Temperature and humidity associated with increases in tuberculosis notifications: a time-series study in Hong Kong

Abstract

Previous studies have revealed associations of meteorological factors with tuberculosis (TB) cases. However, few studies have examined their lag effects on TB cases. This study was aimed to analyse nonlinear lag effects of meteorological factors on the number of TB notifications in Hong Kong. Using a 22-year consecutive surveillance data in Hong Kong, we examined the association of monthly average temperature and relative humidity with temporal dynamics of the monthly number of TB notifications using a distributed lag nonlinear models combined with a Poisson regression. The relative risks (RRs) of TB notifications were >1.15 as monthly average temperatures were between 16.3 and 17.3 °C at lagged 13–15 months, reaching the peak risk of 1.18 (95% confidence interval (CI) 1.02–1.35) when it was 16.8 °C at lagged 14 months. The RRs of TB notifications were >1.05 as relative humidities of 60.0–63.6% at lagged 9–11 months expanded to 68.0–71.0% at lagged 12–17 months, reaching the highest risk of 1.06 (95% CI 1.01–1.11) when it was 69.0% at lagged 13 months. The nonlinear and delayed effects of average temperature and relative humidity on TB epidemic were identified, which may provide a practical reference for improving the TB warning system.

Spatial epidemiological characteristics and exponential smoothing model application of tuberculosis in Qinghai Plateau, China

“…The potential reasons could be: firstly, Qinghai lies in western China where is very cold, therefore local residents prefer staying at home rather than doing activities outdoors, which make people have not much fresh air. Secondly, a dry climate could bring about the delayed increasing trend for the morbidity of TB [ 17 ]. Heating begins in October and lasts for months in Qinghai because of the cold, and could exacerbate the dryness of the climate, which probably resulted in more TB patients showed up in next March and April.…”

Association between climate variables and pulmonary tuberculosis incidence in Brunei Darussalam

“…Natural cubic splines with 7 degrees of freedom (df) per calendar year were used to account for long-term trends and seasonality. This adjustment was included based on previous similar studies for TB 5 , 17 , and the number of df was determined using the Akaike’s Information Criterion (AIC) value. Natural cubic splines with 3 df were used to describe both the lagged and non-linear effects of each climate variable.…”

“…The seasonal variation of tuberculosis (TB) is long known but less understood phenomenon 1 . Many ecological studies have investigated the relationship between TB incidence and climate variables (relating to temperature, humidity, rainfall, sunlight and wind speed) in temperate 2 , 3 , subtropical 4 , 5 ,and tropical 6 , 7 countries. These studies investigated whether climate factors have any effect on the predominantly airborne transmission of Mycobacterium tuberculosis (MTB), the causative agent of TB.…”

“…Due to the relatively long incubation period for TB, it is also important to take in account the delayed and non-linear effects of climate variables when studying TB seasonality. This can be done using the distributed lag non-linear model (DLNM) framework, which was previously applied to TB 4 , 5 , 17 and other diseases such as acute respiratory infections 18 , Zika 19 , and hand, foot and mouth disease 20 .…”

Meta-analysis of the effects of ambient temperature and relative humidity on the risk of mumps

“…Meteorological factors have been considered as important influencing factors to many disease, including non-infectious diseases, such as blood pressure 15 , suicide 16 , stroke occurrence 17 , and infectious diseases, such as hand, foot, and mouth disease (HFMD) 18 , influenza 19 , 20 , tuberculosis 21 – 23 and so on. Many articles have tried to clarify the mechanisms between mumps and meteorological factors.…”