Epidemiological Profile and Spatial Patterns of Enterobiasis in Children Aged 3–9 Years in China from 2016 to 2020
by
,
Jilei Huang
1,2
,
Huihui Zhu
1,2,
Changhai Zhou
1,
Tingjun Zhu
1,
Mizhen Zhang
1,
Yingdan Chen
1,
Menbao Qian
1,2,3,* and
Shizhu Li
1,2,3,* 1
National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Center for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
2
Hainan Tropical Diseases Research Center (Hainan Sub-Center, Chinese Center for Tropical Diseases Research), Haikou 571199, China
3
School of Global Health, Chinese Center for Tropical Diseases Research-Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
*
Authors to whom correspondence should be addressed.
Trop. Med. Infect. Dis. 2023, 8(1), 25; https://doi.org/10.3390/tropicalmed8010025
Submission received: 5 December 2022
/
Revised: 19 December 2022
/
Accepted: 22 December 2022
/
Published: 29 December 2022
Abstract
:(1) Background: Enterobius vermicularis infection causes a significant health burden in children. The infection occurs throughout the country and remains a serious public concern in China. Therefore, it is necessary to know the situation of E. vermicularis infection, to provide a scientific basis for the disease control and the optimum conditions for children’s growth. (2) Methods: Descriptive epidemiological analysis was implemented to demonstrate the status and changing trend of E. vermicularis infection from 2016 to 2020, while the spatial distribution characteristics and spatial-temporal clustering were illuminated by spatial autocorrelation analysis and spatio-temporal scanning analysis. (3) Results: The infection of E. vermicularis showed a fluctuating downward trend with a decline of 32.00% in 2020 compared to that in 2016 and was concentrated in central and southern China. There was no significant difference in infection rate between boys and girls, while the high infection rate was presented in 4-, 5- and 6- year-old children. The hotspots and spatial clustering areas were mainly concentrated in southern China. (4) Conclusions: From 2016 to 2020, the infection rate of E. vermicularis in children aged 3 to 9 years in China demonstrated a declining trend, and its distribution showed spatial clustering, mainly in southern China. Therefore, it is necessary to strengthen surveillance and implement control measures in combination with health education and environmental improvement.
1. Introduction
Enterobiasis caused by Enterobius vermicularis infection is widely distributed around the world [1,2]. Transmission usually occurs among children in childcare agencies and kindergartens [3,4,5]. The main symptoms of enterobiasis include perianal skin itching, night terrors, grinding of teeth, irritability, anorexia and emaciation, but it may also cause appendicitis and urogenital system inflammation due to ectopic parasitism [6,7]. A long-term repeated infection will result in delayed growth and development of children and affect their physical and mental health [8,9,10]. Enterobiasis is prevalent in China [11], in spite of rapid economic and social development, improved quality of life and significantly enhanced health knowledge and awareness. According to the survey of national key human parasitic diseases in China in 2015, the infection rate of E. vermicularis was 0.33%, with an estimation of 2.14 million persons under infection. A high infection rate was presented in some areas (i.e., 3.85% in Hainan Province and 1.24% in Jiangxi Province) [12].
To boost the Healthy China initiative, the Chinese government issued “The national program for prevention and control of echinococcosis and other key parasitic diseases in 2016–2020” (hereinafter referred to as "the prevention and control program") and implemented programs for the prevention and control including a nationwide surveillance network for key parasitic diseases [13,14,15]. Since 2016, enterobiasis has been included in the national surveillance. The distribution characteristics and spatio-temporal clustering of E. vermicularis infection in children aged 3 to 9 years old in China between 2016 and 2020 are analyzed here, to provide a scientific basis for formulating the prevention and control programs of enterobiasis in future.
