Epidemiological Investigation of Yak (Bos grunniens) Fascioliasis in the Pastoral Area of Qinghai–Tibet Plateau, China
by
,
Qijian Cai
1,
Mengtong Lei
2,*,
Chunhua Li
2,
Jinzhong Cai
2,
Doudou Ma
2 and
Houshuang Zhang
1,* 1
Key Laboratory of Animal Parasitology, Ministry of Agriculture and Rural Affairs, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai 200241, China
2
Qinghai Academy of Animal Science and Veterinary Sciences, Xining 810016, China
*
Authors to whom correspondence should be addressed.
Animals 2023, 13(21), 3330; https://0-doi-org.brum.beds.ac.uk/10.3390/ani13213330
Submission received: 21 August 2023
/
Revised: 7 October 2023
/
Accepted: 16 October 2023
/
Published: 26 October 2023
(This article belongs to the Special Issue Veterinary Parasitology: Epidemiology, Control and Prevention Strategies)
Abstract
:Simple Summary
Infection of humans and animals with Fasciola spp. poses a threat to both the health of humans and animals and the animal industry. In the pastoral areas of the Qinghai–Tibet Plateau, yak is the most important economic animal, especially for the herdsmen and their animal products. However, the infection of yaks with Fasciola spp. is often underestimated. In this study, we investigated a total of 1784 yaks in 16 administrative counties in the Qinghai–Tibet Plateau region by fecal examination and autopsy of yaks after slaughter, and the differences in infection rates between different age groups and regions were analyzed. The clustering characteristics of the infection rates in spatial statistics were summarized. This investigation revealed that yaks on the Qinghai–Tibet Plateau had a high Fasciola spp. prevalence (17.32%), age was a risk factor for Fasciola spp. infection, and regional differences were the other risk factor for Fasciola spp. infection.
Abstract
The objective of this investigation was to understand the epidemiology of fascioliasis in yaks in the alpine pastoral areas of the Qinghai–Tibet Plateau, China. The prevalence of Fasciola hepatica infection was estimated by examining eggs in the feces of yaks and by autopsy after the slaughter. Yaks were sampled from a total of 16 representative counties in Qinghai province, and risk factors were assessed based on regional and age characteristics. Fecal samples were obtained from 1542 yaks aged 0–1 (<1 year old), 1–2 (≥1 year old and <3 years old), and over 3 years (≥3 years old). In addition, 242 yaks over 3 years old who had not undergone fecal examinations were randomly selected for autopsy. A total of 267 fecal samples were positive for Fasciola spp. eggs. The average infection rate was 17.32% (0–60.61%), and the average infection intensity was 51.9 eggs per gram (epg) of feces, with intensities ranging from 18 to 112 epg. In Maduo, Dari, Zhiduo, Chengduo, and Datong counties, the Fasciola spp. eggs infection rate was zero. Fasciola spp. adult flukes were detected in 66 out of 242 yaks at autopsy, with a total infection rate of 27.27% and an average infection intensity of 21.2 (adult worms), with intensities ranging from 3 to 46 worms. Logistic regression model analysis showed that age was a significant risk factor for yak infection with Fasciola spp. In addition, the risk varied between regions: Haiyan, Gangcha, Duran, and Wulan were all high-risk areas for yak infection with Fasciola spp. The spatial distribution of the Fasciola spp. infection rate in each region showed a very weak negative correlation (Moran’s I = −0.062), Duran formed a spatial distribution of high–low clusters with surrounding areas, and Datong formed a low–high clustering distribution characteristic with the surrounding areas. This investigation revealed that the infection rate of Fasciola spp. in yaks was higher on the Qinghai–Tibet Plateau. Increasing age was a risk factor for infection with Fasciola spp.; different regions also have a different risk of Fasciola spp. infection. Only two regions showed clustering characteristics in the spatial distribution of infection rates. These findings extend the epidemiological information on Fasciola spp. infection in yaks and provide baseline data for the execution of control measures against Fasciola spp. infection.
1. Introduction
The yak is a unique cattle species produced by severe natural selection and self-adaptation in the Qinghai–Tibet Plateau and its adjacent areas. The yak is a unique biological resource of the plateau in China and cannot be replaced by other animal species. Yaks are mainly distributed on the Qinghai–Tibet Plateau and its adjacent areas, with a population of more than 14 million [1,2]. Yaks provide local herdsmen with production and daily necessities, such as milk, meat, wool, labor, and fuel, which are closely related to production and the daily lives of the local people [3].
