C M Parrinello1, A Crossa, T G Harris. 1. New York City Department of Mental Health and Hygiene, New York, New York, USA. christina.parrinello@einstein.yu.edu
Abstract
SETTING: Several non-US-based studies have found seasonal fluctuations in the incidence of tuberculosis (TB). OBJECTIVE: The current study examined patterns of TB seasonality for New York City verified TB cases from January 1990 to December 2007. DESIGN: Autocorrelation functions and Fourier analysis were used to detect a cyclical pattern in monthly incidence rates. Analysis of variance was used to compare seasonal mean case proportions. RESULTS: A cyclical pattern was detected every 12 months. Of the 34,004 TB cases included, 21.9% were in the fall (September-November), 24.7% in winter (December-February), 27.3% in spring (March-May), and 26.1% in the summer (June-August). The proportion of cases was lowest in fall (P < 0.0001) and highest in the spring (P < 0.0002). CONCLUSION: Possible explanations for seasonal variations in TB incidence include lower vitamin D levels in winter, leading to immune suppression and subsequent reactivation of latent TB; indoor winter crowding, increasing the likelihood of TB transmission; and providers attributing TB symptoms to other respiratory illnesses in winter, resulting in a delay in TB diagnosis until spring. Understanding TB seasonality may help TB programs better plan and allocate resources for TB control activities.
SETTING: Several non-US-based studies have found seasonal fluctuations in the incidence of tuberculosis (TB). OBJECTIVE: The current study examined patterns of TB seasonality for New York City verified TB cases from January 1990 to December 2007. DESIGN: Autocorrelation functions and Fourier analysis were used to detect a cyclical pattern in monthly incidence rates. Analysis of variance was used to compare seasonal mean case proportions. RESULTS: A cyclical pattern was detected every 12 months. Of the 34,004 TB cases included, 21.9% were in the fall (September-November), 24.7% in winter (December-February), 27.3% in spring (March-May), and 26.1% in the summer (June-August). The proportion of cases was lowest in fall (P < 0.0001) and highest in the spring (P < 0.0002). CONCLUSION: Possible explanations for seasonal variations in TB incidence include lower vitamin D levels in winter, leading to immune suppression and subsequent reactivation of latent TB; indoor winter crowding, increasing the likelihood of TB transmission; and providers attributing TB symptoms to other respiratory illnesses in winter, resulting in a delay in TB diagnosis until spring. Understanding TB seasonality may help TB programs better plan and allocate resources for TB control activities.
Authors: Grace A Noppert; Zhenhua Yang; Philippa Clarke; Peter Davidson; Wen Ye; Mark L Wilson Journal: Ann Epidemiol Date: 2019-10-17 Impact factor: 3.797