2. Methods
2.1. Sampling
According to “China’s national surveillance program for clonorchiasis and soil-borne nematodiasis (Trial)” (hereinafter referred to as “the surveillance program”), counties (cities and districts) from 31 provinces (autonomous regions and municipalities) in China were taken as the units and one or two counties were selected from each province to perform fixed site monitoring. Ten to fifteen percent of the counties were then selected for mobile site monitoring, where the monitoring sites were not repeated within 5 years. A total of 1324 monitoring sites were selected in this study. Each monitoring site was divided into five areas according to its geographical location (eastern, western, southern, northern and central areas). One township (town) was randomly selected from each area, and then, one administrative village was further selected from each township. About 200 permanent residents over 3 years old were chosen from each administrative village every year. Thus, a total of 1000 persons were surveyed at each monitoring site and the average proportion of children aged 3 to 9 years was usually not less than 10%. Those children aged 3 to 9 years old were eligible for surveillance of enterobiasis.
2.2. Detection of Infection
One stool sample was collected from each participant, and the modified Kato–Katz thick smear method [16] was adopted to detect helminth eggs. In children aged 3 to 9 years old, the adhesive cellophane-tape anal swab method [17] was simultaneously applied to detect eggs of E. vermicularis. In brief, separate the anus of the child with the index finger and thumb, expand the perianal fold, then press the clear adhesive sticker repeatedly on the anal opening. The adhesive sticker is placed on the slide and then examined under microscope. If eggs of E. vermicularis were detected by any of the two methods, the individual was defined as positive for E. vermicularis infection.
2.3. Database and Statistical Analysis
The detection results and personal information of the subjects at each monitoring site were registered in the recording forms and entered into the surveillance system. In combination with the GPS coordinates of each monitoring site, ArcGIS 10.2 software was used to establish the spatial distribution database of E. vermicularis infection in children aged 3 to 9 in China from 2016 to 2020.
Descriptive epidemiological analysis was used to analyze the epidemiological characteristics of E. vermicularis infection among children aged 3 to 9 years in China from 2016 to 2020. The survey data were statistically analyzed with Microsoft Excel 2016 and SAS 9.3, and E. vermicularis infection rate in children aged 3 to 9 years was calculated. The χ2 test was used to test significance, with a P value less than 0.05 indicating a statistically significant difference.
2.4. Spatial Autocorrelation Analysis
Global spatial autocorrelation analysis was conducted with the global spatial autocorrelation index in Moran’s I in the ArcGIS(Esri® 10.2, Redlands, CA, USA) software [18,19,20], and the spatial clustering of E. vermicularis infection in children was assessed according to the location of elements and attribute values. Hot spot analysis was carried out using Getis-Ord Gi* (ArcGIS 10.1, Esri, Redlands, CA, USA) [21,22], and each element in the data set was analyzed to obtain the Z score and P value. These were used to determine the clustering location of the high-value (hot spot) or low-value (cold spot) elements of E. vermicularis infection in children with statistical significance. The hot spots with statistical significance were detected by scanning for elements with high P and Z values, which were surrounded by other elements with the same high values, thereby identifying high-value cluster areas of E. vermicularis infection in children.
2.5. Spatio-Temporal Analysis
SaTScan (v9.5, Boston, MA, USA) [23] software was used for retrospective spatio-temporal scanning analysis to explore cluster status. The scanning was conducted at different times and areas through scanning windows with dynamically changed sizes and positions. The theoretical number of infected people was calculated according to the number of infected people and investigated people. The actual and theoretical numbers of cases inside and outside the scanning windows were used to construct the Log likelihood ratio (LLR) of test statistics, to evaluate the abnormality of the number of infected people in the scanning window [23,24]. At the same time, the Monte Carlo method was used as the statistical test on the possible abnormal windows, and P < 0.05 indicated statistical significance. On the premise of statistical significance, a larger LLR value suggested a greater probability that the area under the scanning window would be a cluster area [25]. In this study, a Poisson model was adopted for the SaTScan spatio-temporal scanning analysis, and the maximum scanning window was set to 50% of all the population at risk in the study area.
3. Results
3.1. Overall Infection
Out of 245,846 children aged 3 to 9 years in 1324 counties investigated from 2016 to 2020, 5683 ones were infected with E. vermicularis. The average infection rate was 2.31%, while the annual infection rates were 2.50% (911/36,477), 2.84% (1212/42,629), 2.46% (1133/46,087), 2.29% (1459/63,592) and 1.70% (968/57,061), respectively. The infection rate in 2020 decreased by 32.00% compared to that in 2016 (Figure 1 and Table 1).
