ArticleEpidemiology and infection2016
Time-series analysis of monthly age-specific numbers of newly registered cases of active tuberculosis in Japan from 1998 to 2013.
Article in Epidemiology and infection, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Drivers of Seasonal Variation in Tuberculosis Incidence: Insights from a Systematic Review and Mathematical Model.Epidemiology (Cambridge, Mass.) · 2018Pooled it
- Epidemiological features of tuberculosis infection in a rural prefecture of Japan from 2007 to 2018.Scientific reports · 2022Article
- Does sunlight drive seasonality of TB in Vietnam? A retrospective environmental ecological study of tuberculosis seasonality in Vietnam from 2010 to 2015.BMC infectious diseases · 2020Article
- Time-series analysis of geographically specific monthly number of newly registered cases of active tuberculosis in Japan.PloS one · 2019Article
- Times series analysis of age-specific tuberculosis at a rapid developing region in China, 2011-2016.Scientific reports · 2018Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We investigated the seasonality of age-specific tuberculosis (TB) in Japan. To allow the development of TB control strategies for different age groups we used a time-series analysis, including a spectral analysis and least squares method, to analyse the monthly age-specific numbers of newly registered cases of all forms of active TB in Japan from January 1998 to December 2013. The time-series data are reported in 10-year age groups: 0-9, 10-19, …, 70-79, and ⩾80 years. We defined the contribution ratio of the 1-year cycle, Q 1, as the contribution of the amplitude of a 1-year cycle to the whole amplitude of the time-series data. The Q 1 values in the age groups corresponding to adolescence and middle life (10-39 years) and old age (⩾70 years) were high. The peaks in the active TB epidemics for the ⩾70 years age group occurred in August and September, 1-2 months behind the peaks for the 10-39 years age group (June and July). An active TB epidemic might be attributable to travel by public transport and irregular employment in the 10-39 years age group and immune system suppression by low winter temperatures in the ⩾70 years age group.
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