Fascioliasis is an emerging neglected infection caused by Fasciola spp. that affects animals and human health and well-being [4]. Fasciola infection is caused by ingestion of encysted metacercariae; the infected hosts show acute symptoms (fever and abdominal pain) or chronic symptoms (intermittent pain, jaundice and anemia, pancreatitis, liver fibrosis or abscess or cirrhosis, cholangitis, cholecystitis, obstruction of bile flow, and gallstones), and even death [5,6,7,8,9,10,11]. Several studies have shown that Fasciola spp. is the dominant species of yak parasites [12,13,14,15,16]. After yaks are infected with Fasciola spp., their working ability is reduced, their growth is slowed, their development is blocked, production performance and commercial value decrease significantly, and large quantities of slaughtered yak livers that cannot be sold as livestock products are wasted. In particular, this can lead to the death of a large number of young yaks, causing great economic loss to the yak breeding industry while posing a threat to human health.
Qinghai province of the Qinghai–Tibet Plateau is the source region of China’s Three Rivers and has a low air pressure, a low temperature, a large temperature difference between day and night, little but concentrated rainfall, a long period of sunshine, strong solar radiation, and a low oxygen content [17,18]. Winter is cold and long, while summer is cool and short. There are clear differences in climate among the different regions. The altitude is above 3000 m, and there are many rivers, streams, and marshes in most regions, which is suitable for the survival and reproduction of the intermediate hosts of Fasciola spp. Yaks rely on natural pastures for feeding. Due to the lack of infrastructure, herdsmen and yaks drink water from nearby rivers and are vulnerable to parasitic diseases with a variety of pathogens, including Fasciola spp. This phenomenon becomes a favorable condition for the life cycle of Fasciola spp.
Fasciola spp. are the major species of yak parasites, presenting a regional epidemic fascioliasis; however, information on the epidemiology of Fasciola spp. infection in yaks in the pastoral areas of Qinghai province is limited. The objective of this study was to investigate the prevalence of yak fascioliasis in pastoral areas of the Qinghai Plateau through fecal and necropsy examinations, aiming to provide baseline data for the prevention and control of yak fascioliasis in China.
2. Materials and Methods
2.1. Origin of Experimental Animals
From March to April 2020, 1784 yaks were selected as a random subset from yak farms in 16 counties in Qinghai Province, comprising 1542 yaks for fecal tests and 242 yaks for autopsy. All yaks were over 3 years old at autopsy, and the detailed sample collection information is shown in Table 1.
2.2. Examination of Fasciola spp. Eggs in Feces
The random sampling method was adopted. Fresh fecal samples of the yaks were collected through the rectum before grazing in the morning; they were numbered, and their genders, ages, and geographic locations were recorded. The samples collected (each sample was ≥50 g) were placed in zip-locked bags, placed into refrigerated boxes, taken back to the laboratory, and placed in a 4 °C refrigerator until examination.
2.3. Examination and Identification of Adult Worms
We randomly selected 242 yaks over 3 years old without fecal examination from 16 different localities to be autopsied. These autopsy samples were all collected from 16 different regional slaughterhouses; they are shown in Table 2. The flukes recovered from the liver and cholecyst were washed immediately in saline and preserved in 70% ethanol. The identification of Fasciola spp. was based on morphological characteristics [19].
2.4. Molecular Identification of Adult Worms
According to the published sequences of the internal transcribed spacers (ITS) of F. hepatica that are available in the GenBank (accession number: AJ628432, AJ628431), primers for the amplification of ITS-1 and ITS-2 of F. hepatica were designed: ITS-1 primers: F1: CTCATTGAGGTCACAGCAT, F2: CAATGGCAAAGAATGGCAAG; ITS-2 primers: F3: ATATTGCGGCCATGGGTTAG, F4: CCAATGACAAAGTGACAGCG. PCR amplifications of the above regions were performed in 50 µL of a reaction mixture containing 22 L of 2×Taq Mastermix (Qiagen, Hilden, Germany), 0.5 µL of each primer (50 pmol/µL), and 4 µL of template DNA; DNase/RNase-free deionized water was added to bring the volume to 50 µL. A negative control (without DNA) was included in each PCR reaction. The PCR amplification conditions were as follows: initial denaturation at 98 °C for 5 min, followed by 30 cycles consisting of denaturation at 94 °C for 30 s, annealing at 52 °C for 30 s, and extension at 72 °C for 30 s. A final elongation step was conducted at 72 °C for 5 min at the end of the amplification procedure.
