Epidemiological Profile and Spatial Patterns of Enterobiasis in Children Aged 3–9 Years in China from 2016 to 2020
Abstract
:1. Introduction
2. Methods
2.1. Sampling
2.2. Detection of Infection
2.3. Database and Statistical Analysis
2.4. Spatial Autocorrelation Analysis
2.5. Spatio-Temporal Analysis
3. Results
3.1. Overall Infection
3.2. Regional Distribution
3.3. Population Distribution
3.4. Global Spatial Autocorrelation Analysis
3.5. Hotspot Analysis
3.6. Spatio-Temporal Analysis
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Province (Municipality/Autonomous Region) | 2016 N (%) * | 2017 N (%) * | 2018 N (%) * | 2019 N (%) * | 2020 N (%) * | Total N (%) * |
---|---|---|---|---|---|---|
Beijing | 0/161 (0.00) | 0/77 (0.00) | 0/449 (0.00) | 3/374 (0.80) | 0/322 (0.00) | 3/1383 (0.22) |
Tianjing | 0/325 (0.00) | 1/246 (0.41) | 0/210 (0.00) | 0/251 (0.00) | 0/258 (0.00) | 1/1290 (0.08) |
Hebei | 42/2821 (1.49) | 22/2382 (0.92) | 21/2197 (0.96) | 28/2765 (1.01) | 13/2454 (0.53) | 126/12,619 (1.00) |
Shanxi (1) | 10/1101 (0.91) | 22/1336 (1.65) | / | 6/2053 (0.29) | 9/1821 (0.49) | 47/6311 (0.74) |
Inner Mongolia | 0/768 (0.00) | 2/790 (0.25) | 0/1,392 (0.00) | 1/1346 (0.07) | 0/1225 (0.00) | 3/5521 (0.05) |
Liaoning | 0/1153 (0.00) | 0/1133 (0.00) | 0/677 (0.00) | 0/874 (0.00) | 1/814 (0.12) | 1/4651 (0.02) |
Jilin | 0/284 (0.00) | 1/277 (0.36) | 2/840 (0.24) | 0/386 (0.00) | 2/411 (0.49) | 5/2198 (0.23) |
Heilongjiang | 0/1403 (0.00) | 3/904 (0.33) | 0/849 (0.00) | 3/1251 (0.24) | 0/646 (0.00) | 6/5053 (0.12) |
Shanghai | 0/68 (0.00) | 0/17 (0.00) | 0/55 (0.00) | 3/142 (2.11) | 0/42 (0.00) | 3/324 (0.93) |
Jiangsu | 0/214 (0.00) | 4/1055 (0.38) | 0/120 (0.00) | 1/863 (0.12) | 10/810 (1.23) | 15/3062 (0.49) |
Zhejiang | 19/727 (2.61) | 7/804 (0.87) | 2/537 (0.37) | 9/603 (1.49) | 1/476 (0.21) | 38/3147 (1.21) |
Anhui | 3/73 (4.11) | 26/1849 (1.41) | 16/1640 (0.98) | 31/2229 (1.39) | 24/2305 (1.04) | 100/8096 (1.24) |
Fujian | 30/1094 (2.74) | 113/2376 (4.76) | 159/2208 (7.20) | 159/2214 (7.18) | 114/2449 (4.65) | 575/10,341 (5.56) |
Jiangxi | 238/1964 (12.12) | 256/1791 (14.29) | 120/1409 (8.52) | 110/1611 (6.83) | 121/1550 (7.81) | 845/8325 (10.15) |
Shandong | 27/1153 (2.34) | 16/1526 (1.05) | 8/1858 (0.43) | 48/1941 (2.47) | 21/1783 (1.18) | 120/8261 (1.45) |
Henan | 137/4235 (3.23) | 162/4846 (3.34) | 176/4664 (3.77) | 136/4596 (2.96) | 132/3807 (3.47) | 743/22,148 (3.35) |
Hubei | 11/1603 (0.69) | 3/1389 (0.22) | 37/2356 (1.57) | 40/1758 (2.28) | 31/1746 (1.78) | 122/8852 (1.38) |
Hunan | 15/1598 (0.94) | 113/4160 (2.72) | 83/6598 (1.26) | 120/5269 (2.28) | 73/7070 (1.03) | 404/24,695 (1.64) |
Guangdong | 50/913 (5.48) | 174/2346 (7.42) | 188/4122 (4.56) | 178/5039 (3.53) | 160/5743 (2.79) | 750/18,163 (4.13) |
Guangxi | 139/2166 (6.42) | 118/864 (13.66) | 182/2232 (8.15) | 238/3586 (6.64) | 108/2285 (4.73) | 785/11,133 (7.05) |
Hainan | 6/201 (2.99) | 25/343 (7.29) | 27/514 (5.25) | 38/538 (7.06) | 55/573 (9.60) | 151/2169 (6.96) |
Chongqing | 13/527 (2.47) | 42/447 (9.40) | 3/560 (0.54) | 1/478 (0.21) | 4/732 (0.55) | 63/2744 (2.30) |
