Abstract
Summer-spring predominance of tuberculosis (TB) has been widely reported. The relative contributions of exogenous recent infection versus endogenous reactivation to such seasonality remains poorly understood. Monthly TB notifications data between 2005 and 2017 in Hong Kong involving 64,386 cases (41% aged ≥ 65; male-to-female ratio 1.74:1) were examined for the timing, amplitude, and predictability of variation of seasonality. The observed seasonal variabilities were correlated with demographics and clinical presentations, using wavelet analysis coupled with dynamic generalised linear regression models. Overall, TB notifications peaked annually in June and July. No significant annual seasonality was demonstrated for children aged ≤ 14 irrespective of gender. The strongest seasonality was detected in the elderly (≥ 65) among males, while seasonal pattern was more prominent in the middle-aged (45–64) and adults (30–44) among females. The stronger TB seasonality among older adults in Hong Kong suggested that the pattern has been contributed largely by reactivation diseases precipitated by defective immunity whereas seasonal variation of recent infection was uncommon.
Highlights
Summer-spring predominance of tuberculosis (TB) has been widely reported
Population incidence of TB is contributed by not just exogenous recent infection and endogenous reactivation of latent tuberculosis infection (LTBI)[3], the summative effects of which could be hard to delineate by season
Aging population and successful control of tuberculosis transmission prompted a shift of incidence towards older-age groups[19], while increased proportion of which arose from reactivation of past infection[17,20]
Summary
Summer-spring predominance of tuberculosis (TB) has been widely reported. The relative contributions of exogenous recent infection versus endogenous reactivation to such seasonality remains poorly understood. The stronger TB seasonality among older adults in Hong Kong suggested that the pattern has been contributed largely by reactivation diseases precipitated by defective immunity whereas seasonal variation of recent infection was uncommon. Fluctuations in magnitude and shifts in timing of periodic surge in disease incidence over time have complicated the modelling of TB seasonality, while classical stationary approaches assuming constant seasonal pattern might not be justified. Against such background, we set out to investigate the TB seasonality in Hong Kong resulting largely from endogenous reactivation, focusing on the application of non-stationary approaches to characterise the seasonal patterns of TB notifications in population subgroups defined by age, gender, and disease forms
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