2.5. Prevalence of Fasciola spp.
The following calculations were made using the appropriate formulas: infection rate = (number of infected animals/number of examined animals) × 100%. Mean infection intensity = number of detected (eggs or worms)/number of infected animals examined. Range of infection = minimum positive infections − maximum positive infections. Fasciola spp. eggs were all counted as epg, the number of epg in the fecal sample. Subsequent representations of the egg infection intensity were used in the following format: epg of feces (minimum number of infected epg of feces − maximum number of infected epg of feces).
2.6. Statistical Analysis
The differences in prevalence between regions were analyzed using the Bonferroni chi-squared test, and the differences in prevalence between age groups were analyzed using the same method. Variables that were significant (p ≤ 0.1) at the 95% confidence level were tested for collinearity and selected for inclusion in the multivariate logistic regression models. The local spatial autocorrelation test was used to analyze the spatial clustering characteristics of infection rates in different regions, and the results are shown as Moran scatter plots and clustering maps. All data were analyzed using the SPSS statistical package (version 26), and the spatial characteristics data were analyzed using GeoDa software. All plots were generated using GraphPad Prism 9.0 and RStudio software (version 4.2.0).
3. Results
3.1. Identification of Eggs
Eggs of Fasciola spp. from yaks are broadly ellipsoidal, operculated, yellow–brown, measuring 136.43–155.14 µm long by 69.39–87.52 µm wide, and are shedded unembryonated in feces (Figure 1).
3.2. Morphological and Molecular Identification of Adult Worms
Fresh worms were fleshy red and became gray–white after fixation. The size of the worms was 20–75 mm × 8–20 mm. The collected fresh worms were fixed and shown below (Figure 2a), and an adult worm stained by German hematoxylin is shown below (Figure 2b). The sequences of PCR-amplified ITS-1 and ITS-2 were completely consistent with the corresponding F. hepatica sequences available in GenBank.
3.3. Results of the Fecal Examination
3.3.1. Infection of Fasciola spp. by Fecal Examination
The results of fecal examination of Fasciola spp. eggs in yaks from different areas are shown in Table 3. A total of 1542 yak fecal samples were collected from 16 regions, and 267 were positive for Fasciola spp. eggs. The average infection rate was 17.32% (0–40.21%), and the average infection intensity was 51.9 epg (18–112).
3.3.2. Fasciola spp. Infection in Yaks of Different Ages
Table 4 shows the intensity of Fasciola spp. infection in yaks of different ages. The infection rate was 9.90% (0–25.00%) in 0–1 year old yaks, 16.18% (0–37.50%) in 1–2 year old yaks, and 25.88% (0–60.61%) in yaks over 3 years old. A comparison of infection rates between field subgroups using a multigroup Bonferroni chi-squared test revealed significant differences in the infection rates of yaks among the three different age groups (p < 0.0167). The infection rate was significantly lower in the group of 0–1 year olds than in the other two age groups and significantly higher in the over 3 year olds group than in the other two age groups (Figure 3). The mean infection intensity was 51.9 epg (18–112), comprising 45.5 (18–92) in yaks aged 0–1 year, 52.0 (23–93) in yaks aged 1–2 years, and 58.1 (28–112) in yaks aged over 3 years. The results showed that the fecal infection rate and infection intensity of Fasciola spp. increased with the increase in yak age.
3.3.3. Differences in Fasciola spp. Egg Infection in Yaks from Different Areas
The areas with positive yak fecal samples infected with Fasciola spp. are shown in Figure 4a. A comparison of infection rates across site subgroups using a multigroup Bonferroni chi-squared test revealed that Gonghe and Qilian counties had significantly lower infection rates than the other sampling sites, while Wulan had a significantly higher infection rate than the other sites, p < 0.001 (Figure 4b).
3.3.4. Spatial Characteristics of Fasciola spp. Infection in Yaks
The geographical distribution of Fasciola spp. infection in yaks is shown in Figure 5a. The spatial correlation of Fasciola spp. infection rates was explored based on yak infection rates in different regions as a single variable to derive correlations of yak infection rates in different regions. Spatial autocorrelation tests yielded a Moran index of −0.062 and Moran scatter plots distributed in quadrants two and four, indicating that yak infection rates showed a negative spatial correlation (Figure 5b). Regions with high infection rates showed mutual exclusion from other areas with high infection rates, tending to be closer to areas with low infection rates. The significantly spatially linked areas are Datong (p < 0.05) and Duran (p < 0.05) (Figure 5c); Duran formed a spatial distribution of high–low clusters with surrounding areas, and Datong formed a low–high clustering distribution characteristic with the surrounding areas (Figure 5d).
