Prevalence of human echinococcosis
A total of 3,002,828 people were examined and 16,009 echinococcosis-positive patients were identified yielding a 0.53% prevalence rate. Among them, 14,398 (89.94%) CE cases, 942 (5.88%) AE cases and 137 (0.86%) with co infection of CE and AE were identified. A total of 532 cases (3.32%) were unclassified due to a lack of detailed classification records and failure to classify them as cystic or alveolar echinococcosis (Table 1).
The prevalence rate of global human echinococcosis at the township level ranged from 0% to 7.78% in TAR. The three townships with the highest prevalence were Axiu township (7.78%) in the Baqeen County of the Naqu Prefecture-level city with 216/2775 cases, Buta township (3.99%) in Deengqeen County with 130/3260 cases, and Meiyu township (3.90%) in the Zogang county of the Changdu Prefecture-level city with 201/5152 cases. All cases were distributed over 655 townships. However, 37 townships did not show any case of echinococcosis (Fig. 1, Table 2).
The prevalence of CE and AE in each township was further calculated. The overall prevalence rate of CE was 0.48%. All cases were distributed over 655 townships of 74 counties. The three townships with the highest prevalence for CE were Axiu township (6.16%) in Baqeen County of Naqu Prefecture-level city with 171/2775 cases, Meiyu township (3.90%) in Zogang county of Changdu Prefecture-level city with 201/5152 cases, and Baixiong township (3.33%) in Nierong County of Naqu Prefecture-level city with 144/4325 cases (Fig. 2, Table 3). The overall prevalence rate of AE was 0.04%, and the 1079 recorded cases were distributed over 143 townships from 32 counties. The three townships with the highest prevalence for AE were Axiu township with 46/2775 cases (1.66%), Baqeen township with 35/2300 cases (1.52%), both in the Baqeen County of the Naqu Prefecture-level city, and Buta township in Deengqeen County with 34/3260 cases (1.04%) (Fig. 3, Table 4).
Table 1 Epidemic status of human echinococcosis in TAR,2018.
|
Prefecture / Prefecture-level city (municipal level)
|
Number of endemic counties
|
Population of endemic areas
|
All cases
|
Prevalence rate (1/10000)
|
Prevalence rate of CE (1/10000)
|
Prevalence rate of AE (1/10000)
|
Total cases
|
CE
|
AE
|
Co infection of CE and AE cases
|
Unclassified cases
|
Lhasa
|
8
|
477,334
|
958
|
932
|
3
|
1
|
22
|
20.07
|
19.55
|
0.08
|
Changdu
|
11
|
723,005
|
2,856
|
2,266
|
312
|
54
|
224
|
39.50
|
32.09
|
5.06
|
Shannan
|
12
|
306,813
|
1,295
|
1,259
|
1
|
7
|
28
|
42.21
|
41.26
|
0.26
|
Shigatse
|
18
|
772,334
|
3,147
|
3,025
|
10
|
12
|
90
|
40.75
|
39.32
|
0.28
|
Naqu
|
11
|
478,172
|
6,019
|
5,273
|
603
|
44
|
99
|
125.88
|
111.19
|
13.53
|
Ali
|
7
|
103,155
|
1,075
|
986
|
3
|
17
|
69
|
104.21
|
97.23
|
1.94
|
Linzhi
|
7
|
141,995
|
659
|
647
|
10
|
2
|
0
|
46.41
|
45.71
|
0.85
|
Total
|
74
|
3,002,828
|
16,009
|
14,398
|
942
|
137
|
532
|
53.31
|
48.40
|
3.59
|
Classification of the prevalence of human echinococcosis in China
The epidemic level of 692 townships in TAR ranged as follows: 127 (18.35%) were Class I epidemic townships; 446 (64.45%) were Class II epidemic townships; 82 (11.85%) were Class III epidemic townships; and 37 (5.35%) were Class IV epidemic townships (Figure 1, Table 2). The classification of CE and AE was further analyzed according to similar classification criteria. Among the 692 townships in TAR, 655 (94.55%) displayed CE cases with 116 (16.76%) Class I epidemic townships, 445 (64.31%) Class II epidemic townships, 94 (13.58%) Class III epidemic townships and 37 (5.35%) Class IV epidemic townships (Fig. 2, Table 3). With respect to AE, 143 out of 692 townships (20.7%) townships displayed AE cases with 3 (0.43%) Class I epidemic townships, 53 (7.66%) Class II epidemic townships, 87 (12.57%) Class III epidemic townships and 549 (79.34%) Class IV epidemic townships (Fig. 3, Table 4).