3.2. Regional Distribution
Provinces with high E. vermicularis infection rate were mainly distributed throughout southern China. Those with an average infection rate above 5% during the five years included Jiangxi, Guangxi, Hainan and Fujian provinces, with an infection rate of 10.15%, 7.05%, 6.96% and 5.56%, respectively. The infection rate in 11 provinces ranged from 1% to 5%, while the remainder was less than 1% (Table 1).
Among the focus areas, the infection rate of E. vermicularis in children in Jiangxi decreased year by year from 2016 to 2019 but increased slightly in 2020. The infection rates of the five years were 12.12%, 14.29%, 8.52%, 6.83% and 7.81%, respectively, and the infection rate decreased by a total of 35.56% over the five years (Table 1). The infection rates in Guangdong and Guangxi decreased by 49.09% and 26.32%, respectively, over the five years. The infection rate in Hainan province fluctuated from year to year. The infection rate in Fujian firstly increased from 2016 to 2019, and then decreased in 2020 (Table 1).
3.3. Population Distribution
The average infection rate was 2.31% (3015/130,419) in boys and 2.31% (2668/115,427) in girls, and there existed no statistical difference in each year (χ2 = 0.29, P = 0.59; χ2 = 0.13, P = 0.72; χ2 = 0.59, P = 0.44; χ2 = 0.21, P = 0.65; χ2 = 0.07, P = 0.80) (Table 2). The infection rates in boys and girls decreased by 30.49% and 33.86%, respectively, over the five years.
From 2016 to 2020, the infection rate in children from Dong, Han, Hui, Miao, Tujia, Uygur, Yao and Zhuang ethnic groups decreased, while those from Buyi, Kazak and Li increased. There were significant differences in the infection rates among the ethnic groups (χ2 values of 247.19, 453.83, 361.89, 608.68 and 183.41, respectively, with P < 0.0001). The infection rate in children from Zhuang was the highest from 2016 to 2019 (8.35%, 12.93%, 9.63% and 9.86%). In 2020, the infection rate in children from Li was the highest (8.06%), and that from Zhuang ranked second (2.83%). The infection rate in children from Zhuang decreased by 66.11% over the five years, while that in children from Li increased by 164.26%. The average infection rate in children from Han was 2.43% (4708/193,402) and that from other ethnic groups was 1.90% (975/52,444) (χ2 = 60.44, P < 0.0001) (Table 2).
From 2016 to 2020, the infection rate of all ages decreased, and the infection rates in the age of 3-, 4-, 5-, 6-, 7-, 8- and 9-year-old decreased by 57.45%, 52.29%, 16.80%, 25.74%, 28.39%, 12.29% and 17.89%, respectively. In 2016 and 2018, the 4-year-old group had the highest infection rate and the 3-year-old group had the lowest. In 2017 and 2019, the 5-year-old group had the highest infection rate and the 9-year-old group had the lowest. In 2020, the 6-year-old group had the highest infection rate and the 3-year-old group presented the lowest. The infection rates were significantly different by ages in each year (Figure 2; Table 3).
3.4. Global Spatial Autocorrelation Analysis
Moran’s I coefficients from 2016 to 2020 for the global spatial autocorrelation analysis at the provincial level ranged from 0.15 to 0.32, which was greater than expected. Meanwhile, the Z values were all > 0, and the significance values were all P < 0.01 (Table 4), suggesting that there was spatial clustering in the provincial distribution of E. vermicularis infection in children in China during these five years. Global spatial autocorrelation analyses at county levels revealed Moran’s I coefficient to be 0.08 to 0.17, also greater than expected. Z values were >0 and P values were 0, suggesting that the infection was spatially clustered.
