Objectives Chikungunya poses an increasing threat to people living in endemic areas and to travelers from non-endemic regions. This study descriptively characterized imported chikungunya cases in Japan and explored the relationship between local incidence in destination areas and infection risk among Japanese travelers.
Methods First, the descriptive features of imported chikungunya cases in Japan from 2011 to 2023 were examined. Second, monthly and yearly trends in the incidence of imported chikungunya cases among Japanese travelers were compared by destination with incidence in the corresponding destination country. Third, destination-specific incidence among Japanese travelers was compared between high- and low-transmission seasons in each destination country.
Results Of 155 imported chikungunya cases in Japan during 2011–2023, 112 (72.3%) were associated with travel to Myanmar, India, Indonesia, the Philippines, or Thailand. The yearly chikungunya importation rate among Japanese travelers returning from Indonesia and Thailand was correlated with the corresponding rate among local residents. The monthly incidence of imported cases during the high-transmission season was 12.3, 7.4, 12.0, and 4.0 times higher than that during the low-transmission season among travelers returning from Myanmar, India, Indonesia, and the Philippines, respectively.
Conclusion The risk of imported chikungunya infection among Japanese travelers reflected the local epidemiology of chikungunya in destination countries, including both seasonal and long-term patterns. Imported-case data may support risk assessment in destination countries and contribute to traveler-specific prevention, improved diagnosis, and a reduced risk of autochthonous outbreaks.
Objectives
Nosocomial outbreaks involve only a small number of cases and limited baseline data. The present study proposes a method to detect the nosocomial outbreaks caused by rare pathogens, exploiting score prediction interval of a Poisson distribution. Methods
The proposed method was applied to three empirical datasets of nosocomial outbreaks in Japan: outbreaks of (1) multidrug-resistant <i>Acinetobacter baumannii</i> (<i>n</i> = 46) from 2009 to 2010, (2) multidrug-resistant <i>Pseudomonas aerginosa</i> (<i>n</i> = 18) from 2009 to 2010, and (3) <i>Serratia marcescens</i> (<i>n</i> = 226) from 1999 to 2000. Results
The proposed method successfully detected all three outbreaks during the first 2 months. Both the model-based and empirically derived threshold values indicated that the nosocomial outbreak of rare infectious disease may be declared upon diagnosis of index case(s), although the sensitivity and specificity were highly variable. Conclusion
The findings support the practical notion that, upon diagnosis of index patient(s), one should immediately start the outbreak investigation of nosocomial outbreak caused by a rare pathogen. The proposed score prediction interval can permit easy computation of outbreak threshold in hospital settings among healthcare experts.
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