3.4. Autopsy Results
The autopsy results of the yak Fasciola spp. infection are shown in Table 5. A total of 242 yaks were examined, comprising 210 slaughtered yaks and 32 dissected yaks. A total of 66 yaks were found to be infected with Fasciola spp. The average infection rate was 27.27% (0–39.13%), and the average infection intensity was 21.2 worms (3–46).
3.5. Assessment of Risk Factors for Fasciola spp. Infection of Yaks Based on Areas and Age Groups
Logistic regression analysis of high-risk factors for Fasciola spp. infection in yaks was carried out using the presence of Fasciola spp. infection in yaks as the dependent variable and the age group and region as the independent variables. The results showed that both factors are included in the logistic model. In particular, the 2 year old group showed an increased risk of being infected with Fasciola spp. (odds ratio (OR) = 2.816; p < 0.01), and the risk was higher for the over 3 year old group (OR = 3.921; p < 0.001). Being from Haiyan (OR = 2.334; p < 0.05) increased the risk of Fasciola spp. infection in yaks, while yaks from Gangcha (OR = 2.985; p = 0.002), Duran (OR = 3.130; p = 0.001), and Wulan (OR = 3.348; p = 0.001) had a high risk of Fasciola spp. infection (Table 6). An optimized multiple logistic regression of the two factors, age and area, was conducted to obtain a risk assessment model. It was found that Qilan had the lowest risk score among the areas with Fasciola spp. infection, while Wulan had the highest risk score, with the lowest score for the 1 year old age group and the highest score for the over 3 year old age group among the different age groups. The two-factor combination with the highest risk score was the over 3 year old age group, with a combined total score of over 180 for Wulan, which corresponds to a risk of disease greater than 0.5, while the 1 year old age group achieved a combined total score close to 0 in Qilian, which corresponds to a risk of disease of less than 0.1, the two-factor combination with the lowest risk score (Figure 6).
4. Discussion
Of the 1542 tested yak fecal samples from 16 regions, 267 (17.32%) were positive for Fasciola spp. with a mean intensity of 51.9 epg, and the regional prevalence ranged from 0% (Maduo, Dari, Zhiduo, Chengduo, Zeku, and the Datong yak farm) to 40.21% (Wulan). Among different age groups of yaks, the prevalence of Fasciola spp. ranged from 9.90% to 25.88%. By autopsy, the prevalence of Fasciola spp. infection in yaks was 27.27% (66/242) with a mean intensity of 21.16 worms. To the best of our knowledge, this is the first investigation of Fasciola spp. infection in yaks in Guinan, Gangcha, Dulan, Wulan, Dari, Maduo, Zhiduo, Chengduo, Henan, Zeku, and Datong counties in Qinghai province, China. In the previous traditional studies, most researchers showed that yaks were infected with F. hepatica. During 1996 to 2020, the prevalence of F. hepatica was reported in major yak-producing areas in China such as the Tibetan Autonomous Region (18.33–100%) [16,22,23], some counties in Qinghai province (16.7–97%) [24,25,26,27,28,29], the northwest of Sichuan province (23%) [30], and Gansu province (6.55–42.5%) [15,31]. In addition, the prevalence of Fasciola was 10% in India and 16.67% in Nepal [32,33]. These studies indicated that F. hepatica infection is common in yaks in the Qinghai–Tibet Plateau regions, although the prevalence varied across different geographical localities.
Recently, Kong Xiangying et al. [34] found the first Fasciola gigantica in yaks in Haibei, Qinghai Province. Gao Xing et al. [35] isolated the Fasciola intermediate and characterized the mitochondrial genome in yaks from Haibei, Qinghai province. In this study, we identified the morphology of the adult worms and selected some adult samples for molecular biological identification. The PCR amplification and sequencing results of these samples were consistent with the sequences of F. hepatica, which did not exclude the possibility of F. gigantica and F. intermediate in the remaining samples.