3.5. Hotspot Analysis
The hotspot analysis at the provincial level (Figure 3) identified four “hot spot” areas, namely Jiangxi, Guangdong, Guangxi and Fujian in 2016. In 2017, there were six “hot spot” areas, including Jiangxi, Guangdong, Guangxi, Hainan, Chongqing and Fujian. There were five “hot spot” areas in 2018, namely, Jiangxi, Guangxi, Fujian, Guangdong and Hainan, and there were five “hot spot” areas in 2019, including Jiangxi, Guangxi, Fujian, Hainan and Guangdong. There were five “hot spot” areas in 2020, namely, Jiangxi, Hainan, Guangdong, Guangxi and Fujian. There were no “cold spot” areas during the five years.
The results of the hotspot analysis at the county level (Figure 4) demonstrated that “hot spots” included partial districts and counties in Hainan, Guangxi, Guangdong, Fujian, Jiangxi, Hunan, Chongqing, Sichuan, Guizhou, Anhui, Hubei and Henan, while the “cold spots” included some districts and counties in Liaoning, Jilin, Heilongjiang, Inner Mongolia, Hebei, Ningxia and Gansu.
3.6. Spatio-Temporal Analysis
The cluster analysis of spatio-temporal scanning statistics at the county levels (Figure 5) illustrated that the infection rate of E. vermicularis among children in China showed 9 clustering areas from 2016 to 2020 (Table 5). The successive decrease in LLR indicated that the clustering intensity was weakening over the five years. From 2016 to 2018, there were 7 clustering areas, involving 317 counties belonging to 10 provinces, namely, Hainan, Guangxi, Guangdong, Fujian, Jiangxi, Hunan, Sichuan, Chongqing, Anhui and Hebei. The radius of the largest clustering area was 647.46 km. Two clustering areas were observed in 2019–2020, involving 43 counties belonging to Henan and Xinjiang. The radius of the largest clustering area here was 257.96 km.
4. Discussion
Enterobiasis is a common parasitic disease in children worldwide, especially in poor areas of developing countries. Due to a lack of attention, enterobiasis has affected the growth of children. In 2015, the national survey for major human parasitic diseases in China demonstrated that E. vermicularis infection was present in 28 provinces and children under 9 years were the majorly afflicted population [12]. From 2016 to 2020, China increased the control of soil-borne nematodiasis and established a surveillance network in which E. vermicularis infection in children aged 3 to 9 was included [26,27]. This supports the capture of the epidemic situation of enterobiasis in children in China, with benefit in formulating and improving intervention measures.
The results of this study indicate that the infection rate of E. vermicularis in children aged 3 to 9 years in China dropped significantly, by 32% in 2020 compared to that in 2016. However, enterobiasis is still prevalent in some areas, where there exist a suitable climate, ecological environment, and production and lifestyle. The infection rate of boys and girls both decreased, while the difference was not significant in different genders. This result was consistent with the findings of the studies carried out in Shandong [28], Guangxi [29], Henan [30], Anhui, Fujian and other provinces [31]. In addition, the infection rate of E. vermicularis was the highest in children from the Zhuang ethnic group during 2016–2019, while it was the highest in children from Li in 2020, because they live in Guangxi and Hainan, where the climate and abundant rainfall are suitable for the survival and reproduction of the parasite. Additionally, poor hygiene habits, ethnic diets and poor living conditions coupled with a lack of awareness also cause a high infection rate [32,33,34]. In this study, the infection rate was higher in 4-, 5- and 6- year-old children, while a lower infection rate was observed in children aged 3 and 9. The high infection rate in children aged 4 to 6 years may be due to children in this age group starting to enter kindergarten, which increases the risk of infection [35]. The infection rate in the 3-year-old group was low, as these children were probably still at home or only attended kindergarten intermittently. Older children probably suffer less from E. vermicularis infection as personal hygiene habits improve with age and education level [36].
