubella vaccine might not have affected the 1-year and 6-month modes of the time series data. The results of the study suggest an association between mean temperature and mumps epidemics in Japan.

Time series analysis of reported cases of hand, foot, and mouth disease from 2010 to 2013 in Wuhan, China.

BACKGROUND: Hand, foot, and mouth disease (HFMD) is an infectious disease caused by a group of enteroviruses, including Coxsackievirus A16 (CVA16) and Enterovirus A71 (EV-A71). In recent decades, Asian countries have experienced frequent and widespread HFMD outbreaks, with deaths predominantly among children. In several Asian countries, epidemics usually peak in the late spring/early summer, with a second small peak in late autumn/early winter. We investigated the possible underlying association between the seasonality of HFMD epidemics and meteorological variables, which could improve our ability to predict HFMD epidemics. METHODS: We used a time series analysis composed of a spectral analysis based on the maximum entropy method (MEM) in the frequency domain and the nonlinear least squares method in the time domain. The time series analysis was applied to three kinds of monthly time series data collected in Wuhan, China, where high-quality surveillance data for HFMD have been collected: (i) reported cases of HFMD, (ii) reported cases of EV-A71 and CVA16 detected in HFMD patients, and (iii) meteorological variables. RESULTS: In the power spectral densities for HFMD and EV-A71, the dominant spectral lines were observed at frequency positions corresponding to 1-year and 6-month cycles. The optimum least squares fitting (LSF) curves calculated for the 1-year and 6-month cycles reproduced the bimodal cycles that were clearly observed in the HFMD and EV-A71 data. The peak months on the LSF curves for the HFMD data were consistent with those for the EV-A71 data. The risk of infection was relatively high at 10 °C ≤ t < 15 °C (t, temperature [°C]) and 15 °C ≤ t < 20 °C, and peaked at 20 °C ≤ t < 25 °C. CONCLUSION: In this study, the HFMD infections occurring in Wuhan showed two seasonal peaks, in summer (June) and winter (November or December). The results obtained with a time series analysis suggest that the bimodal seasonal peaks in HFMD epidemics are attributable to EV-A71 epidemics. Our results suggest that controlling the spread of EV-A71 infections when the temperature is approximately 20-25 °C should be considered to prevent HFMD infections in Wuhan, China.