Table 3 Seasonality of pulmonary (PTB) and extrapulmonary tuberculosis (EPTB) by gender and age.

From: Seasonality of tuberculosis in intermediate endemicity setting dominated by reactivation diseases in Hong Kong

Age group

Gender

Pulmonary Tuberculosis

Extrapulmonary Tuberculosis

Continuous wavelet transform (power spectrum)

Dynamic generalised linear regression

Continuous wavelet transform (power spectrum)

Dynamic generalised linear regression

Globala

Localb

Seasonal amplitude (peak-to-tough ratio)

Peak timing in year (months)

Globala

Localb

Seasonal amplitude (peak-to-tough ratio)

Peak timing (months)

Elderly (≥ 65)

Male

*

2005–2012

1.22 (1.13–1.33)

1.16 (1.12–1.24)

6.42 (5.96–6.82)

6.31 (5.85–6.80)

–

–

–

–

–

–

Female

–

–

–

–

–

–

*

2009–2012; & 2014–2017

1.64 (1.50–2.22)

1.64 (1.45–1.91)

7.56 (7.11–8.09)

7.56 (6.97–8.01)

Middle aged (45–64)

Male

*

2005–2008; & 2012

1.16 (1.08–1.28)

1.16 (1.08–1.24)

6.65 (5.94–7.56)

6.65 (5.84–7.35)

*

2013–2015

1.33 (1.07–1.52)

1.22 (1.10–1.67)

7.52 (5.01–8.20)

5.44 (5.06–8.11)

Female

*

2005–2013

1.33 (1.27–1.58)

1.33 (1.24–1.48)

7.50 (6.93–8.11)

7.49 (7.01–8.06)

*

2012–2015

1.28 (1.17–1.44)

1.28 (1.18–1.45)

6.60 (5.87–7.33)

6.60 (5.90–7.33)

Adult (30–44)

Male

–

–

–

–

–

–

–

–

–

–

–

–

Female

*

2005–2007; &2011–2014

1.29 (1.20–1.40)

1.29 (1.20–1.39)

6.91 (6.33–7.37)

6.91 (6.34–7.36)

*

2005–2008

1.93 (1.13–2.10)

1.24 (1.09–1.59)

7.03 (4.17–7.13)

4.39 (3.93–7.66)

Youngadults (15–29)

Male

*

2005–2006; and 2013

1.18 (1.10–1.29)

1.18 (1.10–1.30)

7.14 (6.22–7.89)

7.14 (6.15–7.93)

*

2007–2008; and 2010–2013

1.48 (1.25–1.90)

1.22 (1.18–1.90)

8.14 (5.98–8.41)

5.79 (4.75–8.11)

Female

*

2005–2007

1.28 (1.16–1.38)

1.28 (1.16–1.38)

7.13 (6.43–7.74)

7.13 (6.45–7.74)

*

2005; 2009

1.39 (1.16–1.72)

1.34 (1.15–1.69)

5.82 (4.75–6.90)

5.80 (4.62–7.00)

Children (0–14)

Male

–

–

–

–

–

–

–

–

–

–

–

–

Female

–

–

–

–

–

–

–

–

–

–

–

–

  1. aGlobal wavelet power spectrums determined the existence of a dominating and significant annual periodicity overall through the time series.
  2. bLocal wavelet power spectrums showed the time evolution of annual periodic components and predictability of the seasonal variation.
  3. *Indicated presence of significant annual seasonality.
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