The results of the hotspot analysis at the provincial and county levels showed that the hotspots of E. vermicularis infection among children aged 3 to 9 in China were concentrated in the southern areas of the Yangtze River, such as Jiangxi, Guangxi and Hainan. The SaTScan spatial–temporal scanning analysis demonstrated that the largest clustering areas of infection among children included Hainan, Guangxi, Guangdong, Fujian and Jiangxi. From 2016 to 2020, the high infection areas were Jiangxi (14.29%), Guangxi (13.66%), Hainan (9.60%), Chongqing (9.40%), Guangdong (7.42%) and Fujian (7.20%) (Table 5), respectively. After comparison, it is consistent with the hotspot areas and the largest cluster areas. Firstly, the temperature and humidity in the southern region are higher compared to other regions, rendering the soil more suitable for the growth and development of E. vermicularis. Secondly, these areas are lacking in sanitation and hygiene, which favors infection [37,38].
5. Conclusions
In conclusion, E. vermicularis infection in children aged 3 to 9 years in China decreased considerably from 2016 to 2020 by 32% and the high infection rate was concentrated in 4-, 5- and 6-year-old children. However, there still exist high infection areas, mainly concentrated in the south of the Yangtze River in China. Thus, it is necessary to strengthen surveillance and implement control measures in combination with health education and environmental improvement. This study adds to the growing body of knowledge concerning the epidemic situation of enterobiasis among children aged 3 to 9 years in China, thus providing support for formulating prevention and control strategies and optimizing the allocation of resources for enterobiasis.
Author Contributions
Writing—original draft, J.H.; Writing—review & editing, J.H., S.L. and M.Q.; Conceptualization, J.H., S.L. and M.Q.; Data curation, J.H., H.Z. and T.Z.; Formal analysis, J.H., H.Z.; Investigation, J.H., H.Z., C.Z., T.Z. and M.Z.; Methodology, J.H., H.Z. and S.L.; Funding acquisition, Y.C. and M.Q. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported by the National Key Research and Development Program of China (No. 2021YFC2300800, 2021YFC2300804); National Natural Science Foundation of China (No.32161143036); Science & Technology Fundamental Resources Investigation Program (Grant No. 2022FY100900, 2022FY100904).
Institutional Review Board Statement
The article was based on the monitoring data from the National Institute of Parasitic Diseases (NIPD), Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), and it received approval from the Institutional Ethical Review Committee of NIPD with the document No. 2021006.
Informed Consent Statement
Informed consent for fecal sample collection was obtained from all parents or caretakers of the respondents and the statement consent was verbal.
Data Availability Statement
Data cannot be shared publicly because of personal information presented in the database. Data are deposited in the National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), of which access is available through corresponding author ([email protected]) for researchers who meet the criteria for access to confidential data.
Acknowledgments
We are grateful to the Centers for Disease Control and Prevention staff from provincial, municipal and county levels.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Fan, C.K.; Chuang, T.W.; Huang, Y.C.; Yin, A.W.; Chou, C.M.; Hsu, Y.T.; Kios, R.; Hsu, S.L.; Wang, Y.T.; Wu, M.S.; et al. Enterobius vermicularis infection: Prevalence and risk factors among preschool children in kindergarten in the capital area, Republic of the Marshall Islands. BMC Infect. Dis. 2019, 19, 536. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kucik, C.J.; Martin, G.L.; Sortor, B.V. Common intestinal parasites. Am. Fam. Physician 2004, 69, 1161–1168. [Google Scholar] [PubMed]
