Epidemiological characteristic of rubella by age group during 12 years after the national introduction of rubella vaccine in Hangzhou, China

Figures & data

Figure 1. Yearly rubella cases and confirmation status and incidence rate, 2009–2020.

Figure 2. Reported rubella incidence by age group, 2009–2020.

Figure 3. Reported rubella cases distribution by gender and age group.

Table 1. Rubella vaccination status by age group, 2015–2020

RCV receipt history	<12 months (n, %)	1 years (n, %)	2-4 years (n, %)	5-9 years (n, %)	10-19 years (n, %)	20+years (n, %)	Total (n, %)
0 dose	5(19.23)	0	0	0	1(3.70)	10(3.82)	16(4.94)
1 dose	21(80.77)	3(75)	0	0	2(7.41)	4(1.53)	30(9.26)
2 doses	0	1(25)	4(100)	1(100)	1(3.70)	1(.38)	8(2.47)
Unknown	0	0	0	0	23(85.19)	247(94.27)	269(83.02)
total	26(100)	4(100)	4(100)	1(100)	27(100)	262(100)	324(100)

Figure 4. Yearly positive rate for rubella IgG antibody, 2009–2020.

Figure 5. Seroepidemiology of rubella IgG in population by age groups.

Table 2. Rubella IgG detection results in population among various groups, 2009–2020

Variable	Total (n)	Rubella positive (n, %)	2, P	Rubella GMC(IU/ml)	t/F, P
Gender			Χ2=.274		t=-2.751
Male	2205	1770(80.3)	P=0.601	55.37	P = .006
Female	2157	1745(80.9)		61.47
District
Urban	1496	1205(80.5%)	Χ^2=0.002	56.01	t=-2.317
Rural	2866	2310(80.6%)	P=0.967	59.26	P=0.021
Age(y)			Χ^2=450.978		F = 42.878
<1	505	243(48.1)	P<.001	14.51	P < .001
1	360	309(85.8)		98.57
2	339	320(94.4)		97.87
3-4	496	460(92.7)		74.51
5-6	413	346(83.8)		59.12
7-9	367	288(78.5)		44.61
10-14	392	308(78.6)		37.34
15-19	502	423(84.3)		54.14
20-29	372	316(84.9)		74.30
30-39	300	252(84.0)		67.27
≥40	316	250(78.9)		44.62
Total	4362	3515(80.6)		58.34

Figure 6. Seroepidemiology of rubella IgG in population by year.

Table 3. Association of seroepidemiology of rubella IgG and related variables via multivariate analysis

The independent variables	Seropositivity of rubella = y^a		GMC(IU/ml) of rubella = y^b
	OR (95%CI)	P-values	OR (95%CI)	P-values
Gender
Male	1		1
Female	1.035(.881–1.217)	0.675	1.024(.995–1.06)	0.104
District
Urban	1		1
Rural	1.018(.861–1.203)	0.835	1.033(1.005–1.074)	0.024
Age(y)
<1	1		1
1	0.153(.108–.216)	<.001	0.761(.58–.662)	<.001
2	0.055(.034–.09)	<.001	1.058(1.044–1.204)	0.002
3-4	0.072(.049–.106)	<.001	1.105(1.143–1.323)	<.001
5-6	0.179(.131–.245)	<.001	1.031(.989–1.127)	0.103
7-9	0.254(.187–.344)	<.001	0.968(.876–1.005)	0.071
10-14	0.253(.188–.341)	<.001	0.938(.818–.944)	<.001
15-19	0.173(.128–.232)	<.001	0.923(.798–.918)	<.001
20-29	0.163(.117–.228)	<.001	1.037(1.001–1.154)	0.047
30-39	0.175(.122–.25)	<.001	1.01(.947–1.102)	0.581
≥40	0.243(.176–0336)	<.001	0.964(.856–.994)	0.034

Logistic regression was used to analyze the associations between the changes in the rate of rubella IgG seropositivity and the related factors.

Linear regression was used to analyze the associations between the changes in the GMC levels of rubella IgG and the related factors.