Table 2 Classification of the prevalence of human echinococcosis at township level in TAR,2018
|
District/ Prefecture-level city (municipal level)
|
Total number of towns
|
P≥ 100/10000
|
10/10000 ≤P < 100/10000
|
0 <P < 10/10000
|
P = 0
|
Number of towns
|
constituent ratio (%)
|
Number of towns
|
Constituent ratio (%)
|
Number of towns
|
Constituent ratio (%)
|
Number of towns
|
Constituent ratio (%)
|
Lhasa
|
65
|
1
|
1.54
|
39
|
60.00
|
22
|
33.85
|
3
|
4.62
|
Changdu
|
138
|
11
|
7.97
|
95
|
68.84
|
24
|
17.39
|
8
|
5.80
|
Shannan
|
82
|
8
|
9.76
|
46
|
56.10
|
14
|
17.07
|
14
|
17.07
|
Shigatse
|
203
|
24
|
11.82
|
157
|
77.34
|
19
|
9.36
|
3
|
1.48
|
Naqu
|
114
|
66
|
57.89
|
46
|
40.35
|
2
|
1.75
|
0
|
0.00
|
Ali
|
37
|
15
|
40.54
|
22
|
59.46
|
0
|
0.00
|
0
|
0.00
|
Linzhi
|
53
|
2
|
3.77
|
41
|
77.36
|
1
|
1.89
|
9
|
16.98
|
Total
|
692
|
127
|
18.35
|
446
|
64.45
|
82
|
11.85
|
37
|
5.35
|
P: Prevalence rate
|
Table3. Classification of the prevalence of human CE at township level in TAR,2018
|
District/ Prefecture-level city (municipal level)
|
Total number of towns
|
P≥ 100/10000
|
10/10000 ≤P < 100/10000
|
0 <P < 10/10000
|
P = 0
|
Number of counties
|
constituent ratio (%)
|
Number of counties
|
Constituent ratio (%)
|
Number of counties
|
Constituent ratio (%)
|
Number of counties
|
Constituent ratio (%)
|
Lhasa
|
65
|
1
|
1.54
|
37
|
56.92
|
24
|
36.92
|
3
|
4.62
|
Changdu
|
138
|
9
|
6.52
|
90
|
65.22
|
31
|
22.46
|
8
|
5.80
|
Shannan
|
82
|
7
|
8.54
|
46
|
56.10
|
15
|
18.29
|
14
|
17.07
|
Shigatse
|
203
|
24
|
11.82
|
158
|
77.83
|
18
|
8.87
|
3
|
1.48
|
Naqu
|
114
|
61
|
53.51
|
49
|
42.98
|
4
|
3.51
|
0
|
0.00
|
Ali
|
37
|
12
|
32.43
|
25
|
67.57
|
0
|
0.00
|
0
|
0.00
|
Linzhi
|
53
|
2
|
3.77
|
40
|
75.47
|
2
|
3.77
|
9
|
16.98
|
Total
|
692
|
116
|
16.76
|
445
|
64.31
|
94
|
13.58
|
37
|
5.35
|
P: Prevalence rate
|
Table4. Classification of the prevalence of human AE at township level in TAR, 2018
|
District/ Prefecture-level city (municipal level)
|
Total number of towns
|
P≥ 100/10000
|
10/10000 ≤P < 100/10000
|
0 <P < 10/10000
|
P = 0
|
Number of counties
|
constituent ratio (%)
|
Number of counties
|
Constituent ratio (%)
|
Number of counties
|
Constituent ratio (%)
|
Number of counties
|
Constituent ratio (%)
|
Lhasa
|
65
|
0
|
0.00
|
0
|
0.00
|
2
|
3.08
|
63
|
96.92
|
Changdu
|
138
|
1
|
0.72
|
12
|
8.70
|
26
|
18.84
|
99
|
71.74
|
Shannan
|
82
|
0
|
0.00
|
0
|
0.00
|
6
|
7.32
|
76
|
92.68
|
Shigatse
|
203
|
0
|
0.00
|
4
|
1.97
|
10
|
4.93
|
189
|
93.10
|
Naqu
|
114
|
2
|
1.75
|
33
|
28.95
|
33
|
28.95
|
46
|
40.35
|
Ali
|
37
|
0
|
0.00
|
3
|
8.11
|
3
|
8.11
|
31
|
83.78
|
Linzhi
|
53
|
0
|
0.00
|
1
|
1.89
|
7
|
13.21
|
45
|
84.91
|
Total
|
692
|
3
|
0.43
|
53
|
7.66
|
87
|
12.57
|
549
|
79.34
|
P: Prevalence rate
|
Spatial distribution and identification of clusters of human echinococcosis
Spatial clustering of human echinococcosis
