| Literature DB >> 27565768 |
Nusirat Elelu1,2, Abdulganiyu Ambali3, Gerald C Coles4, Mark C Eisler4.
Abstract
BACKGROUND: Trematode infections of livestock are of global veterinary and public health importance causing serious economic losses. Majority of data on burden of trematode infections in Nigeria are based on abattoir surveys and there are very few data on herd level risk factors. The present study investigated the prevalence of, and herd level risk factors for, fasciolosis and other trematode infections in cattle in Edu Local Government Area (LGA).Entities:
Keywords: Dicrocoelium; FAMACHA©; Fasciola; Kwara; Nigeria; Paramphistomes; Prevalence; Risk factors; Schistosoma; Trematodes
Mesh:
Year: 2016 PMID: 27565768 PMCID: PMC5002138 DOI: 10.1186/s13071-016-1737-5
Source DB: PubMed Journal: Parasit Vectors ISSN: 1756-3305 Impact factor: 3.876
Fig. 1Map of Kwara State showing the location of Edu Local Government Area (study location). The inset map shows Kwara State within Nigeria
Fig. 2Proportions of single infections and co-infections by trematodes in cattle from the Edu Local Government Area of Kwara State, Nigeria
Households and cattle trematode infections from villages studied in Edu LGA, Kwara State, Nigeria
| Households | Cattle | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Village | Altitude (m) |
| Paramphistomes |
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| Paramphistomes |
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| (%) |
| (%) |
| (%) |
| (%) | ||
| Bacita | 106 | 2 | 2 | 2 | 2 | 0 | 22 | 7 | (31.8) | 6 | (27.3) | 3 | (13.6) | 0 | (0.0) |
| Belle | 76 | 5 | 5 | 5 | 1 | 0 | 48 | 48 | (100) | 28 | (58.3) | 6 | (12.5) | 0 | (0.0) |
| Bokungi | 221 | 3 | 3 | 3 | 2 | 0 | 23 | 12 | (52.2) | 2 | (8.7) | 2 | (8.7) | 0 | (0.0) |
| Fanagun | 82 | 14 | 14 | 7 | 5 | 3 | 158 | 122 | (77.2) | 12 | (7.6) | 9 | (5.7) | 3 | (1.9) |
| Fedudangi | 193 | 3 | 3 | 1 | 0 | 0 | 14 | 12 | (85.7) | 2 | (14.3) | 1 | (7.1) | 0 | (0.0) |
| Gonandogo | 84 | 10 | 10 | 4 | 4 | 2 | 136 | 100 | (73.5) | 2 | (1.5) | 3 | (2.2) | 2 | (1.5) |
| Mokwagi | 114 | 1 | 1 | 1 | 0 | 0 | 13 | 5 | (38.5) | 1 | (7.7) | 0 | (0.0) | 0 | (0.0) |
| Ndabata | 202 | 2 | 2 | 1 | 2 | 0 | 25 | 19 | (76.0) | 5 | (20.0) | 6 | (24.0) | 0 | (0.0) |
| Ndachewoye | 98 | 21 | 21 | 17 | 9 | 2 | 196 | 167 | (85.2) | 45 | (23.0) | 13 | (6.6) | 3 | (1.5) |
| Tshonga Farm | 175 | 2 | 1 | 1 | 2 | 0 | 28 | 1 | (3.6) | 1 | (3.6) | 3 | (10.7) | 0 | (0.0) |
| Yelwa | 77 | 2 | 2 | 2 | 2 | 0 | 23 | 21 | (91.3) | 6 | (26.1) | 4 | (17.4) | 0 | (0.0) |
| Total | 65 | 64 | 44 | 29 | 7 | 686 | 514 | (74.9) | 110 | (16.0) | 50 | (7.3) | 8 | (1.2) | |
Abbreviations: N number of samples, n number of infected, (%) prevalence
Fig. 3Distribution of trematode prevalence across villages sampled in Edu Local Government Area of Kwara State, North-central Nigeria. The size of the circles is proportional to prevalence: small circles (0 %); largest circle (100 %)
Mean packed cell volume (PCV) of cattle in different categories of FAMACHA© score
| FAMACHA© score | Number of cattle | Mean PCV | Range PCV |
|---|---|---|---|
|
| |||
| 1 | 56 (25.8) | 35.9 | 22–48 |
| 2 | 128 (58.9) | 34.9 | 20–48 |
| 3 | 23 (24.4) | 30.5 | 20–46 |
| 4 | 10 (4.6) | 27.7 | 12–41 |
Total number of cattle: 217
Two-by-two contingency table of PCV and FAMACHA© score of cattle
| FAMACHA© Score | ||||
|---|---|---|---|---|
| FS 4–5 (Anaemic) | FS 1–3 (Non-anaemic) | Total | ||
| PCV | ≤ 24 % (Anaemic) | 4 | 18 | 22 |
| > 24 % (Non-anaemic) | 6 | 189 | 195 | |
| Total | 10 | 207 | 217 | |
Sensitivity: 18.2 %; Specificity: 96.9 %
Binary logistic regression to investigate risk factors for cattle trematode infections in Kwara State, Nigeria
| Parasite | Risk factor | Odds ratio | 95 % CI |
|
|---|---|---|---|---|
|
| Cattle herd size > 100 | 0.28 | 0.14–0.58 | 0.001 |
| Adult cattle (≥ 2 years) | 1.94 | 1.19–3.16 | 0.008 | |
| Paramphistomes | Ethnicity of head of respondents | 0.05 | 0.01–0.22 | 0.001 |
| Head of respondents (40–59 years) | 1.95 | 1.02–3.74 | 0.043 | |
|
| Cattle herd size > 100 | 6.98 | 2.94–16.6 | 0.001 |