Sichuan | 67/1293 (5.18) | 49/1301 (3.77) | 68/1421 (4.79) | 77/3118 (2.47) | 29/1194 (2.43) | 290/8327 (3.48) |
Guizhou | 49/2028 (2.42) | 33/2110 (1.56) | 4/948 (0.42) | 23/2699 (0.85) | 29/2555 (1.14) | 138/10,340 (1.33) |
Yunnan | 3/1336 (0.22) | 6/1465 (0.41) | 0/1016 (0.00) | 11/2026 (0.54) | 4/1834 (0.22) | 24/7677 (0.31) |
Tibet (2) | / | / | / | 1/1117 (0.09) | 0/893 (0.00) | 1/2010 (0.05) |
Shaanxi | 15/1228 (1.22) | 0/1212 (0.00) | 11/1365 (0.81) | 15/1490 (1.01) | 2/1167 (0.17) | 43/6462 (0.67) |
Gansu | 7/1470 (0.48) | 1/1414 (0.07) | 1/1399 (0.07) | 6/3164 (0.19) | 6/3712 (0.16) | 21/11,159 (0.19) |
Qinghai | 0/1044 (0.00) | 0/615 (0.00) | 0/893 (0.00) | 0/1069 (0.00) | 1/980 (0.10) | 1/4601 (0.02) |
Ningxia | 21/853 (2.46) | 1/435 (0.23) | 3/665 (0.45) | 21/2968 (0.71) | 10/2338 (0.43) | 56/7259 (0.77) |
Xinjiang | 9/2673 (0.34) | 12/3119 (0.38) | 22/2893 (0.76) | 152/5774 (2.63) | 8/3066 (0.26) | 203/17,525 (1.16) |
Feature | 2016 N (%) * | 2017 N (%) * | 2018 N (%) * | 2019 N (%) * | 2020 N (%) * | Total N (%) * |
---|---|---|---|---|---|---|
Gender | ||||||
Boys | 479/19,497 (2.46) | 650/22,647 (2.87) | 592/24,601 (2.41) | 781/33,666 (2.32) | 513/30,008 (1.71) | 3015/130,419 (2.31) |
Girls | 432/16,980 (2.54) | 562/19,982 (2.81) | 541/21,486 (2.52) | 678/29,926 (2.27) | 455/27,053 (1.68) | 2668/115,427 (2.31) |
Ethnicity | ||||||
Buyi | 1/308 (0.32) | 0/365 (0.00) | 0/193 (0.00) | 1/523 (0.19) | 11/462 (2.38) | 13/1851 (0.70) |
Dong | 8/128 (6.25) | 6/419 (1.43) | 7/196 (3.57) | 0/96 (0.00) | 7/633 (1.11) | 28/1472 (1.90) |
Han | 764/28,455 (2.68) | 1034/34,263 (3.02) | 956/38,094 (2.51) | 1091/47,492 (2.30) | 863/45,098 (1.91) | 4708/193,402 (2.43) |
Hui | 22/1039 (2.12) | 2/997 (0.20) | 5/656 (0.76) | 13/2128 (0.61) | 17/2,269 (0.75) | 59/7089 (0.83) |
Kazak | 2/461 (0.43) | 4/645 (0.62) | 3/323 (0.93) | 0/103 (0.00) | 4/534 (0.75) | 13/2066 (0.63) |
Li | 6/197 (3.05) | 19/313 (6.07) | 11/143 (7.69) | 3/238 (1.26) | 20/248 (8.06) | 59/1139 (5.18) |
Miao | 19/709 (2.68) | 12/937 (1.28) | 10/330 (3.03) | 6/574 (1.05) | 5/924 (0.54) | 52/3474 (1.50) |
Tujia | 2/833 (0.24) | 3/681 (0.44) | 2/684 (0.29) | 0/516 (0.00) | 1/832 (0.12) | 8/3546 (0.23) |
Uygur | 3/1,644 (0.18) | 2/963 (0.21) | 17/1787 (0.95) | 152/5020 (3.03) | 1/1046 (0.10) | 175/10,460 (1.67) |
Yao | 3/65 (4.62) | 16/234 (6.84) | 10/169 (5.92) | 2/78 (2.56) | 11/413 (2.66) | 42/959 (4.38) |
Zhuang | 77/922 (8.35) | 102/789 (12.93) | 107/1111 (9.63) | 174/1764 (9.86) | 18/637 (2.83) | 478/5223 (9.15) |
Others | 4/1716 (0.23) | 12/2023 (0.59) | 5/2401 (0.21) | 17/5060 (0.34) | 10/3965 (0.25) | 48/15,165 (0.32) |
Ages | 2016 N (%) * | 2017 N (%) * | 2018 N (%) * | 2019 N (%) * | 2020 N (%) * | Total N (%) * |
---|---|---|---|---|---|---|
3 | 117/4984 (2.35) | 102/5655 (1.80) | 122/6613 (1.84) | 113/9262 (1.22) | 81/8093 (1.00) | 535/34,607 (1.55) |
4 | 180/5505 (3.27) | 199/6111 (3.26) | 221/6868 (3.22) | 213/8809 (2.42) | 133/8551 (1.56) | 946/35,844 (2.64) |