In the present study, the location and age of yaks were associated with Fasciola spp. infection in yaks in the investigated areas. The trend of Fasciola spp. prevalence increased with the age of yaks, which was in accordance with previous reports [15,16]. Under the same grazing mode, the difference in Fasciola spp. prevalence may be caused by a difference in immunity, feeding conditions, management measures (e.g., prevention and control measures; degrees of repeated grazing; and types, frequency of use, and dosage of anthelmintic), regional ecological environment (e.g., number of rivers, mountains, low-lying swamps, altitude, moisture, temperature, and Lymnaea stagnalis), and sampling season. For example, in the survey areas with a high positive rate, there were more wetlands and grasslands that closely border marshes; these areas have similar water environmental conditions and many wild animals that drink water from the same nearby rivers that domestic animals drink from. The infected yaks could shed Fasciola spp. eggs into the environment. The intermediate host of Fasciola spp. is L. stagnalis, which becomes infected by swallowing the Fasciola spp. eggs excreted by yaks. Then, the infected L. Stagnalis sheds cercariae into the environment from July to October. The cercariae then develop into cysticerci and infect hosts, such as yaks and sheep, in rivers and grasslands. This creates a vicious cycle of persistent Fasciola spp. infection. It is interesting to note that the yaks sampled at the Datong yak farm had no Fasciola spp. infection. This is because the Datong yak farm is located in the interlacing zone of agriculture and pasture, the disinfection procedures are more standardized, and the deworming frequency is more intensive; thus, Fasciola spp. infection is better controlled.
In addition, the current study found that the infection rate of Fasciola spp. in yaks did not show obvious spatial characteristics, and the regions occasionally show a pattern of low–high clustering and high–low clustering. The regions showing this local clustering are Datong and Duran counties. It is speculated that the reason for this cluster pattern is the difference in the natural geography and grazing characteristics between the two places and the surrounding bordering areas. In other words, the disease flow factors in the regions and the surrounding areas are not continuous, and the epidemic factors are discontinuous in the geographical pattern. The distribution of disease epidemic factors tends to be discrete.
5. Conclusions
This survey showed a high Fasciola spp. prevalence (17.32% by fecal test and 27.27% by autopsy) in yaks in 16 counties of Qinghai province in the Qinghai–Tibet Plateau, which causes economic losses to the local yak industry and poses a potential threat to the health of the native population. Moreover, the location and age of yaks in the surveyed area are related to the Fasciola spp. infection. These findings not only extend the epidemiological information on Fasciola spp. infection in yaks but also provide useful baseline data for the prevention and control of fascioliasis in yaks.
Author Contributions
Sample collection, J.C., M.L., C.L., Q.C. and D.M.; data curation and statistical analysis, Q.C. and D.M.; formal analysis, J.C. and C.L.; methodology, J.C.; writing—original draft, Q.C.; writing—review and editing, M.L. and H.Z. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported by grants from the National Key Research and Development Program of China (No.2017YFE0108600), the National Key R&D Plan Special Project (2018YFD0502305), and the Qinghai Province Science and Technology Achievements Transformation Project (2022-NK-118).
Institutional Review Board Statement
The animal study protocol was approved by the Ethics Committee of Qinghai University (protocol code 2023-QHMKY-008, date of approval: 5 April 2023).
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Acknowledgments
We would like to acknowledge the staff, workers, and herdsmen who assisted us in sample collection.
Conflicts of Interest
The authors declare no conflict of interest.
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Figure 1.
Identification of Fasciola spp. eggs isolated from feces. The complete Fasciola spp. egg form is visible, golden-yellow, long elliptic or oval, narrow at one end, and blunt at the other end (multiple: 10 × 10).
Figure 1.
Identification of Fasciola spp. eggs isolated from feces. The complete Fasciola spp. egg form is visible, golden-yellow, long elliptic or oval, narrow at one end, and blunt at the other end (multiple: 10 × 10).
Figure 2.
Morphology of Fasciola spp.; (a) sample of collected worm; and (b) an adult worm stained with German hematoxylin.
Figure 2.
Morphology of Fasciola spp.; (a) sample of collected worm; and (b) an adult worm stained with German hematoxylin.
Figure 3.
Bar chart and differences in infection rate in yaks by age group (groups marked with the same letter are not significantly different).
Figure 3.
Bar chart and differences in infection rate in yaks by age group (groups marked with the same letter are not significantly different).
Figure 4.
Examination results of Fasciola spp. infection in yaks from different areas; (a) regional composition of positive samples; and (b) group bar charts of regional infection conditions (groups marked with the same letter are not significantly different).
Figure 4.
Examination results of Fasciola spp. infection in yaks from different areas; (a) regional composition of positive samples; and (b) group bar charts of regional infection conditions (groups marked with the same letter are not significantly different).
Figure 5.
Examination results of Fasciola spp. infection rate in yaks in different areas spatial features: (a) map of the regional distribution of Fasciola spp. infection rates in yaks; (b) univariate Moran scatter plots of Fasciola spp. infection in yaks in different regions; (c) spatially relevant areas with significance; and (d) areas where clustering characteristics of infection rates are spatially significantly correlated.