- Burkhart, C.N.; Burkhart, C.G. Assessment of frequency, transmission, and genitourinary complications of enterobiasis (pinworms). Int. J. Dermatol. 2005, 44, 837–840. [Google Scholar] [CrossRef] [PubMed]
- Al-Daoody, A.A.K.; Al-Bazzaz, E.N.H. Impact of Enterobius vermicularis infection on biochemical parameters in the blood of children in Erbil Province, Iraq. BMC Infect. Dis. 2020, 20, 1–6. [Google Scholar] [CrossRef]
- An, Y.; Pang, X.; Liu, J.; Huang, S. Advances in research on harm and control of Enterobius vermicularis infection in children. Chin. J. Schisto. Control 2012, 24, 598–600. [Google Scholar]
- Tsai, C.Y.; Junod, R.; Jacot-Guillarmod, M.; Beniere, C.; Ziadi, S.; Bongiovanni, M. Vaginal Enterobius vermicularis diagnosed on liquid-based cytology during Papanicolaou test cervical cancer screening: A report of two cases and a review of the literature. Diagn. Cytopathol. 2018, 46, 179–186. [Google Scholar] [CrossRef] [Green Version]
- Altun, E.; Avci, V.; Azatcam, M. Parasitic infestation in appendicitis. A retrospective analysis of 660 patients and brief literature review. Saudi Med. J. 2017, 38, 314–318. [Google Scholar] [CrossRef]
- Li, Y. Human Parasitology, 7th ed.; People’s Medical Publishing House: Beijing, China, 2008; pp. 166–168. [Google Scholar]
- Zhu, X.P.; Su, C. Human Parasitology, 8th ed.; People’s Medical Publishing House: Beijing, China, 2013; pp. 161–163. [Google Scholar]
- Wendt, S.; Trawinski, H.; Schubert, S.; Rodloff, A.C.; Mössner, J.; Lübbert, C. The Diagnosis and Treatment of Pinworm Infection. Dtsch. Ärzteblatt Int. 2019, 116, 213–219. [Google Scholar] [CrossRef]
- Zhou, C.; Zhu, H.; Zang, W.; Zhang, X.; Chen, Y. Monitoring of Enterobius vermicularis infection among children from 2006 to 2010 and SWOT analysis. Chin. J. Schisto. Control 2014, 26, 370–375. [Google Scholar]
- Zhou, X. Report on the National Survey of Important Human Parasitic Diseases in China (2015); People’s Medical Publishing House: Beijing, China, 2018; pp. 2, 64–66. [Google Scholar]
- Gao, F. Annual Report on Surveillance of Infectious Disease in China, 2016; Chinese Center for Disease Control and Prevention: Beijing, China, 2017; pp. 384–392. [Google Scholar]
- Gao, F. Annual Report on Surveillance of Infectious Disease in China, 2020; Chinese Center for Disease Control and Prevention: Beijing, China, 2021; pp. 391–398. [Google Scholar]
- Zhu, H.; Huang, J.; Zhu, T.; Duan, L.; Zhou, C.; Qian, M.; Chen, Y. National surveillance of soil-transmitted helminth infections in 2017. Chin. J. Parasitol. Parasit. Dis. 2019, 37, 12–17. [Google Scholar] [CrossRef]
- Wang, S.; Yu, B.; Fan, B. Introduction of the modified Kato-Katz thick smear method. Dis. Surveill. 1994, 12, 344. [Google Scholar]
- Fang, Y.; Cheng, Y.; Xu, X. Improvement and use of cellophane anal swab. J. Pract. Parasit. Dis. 1997, 01, 23. [Google Scholar]
- Blazquez, C.A.; Picarte, B.; Calderon, J.F.; Losada, F. Spatial autocorrelation analysis of cargo trucks on highway crashes in Chile. Accid. Anal. Prev. 2018, 120, 195–210. [Google Scholar] [CrossRef]
- Adham, D.; Moradi-Asl, E.; Dorosti, A.; Khaiatzadeh, S. Spatial autocorrelation and epidemiological survey of visceral leishmaniasis in an endemic area of Azerbaijan region, the northwest of Iran. PLoS ONE 2020, 15, e236414. [Google Scholar] [CrossRef]
- Ren, H.; Shang, Y.; Zhang, S. Measuring the spatiotemporal variations of vegetation net primary productivity in Inner Mongolia using spatial autocorrelation. Ecol. Indic. 2020, 112, 106108. [Google Scholar] [CrossRef]