5 | 144/5622 (2.56) | 293/6917 (4.24) | 210/7556 (2.78) | 325/10,598 (3.07) | 183/8582 (2.13) | 1155/39,275 (2.94) |
6 | 166/5484 (3.03) | 226/6470 (3.49) | 210/7262 (2.89) | 294/9773 (3.01) | 201/8921 (2.25) | 1097/37,910 (2.89) |
7 | 154/4971 (3.10) | 154/5899 (2.61) | 175/5953 (2.94) | 208/8663 (2.40) | 172/7764 (2.22) | 863/33,250 (2.60) |
8 | 91/5095 (1.79) | 135/6108 (2.21) | 118/5923 (1.99) | 197/8580 (2.30) | 127/8095 (1.57) | 668/33,801 (1.98) |
9 | 59/4816 (1.23) | 103/5469 (1.88) | 77/5912 (1.30) | 109/7907 (1.38) | 71/7055 (1.01) | 419/31,159 (1.34) |
Year | Moran’s I | Expected Moran’s I value | Variance | Z value | P value |
---|---|---|---|---|---|
2016 | 0.154787 | −0.034483 | 0.004674 | 2.768400 | 0.005633 |
2017 | 0.235557 | −0.034483 | 0.00531 | 3.705713 | 0.000211 |
2018 | 0.226277 | −0.035714 | 0.006286 | 3.304426 | 0.000952 |
2019 | 0.314987 | −0.033333 | 0.008858 | 3.700856 | 0.000215 |
2020 | 0.230413 | −0.033333 | 0.007734 | 2.999004 | 0.002709 |
Year | Cluster Center (°) | Radius (km) | No. of Clustered Counties | LLR | No. of Observed | No. of Expected | P Value | |
---|---|---|---|---|---|---|---|---|
Latitude | Longitude | |||||||
2017–2018 | 22.5199 | 113.3940 | 647.46 | 234 | 532.57 | 1359 | 523.50 | 0.0000 |
2016–2017 | 29.5538 | 117.2960 | 128.07 | 11 | 238.40 | 184 | 21.04 | 0.0000 |
2016–2017 | 29.1221 | 105.4950 | 171.33 | 37 | 110.50 | 150 | 33.24 | 0.0000 |
2018 | 34.3418 | 111.4940 | 99.94 | 13 | 65.64 | 80 | 15.87 | 0.0000 |
2019 | 37.2055 | 78.5104 | 257.96 | 10 | 53.63 | 124 | 41.60 | 0.0000 |
2019–2020 | 33.1618 | 113.8890 | 154.52 | 33 | 39.56 | 177 | 84.13 | 0.0000 |
2018 | 31.9484 | 104.9240 | 118.98 | 15 | 27.97 | 34 | 6.70 | 0.0000 |
2016–2017 | 38.0833 | 116.3760 | 47.61 | 3 | 18.12 | 51 | 19.19 | 0.0001 |
2017 | 35.6715 | 114.4770 | 39.42 | 4 | 12.54 | 32 | 11.36 | 0.0190 |
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Huang, J.; Zhu, H.; Zhou, C.; Zhu, T.; Zhang, M.; Chen, Y.; Qian, M.; Li, S. Epidemiological Profile and Spatial Patterns of Enterobiasis in Children Aged 3–9 Years in China from 2016 to 2020. Trop. Med. Infect. Dis. 2023, 8, 25. https://doi.org/10.3390/tropicalmed8010025
Huang J, Zhu H, Zhou C, Zhu T, Zhang M, Chen Y, Qian M, Li S. Epidemiological Profile and Spatial Patterns of Enterobiasis in Children Aged 3–9 Years in China from 2016 to 2020. Tropical Medicine and Infectious Disease. 2023; 8(1):25. https://doi.org/10.3390/tropicalmed8010025
Chicago/Turabian StyleHuang, Jilei, Huihui Zhu, Changhai Zhou, Tingjun Zhu, Mizhen Zhang, Yingdan Chen, Menbao Qian, and Shizhu Li. 2023. "Epidemiological Profile and Spatial Patterns of Enterobiasis in Children Aged 3–9 Years in China from 2016 to 2020" Tropical Medicine and Infectious Disease 8, no. 1: 25. https://doi.org/10.3390/tropicalmed8010025
APA StyleHuang, J., Zhu, H., Zhou, C., Zhu, T., Zhang, M., Chen, Y., Qian, M., & Li, S. (2023). Epidemiological Profile and Spatial Patterns of Enterobiasis in Children Aged 3–9 Years in China from 2016 to 2020. Tropical Medicine and Infectious Disease, 8(1), 25. https://doi.org/10.3390/tropicalmed8010025