Figure 5.
Examination results of Fasciola spp. infection rate in yaks in different areas spatial features: (a) map of the regional distribution of Fasciola spp. infection rates in yaks; (b) univariate Moran scatter plots of Fasciola spp. infection in yaks in different regions; (c) spatially relevant areas with significance; and (d) areas where clustering characteristics of infection rates are spatially significantly correlated.
Figure 6.
A disease risk assessment graph (nomogram) generated using a logistic regression model based on sample regions and yak age. The positions of the scales for different ages and regions correspond to the first row. For each factor, one can take the score for the corresponding position in the top row, add up the scores for all factors, find the scale for the corresponding total score in the fourth row, and then observe the risk of disease below the total points relative position.
Figure 6.
A disease risk assessment graph (nomogram) generated using a logistic regression model based on sample regions and yak age. The positions of the scales for different ages and regions correspond to the first row. For each factor, one can take the score for the corresponding position in the top row, add up the scores for all factors, find the scale for the corresponding total score in the fourth row, and then observe the risk of disease below the total points relative position.
Table 1.
The information about the samples collected in this study.
| Areas | Geographic Coordinates | Altitude (m) | Annual Precipitation (mm) | Fecal Test (Number) | Autopsy (Number) |
|---|---|---|---|---|---|
| Gonghe | E 100°62′66.23″, N 36°28′87.03″ | above 3200 | 371.0 | 96 | 22 |
| Xinghai | E 99°58′57.18″, N 35°35′18.25″ | above 3306 | 360.0 | 98 | 21 |
| Guinan | E 100°13′–101°31′, N 35°09′–36°08′ | about 3100 | 488.0 | 96 | 22 |
| Qilian | E 100°26′40.41″, N 38°03′44.15″ | above 2717 | 406.7 | 97 | 26 |
| Gangcha | E 100°08′45.00″, N 37°19′31.69″ | above 3700 | 345.0 | 96 | 23 |
| Haiyan | E 100°59′39.95″, N 36°53′40.81″ | above 3008 | 447.4 | 96 | 22 |
| Dulan | E 98°06′09.74″, N 36°18′27.40″ | above 3041 | 213.4 | 96 | 24 |
| Wulan | E 98°48′67.39″, N 36°93′57.48″ | above 3100 | 210.4 | 97 | 26 |
| Dari | E 99°39′3.99″, N 33°45′12.55″ | above 3900 | 531.5 | 96 | 20 |
| Maduo | E 97°19′15.99″, N 34°57′10.55″ | above 4290 | 585.5 | 96 | 20 |
| Yushu | E 97°00′87.85″, N 32°99′31.07″ | above 3681 | 487.0 | 97 | 22 |
| Chengduo | E 97°06′39.00″, N 33°22′09.18″ | above 3851 | 500.0 | 96 | 20 |
| Nangqian | E 96°48′58″, N31°32′20″ | above 3650 | 527.3 | 96 | 22 |
| Henan | E 102°08′56.36″, N 34°29′16.96″ | above 3520 | 597.1 | 96 | 20 |
| Zeku | E 100°34′–102°08′, N 34°45′–35°32′ | above 3650 | 564.9 | 96 | 20 |
| Datong | E 101°38′00.28″, N 37°25′23.12″ | above 2950 | 547.2 | 97 | 32 |
| Total | 1542 | 242 |
Table 2.
The slaughterhouse source of the autopsy samples.
| Number | Slaughterhouse |
|---|---|
| 1 | Qinghai Lake meat industry Co., Ltd., slaughterhouse (Gonghe, China) |
| 2 | Xinghai County green grass source food Co., Ltd., slaughterhouse (Xinghai, China) |
| 3 | Guinan County Lvjiayuan cattle and sheep slaughterhouse (Guinan, China) |
| 4 | Qilian Yida animal products Co., Ltd., slaughterhouse (Qilian, China) |
| 5 | Gangcha County Yipin animal products Co., Ltd., slaughterhouse (Gangcha, China) |
| 6 | Haiyan County Huaxia cattle and sheep slaughterhouse (Haiyan, China) |
| 7 | Qinghai Kaitai agriculture and animal husbandry Co., Ltd., slaughterhouse (Dulan, China) |
| 8 | Wulan County Hengcheng beef and mutton slaughterhouse (Wulan, China) |
| 9 | Guoluo Haoyun designated Cattle and Sheep Co., Ltd. (Dari, China) |
| 10 | Guoluo Jin Grassland yak slaughtering and processing Co., Ltd. (Maduo, China) |
| 11 | Zhiduo County meat food Co., Ltd., slaughterhouse (Zhiduo, China) |
| 12 | Chengduo County plateau yak livestock products Co., Ltd., slaughterhouse (Chengduo, China) |
| 13 | Yushu Muyuan meat industry Co., Ltd., slaughterhouse (Yushu, China) |
| 14 | Sanjiang Ranch Co., Ltd., slaughterhouse (Henan, China) |
| 15 | Qinghai Northwest Hong organic resources development Co., Ltd., cattle and sheep slaughterhouse (Zeku, China) |
| 16 | Qinghai Datong Jinlu Industry and Trade Co., Ltd., slaughterhouse (Datong, China) |
Table 3.