Based on the echinococcosis cases and exposed population in the 692 townships at the end of 2018, spatial clustering scanning analysis was performed to explore key epidemic clusters of echinococcosis in TAR.
CE displayed one primary cluster and seven secondary clusters. The primary cluster was centered at 36°10’ North and 89°39’ East with a radius of 632.91 km, covering 88 townships in 12 counties. It was dominated by Naqu Prefecture-level city, with 82 townships in all the 10 epidemic counties (Nagqum, BIrum, Nyainrong, Amdo, Xainza, Sog, Bangoin, Baqeen, Nyima, Shuanghu), followed by Damxung in Lhasa city and Geerzee in the Ali Prefecture. This cluster involved 356,976 exposed persons, with a risk of infection 3.35 times higher than in other areas (P<0.01). It is the key area for the prevention and control of CE in TAR. Extent and risk status of the secondary clusters are shown in Figure 4 and Table 5. A relatively important secondary cluster area was centered at 30°11’ North and 92°86’ East with a radius of 103.61km, covering 27 towns from 7 counties, including Maizhokunggar in Lhasa city, Sangri and Gyaca of Shannan Prefecture-level city, Nagqu and Jiali in Naqu Prefecture-level city, and Nyingchi and Gongbo’gyamda in Linzhi Prefecture-level city. The RR value of this cluster was 1.77 (P<0.01). Another important secondary cluster area was centered at 28°75’ North and 84°83’ East with a radius of 151.51 km, covering 25 towns from 6 counties. The RR value of this cluster was 1.71 (P<0.01). The remaining secondary clusters were relatively small, involving only a few townships. These gathering areas exist sporadically. We suggest that the relevant departments of the epidemic counties to which these towns belong pay more attention to the epidemic towns in the gathering areas, and strengthen the monitoring of echinococcosis and patient screening in these towns. If the epidemic area involves the junction area of multiple epidemic counties, relevant epidemic counties need to cooperate to carry out prevention and control work together.
The spatial clustering scan of AE showed the presence of one primary cluster and two secondary clusters (Figure 5 and Table 6). The primary cluster was centered at 32°49’ North and 94°54’ East, with Gongri township in Baqeen county as the center and a radius of 157.23 km, covering 38 townships in 6 counties, including Deengqeen and Banbar in Changdu Prefecture-level city and Biru, Nyainrong, Sog, and Baqeen in Naqu Prefecture-level city. The RR value of this cluster area was as high as 21.04 times that of the surrounding area (P<0.01).
One secondary cluster was centered on 31°56’ North and 89°52’ East, with Mendang township inBangoin county at the center and a radius of 158.35 km, covering 22 townships in 4 counties in Naqu Prefecture-level city, including 10 townships in Bangoin county,7 townships in Xainza county,1 township in Suanghu county and 1 in Amdo county. The RR value of this cluster area was 8.02. The risk of AE transmission in this aggregation area is significantly higher than that in the surrounding area.