- Zhang, Z.; Clark, A.B.; Bivand, R.; Chen, Y.; Carpenter, T.E.; Peng, W.; Zhou, Y.; Zhao, G.; Jiang, Q. Nonparametric spatial analysis to detect high-risk regions for schistosomiasis in Guichi, China. Trans. Roy. Soc. Trop. Med. Hyg. 2009, 103, 1045–1052. [Google Scholar] [CrossRef]
- Mashinini, D.P.; Fogarty, K.J.; Potter, R.C.; Berles, J.D. Geographic hot spot analysis of vaccine exemption clustering patterns in Michigan from 2008 to 2017. Vaccine 2020, 38, 8116–8120. [Google Scholar] [CrossRef]
- Jung, I.; Kulldorff, M.; Klassen, A.C. A spatial scan statistic for ordinal data. Stat. Med. 2007, 26, 1594–1607. [Google Scholar] [CrossRef]
- Xue, J.; Xia, S.; Zhang, X.; Hu, H.; Wang, Q.; Zhou, Y.; Li, S. Pattern analysis of tempo-spatial distribution of schistosomiasis in marshland epidemic areas in stage of transmission control. Chin. J. Schisto. Control 2016, 28, 624–629. [Google Scholar] [CrossRef]
- Anselin, L. Local indicators of spatial association-LISA. Geogr. Anal. 1995, 27, 93–115. [Google Scholar] [CrossRef]
- Huang, J.; Zhang, M.; Zhu, H.; Zhu, T.; Zhou, C.; Qian, M.; Chen, Y. National surveillance on Enterobius vermicularis infections among children at ages of 3 to 9 years in China from 2016 to 2018. Chin. J. Schisto. Control 2020, 32, 54–59. [Google Scholar] [CrossRef]
- Zhu, H.; Huang, J.; Chen, Y.; Zhou, C.; Zhu, T.; Qian, M.; Zhang, M.; Li, S.; Zhou, X. Analysis on endemic status of soil-transmitted nematode infection in China in 2019. Chin. J. Parasitol. Parasit. Dis. 2021, 39, 666–673. [Google Scholar] [CrossRef]
- Bu, X.; Zhao, C.; Yan, G.; Wang, Y.; Wang, L.; Kong, X.; Xu, Y.; Zhang, B. Surveillance of Enterobius vermicularis infections among children in Shandong Province from 2016 to 2020. Chin. J. Schisto. Control 2021, 33, 401–405. [Google Scholar] [CrossRef]
- Wan, X.; Lv, G.; Jiang, Z.; Ou, F.; Wei, H.; Tang, W.; Li, Y.; Zhang, W.; Huang, K.; Shi, Y.; et al. Surveillance on soil-transmitted nematode infections in population in Guangxi Zhuang Autonomous Region during 2016–2020. Chin. J. Parasitol. Parasit. Dis. 2021, 39, 800–806. [Google Scholar] [CrossRef]
- Song, C.; Jiao, X.; Jiang, T.; Liang, G.; Wang, L.; Xu, Y.; Huang, S.; Chen, W.; Deng, Y.; Zhang, Y. Prevalence and influencing factors of Enterobius vermicularis infections among children in Fanxian County of Henan Province in 2019. Chin. J. Schisto. Control 2021, 33, 406–410. [Google Scholar] [CrossRef]
- Chen, Y.; Wang, J.; Zhu, H.; Zhu, T.; Zang, W.; Qian, M.; Li, H.; Zhou, C.; Wang, G.; Xu, L. Enterobius vermicularis Infection Status among Children in 9 Provinces/Autonomous regions/Municipalities of China. Chin. J. Parasitol. Parasit. Dis. 2013, 31, 251–255. [Google Scholar]
- Kuang, C.; Wu, X.; Chen, W.; Wu, F.; Zhuo, F. Prevalence and risk factors of Enterobius vermicularis among preschool children in kindergartens in Luohu District, Shenzhen City. Chin. J. Schisto. Control 2015, 27, 76–78. [Google Scholar] [CrossRef]
- Chen, W.; Li, S.; Zhang, Y.; Deng, Y.; Xu, B.; Zhang, H.; Lin, X.; Li, P.; Zhao, Y.; Yang, C.; et al. Prevalence and influencing factors of intestinal parasitic diseases among rural children in Henan Province. Chin. J. Schisto. Control 2019, 31, 491–497. [Google Scholar] [CrossRef]
- Mao, F.; Yang, Y.; Zhang, Q.; Ding, X.; Xu, X.; Chen, Y.; Dai, Y.; Cao, J. Knowledge and Practice of Pinworm Infection in Preschool Children, Jiangsu Province, China, 2019–2020. Am. J. Public Health 2022, 112, 1716–1720. [Google Scholar] [CrossRef]
- Wang, X.; Zhou, Q.; Sh, A.; Li, L.; Wang, Y.; Hu, S.; Cui, J. A survey on Enterobius vermicularis infection among pre-school children in Guoyang County of Anhui Province. Chin. J. Parasitol. Parasit. Dis. 2018, 36, 139–143. [Google Scholar]