The fecal worm egg infection of 1542 yaks Fasciola spp. in different areas.
| Areas | Number of Investigated Yaks | Positive Rate (%) | Mean Intensity (epg) |
|---|---|---|---|
| Gonghe | 96 | 17.71 (17/96) | 53.3 (29–79) |
| Xinghai | 98 | 23.47 (23/98) | 46.3 (21–66) |
| Guinan | 96 | 27.08 (26/96) | 45.6 (20–70) |
| Qilian | 97 | 17.53 (17/97) | 49.7 (23–76) |
| Gangcha | 96 | 37.50 (36/96) | 57.9 (30–112) |
| Haiyan | 96 | 32.29 (31/96) | 53.8 (28–97) |
| Dulan | 96 | 38.54 (37/96) | 55.7 (27–82) |
| Wulan | 97 | 40.21 (39/97) | 63.1 (36–103) |
| Dari | 96 | 0 | 0 |
| Maduo | 96 | 0 | 0 |
| Zhiduo | 97 | 0 | 0 |
| Chengduo | 96 | 0 | 0 |
| Nangqian | 96 | 19.79 (19/96) | 45.1 (18–84) |
| Henan | 96 | 22.92 (22/96) | 48.1 (32–59) |
| Zeku | 96 | 0 | 0 |
| Datong | 97 | 0 | 0 |
| Total | 1542 | 17.32 (267/1542) | 51.9 (18–112) |
Table 4.
The intensity and rate of Fasciola spp. infection in yaks of different ages.
| Areas | 0–1 (<1 Year Old) | 1–2 (≥1 Year Old and <3 Years Old) | Over 3 Years (≥3 Years Old) | |||
|---|---|---|---|---|---|---|
| Number | Mean Intensity (Epg) | Number | Mean Intensity (Epg) | Number | Mean Intensity (Epg) | |
| Gonghe | 32 | 47.4 (29–62) | 32 | 53.2 (37–64) | 30 | 59.3 (34–79) |
| Xinghai | 33 | 42.3 (21–58) | 32 | 46.6 (30–59) | 31 | 50.1 (28–66) |
| Guinan | 32 | 39.5 (20–62) | 32 | 44.8 (27–70) | 31 | 52.6 (36–68) |
| Qilian | 32 | 43.9 (23–53) | 32 | 50.3 (33–68) | 30 | 54.8 (33–76) |
| Gangcha | 33 | 50.2 (30–92) | 32 | 57.4 (38–89) | 31 | 66.1 (29–112) |
| Haiyan | 33 | 45.7 (28–71) | 32 | 53.0 (39–82) | 32 | 62.6 (40–97) |
| Dulan | 32 | 48.9 (27–54) | 32 | 57.7 (31–69) | 32 | 60.4 (39–82) |
| Wulan | 34 | 55.1 (36–79) | 32 | 63.2 (39–93) | 32 | 71.0 (43–103) |
| Dari | 32 | 0 | 32 | 0 | 32 | 0 |
| Maduo | 32 | 0 | 32 | 0 | 32 | 0 |
| Zhiduo | 33 | 0 | 32 | 0 | 32 | 0 |
| Chengduo | 32 | 0 | 32 | 0 | 32 | 0 |
| Nangqian | 32 | 38.7 (18–54) | 32 | 45.5 (25–61) | 31 | 51.2 (37–84) |
| Henan | 32 | 43.5 (32–54) | 32 | 48.5 (41–58) | 32 | 52.7 (43–65) |
| Zeku | 0 | 0 | 0 | 0 | 0 | 0 |
| Datong | 33 | 0 | 33 | 0 | 32 | 0 |
| Total | 515 | 45.5 (18–92) | 513 | 52.0 (23–93) | 514 | 58.1 (28–112) |
| Infection rate | 9.90% | 16.18% | 25.88% | |||
Table 5.