The other secondary cluster was centered on 30°34’ North and 93°04’ East, with Niangpu township in Gongbo' gyamda as the center and a radius of 93.93 km, covering 20 townships in 4 counties, including 8 townships in Gongbo' gyamda, 10 townships in Jiali county,1 township in MaizhoKunggar county and 1 in Banbar county. The RR value of this cluster area was 2.58 (P<0.01).
The spatial distribution of AE is more limited, with only three aggregation areas, but the epidemic risk is relatively high, especially in the primary cluster area, suggesting that these aggregation areas require a strengthening of prevention and control.
Table 5 Spatial clustering analysis of human CE in TAR,2018
|
Cluster
|
The center point
|
Scope
|
Radius(km)
|
Exposed population
|
Number of cases
|
Expected cases
|
RR
|
LLR
|
P-value
|
latitude
|
longitude
|
center town
|
Number of towns
|
Primary cluster
|
36.099499 N
|
89.386002 E
|
Sewu town of Amdo county
|
88
|
632.91
|
356,976
|
4,494
|
1,716
|
3.35
|
1,876.79
|
<0.01
|
Secondary cluster1
|
30.110399 N
|
92.856300 E
|
Jinda town of Gongbo' gyamda
|
27
|
103.61
|
98,424
|
815
|
473
|
1.77
|
105.65
|
<0.01
|
Secondary cluster2
|
28.750000 N
|
84.828003 E
|
Gongdang town of Gyirong county
|
25
|
151.51
|
53,153
|
431
|
255
|
1.71
|
51.00
|
<0.01
|
Minor secondary cluster1
|
28.343500 N
|
89.611000 E
|
Samada town of Kangmar county
|
9
|
48.71
|
18,832
|
219
|
91
|
2.44
|
65.61
|
<0.01
|
Minor secondary cluster2
|
30.401300 N
|
98.491096 E
|
Latuo town of Konjo county
|
7
|
37.23
|
22,215
|
233
|
107
|
2.20
|
56.17
|
<0.01
|
Minor secondary cluster3
|
28.755199 N
|
91.116699 E
|
Gongbuxue town of Nagarzee county
|
3
|
30.80
|
16,538
|
371
|
79
|
4.76
|
283.07
|
<0.01
|
Minor secondary cluster4
|
29.071199 N
|
90.505997 E
|
Kalong town of Nagarzee county
|
4
|
20.62
|
8,920
|
98
|
43
|
2.29
|
26.01
|
<0.01
|
Minor secondary cluster5
|
28.648899 N
|
97.541801 E
|
Zhuwagen town of Zayuu county
|
2
|
47.02
|
6,316
|
73
|
30
|
2.41
|
21.48
|
<0.01
|
Minor secondary cluster6
|
31.132999 N
|
98.431099 E
|
Niangxi town of Jomda county
|
2
|
21.23
|
10,820
|
104
|
58
|
1.80
|
14.96
|
<0.05
|
Table 6 Spatial clustering analysis of human AE in TAR,2018
|
Cluster
|
The center point
|
Scope
|
Radius(km)
|
Exposed population
|
Number of cases
|
Expected cases
|
RR
|
LLR
|
P-value
|
latitude
|
longitude
|
center town
|
Number of towns
|
Primary cluster
|
32.494598 N
|
94.544701 E
|
Gongri town of Baqeen county
|
38
|
157.23
|
194,212
|
557
|
61
|
21.04
|
916.09
|
<0.01
|
Secondary cluster1
|
31.559900 N
|
89.523499 E
|
Mendang town of Bangoin county
|
22
|
158.35
|
70,604
|
152
|
22
|
8.02
|
173.05
|
<0.01
|
Secondary cluster2
|
30.342400 N
|
93.036400 E
|
Niangpu town of Gongbo' gyamda
|
20
|
93.93
|
69,309
|
54
|
22
|
2.58
|
17.56
|
<0.01
|