Time-series analysis of Japanese surveillance data identified dominant epidemic cycles of 6.9, 3.8, 4.3, 9.5, and 7.8 years for Coxsackievirus B serotypes 1 through 5, respectively.
Observational
Time-series analysis of Japanese surveillance data revealed multi-year periodic cycles for Coxsackievirus B serotypes, similar to the cyclical variations observed in type 1 diabetes incidence.
Objective: Coxsackievirus B (CVB) is associated with the development of human diseases including type 1 diabetes. Previous studies identified cyclical variations in type 1 diabetes incidence—peak incidences occurring in 4- to 6-year periods in two regions in England, a 5-year period in Western Australia, and 5.33-year period in Poland. However, it is not clear whether CVB infection rates demonstrate similar cyclical variation characteristics. The purpose of this study was to characterize the periodicity in CVB surveillance data. Results: Maximum entropy spectral analysis was performed on monthly CVB surveillance data in Japan. In addition to demonstrate a 1-year cycle for all the serotypes, spectral peaks were demonstrated for dominant cycles—6.9-, 3.8-, 4.3-, 9.5-, and 7.8- year periods for CVB1, CVB2, CVB3, CVB4, and CVB5, respectively. Pearson correlation was used to compare the least-squares fit curves based on periods estimated from the analysis with the original data. The results for all five serotypes—CVB1, CVB2, CVB3, CVB4, and CVB5—demonstrated good correlation— ρ = 0.96, ρ = 0.60, ρ = 0.90, ρ = 0.88, and ρ = 0.67, respectively. This method could be a useful tool for the efficient investigation of CVB as a pathogen of type 1 diabetes.
Keiji et al. (Thu,) conducted a observational in Coxsackievirus B infection. Time-series analysis of Japanese surveillance data identified dominant epidemic cycles of 6.9, 3.8, 4.3, 9.5, and 7.8 years for Coxsackievirus B serotypes 1 through 5, respectively.