Investigation of Fasciola spp. infection in yaks in different areas by autopsy.
| Study Areas | Number of Yaks Examined | Prevalence (%) | Mean Intensity (Number of Worms) |
|---|---|---|---|
| Gonghe | 22 | 22.73 (5/22) | 9.2 (3–22) |
| Xinghai | 21 | 28.57 (6/21) | 17.5 (4–37) |
| Guinan | 22 | 27.27 (6/22) | 14.2 (6–26) |
| Qilian | 26 | 19.23 (5/26) | 11.6 (6–18) |
| Gangcha | 23 | 39.13 (9/23) | 30.6 (7–46) |
| Haiyan | 22 | 31.82 (7/22) | 22.7 (3–21) |
| Dulan | 24 | 37.50 (9/24) | 28.3 (4–34) |
| Wulan | 26 | 38.46 (10/26) | 28.6 (9–39) |
| Dari | 20 | 0 | 0 |
| Maduo | 20 | 0 | 0 |
| Yushu | 22 | 0 | 0 |
| Chengduo | 20 | 0 | 0 |
| Nangqian | 22 | 22.73 (5/22) | 20.1 (7–43) |
| Henan | 20 | 20.00 (4/20) | 16.8 (12–36) |
| Zeku | 20 | 0 | 0 |
| Datong | 32 | 0 | 0 |
| Total | 242 | 27.27 (66/242) | 21.2 (3–46) |
Table 6.
Risk factors for Fasciola spp. infection in yaks.
| Factor | Group | n | Prevalence (%) | OR | 95% CI for the OR | p-Value | |
|---|---|---|---|---|---|---|---|
| Upper Limit | Lower Limit | ||||||
| Age | 1 year | 322 | 15.84 | 1.000 | |||
| 2 years | 320 | 25.94 | 1.895 | 1.275 | 2.816 | 0.002 | |
| Over 3 years | 322 | 41.30 | 3.921 | 2.681 | 5.736 | <0.001 | |
| Areas | Qilian | 97 | 17.53 | 1.000 | |||
| Gonghe | 96 | 17.71 | 1.007 | 0.472 | 2.146 | 0.986 | |
| Xinghai | 98 | 23.47 | 1.459 | 0.711 | 2.993 | 0.303 | |
| Guinan | 96 | 27.08 | 1.789 | 0.881 | 3.632 | 0.108 | |
| Gangcha | 96 | 37.50 | 2.985 | 1.503 | 5.927 | 0.002 | |
| Haiyan | 96 | 32.29 | 2.334 | 1.166 | 4.675 | 0.017 | |
| Dulan | 96 | 38.54 | 3.130 | 1.578 | 6.207 | 0.001 | |
| Wulan | 97 | 40.21 | 3.348 | 1.693 | 6.619 | 0.001 | |
| Nangqian | 96 | 19.79 | 1.162 | 0.553 | 2.440 | 0.692 | |
| Henan | 96 | 22.92 | 1.413 | 0.685 | 2.917 | 0.349 | |
| Total | 964 | 27.70 | |||||
The results of the analysis are presented as the number of yaks (n), odds ratio (OR), and 95% confidence intervals (CI).
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MDPI and ACS Style
Cai, Q.; Lei, M.; Li, C.; Cai, J.; Ma, D.; Zhang, H. Epidemiological Investigation of Yak (Bos grunniens) Fascioliasis in the Pastoral Area of Qinghai–Tibet Plateau, China. Animals 2023, 13, 3330. https://0-doi-org.brum.beds.ac.uk/10.3390/ani13213330
AMA Style
Cai Q, Lei M, Li C, Cai J, Ma D, Zhang H. Epidemiological Investigation of Yak (Bos grunniens) Fascioliasis in the Pastoral Area of Qinghai–Tibet Plateau, China. Animals. 2023; 13(21):3330. https://0-doi-org.brum.beds.ac.uk/10.3390/ani13213330
Chicago/Turabian StyleCai, Qijian, Mengtong Lei, Chunhua Li, Jinzhong Cai, Doudou Ma, and Houshuang Zhang. 2023. "Epidemiological Investigation of Yak (Bos grunniens) Fascioliasis in the Pastoral Area of Qinghai–Tibet Plateau, China" Animals 13, no. 21: 3330. https://0-doi-org.brum.beds.ac.uk/10.3390/ani13213330
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