- Chen, Z.; Jiang, W.; Ge, J.; Dai, K.; Li, D.; Liu, K.; Zeng, X. Analysis on the results of surveillance of Enterobius vermicularis infection among children in rural areas in Jiangxi Province during 2016–2019. Chin. J. Parasitol. Parasit. Dis. 2020, 38, 542–547. [Google Scholar] [CrossRef]
- Jiang, L. Investigation of pinworm infection among children in a county of Pingxiang, Jiangxi Province from 2016 to 2019. Shanghai Med. Pharm. J. 2021, 42, 60–62. [Google Scholar]
- Chi, J.; Sun, M. Analysis of enterobius vermicularis infection among children aged from 3 to 7 years in Chuzhou area. J. Qiqihar Med. Univ. 2020, 41, 1131–1133. [Google Scholar]
Figure 1.
Enterobius vermicularis infections among children aged 3 to 9 years old in China from 2016 to 2020. The differences of the annual infection rates were statistically significant from 2016 to 2020 (χ2 = 159.02, P < 0.0001).
Figure 1.
Enterobius vermicularis infections among children aged 3 to 9 years old in China from 2016 to 2020. The differences of the annual infection rates were statistically significant from 2016 to 2020 (χ2 = 159.02, P < 0.0001).
Figure 2.
Enterobius vermicularis infection among children by ages in China from 2016 to 2020. The difference in infection rate was significant among ages in each year (χ2 values of 70.32, 112.62, 79.89, 128.73 and 84.33, respectively, with P < 0.0001).
Figure 2.
Enterobius vermicularis infection among children by ages in China from 2016 to 2020. The difference in infection rate was significant among ages in each year (χ2 values of 70.32, 112.62, 79.89, 128.73 and 84.33, respectively, with P < 0.0001).
Figure 3.
The provincial results of Getis-Ord Gi* from 2016 to 2020.
Figure 4.
The county-level results of Getis-Ord Gi* from 2016 to 2020.
Figure 5.
Space–time scanning analysis of Enterobius vermicularis infection among children in China from 2016 to 2020.
Figure 5.
Space–time scanning analysis of Enterobius vermicularis infection among children in China from 2016 to 2020.
Table 1.
Enterobius vermicularis infection among children aged 3 to 9 years old in China from 2016 to 2020.
Table 1.
Enterobius vermicularis infection among children aged 3 to 9 years old in China from 2016 to 2020.
| 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) |
* N = No. infected/No. examined. (1) No surveillance was implemented in Shanxi Province in 2018. (2) No surveillances were implemented in Tibet from 2016 to 2018.
Table 2.
Enterobius vermicularis infection among children by gender and ethnicity in China from 2016 to 2020.
Table 2.
Enterobius vermicularis infection among children by gender and ethnicity in China from 2016 to 2020.
| 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) |
* N = No. infected/No. examined.
Table 3.
Enterobius vermicularis infection among children by ages in China from 2016 to 2020.
| 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) |
* N = No. infected/No. examined.
Table 4.
Global spatial autocorrelation analysis of Enterobius vermicularis infection among children in China from 2016 to 2020.
Table 4.
Global spatial autocorrelation analysis of Enterobius vermicularis infection among children in China from 2016 to 2020.
| 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 |
Table 5.
Cluster analysis of Enterobius vermicularis infection among children in China from 2016 to 2020 by spatial and space–time scan statistic.
Table 5.
Cluster analysis of Enterobius vermicularis infection among children in China from 2016 to 2020 by spatial and space–time scan statistic.
| 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 |
° A unit of measure for latitude and longitude, the combination of latitude and longitude can mark any location on Earth.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
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
AMA Style
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
